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JMIR Preprints
A preprint server for pre-publication/pre-peer-review preprints intended for community review as well as ahead-of-print (accepted) manuscripts
Background: During a sexual assault report, physicians gather a significant amount of information: socio-
demographic characteristics of the victims, events and documentation of injuries. However, the
literature highlights the lack of comparative information from available clinical research
studies. The World Health Organization (WHO) and Council of Europe emphasized the urgent
need for a common methodology to document sexual assaults and to strengthen care. Objective: We describe the methods used at the Obstetrics and Gynecology Emergency Departments
(ObGyn ED) of Geneva University Hospitals (HUG) to create a comprehensive, systematic and
reproductible digital datasheet for medico-legal sexual assault reports, with the aim of
informing the creation of a regional sexual assault patient cohort for French-speaking
Switzerland. Integrated into the patient’s electronic medical record (EMR), the ease of access
restricted to authorized staff should enhance the efficiency of the clinical workflow. Methods: Identification of data and variables of the electronic Sexual Assault Report (eSAR) was guided
by a retrospective study conducted between 2018 and 2021 in the Swiss University Hospitals
of Geneva and Lausanne and included 740 sexual assault reports. Standardized classifications
and clinical scales were utilized. For one year, the eSAR was revised and improved by a
multidisciplinary panel of experts, through clinical application. Results: The implementation of the eSAR ensures the collection of 100% of selected variables, monitors
data to identify finalized and not finalized records and provides full traceability of access for
security. Designed to be inclusive of gender diversity, the eSAR is replicable for Adult and
Pediatrics ED. Conclusions: Our method for medico-legal sexual assault reporting builds a comprehensive IT guideline for
new doctors through harmonized terminologies and decreases administrative burden to finalize
reports. The eSAR provides IT assistance for the clinical and administrative management of
patients and is intended to contribute to overall efforts to improve research and health services.
Journal Description
JMIR Preprintscontains pre-publication/pre-peer-review preprints intended for community review (FAQ: What are Preprints?). For a list of all preprints under public review click here. The NIH and other organizations and societies encourage investigators to use interim research products, such as preprints, to speed the dissemination and enhance the rigor of their work. JMIR Publications facilitates this by allowing its authors to expose submitted manuscripts on its preprint server with a simple checkbox when submitting an article, and the preprint server is also open for non-JMIR authors.
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For pathway 2, if authors do not wish to have the preprint considered in a partner journal (or a specific journal), this should be noted in the cover letter. Also, note if you want to have the paper only considered/forwarded to specific journals, e.g. JMIR, PLOS, PEERJ, BMJ Open, Nature Communications etc), please specify this in the cover letter.
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Background: During a sexual assault report, physicians gather a significant amount of information: socio-
demographic characteristics of the victims, events and documentation of injuries. However, th...
Background: During a sexual assault report, physicians gather a significant amount of information: socio-
demographic characteristics of the victims, events and documentation of injuries. However, the
literature highlights the lack of comparative information from available clinical research
studies. The World Health Organization (WHO) and Council of Europe emphasized the urgent
need for a common methodology to document sexual assaults and to strengthen care. Objective: We describe the methods used at the Obstetrics and Gynecology Emergency Departments
(ObGyn ED) of Geneva University Hospitals (HUG) to create a comprehensive, systematic and
reproductible digital datasheet for medico-legal sexual assault reports, with the aim of
informing the creation of a regional sexual assault patient cohort for French-speaking
Switzerland. Integrated into the patient’s electronic medical record (EMR), the ease of access
restricted to authorized staff should enhance the efficiency of the clinical workflow. Methods: Identification of data and variables of the electronic Sexual Assault Report (eSAR) was guided
by a retrospective study conducted between 2018 and 2021 in the Swiss University Hospitals
of Geneva and Lausanne and included 740 sexual assault reports. Standardized classifications
and clinical scales were utilized. For one year, the eSAR was revised and improved by a
multidisciplinary panel of experts, through clinical application. Results: The implementation of the eSAR ensures the collection of 100% of selected variables, monitors
data to identify finalized and not finalized records and provides full traceability of access for
security. Designed to be inclusive of gender diversity, the eSAR is replicable for Adult and
Pediatrics ED. Conclusions: Our method for medico-legal sexual assault reporting builds a comprehensive IT guideline for
new doctors through harmonized terminologies and decreases administrative burden to finalize
reports. The eSAR provides IT assistance for the clinical and administrative management of
patients and is intended to contribute to overall efforts to improve research and health services.
Background: Video games, especially action games, has become increasingly prevalent among adolescents, with studies indicating potential cognitive benefits, particularly on attention and working memor...
Background: Video games, especially action games, has become increasingly prevalent among adolescents, with studies indicating potential cognitive benefits, particularly on attention and working memory. However, the effects of video gaming on underprivileged teenagers remain underexplored, despite the unique cognitive challenges they face due to their level of exposure, level of cognitive abilities, and socioeconomic factors. Objective: The present study aimed to evaluate the effects of action video games on attention span and visual working memory retention among underprivileged adolescents. By comparing cognitive performance between those exposed to action games and those in a control group, as well as a sub-group analysis into the difference between older (16-18) and younger groups (13-15), we sought to determine if gaming could enhance cognitive functions in this population, and whether age has any significant factor to play in memory and attention scores. Methods: A sample of 100 adolescents aged 13-18 from the Panaah Communities Center in Maharashtra, India, was divided into control (n=50) and experimental (n=50) groups. The experimental group engaged in a 20-minute action game before completing two assessments: the Continuous Performance Test (CPT) to measure attention and the Visual Pattern Test (VPT) for visual working memory. Each day, the experimental and control groups sat for different tests to ensure reliable results. Statistical analyses were conducted to compare group performances and assess age-related differences. T-test Assuming Unequal Variance and the Mann-Whitney U Test were utilized to measure statistical significance. Cohen's d was applied to all variables to ensure real-life applicability through effect size. Results: The experimental group scored higher than the control group in both attention (CPT: M = 79.028, SD = 32.0; p = 0.034) and working memory (VPT: M = 77.019, SD = 51.5; p = 0.026), suggesting that video game exposure had a positive effect on cognitive functioning. Further analysis revealed minimal age-related differences in cognitive outcomes. High variability in responses, especially among those in the experimental group, highlighted the influence of individual baseline characteristics inherently present in the population. Conclusions: The findings indicate that action video games can enhance attention and visual working memory in underprivileged adolescents, though individual differences must be considered. These results emphasize the potential for video games as supplementary cognitive training tools in the classroom, especially for those who have cognitive deficits or trouble learning in normal, peer-group settings.
Background: Genetic testing has become a common way of identifying a woman’s risk of developing hereditary breast and ovarian cancer, however, not all medical providers have the necessary informatio...
Background: Genetic testing has become a common way of identifying a woman’s risk of developing hereditary breast and ovarian cancer, however, not all medical providers have the necessary information to support patients interested in genetic testing, nor do they always have the proper information for patients once they have been diagnosed. Therefore, many previvors, the name of those who have tested positive for the BRCA genetic mutation, have taken to social media to inform others about the importance of genetic testing and explain to them how to understand their test results. Historically, those desiring to speak about their medical issues online have sought out structured support groups or chat rooms, however, many previvors today are instead posting on their own personal social media accounts and creating more niche communities. Objective: This study aimed to examine why BRCA previvors are sharing content on their personal social media accounts and how posting online in this way serves a purpose for their larger community. Methods: A total of 16 semi-structured interviews were conducted with individuals who post about their experience being diagnosed with the BRCA genetic mutation and their subsequent treatment on their personal social media accounts specifically for followers interested in their medical journey. The interviews were recorded, transcribed, and coded by an experienced qualitative researcher and a graduate student using inductive techniques and a reflexive thematic analysis was applied to the transcripts. Results: The results suggest BRCA previvors want to control the narrative around their personalized medical experiences rather than participating in existing groups or chat rooms. Controlling their own story, rather than adding to existing narratives, gives previvors a sense of control. It also allows them to set boundaries around the types of experiences they have online when sharing their medical journey. Finally, previvors said they feel they’re serving the larger BRCA community by each sharing their individual journeys to hopefully avoid stereotyping and homogenizing the experience of BRCA patients. Conclusions: Research with the objective of understanding the experiences of BRCA previvors should include exploring how and why they talk about their journeys, especially due to the lack of knowledge BRCA previvors say many of their medical providers have. We suggest further research should examine how other BRCA patients, especially BIPOC patients, are navigating their own content creation, especially considering content moderation policies that social media platforms are continuing to implement that directly impact users’ ability to share about their medical experiences.
Background: Alzheimer’s disease (AD) is a type of dementia that is irreversible and continues to worsen over time; it is the most common form of dementia in the world affecting over 50 million peopl...
Background: Alzheimer’s disease (AD) is a type of dementia that is irreversible and continues to worsen over time; it is the most common form of dementia in the world affecting over 50 million people with projections of this figure tripling in 2050 due to aging populations. It is especially important to diagnose it early because therapeutic approaches are more effective when applied at the preclinical or MCI stages when the neuronal loss may be slowed down or reduced. However, the current diagnostic clinical tools which include clinical examination, MRI and PET are not effective in detecting the disease at early stages when intervention would be most beneficial. Objective: Primary objective
1. To build a robust, scalable predictive model capable of detecting early-stage AD with high precision.
2. By using a hybrid architecture that integrates imaging features, fluid biomarkers, genetic profiles, and longitudinal cognitive scores
3. we aim to provide clinically interpretable outputs that could guide personalized intervention strategies. Methods: This study is a multi-center, multimodal biomarker research to identify early AD using hybrid deep learning and ensemble-based machine learning techniques. The methodology combines high-level data structures, modern machine learning networks, and stringent statistical testing procedures in order to guarantee the method’s stability, transparency, and applicability to clinical scenarios Results: The findings of this study are organized to give a comprehensive account of the assessment of the predictive model, with an emphasis on the accuracy, modality invariance, and clinical interpretability. The findings show that the multimodal integration framework works effectively, is portable across centers, and has clinical applicability in the assessment of early onset Alzheimer’s Disease (AD). Conclusions: This work presents a new, multiplex machine learning approach to AD diagnosis at the prodromal stage by incorporating neuroimaging, biofluid markers, genomics, and neuropsychological tests. The model surpasses the results of single-modality and existing multimodal frameworks, showing high predictive accuracy and cross-dataset and cross-site generalization on ADNI, OASIS, and an independent clinic-based sample. CNN, LSTM networks, GNNs, federated learning and GAN based domain adaptation are employed to build a reliable and scalable model which can pave the way to develop a clinically feasible and interpretable biomarker of AD risk.
However, the proposed model has some issues like data heterogeneity and limited demographic diversity, and thus the proposed model needs to be improved. The future studies should try to collect data from a broader population and apply new biomarkers for improving the prediction of the outcomes. It will, therefore, be crucial to test the model in clinical trials to determine its efficiency in real life. In summary, this work provides the evidence of the importance of the integrative and multiple approach for the early AD diagnostics and management, and can potentially contribute to better patient prognosis, as well as the development of individualized medicine.
Background: : The Insertable Cardiac Monitor (ICM) clinical pathway in Tampere Heart Hospital, Finland, did not correspond to the diagnostic needs of the population due to a lack of resources for inse...
Background: : The Insertable Cardiac Monitor (ICM) clinical pathway in Tampere Heart Hospital, Finland, did not correspond to the diagnostic needs of the population due to a lack of resources for insertion and follow-up. There has been growing evidence of delegating the insertion from cardiologists to specially trained nurses and outsourcing the remote follow-up. However, it is unclear if the change in the clinical pathway is safe and improves efficiency. Objective: To describe and assess the efficiency of the change in the clinical pathway for patients eligible for an ICM. Methods: Clinical pathway improvements included initiating nurse-performed insertions, relocating the procedure from the catheterization laboratory to a procedure room, and outsourcing part of the remote follow-up to manage ICM workload. Data was collected from EHR concerning all patients who received an ICM in the Tampere Heart Hospital in 2018 and 2020. Follow-up data was collected 12, 24, and 36 months after insertion for both groups. Results: The number of inserted ICMs doubled from 74 in 2018 to 159 in 2020. In 2018, cardiologists completed all insertions, while in 2020, 70.4% were completed by nurses. The waiting time from referral to procedure was significantly shorter in 2020 (mean=36 days) compared with 2018 (mean=49 days), P=.02. The scheduled ICM procedure time decreased from 60 minutes in 2018 to 45 minutes in 2020. Insertions performed in the catheterization laboratory decreased significantly (18.9% in 2018; 1.9% in 2020, P=<.001). Patients receiving an ICM after syncope increased from 71 to 94 patients. Stroke and transient ischemic attack (TIA) as an indication increased substantially from 2018 to 2020 (2 and 62 patients, respectively). In 2018, nurses analyzed all remote transmissions. In 2020, the external monitoring service escalated only 11.2% of the transmissions (204 out of 1817) to the clinic for revision. This saved 296 hours of nursing time in 2020. Having nurses insert ICM in 2020 saved 48 hours of physicians’ time and the shorter procedure additional 40 hours of nursing time compared with the process in 2018. Also, the catheterization laboratory was released for other procedures (27 hours per year). The complication rate did not change significantly (2.7% in 2018 and 3.1% in 2020, P=.85). The 36-month diagnostic yield for syncope remained high in 2018 and 2020 (45.1% and 38.3%, P<.005). The diagnostic yield for stroke patients with a procedure in 2020 was 43.5%. Conclusions: The efficiency of the clinical pathway for patients indicated for an ICM can be increased significantly by changing to nurse-insertions in procedure rooms and to the use of an external monitoring and triaging service. Thereby, patient access to an ICM is increased while a significant amount of staff time and resources are saved without any compromise to treatment quality.
Background: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain ass...
Background: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems. However, most prior work has focused on healthy subjects in controlled environments, with limited attention to real-world postoperative pain scenarios. This gap necessitates the development of robust, multimodal approaches capable of addressing the unique challenges associated with assessing pain in clinical settings, where factors like motion artifacts, imbalanced label distribution, and sparse data further complicate pain monitoring. Objective: To develop and evaluate a multimodal machine learning-based framework for the objective assessment of pain in postoperative patients using biosignals such as electrocardiogram (ECG), electromyogram (EMG), electrodermal activity (EDA), and Respiration Rate signals. Methods: The iHurt study was conducted on 25 postoperative patients at the University of California, Irvine Medical Center. The study captured multimodal biosignals during light physical activities, with concurrent self-reported pain levels using the Numerical Rating Scale (NRS). Data preprocessing involved noise filtering, feature extraction, and combining handcrafted (HC) and automatic features through convolutional and long-short-term memory autoencoders. Machine learning classifiers, including Support Vector Machine (SVM), Random Forest (RF), AdaBoost, and K-Nearest Neighbors (KNN), were trained using weak supervision and minority oversampling to handle sparse and imbalanced pain labels. Pain levels were categorized into baseline (BL) and three levels of pain intensity (PL1-3). Results: The multimodal pain recognition models achieved an average balanced accuracy of over 80% across the different pain levels. Respiratory rate (RR) models consistently outperformed other single modalities, particularly for lower pain intensities, while facial muscle activity (EMG) was most effective for distinguishing higher pain intensities. Although single-modality models, especially RR, generally provided higher performance compared to multimodal approaches, our multimodal framework still delivered results that surpass previous works in terms of overall accuracy. This suggests that while RR remains a strong modality on its own, the combination of multiple biosignals offers valuable insights and potential improvements for more complex pain recognition tasks in clinical settings. Conclusions: This study presents a novel, multimodal machine learning framework for objective pain recognition in postoperative patients. The results highlight the potential of integrating multiple biosignal modalities for more accurate pain assessment, with particular value in real-world clinical settings. Future work should focus on developing personalized models to account for individual variability in pain responses, ultimately improving clinical pain management
Background: Childhood myopia has become an increasingly serious public health problem worldwide. Objective: This study aims to explore the prevalence of myopia, axial length changes, and their influen...
Background: Childhood myopia has become an increasingly serious public health problem worldwide. Objective: This study aims to explore the prevalence of myopia, axial length changes, and their influencing factors among children and adolescents aged 4 to 18 years in Beijing. The findings are expected to provide a scientific basis for taking effective measures to prevent and control myopia for government decision-making. Methods: This cross-sectional survey involved 2595 children from 9 randomly selected educational institutions (1 kindergarten and 8 schools) in northern China. The survey included a questionnaire, visual acuity examination, refractive screening, and axial length measurement. Results: The prevalence of myopia among the tested students was 56.53%, and 50.98% of students had an axial length (AL) of >23.5 mm. The AL is elongated with age, and the right was longer than the left (P<0.05). Excluding preschool children, the AL was significantly different between students with and without myopia (P<0.05). The univariate analysis showed significant differences in the myopia rates by age, reading distance, close learning time, lighting environment, and myopia in parents (P<0.05). The multivariate logistic analysis showed that older children and myopia in parents were risk factors for myopia and a longer AL, with girls being more likely to develop myopia than boys (odds ratio, 1.35; 95% confidence interval, 1.133–1.597). Conclusions: The prevalence of myopia and the proportion of excessive increase of AL were high in children and adolescents aged 4 to 18 years. Therefore, it is possible to predict the occurrence and development of myopia in children by measuring the AL and to prevent and control myopia in children and adolescents by reducing the short-distance reading time and maintaining an adequate reading distance.
Background: The research study aimed to detect the vocal features immersed in empathic counsellor speech using samples of calls to a mental health (MH) helpline service. Objective: The study aimed to...
Background: The research study aimed to detect the vocal features immersed in empathic counsellor speech using samples of calls to a mental health (MH) helpline service. Objective: The study aimed to produce an algorithm for the identification of empathy from these features, which could act as a training guide for counsellors and conversational agents who need to transmit empathy in their vocals. Methods: Two annotators with a psychology background and English heritage provided empathy ratings for 57 calls involving female counsellors, as well as multiple short call segments within each of these calls. These ratings were found to be well correlated between the two raters in a sample of six common calls. Using vocal feature extraction from call segments and statistical variable selection methods, such as L1 penalised Least Absolute Shrinkage and Selection Operator (LASSO) and forward selection, a total of 14 significant vocal features were associated with empathic speech. Results: Generalised additive mixed models (GAMM), binary logistics regression with splines and random forest models were employed to obtain an algorithm that differentiated between high and low empathy call segments. Slightly higher predictive accuracies of empathy were reported from the binary logistics regression model (AUC=0.617) than the GAMM (AUC=0.605) and the random forest model (AUC= 0.600). Conclusions: This study suggests that the identification of empathy from vocal features alone is challenging and further research involving multi-modal models (e.g. models incorporating facial expression, words used and vocal features) are encouraged for detecting empathy in the future.
This study has several limitations including a relatively small sample of calls and only two empathy raters. Future research should focus on accommodating multiple raters with varied backgrounds, to explore these effects on perceptions of empathy. In addition, considering counsellor vocals from larger more heterogeneous populations, including mixed-gender samples, will allow an exploration of the factors influencing the level of empathy projected in counsellor voices more generally.
Background: Emerging adult sexual and gender minority people (EASGM) are at increased risk for suicide due to unique experiences including discrimination, family/friend rejection, and low positive aff...
Background: Emerging adult sexual and gender minority people (EASGM) are at increased risk for suicide due to unique experiences including discrimination, family/friend rejection, and low positive affect. Peer Mentors (PMs) may offer a unique opportunity for intervention but are underutilized for suicide prevention among EASGM. Objective: We developed an intervention, Supporting Transitions to Adulthood and Reducing Suicide (STARS), to improve suicide prevention among EASGM and increase social support, coping, and positive affect. Peer Mentors meet virtually for six weeks, providing social support, strategies to diminish the impact of discrimination, connection to safe spaces, and reinforcement of intentions to use Safety Plans. Methods: To understand PMs’ experiences in their role, including distress, fidelity to the manual, and perceptions of feasibility and acceptability of STARS and participants’ Safety Plan, we collected survey data from participants and PMs as well as in-depth interviews with PMs after the completion of the intervention. Results: PMs reported overall high comfort (8.52; SD=1.60) and low distress (1.93; SD = .87) during sessions. PMs had high fidelity (>90%) to the PM intervention training. PMs reported high feasibility (17.50; SD = 2.38), acceptability (20; SD = 0), and appropriateness (20; SD = 0) of the STARS intervention. Conclusions: Peer mentorship for EASGM who are at risk for suicide was deemed as feasible and acceptable by PMs and participants alike. PMs reported that they felt comfortable and confident during the sessions. Future research should explore the optimal strategies to support PMs and participants as they engage in suicide prevention work as well as incorporate feedback from the PMs in this study to ensure optimal outcomes. Clinical Trial: NCT05018143
Background: Insomnia is a common sleep disorder, especially among the elderly, with a significant impact on the quality of life (QoL) and is associated with various comorbidities. Traditional pharmaco...
Background: Insomnia is a common sleep disorder, especially among the elderly, with a significant impact on the quality of life (QoL) and is associated with various comorbidities. Traditional pharmacotherapy for insomnia is often unsuitable for older adults because of potential drug interactions and side effects, making non-pharmacological interventions such as cognitive behavioral therapy for insomnia (CBT-I) more appropriate. However, delivering CBT-I in a traditional face-to-face setting poses challenges including accessibility and adherence, particularly for older adults. Objective: This study aimed to evaluate the effectiveness of an information and communication technology (ICT)-based CBT-I program, “Smart Sleep,” specifically designed to improve insomnia among community-dwelling elderly persons. Methods: A randomized, single-blind controlled trial was conducted with 59 elderly participants from Incheon, South Korea. Participants were divided into an intervention group, which used the Smart Sleep mobile app, and a control group. The intervention group received 8 weeks of non-face-to-face CBT-I through the application, which included sleep diaries, relaxation exercises, and real-time consultations. Outcomes were measured at baseline, week 4, and week 8, with a focus on insomnia severity, sleep quality, sleep efficiency, dysfunctional beliefs about sleep, depression, and QoL. Results: The intervention group showed significant improvements in insomnia severity, sleep quality, sleep efficiency, and dysfunctional beliefs about sleep compared with the control group. However, there was no significant difference in the QoL between the two groups (F=0.998, p=.372). Participation rates in the Smart Sleep program were high, with a 94% completion rate for sleep diary tasks and 100% participation in real-time consultations. Conclusions: The ICT-based CBT-I program "Smart Sleep" effectively improved sleep-related outcomes among elderly participants, demonstrating the potential of non-face-to-face interventions in managing insomnia in this population. The program is user-friendly, and ICT-based coaching contributed to high engagement. To ensure broader access for the elderly, distribution through community welfare or public health centers is recommended. Clinical Trial: cris.org KCT0007287
Background: Pathologists are grappling with high workloads and uneven resource distribution, which can impede professional development and the delivery of quality patient care. The advent of generativ...
Background: Pathologists are grappling with high workloads and uneven resource distribution, which can impede professional development and the delivery of quality patient care. The advent of generative large language models (LLMs) has the potential to revolutionize pathological field, where efficiency and resource accessibility are paramount. Objective: This study aimed to investigate the perceptions and willingness of Chinese pathologists to adopt generative LLMs. Methods: We conducted a questionnaire survey at the National Pathology Academic Annual Conference in April 2024, involving 339 certified Chinese pathologists. Participant responses were measured with a 5-point Likert scale for the performance of generative LLMs in clinical, research, and educational settings, with statistical analysis using mean and standard deviation (SD). Multivariable logistic regression models were employed to explore factors associated with the adoption of generative LLMs, reporting odds ratios (ORs) and 95% confidence intervals (CIs). Results: A total of 339 valid questionnaires were returned. The results revealed that pathologists generally supported the performance of generative LLMs in clinical (mean 3.87, SD 0.96), research (mean 3.88, SD 1.09), and educational (mean 4.04, SD 0.82) contexts. Positive attitudes towards the use of generative LLMs were prevalent. Notably, pathologists practicing in less developed urban areas (OR=1.99, 95% CI=1.07 to 3.69, p=0.030), those with higher caseloads (>5000 cases/year; OR=2.12, 95% CI=1.01 to 4.44, p=0.047), and those engaged in research (OR=2.94, 95% CI=1.61 to 5.34, p<0.001) and teaching (OR=2.37, 95% CI=1.42 to 3.96, p=0.001) activities, as well as those with prior experience with generative LLMs (OR=2.45, 95% CI=1.38 to 4.37, p=0.002), showed a greater inclination towards future adoption. Conclusions: Chinese pathologists are receptive to generative LLMs, showing a positive inclination for their application. The study advocates for fostering the adoption of generative LLMs to improve the efficiency and accuracy of diagnosis, reduce the burden on pathologists, and improve the overall service level in the field of pathology.
Background: The growing use of technology means that there is a need for a framework that can evaluate the learners’ and educators’ acceptance of these technologies. In this context, the Technolog...
Background: The growing use of technology means that there is a need for a framework that can evaluate the learners’ and educators’ acceptance of these technologies. In this context, the Technology Acceptance Model (TAM) offers a valuable theoretical framework, providing insights into the determinants influencing the users' acceptance and adoption of technology. Objective: This study aims to systematically synthesize the body of research in medical education that employs the TAM. Methods: An electronic literature search was conducted using the PRISMA approach in February 2024 on the Embase, Medline, PyscINFO, PubMed, and Web of Science databases, yielding 680 articles. Upon elimination of duplicates and applying the exclusion criteria, a total of 39 articles were retained. To evaluate the quality of the study, the Medical Education Research Study Quality Instrument (MERSQI) score was calculated for each analysis with a qualitative component. Results: The review found that the studies using TAM only started in 2010, with the model relatively sparse until 2021. Most of the studies were quantitative, operationalizing the TAM as a survey instrument, but it was also used as a research framework in qualitative data analysis. SEM, descriptive analysis, and correlation analysis are the most common data analysis approaches in the study. E-learning and mobile learning were the predominant learning interventions explored, but there were indications that novel learning technologies such as augmented reality, virtual reality, and 3D printing were being investigated. Conclusions: The study's findings reveal an expanding scholarly engagement with the use of TAM in medical education. While the TAM has been mostly used as a survey instrument, it can also be adapted as a research framework to analyze data qualitatively. This systematic review provides a foundation for future research to understand the factors influencing users' acceptance of technology, especially in medical education. Clinical Trial: Not applicable
Background: Depression is a severe and prevalent mental disorder among youth that requires professional care, but various barriers hinder access to effective treatments. Chatbots, the latest innovatio...
Background: Depression is a severe and prevalent mental disorder among youth that requires professional care, but various barriers hinder access to effective treatments. Chatbots, the latest innovation in the research on digital mental health interventions (DMHIs), have shown potential in addressing these barriers. However, most studies on how to design chatbots to treat depression have focused on adult populations or on prevention among the general population. Objective: The current study aims to investigate the problems faced by youth with depression and their coping strategies as well as attitudes, expectations, and design preferences for chatbots designed to treat depression in youths. Methods: We conducted a mixed-methods study, compromising a questionnaire, a semi-structured interview, and a concurrent think-aloud session with a chatbot prototype with 14 youth with a current or remitted depressive episode. Results: Participants reported a wide range of problems beyond core depressive symptoms, such as interpersonal challenges, concerns about school and the future and problems with human therapists. Coping strategies varied, with most seeking social support or engaging in pleasant activities. Attitudes towards chatbots for depression treatment were predominantly positive, with participants expressing less anxiety about using a chatbot than seeing a human therapist. Participants showed diverse and partially contradictory design preferences. Design preferences included diverse dialogue topics, such as discussing daily life, acute problems and therapeutic exercises, as well as various preferences for the personality, language use and personalization of the chatbot. Conclusions: Our study provides a comprehensive foundation for designing chatbots that meet the unique needs and design preferences of youth with depression. The findings can inform the design of engaging and effective chatbots tailored to this vulnerable population.
Background: Pregnant people of color often report poor communication with their healthcare providers, yet there is limited understanding of how their experiences with both face-to-face and digital com...
Background: Pregnant people of color often report poor communication with their healthcare providers, yet there is limited understanding of how their experiences with both face-to-face and digital communication intersect and effect their care. Objective: The aim of this study was to explore pregnant people of color’s perceptions of communication with their providers, both in-person and via the patient portal, to identify barriers and facilitators to quality communication with their prenatal providers. Methods: Qualitative directed content analysis was completed on 4 open-ended questions inquiring about the facilitators and barriers to in-person and digital communication. The questions were part of a cross-sectional descriptive research study on respectful patient-provider communication and patient portal use in pregnant people of color. After completion of content analysis, frequency of categories was compared between groups based on age, gestational age, parity, insurance type and portal use. Results: The analysis of 375 responses from 130 pregnant people of color revealed both facilitators and barriers to quality communication in healthcare. Facilitators included two main categories: provider behaviors and the functionality of MyChart, the patient portal. The functionality of MyChart had three subcategories: the ability to send secure messages, ease of use, and portal notifications. Three categories were identified as barriers to quality communication: the quality of responses, dealing with multiple providers, and digital access and literacy. The quality of responses had two subcategories: slow response times and responses from staff other than the primary provider. Comparative analysis showed that pregnant people over the age of 35 and those with private insurance did not identify multiple providers as a barrier to quality communication. However, digital access and literacy were significant barriers for participants who did not use the patient portal, though it was less prominent among those less than 32 weeks gestation. Conclusions: Study participants expressed a preference for prompt responses and direct digital communication with their prenatal providers. To ensure digital health equity in pregnancy, it's crucial for providers to set clear expectations regarding response times, identify who will be responding to messages, and assess patients' digital literacy and access.
Background: The use of remote monitoring technology for patients with cardiac implantable electronic devices (CIED) is the standard of care as highlighted by international guidelines. However, remote...
Background: The use of remote monitoring technology for patients with cardiac implantable electronic devices (CIED) is the standard of care as highlighted by international guidelines. However, remote monitoring has not yet been integrated to universal, routine clinical practice. Objective: We aimed to identify barriers and enablers of routine implementation of CIED remote monitoring. Methods: We conducted semi-structured interview to explore the barriers and enablers encountered when incorporating remote monitoring to CIED management. Participants included a broad range of stakeholders including cardiologists, cardiac clinicians/physiologists, nurses and patients. Interviews were transcribed verbatim and analysed through inductive thematic analysis and deductive approaches. We used the theoretical domains framework to understand barriers and enablers through an implementation science lens. Our study aligns with the COnsolidated criteria for REporting Qualitative (COREQ) research checklist. Results: 35 interviews were conducted, including 16 patients, 10 cardiologists, and 9 cardiac physiologists and nurses. Five main themes and 13 subthemes were identified. The five main themes and the associated subthemes were 1) Patient benefits from remote monitoring, such as improved CIED and Cardiovascular management, and improved patient-centred care; 2) Insufficient allocation of CIED remote monitoring resources, which included insufficient funding and staffing, insufficient reimbursement, infrastructure and access inequity; 3) Suboptimal management of data which includes inconsistent workflow, lack of guidance for clinic staff and has resulted in an increased alert burden; 4) Insufficient patient education post-CIED implant, this was attributed to limited healthcare worker availability and resulted in inadequate patient knowledge and anxiety associated with remote monitoring; and 5) Patient engagement with CIED management, which included the need for increased patient interaction and ability to share data with patients. These subthemes were mapped to 6 specific domains of the theoretical domains framework: ‘Beliefs about capabilities’, ‘Environmental Context and Resources’, ‘Beliefs about consequences’, ‘Knowledge’, ‘Emotions’, and ‘Goals’. Conclusions: Patient engagement was identified in 3 of the 5 themes describing barriers and enablers to RM. These highlight the importance of addressing patient engagement with RM to better implement and integrate the use of RM into routine clinical practice. Barriers and enablers extend across multiple domains and suggest a multi-pronged approach is required to translate the gold standard care of remote monitoring to routine clinical practice.
Background: There is potential for digital mental health interventions to provide affordable, efficient, and scalable support to individuals. Digital interventions, including CBT, stress-management, a...
Background: There is potential for digital mental health interventions to provide affordable, efficient, and scalable support to individuals. Digital interventions, including CBT, stress-management, and mindfulness programs, have shown promise when applied in workplace settings. Objective: The aim of this study is to conduct an umbrella review of systematic reviews in order to critically evaluate, synthesise, and summarise evidence of various digital mental health interventions available within a workplace setting. Methods: A systematic search was conducted to identify systematic reviews relating to digital interventions for the workplace, using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA). The review protocol was registered in the Open Science Framework (OSF) https://doi.org/10.17605/OSF.IO/RC6DS
The following databases were searched: Pubmed, Web of Science, Medline, and Cochrane Library. Data was extracted using a pre-defined extraction table. To assess the methodological quality of a study, the AMSTAR-2 tool was used to critically appraise systematic reviews of healthcare interventions. Results: The literature search resulted in 4,122 records, which was reduced to 13 full-text systematic literature reviews with the use of Covidence to remove duplicates and screen titles and abstracts. The 13 included reviews were published between 2014 and 2023, comprising of eight systematic reviews and five systematic reviews and meta-analysis. AMSTAR-2 was used to complete a quality assessment of the reviews, the results were critically low (n = 7), and low (n = 6).
The most common types of digital intervention studied were cognitive behavioural therapy (CBT), mindfulness/meditation, stress-management followed by other self-help interventions. Effectiveness of digital interventions was found for many mental health symptoms and conditions in employee populations, such as stress, anxiety, depression, burnout and psychological wellbeing. Factors such as type of technology, guidance, recruitment, tailoring, and demographics were found to impact on effectiveness. Conclusions: This umbrella review aimed to critically evaluate, synthesise and summarise evidence of various digital mental health interventions available within a workplace setting. Despite the low quality of the reviews, best practice guidelines can be derived from factors that impact the effectiveness of digital interventions in the workplace.
Background: Immunochemotherapy has brought new hope for the first-line treatment of advanced gastric cancer(GC) patients; however, there is still a lack of simple and effective models to predict the e...
Background: Immunochemotherapy has brought new hope for the first-line treatment of advanced gastric cancer(GC) patients; however, there is still a lack of simple and effective models to predict the efficacy of immunochemotherapy in this setting. Objective: This study aimed to develop prognostic models and chose the better one to assess the benefit of first-line immunochemotherapy in patients with advanced GC. Methods: To predict the efficacy of first-line immunochemotherapy in advanced GC patients, we retrospectively collected clinical data at The First Affiliated Hospital of Nanjing Medical University between January 2018 and October 2023. The dataset was split into training (70%) and validation (30%) sets. Additionally, a temporal validation cohort between November 2023 and September 2024 was used to further assess model performance over time. Univariate and multivariate Cox regression, least absolute shrinkage and selection operator (LASSO) regression, and clinical experience were used to select significant features associated with the response of first-line immunochemotherapy in advanced GC patients. Two survival models, LASSO-Cox and Random Survival Forest (RSF) were developed using the training set. Model performance was evaluated on the validation set using an area under the curve (AUC), continuous concordance index, time-dependent receiver operating characteristic (ROC) curves, and calibration plots. Additionally, decision curve analysis(DCA) was performed to evaluate clinical utility, and Kaplan-Meier curves were used to compare survival outcomes. Results: In this study, we compared the performance of the RSF model and the LASSO-Cox model in predicting progression-free survival (PFS). The ROC curves showed that the RSF model significantly outperformed the LASSO-Cox model in the training and validation cohorts, with higher AUCs at 6, 12, and 18 months. Additionally, in the ROC curves for the temporal validation cohort, the RSF model demonstrated superior discriminatory ability compared to the LASSO-Cox model. Calibration curves indicated that the RSF model demonstrated good discrimination for PFS predictions. Continuous AUCs and C-index values consistently showed the RSF model's robust performance across different time points. In terms of clinical application, DCA curves demonstrated that the RSF model yielded greater net benefits compared to the LASSO-Cox model. We calculated risk scores for each patient using the RSF model, categorizing them into high-risk (risk score ≥ 55.42) and low-risk (risk score < 55.42) groups. Kaplan-Meier analysis revealed that the low-risk group had a significantly higher progression-free survival rate than the high-risk group, further highlighting the RSF model's importance in patient risk stratification. In summary, the RSF model exhibited superior accuracy and clinical utility in predicting PFS, particularly for long-term predictions compared to the LASSO-Cox model. Conclusions: This study retrospectively collected clinical data from advanced GC patients undergoing first-line immunochemotherapy and established LASSO-Cox and RSF models. By comparing the discrimination, calibration, and clinical utility of the two models across the training set, internal validation set, and temporal validation cohort, we found that the RSF model consistently outperformed the LASSO-Cox model. This highlights the RSF model's superior predictive accuracy and its potential to offer valuable insights for improving clinical decision-making in advanced GC.
Background: Rotator cuff (RC) disorders are the most common cause of shoulder pain, with a prevalence that increases with age. RC tears significantly impact patients' quality of life and pose a substa...
Background: Rotator cuff (RC) disorders are the most common cause of shoulder pain, with a prevalence that increases with age. RC tears significantly impact patients' quality of life and pose a substantial economic burden due to high surgical and rehabilitation costs. Traditional in-person rehabilitation can be challenging for many patients due to logistical barriers. Telerehabilitation, which delivers rehabilitation services remotely, has emerged as a potential alternative, yet its effectiveness for postoperative RC repair remains uncertain. Objective: The primary aim of our study is to evaluate the effectiveness of telerehabilitation for patients recovering from RC repair surgery. Methods: This study followed PRISMA guidelines for systematic reviews and meta-analyses. A comprehensive literature search was conducted across PubMed, EMBASE, MEDLINE, CENTRAL, CINAHL, and Web of Science for English-language publications up to July 1, 2024. Randomized controlled trials (RCTs) evaluating the effectiveness of telerehabilitation's effectiveness for postoperative RC repair were included. Data were extracted on study characteristics, interventions, outcomes, and risk of bias. The primary outcome was the Constant-Murley Shoulder Outcome Score (CM score) ; secondary outcomes included the Disabilities of the Arm, Shoulder, and Hand (DASH) score and, Visual Analogue Scale (VAS). Meta-analyses were conducted using a random-effects model. Results: The search yielded 1387 articles, reduced to 925 after excluding duplicates and ineligible records. Screening led to 33 full-text articles, of which 6 met inclusion criteria. The 6 RCTs included 388 participants post-RC repair, with various telerehabilitation interventions such as mobile applications, videotape, telephone calls, and gamification. PEDro scores ranged from 4 to 8 out of 10. Two studies were high risk and four had some concerns according to ROB2. No significant differences were found between telerehabilitation and control groups in CM score, DASH score, and VAS. Conclusions: Telerehabilitation is a viable alternative to traditional rehabilitation post-RC repair, showing comparable improvements in functional recovery and pain management. Further research is needed to standardize its implementation and assess long-term effects.
Background: Digital health (DH) interventions have increased across the past two decades, providing patients with alternative remote pathways to receiving healthcare services. Patients with major trau...
Background: Digital health (DH) interventions have increased across the past two decades, providing patients with alternative remote pathways to receiving healthcare services. Patients with major trauma frequently require long-term access to healthcare services to support their mental and physical health and their overall quality of life. DH interventions could help patients stay connected to rehabilitation services to enhance their health condition and regain their independence to enable them to return to the workplace and/or regain a role in society. There is a need to explore existing evidence on the effectiveness of DH interventions in improving health-related outcomes of patients with major trauma. Objective: This review aims to identify DH interventions that support physical and/or mental rehabilitation of patients who have been subject to major physical trauma. Methods: This review targets randomised controlled trials. Eligibility criteria include studies investigating DH interventions in adult patients with major traumatic physical injuries as end users of the intervention. Digital interventions that are delivered remotely and studies that report the impact of DH interventions on patients’ health-related outcomes will be included. The search strategy will be limited to time (since year 2000 to date) and to peer reviewed journals. No language restriction will be used, and articles that are not written in English will be translated. The search will be conducted in MEDLINE, EMBASE, AMED, CINAHL Plus, and PsycInfo. Grey literature, bibliographies of included studies and of relevant reviews will also be searched for potentially relevant articles. A minimum of two reviewers will independently screen retrieved references. Data extraction will be conducted by one reviewer and independently checked by another reviewer. Quality assessment of included studies will be conducted using the Cochrane RoB-2 tool. Any disagreements arising at any stage of the review will be resolved through discussion or by consulting a third reviewer where needed. A meta-analysis will be performed where possible, and a descriptive analysis of included studies will be reported. Results: Results will be available on completion of the review. Conclusions: The review findings will help identify existing evidence regarding DH interventions used to support physical and/or mental rehabilitation needs of patients with major trauma. This would help guide practitioners and policy makers to implement effective interventions to better support patient outcomes. The evidence synthesised from this review will also identify existing gaps and direct future research. Clinical Trial: Systematic review protocol is registered at PROSPERO International Prospective Register of Systematic Reviews (registration reference CRD42023485748).
Background: The mental health crisis among college students intensified amid the COVID-19 pandemic, suggesting an urgent need for innovative solutions to support them. Previous efforts to address ment...
Background: The mental health crisis among college students intensified amid the COVID-19 pandemic, suggesting an urgent need for innovative solutions to support them. Previous efforts to address mental health concerns have been constrained, often due to the underutilization and/or shortage of services. Mobile health (mHealth) technology holds significant potential for providing resilience-building support and enhancing access to mental health care. Objective: This study aimed to observe outcomes in health-related quality of life (HRQOL) among college students as the COVID-19 pandemic progressed over a three-year period, and whether the use of a positive psychology-based mHealth app (Roadmap app) was associated in these outcomes. Methods: A longitudinal study was conducted remotely from a large public academic institution in the Midwestern United States, evaluating mental health and well-being outcomes among college students using the Roadmap mHealth app over three fall semesters from 2020 to 2022. The study enrolled 2,164 college students in Year I, with 1,128 and 1,033 students returning in Years II and III, respectively. Participants completed various self-reported measures, including PHQ-9 for depression, GAD-7 for anxiety, and additional metrics for coping, flourishing, and loneliness. Results: Results indicated an evolving trajectory in students' mental health. Depression and anxiety levels were stable between Year I and Year II, later showing significant improvements by Year III (from Year I to Year III; P=0.005 and P=0.046, respectively). Problem-focused coping initially decreased from Year I to Year II (P<0.01), then increased between Years II and III (P=0.024), while emotion-focused and avoidant coping decreased continuously across all study years (from Year I to Year III; P<0.001 and P=0.02, respectively). Furthermore, decreases in loneliness (from Year I to Year III; P<0.001) were accompanied by increases in flourishing (from Year I to Year III; P<0.001). App usage analysis revealed that activities, such as Positive Piggy Bank and Gratitude Journal were most favored. Greater app engagement was positively correlated with enhanced flourishing, after adjusting for demographic and socio-behavioral characteristics (P=0.03). Conclusions: Over the three years, students' mental health and well-being improved, with notable reductions in depression, anxiety, and loneliness, associated with an increase in flourishing. The Roadmap mHealth app did not appear to worsen mental health outcomes for students. Based on the usage pattern, it is possible the app enhanced positive psychology-based practices. Future research should explore the efficacy of similar mHealth interventions through randomized controlled trials to further understand their impact on college students' mental health outcomes. Clinical Trial: ClinicalTrials.gov NCT04766788; https://clinicaltrials.gov/ct2/show/NCT04766788
Background: Surgical site infections (SSIs) are among the most common and serious complications following surgery, prolonging hospital stays and delaying patient recovery. Recent international consens...
Background: Surgical site infections (SSIs) are among the most common and serious complications following surgery, prolonging hospital stays and delaying patient recovery. Recent international consensus recommendations have identified evidence-based practices to reduce SSIs, but not how to apply them efficiently and in an interdisciplinary manner in the operating theatre. Therefore, further efforts are needed to identify and study the best interdisciplinary organisation to prevent SSIs. Objective: To map the extent, diversity and nature of research on interdisciplinary strategies to reduce SSIs and to analyse the impact of interdisciplinarity on the effectiveness of preventive interventions Methods: Using the JBI methodology for scoping reviews, the databases Embase (including MEDLINE and PubMed-not-MEDLINE), Cochrane Library will be searched, with manual searches of references cited in the included articles. Studies published in English or French only will be included.
Inclusion criteria: Based on the Participants, Concept, and Context (PCC) framework, the eligible population will include surgical teams. The concept of interest is interdisciplinary strategies to prevent the risk of infection. The context will be that of adult surgery in the operating room during turnover. Studies with experimental, quasi-experimental, pre-experimental, observational, case-control and cross-sectional designs will be considered. Results: Of the 1,679 articles identified, 45 were selected for in-depth analysis by four reviewers. The reading of the articles included will be completed by the end of October. Conclusions: Emerging interdisciplinary strategies show promising potential to prevent surgical site infections. This approach is part of a global project aimed at co-constructing a standard procedure during preoperative preparation in the operating room to reduce SSI. This literature review will be followed by a qualitative survey and a pre/post quasi-experimental quantitative study to assess its integration into current practice. Clinical Trial: The review protocol will be registered in Open Science Framework (OSF) on 2024.
Background: Access to mental health services continues to pose a global challenge, with current services often unable to meet the growing demand. This has sparked interest in conversational artificial...
Background: Access to mental health services continues to pose a global challenge, with current services often unable to meet the growing demand. This has sparked interest in conversational artificial intelligence (AI) agents as potential solutions. Despite this, the development of a reliable virtual therapist remains challenging, and the feasibility of AI fulfilling this sensitive role is still uncertain. One promising approach involves using AI agents for psychological self-talk, particularly within virtual reality (VR) environments. Self-talk in VR allows for externalizing self-conversation by enabling individuals to embody avatars representing themselves as both patient and counselor, thus enhancing cognitive flexibility and problem-solving abilities. However, participants sometimes experience difficulties progressing in sessions, which is where AI could offer guidance and support. Objective: This formative study aimed to assess the challenges and advantages of integrating an AI agent into self-talk in VR for psychological counseling. Methods: We carried out an iterative design and development of a system and protocol integrating LLMs within VR self-talk. In addition, we conducted an exploratory study in which 11 participants completed a session including: identifying a problem they wanted to address, attempting to address this problem using self-talk in VR, and then continuing self-talk in VR, but this time with the assistance of an LLM-based virtual human. The sessions were carried out with a trained clinical psychologist and were followed by semi-structured interviews. We used qualitative analysis after the interviews to code and develop key themes for the participants that addressed our research objective. Results: In total, four themes were identified regarding the quality of advice, the potential advantage of human-AI collaboration in self-help, the believability of the virtual human and other topics. The participants rated 8.3 out of 10 their desire to engage in additional such sessions, and more than half of the respondents indicated that they prefer using VR self-talk with AI rather than without it. Conclusions: This exploratory study suggests that the VR self-talk paradigm can be enhanced by LLM-based agents, how exactly to achieve this, potential pitfalls, and additional insights.
Background: Adverse drug reactions (ADRs) pose serious risks to patient health, and effectively predicting and managing them is an important public health challenge. Given the complexity and specifici...
Background: Adverse drug reactions (ADRs) pose serious risks to patient health, and effectively predicting and managing them is an important public health challenge. Given the complexity and specificity of biomedical text data, the traditional context-independent language model, Word2Vec, has limitations in fully reflecting the domain specificity of such data. Therefore, to predict drug-side effect relationships more accurately, we applied a Bidirectional Encoder Representations from Transformers (BERT) model specialized for biomedical applications. Objective: This study aimed to propose a method for extracting drug-side effect relationships from embedding vectors generated by biomedical language models, specifically BERT-based models pre-trained on biomedical corpora. This approach aims to overcome the limitations of the traditional Word2Vec model in accurately capturing complex relationships in biomedical data. Methods: Using data from 158,096 pairs of drug-side effect relationships from the Side Effect Resource (SIDER) database, we generated an adjacency matrix and calculated the cosine similarity between the word embedding vectors of drugs and side effects. Relation scores were calculated for a total of 8,235,435 drug-side effect pairs using this similarity. To evaluate the prediction accuracy of drug-side effect relationships, the area under the curve (AUC) value was measured using the calculated relation score and 158,096 known drug-side effect relationships provided by SIDER. Results: The clagator/biobert_v1.1 model achieved an AUC of 0.915 at an optimal threshold of 0.289, largely outperforming the existing Word2Vec model, which had an AUC of 0.848. The BERT-based model pre-trained on the biomedical corpus outperformed the vanilla BERT model, with an AUC of 0.857. Furthermore, external validation with the FDA Adverse Event Reporting System (FAERS) data, using Fisher’s exact test based on 8,235,435 predicted drug-side effect pairs and 901,361 known relationships, confirmed high statistical significance (P<.001) with an odds ratio of 4.830. Additionally, a literature review was conducted for predicted drug-side effect relationships. This review reveals that these relationships have been reported in recent studies published after 2016. Conclusions: This study introduces a method for extracting drug-side effect relationship data embedded in the pre-trained parameters of language models pre-trained on biomedical corpora and using this information to predict the probability of previously unknown drug-side effect relationships. We improved the accuracy of predicting drug-side effect relationships by using BERT-based models instead of the Word2Vec model. We found that BERT-based models pre-trained with biomedical corpora consider contextual information and achieve better performance in drug-side effect relationship prediction. External validation using the FAERS dataset combined with a literature review of certain cases confirmed high statistical significance, demonstrating the practical applicability of this approach. These results highlight the utility of natural language processing-based approaches for predicting and managing ADRs.
Background: Over the last 10-15 years, U.S. healthcare and the practice of medicine itself have been transformed by a proliferation of digital medicine and digital therapeutic (collectively, digital h...
Background: Over the last 10-15 years, U.S. healthcare and the practice of medicine itself have been transformed by a proliferation of digital medicine and digital therapeutic (collectively, digital health tool; DHT) products. While a number of DHT classifications have been proposed to help organize these tools for discovery, retrieval, and comparison by healthcare organizations seeking to potentially implement them, none have specifically addressed that organizations considering their implementation tend to approach the DHT discovery process with one or more specific outcomes in mind. An outcomes-based DHT ontology could therefore be valuable not only for health systems seeking to evaluate tools that influence certain outcomes, but for regulators and vendors seeking to ascertain potential substantial equivalence to predicate devices. Objective: Our objective was to develop, with the input of industry, healthcare, payer, regulatory, and patient input through the Accelerated Digital Clinical Ecosystem (ADviCE) consortium, an ontology specific to DHT outcomes, the Digital medicine Outcomes Value Set (DOVeS), and to make this ontology publicly available and free to use. Methods: From a starting point of a 4 generation deep hierarchical taxonomy developed by ADviCE, we developed DOVeS using the Web Ontology Language (OWL) through the open-source ontology editor Protégé, and data from 185 vendors who had submitted structured product information to ADviCE. We adhered to OBO Foundry principles and incorporated the MONDO Disease Ontology and the Ontology of Adverse Events (OAE). After development, DOVeS was field tested between December, 2022 and May, 2023 with 40 additional independent vendors previously unfamiliar with ADviCE or DOVeS; a process that continued until the top 4 generations of classes in the ontology received no further modification suggestions. As a proof of concept, we subsequently developed a prototype DHT Application Finder leveraging DOVeS to enable a user to query for DHT products based on specific outcomes of interest. Results: In its current state, DOVeS contains 42,320 and 9,481 native axioms and distinct classes respectively. These numbers are enhanced when taking into account the axioms and classes contributed by MONDO and the OAE. Conclusions: DOVeS is publicly available on BioPortal and Github, and has a Creative Commons license CC-BY-SA that is intended to encourage stakeholders to modify, adapt, build upon, and distribute it. While no ontology is complete, DOVeS will benefit from a strong and engaged user base to help it grow and evolve in a way that best serves DHT stakeholders and the patients they serve.
Background: Artificial Intelligence (AI) has the potential to transform medical education and research. However, in Omani medical institutions, AI adoption remains limited due to high costs, faculty t...
Background: Artificial Intelligence (AI) has the potential to transform medical education and research. However, in Omani medical institutions, AI adoption remains limited due to high costs, faculty training needs, and infrastructure challenges. Traditional research methods are less effective in managing the growing complexity of medical data. Objective: This innovation sought to improve data analysis and decision-making in Omani medical schools by integrating AI tools such as DataRobot and SAS Viya, aiming to enhance research efficiency and educational outcomes. Methods: The study adopted desktop research to map AI Integration gaps in the research process at Sultan Qaboos University (SQU) and other healthcare institutions in Oman. A benchmarking exercise comparing Omani medical schools and healthcare institutions with regional universities like the University of Sharjah College of Medicine and Western institutions such as Harvard Medical School was conducted. Results: A gap exists in Integrating AI Tools for data cleaning and preparation and data analysis in research process for medical schools and healthcare institutions in Oman, including SQU. AI tools reduced data processing times by 30% and improved research accuracy. Conclusions: AI integration in Omani medical education is both feasible and effective, offering significant improvements in research efficiency and educational outcomes. Continued investment in AI infrastructure and faculty development is critical for maximizing its potential in medical education. Clinical Trial: Not applicable
Background: In healthcare settings, nurse scheduling presents a significant challenge that impacts both patient care quality and nurse well-being. Traditional scheduling methods often neglect individu...
Background: In healthcare settings, nurse scheduling presents a significant challenge that impacts both patient care quality and nurse well-being. Traditional scheduling methods often neglect individual preferences and constraints, leading to dissatisfaction, burnout, and high turnover rates. The negative effects of inadequate scheduling practices, including restricted autonomy and lack of transparency, can adversely affect nurse morale and patient outcomes. Research indicates that flexible, participative scheduling approaches can mitigate these issues by incorporating nurse preferences and enhancing job satisfaction. Mathematical and AI-based scheduling methods offer potential solutions for optimizing scheduling practices and addressing these challenges. Objective: The aim is to develop a comprehensive framework for integrating nurses' preferences into nursing scheduling methods. This involves gathering detailed insights from nursing staff as well as supervisors and mapping these findings to mathematical and AI-based scheduling techniques. Methods: This study utilizes and summarizes results of focus group interviews in Swiss healthcare institutions that gain in-depth insights into nurses' experiences and preferences regarding staff scheduling. Interviews provided qualitative data, which were analyzed through open and axial coding to identify key themes. These themes are mapped here to relevant AI methodologies, including Mixed-Integer Programming, Constraint Programming, Genetic Programming, and Reinforcement Learning. Results: The interview study identified a strong demand for fair, participative scheduling systems that accommodate individual preferences and ensure transparency. AI-based scheduling is anticipated to improve efficiency and fairness, though concerns about system reliability and the loss of human oversight persist. Mapping key issues to AI methods indicates that these techniques could effectively address specific scheduling challenges, provided they are integrated holistically rather than applied individually, as is still frequently the case. Conclusions: Our work underscores the critical role of staff scheduling in healthcare settings and highlights the need for improvements. AI-based scheduling presents a promising solution, offering potential benefits such as increased accuracy, efficiency, and reduced administrative workload. However, it is essential to address concerns related to the limitations of AI, including its ability to fully accommodate individual preferences and the risk of over-reliance on technology.
Background: Ecological Momentary Assessment (EMA) is increasingly used to capture real-time data on well-being and time use in daily life, yet its feasibility in specific, particularly time-strained p...
Background: Ecological Momentary Assessment (EMA) is increasingly used to capture real-time data on well-being and time use in daily life, yet its feasibility in specific, particularly time-strained populations, such as parents, is not well understood. Objective: This study examines compliance rates and feasibility of EMA for measuring daily well-being and time use among parents. Methods: An explanatory mixed-methods study was conducted with 74 parents who completed baseline and follow-up online questionnaires after completing EMA surveys four times daily over one week, whereby a subset of parents were subsequently interviewed about their experience. Compliance and feasibility were analysed using a combination of quantitative and qualitative analyses. Results: Despite several aspects of the study design impeding feasibility—such as difficulties accommodating the 7:30 survey time point and challenges integrating daily surveys into individual routines—participants completed 82.5% of the daily surveys on average. Men showed significantly higher compliance than women. Participants generally found the survey frequency and length manageable, though some suggested longer or shorter study periods depending on their personal routines. Qualitative analysis revealed additional points for improvement, for instance, regarding the data collection format, and technical issues. Conclusions: The study demonstrates that, when accounting for certain sociodemographic and study design factors, EMA can be a feasible method for data collection regarding daily well-being and time use, even in highly time-constrained populations like parents, showing great potential for future research and complementing established methods (e.g., retrospective daily diaries). Clinical Trial: Open Science Framework: https://osf.io/8qj3d
Background: Digital technologies can substantially improve mental health care by facilitating measurement-based care through routine outcome monitoring. However, their effectiveness is constrained by...
Background: Digital technologies can substantially improve mental health care by facilitating measurement-based care through routine outcome monitoring. However, their effectiveness is constrained by the extent to which these technologies are used by services, clinicians, and clients. Objective: This study aims to investigate engagement with the Innowell platform, a measurement-based digital mental health technology (DMHT), to gain insights into the individual and service-level factors influencing engagement. Methods: Participants were 2,682 help-seeking clients from 12 Australian mental health services (11 headspace centers and one private practice, Mind Plasticity) wherein the Innowell platform was implemented. Although the initial implementation was standardized, services varied in their practical and continued use of the platform, as well as in the resources allocated to foster engagement. All participants completed an initial assessment during onboarding. Engagement here was defined as their ensuing completion of the summary questionnaire, designed for routine outcome monitoring. Participants were classified as ‘Initial Assessment Only’, 'Single Use' (one completion of the summary questionnaire), or '2+ Uses' (two or more completions). We analyzed engagement differences across services and associations between engagement and initial assessment scores. Results: Of the sample, 75.4% completed the initial assessment only, 11.5% had one completion of the summary questionnaire, and 13.0% had two or more completions. The service center was the strongest predictor of engagement, with Mind Plasticity participants showing over eight times higher engagement than other centers. At the individual level, higher scores in depression (P = .002), mania-like experiences (P = .047), suicide ideation (P = .004), hospitalization history for mental illness (P = .013), and physical activity (P < .001) were associated with increased engagement. Conversely, higher levels of anxiety symptoms (P = .011), substance misuse (P < .001), self-reported mental illness severity (P = .024), and social support (P = .047) predicted lower engagement. Age and several other clinical variables were not significant predictors when controlling for service-level factors. Conclusions: This study reveals that both individual and service-level factors significantly influence DMHT engagement, with the service center being the strongest predictor. This highlights the importance of service-level technology integration and support roles like Digital Navigators in fostering engagement. Significant variation in engagement among user groups indicates the need for a nuanced approach to measurement-based care. While mental illness generally did not impede engagement, self-perceived severity and anxiety symptoms were barriers. These findings underscore the critical importance of systemic factors and service-level integration strategies in driving DMHT engagement. User-centered designs remain important, but effective integration of DMHTs into existing mental health services is paramount for improving engagement across diverse user groups and clinical presentations. This multi-level approach – encompassing individual, service, and system-wide considerations – is essential for realizing DMHTs' full potential in delivering effective measurement-based care.
Background: Fibromyalgia is a prevalent musculoskeletal condition that incurs significant personal, social, and societal costs. Self-management, particularly in the areas of lifestyle, physical activi...
Background: Fibromyalgia is a prevalent musculoskeletal condition that incurs significant personal, social, and societal costs. Self-management, particularly in the areas of lifestyle, physical activity and in the cognitive and mental areas, plays an important role in fibromyalgia as pharmacological treatments often are not effective. Digital health applications are increasingly recognized as point-of-care to deliver and coordinate self-management programs to patients. However, the therapeutic content they offer is often inconsistent, lacks transparency, and may not be evidence-based. Objective: To elaborate an online self-management program for fibromyalgia patients based on current evidence and to explore optimization strategies. Methods: PubMed and Cochrane databases were searched for guidelines and systematic reviews of randomized controlled trials on self-management interventions for adults diagnosed with fibromyalgia or other nociplastic pain conditions. The AGREE II – GRS or the AMSTAR 2 tools were used to assess the selected studies. Self-management interventions considered had to be adaptable to a mobile application. Results: Thirty systematic reviews and eight guidelines were included in the analysis. Three categories of self-management interventions for fibromyalgia emerged: 1. Physical activity 2. Psycho-education and 3. Mind-Body exercises. While flexibility exercises did not demonstrate significant benefits, aerobic and resistance exercises showed potential in reducing fibromyalgia symptoms. Psycho-educative interventions, such as cognitive-behavioural therapies and educational intervention, are also considered to improve fibromyalgia symptoms. Mind-body therapies had mixed effects, with meditative movement therapies like Qi Gong, Tai Chi, and Yoga showing benefits, while meditation, hypnosis, and relaxation did not exhibit significant efficacy. Psycho-educative therapies in form of cognitive behaviour therapy (CBT) followed by physical exercise instructions were considered as the most suitable evidence-based content to be integrated in mobile health applications. Conclusions: Effective mHealth self-management programs for fibromyalgia patients should consist of tailored multicomponent interventions with proven evidence. Psycho-educative and physical activity interventions appear to be most adaptable for the integration in mobile health applications.
Background: Perinatal women are increasingly turning to digital media for maternal health information; however, concerns regarding the quality of this information persist. Understanding women's percep...
Background: Perinatal women are increasingly turning to digital media for maternal health information; however, concerns regarding the quality of this information persist. Understanding women's perceptions of information quality is essential for enhancing the effectiveness of information services. Objective: This review aims (1) to identify the key features that perinatal women focus on and prefer when perceiving the quality of maternal health information on digital media; (2) to summarize the quality issues with maternal health information on digital media that perinatal women have reported. Methods: A scoping review was conducted using databases including PubMed, Web of Science, Embase, Scopus, and ScienceDirect to synthesize research on perinatal women's perceptions of the quality of maternal health information available on digital media from 2000 to 2024. Data were synthesized using thematic analysis and reported according to the PRISMA-ScR guidelines. Results: From a total of 5290 records identified, 30 articles were selected for inclusion in this review. The perceived quality of information among perinatal women can be categorized into four distinct aspects: (1) quality of information providers, which encompasses two features: transparency and authority; (2) quality of information content, consisting of nine features: trustworthiness, evidence-based, timeliness, comprehensiveness, need-based relevance, practicality, motivational simulation, emotional supportiveness, and cultural sensitivity; (3) quality of information presentation, which includes three features: understandability, attractiveness, and conciseness; and (4) quality of information platforms, comprising 3 features: user-friendly navigation, proactive delivery, and interactivity. Furthermore, several perceived quality issues associated with these aspects are noteworthy. Specifically, (1) quality issues regarding information providers primarily pertain to their lack of credibility; (2) quality issues of information content encompass an overwhelming volume of information, inaccuracies, lack of scientific evidence, prevalence of contradictory information, insufficient breadth and depth, a mismatch between content and the needs of women, and information that induces negative emotions. (3) presentation issues manifest as difficulties in understanding the information; and (4) quality issues of information platforms include poor usability and the commercialization of these platforms. Conclusions: Our review identifies 17 key quality features across various dimensions that are valued by perinatal women. While there are similarities with quality indicators found in general health information, the unique quality features shaped by the specific characteristics of the perinatal population cannot be overlooked. These distinctive attributes highlight the importance of tailoring maternal health information to meet the unique needs and preferences of perinatal women.Although digital media information services offer many benefits, this study indicates that women are dissatisfied with the quality of existing maternal health information. Clearly, future efforts should focus on integrating perinatal women's perceptions of information quality to ensure ongoing improvements in information quality.
Background: Major depressive disorder (MDD) is one of the leading causes of disability and death by suicide globally. Unguided Internet-based cognitive behavioral therapy (ICBT), with the promise to i...
Background: Major depressive disorder (MDD) is one of the leading causes of disability and death by suicide globally. Unguided Internet-based cognitive behavioral therapy (ICBT), with the promise to improve accessibility and affordability, has been proven to be effective for MDD. However, few studies have examined the cost-effectiveness of unguided ICBT for MDD in low-resource countries and under non-specialist routine care. Objective: This study aimed to evaluate the short- and long-term cost-utility of unguided ICBT (named Morning Mood, a self-developed course on the WeChat Mini-program) compared to waiting-list control for persons suffering from MDD from the perspectives of society and healthcare system Methods: This cost-utility analysis was implemented alongside an 8-week 2-arm pragmatic randomized controlled trial with a 12-month follow-up conducted in Shenzhen City, China (Trial Registration: ChiCTR2100046425). Outcome data including cost and health utility were collected at baseline or pre-treatment, post-treatment, 3, 6, and 12 months after the intervention. Both societal and healthcare system perspectives were adopted. Direct medical costs and indirect costs were prospectively collected through the hospital information system and the Sheehan Disability Scale. Health outcome was measured by the Chinese version of SF-6Dv2. The primary outcome was incremental cost-utility ratio (ICUR), expressed as the difference in costs between two therapies by the difference in quality-adjusted life years (QALYs). Seemingly unrelated regression and the bootstrap method were performed to estimate adjusted ICURs and the corresponding 95% confidence intervals. Cost-effectiveness planes and cost-effectiveness acceptability curves were used to demonstrate the uncertainty of the results. A series of scenario analyses were conducted to verify the robustness of base-case results. Results: A total of 244 participants with MDD were randomly allocated to the ICBT (n=122) or the waiting-list (n=122) group. In the base-case analysis, the adjusted ICURs at post-treatment were respectively -194,720.38 and 49,700.33 Chinese Yuan (CNY) per QALY from societal and healthcare system perspectives, with the probability of unguided ICBT being cost-effective of 75.93% and 54.40% if the willingness-to-pay (WTP) was set at 1 time per capita gross domestic product. In scenario analyses, the probabilities respectively increased to 76.85% and 77.61%, indicating the potential of ICBT to be cost-effective over the long term from both the perspectives of society and healthcare system. Conclusions: Unguided ICBT is a cost-effective treatment for MDD. This intervention not only helps patients with MDD to improve clinically but also generates societal savings. These findings provide the health economic evidence for a potential scalable MDD treatment method in developing countries. Clinical Trial: Chinese Clinical Trial Registry (ChiCTR2100046425); https://tinyurl.com/bdcrj4zv
Background: According to the World Health Organization (WHO), coronary artery disease (CAD), which is in the group of non-communicable diseases, is one of the most important causes of mortality in dev...
Background: According to the World Health Organization (WHO), coronary artery disease (CAD), which is in the group of non-communicable diseases, is one of the most important causes of mortality in developed and developing countries, and its prevalence is increasing (1,2). It is seen that 45% of all deaths in our country are from cardiovascular diseases (CVD), and 36% (including 32% from CAD) are from heart diseases (3). Cardiac rehabilitation (CR) includes individually planned, supervised exercise interventions, medical assessments, risk profiling, education and counseling, and pharmacological and non-pharmacological interventions for cardiac patients. It is defined as a comprehensive and long-term program aiming to maximize the quality of life of cardiac patients in terms of physical, physiological, psychological, social, and work efficiency (4). The basic building block of the cardiac rehabilitation program, which is also used in treating coronary artery diseases, is aerobic exercise (5,6). Aerobic exercise can be performed intervally or continuously (7). Continuous exercise training is the more well-known type of exercise that continues at a constant value. In interval exercise training, in contrast to continuous exercise training, exercise is followed by intervals of exercise and recovery periods. Both types of exercise are recommended in cardiac rehabilitation by the European Society of Cardiology and the European Association for Cardiovascular Prevention and Rehabilitation (8). In the literature, aerobic exercise training has been frequently used in treating coronary artery disease; however, studies examining the effect of aerobic exercise types on this disease have yet to be included. With the idea that patients may better tolerate interval training, our aim in this study was to investigate whether the application of a personalized exercise program in the form of interval and continuous aerobic training is superior to each other in increasing the exercise capacity and quality of life of the patient. Objective: This research compares the effects of interval and continuous aerobic training on people's quality of life and exercise capacity. Methods: The participants are diagnosed with coronary artery disease, aged between 40- 80, and have no mental or physical disability to join in the research. The participants" demographic info and clinical stories were recorded. We used the symptom-limited and six-minute walking tests (6DWT) to evaluate exercise capacity. We evaluate the quality of life by using Short Form-36 (SF-36). All evaluation tests are done before and after training. Participants were randomly divided into two groups: interval aerobic training (IAE) and continuous aerobic training (CAE). The training lasted three times a week for six weeks. Results: In both groups, significant changes were found in evaluation test scores after the rehabilitation program (p<0,05). However, only the IAE group had significant statistical differences compared to the CAE group regarding test time and 6DYT scores. After training, the CAE group showed significant statistical change in every SF-36 parameter, while the IAE group showed significant values except energy/fatigue (p<0,05). The IAE group has statistically significant changes compared to the CAE group on the parameters: physical function, role limitations due to physical function, role limitations due to emotional function, and general health (p<0,05). Conclusions: Although both training methods benefitted cardiac rehabilitation, interval aerobic training was superior in some assessment parameters and was better tolerated than continuous aerobic training. For this reason, it was concluded that increasing patients' exertion capacity would be more helpful. Clinical Trial: clinical trails number of the article study retrieved from NCT06525233.
Background: Chronic pain, an unpleasant sensory and emotional experience lasting over six months, affects a large proportion of the global population and significantly impacts health and quality of li...
Background: Chronic pain, an unpleasant sensory and emotional experience lasting over six months, affects a large proportion of the global population and significantly impacts health and quality of life. Certain diseases cause chronic pain, resulting in a social and medical misunderstanding that intensity the patient’s emotional suffering. In recent years, the social media platform Twitter, now called “X,” has become a valuable resource for research and discussion on chronic pain, providing an accessible environment for communication and information exchange. Objective: To analyze content on Twitter related to fibromyalgia, headache, paraplegia, neuropathy, and multiple sclerosis, as well as characterize the profile of users involved in these conversations, identify prevalent topics, measure public perception, evaluate treatment efficacy, and detect discussions related to the most frequent non-medical issues. Methods: 72,874 tweets in English and Spanish containing pre-specified keywords were collected between 2018 and 2022. A manual review was conducted on 2,500 tweets, and the larger subset was classified by machine learning methods. Subsequently, tweets related to chronic pain conditions were analyzed to examine their medical and non-medical content, types of X users, the origin of the disease, and the efficacy of treatments. Results: Of the total tweets collected, 55,451 (76,1%) were classifiable. The most active users were healthcare professionals and institutions. The primary perceived etiology was pharmacological, and higher treatment efficacy was noted in neuropathy, paraplegia, and multiple sclerosis. Regarding non-medical content, there were more tweets related to the definition and understanding of the disease. Conclusions: Social media platforms, such as X, are playing a crucial role in the dissemination of information on chronic pain. Discussions largely focus on the available treatments and the need to enhance public education, utilizing these platforms to correct misconceptions and provide better support to patients.
Background: The Digital Education platform, DoctorviceⓇ (iKooB Inc., Seoul, South Korea), offers both physicians' face-to-face education and remote glucose monitoring, which is expected to be effect...
Background: The Digital Education platform, DoctorviceⓇ (iKooB Inc., Seoul, South Korea), offers both physicians' face-to-face education and remote glucose monitoring, which is expected to be effective for personalized diabetes care. Objective: To evaluate the effectiveness of the digital education platform for diabetes care and compare cases where both face-to-face education and remote monitoring were provided with cases where only education was provided. Methods: Sixty-six patients with type 2 diabetes mellitus who visited the Diabetes Center of Seoul St. Mary’s Hospital were enrolled in this randomized clinical study. Participants were aged ≥19 years and had hemoglobin A1C (HbA1C) levels of 7.5–9.5%. Of the 66 participants, 26 in the intervention group and 30 in the control group were analyzed, excluding 10 who dropped out of the study. In the intervention group, physicians used the digital education platform to provide face-to-face education at enrollment and at the 3- and 6-month visits, along with remote monitoring during the first 3 months of the 6-month study period. The control group received conventional outpatient education. The primary endpoint was the change in the HbA1c levels. Results: The baseline HbA1c levels were 8.3±0.6% in the intervention group and 8.0±0.5% in the control group. At the 3-month follow-up, HbA1c decreased by 0.5% to 7.8±0.9% (P=.010) in the intervention group and by 0.2% to 7.8±0.7% in the control group. HbA1c levels significantly improved during the first 3 months with both face-to-face education and remote glucose monitoring; however, HbA1c tended to increase without the remote monitoring service during the 3 to 6-month follow-up in the intervention group. Subgroup analysis indicated that the effect of reducing HbA1c was greater for patients with baseline HbA1c levels≥8.0%, those aged≥65 years, smokers, drinkers, and those with obesity in the intervention group. Conclusions: The digital education platform for personalized diabetes management appears beneficial for glycemic control in type 2 diabetes mellitus. It was especially effective when physicians provided personalized face-to-face education and remote feedback together. Clinical Trial: KCT0007953
Background: Artificial Intelligence (AI) has the potential to revolutionize healthcare by enhancing both clinical outcomes and operational efficiency. However, its clinical adoption has been slower th...
Background: Artificial Intelligence (AI) has the potential to revolutionize healthcare by enhancing both clinical outcomes and operational efficiency. However, its clinical adoption has been slower than anticipated, largely due to the absence of comprehensive evaluation frameworks. Existing frameworks remain insufficient and tend to emphasize technical metrics like accuracy and validation, while overlooking critical real-world factors such as clinical impact, integration, and economic sustainability. This narrow focus prevents AI tools from being effectively implemented, limiting their broader impact and long-term viability in clinical practice. Objective: This study aimed to create a comprehensive framework for assessing AI in healthcare, extending beyond technical metrics to incorporate social and organizational dimensions. The framework was developed by systematically reviewing, analyzing, and synthesizing the evaluation criteria necessary for successful implementation, focusing on the long-term real-world impact of AI in clinical practice. Methods: A comprehensive search was performed in July 2024 across PubMed, Cochrane, Scopus, and IEEE Xplore databases to identify relevant studies published in English between January 2019 and mid-July 2024, yielding 3528 results, of which 44 studies met the inclusion criteria. The systematic review followed PRISMA guidelines and the Cochrane Handbook for Systematic Reviews to ensure a systematic approach. Data were analyzed using NVivo (QSR International) through thematic analysis and narrative synthesis to identify key emergent themes in the studies. Results: By synthesizing the included studies, we developed a framework that goes beyond the traditional focus on technical metrics or study-level methodologies. It integrates clinical context and real-world implementation factors, offering a more comprehensive approach to evaluating AI tools. With our focus on assessing the long-term real-world impact of AI technologies in healthcare, we named the framework AI for IMPACTS. The criteria are organized into seven key clusters, each corresponding to a letter in the acronym: (I) integration, interoperability and workflow (M) monitoring, governance, and accountability (P) performance and quality metrics (A) acceptability, trust, and training (C) cost and economic evaluation (T) technological safety and transparency (S) scalability and impact. These are further broken down into 32 specific sub-criteria. Conclusions: The AI for IMPACTS framework offers a holistic approach to evaluating the long-term real-world impact of AI tools in the heterogeneous and challenging healthcare context, but further validation through expert consensus and testing of the framework in real-world healthcare settings would strengthen the findings. It is important to emphasize that multidisciplinary expertise is essential for thorough assessment, yet many assessors lack the necessary training. Additionally, traditional evaluation methods struggle to keep pace with AI's rapid development. To ensure successful AI integration, flexible, fast-tracked assessment processes and proper assessor training are needed that maintain rigorous standards while adapting to AI’s dynamic evolution. Clinical Trial: NA
Background: OBJECTIVE: To observe the clinical safety, tolerability, pharmacokinetics and preliminary efficacy of lipo-HK for injection as a monotherapy in patients with recurrent high-grade glioma an...
Background: OBJECTIVE: To observe the clinical safety, tolerability, pharmacokinetics and preliminary efficacy of lipo-HK for injection as a monotherapy in patients with recurrent high-grade glioma and to provide the basis for drug dose and method of administration.
Methods: Patients with recurrent high-grade glioma were screened according to inclusion and exclusion criteria. A total of 5 experimental dose groups were included. The initial dose was 80 mg, and the dose was escalated according to the modified Fisher method, and the highest dose was 420 mg. Each patient received only one dose of administration. This clinical trial consists of two phases - a dose escalation phase and a dose expansion phase. The dose escalation phase includes a single-dose period (1 day of single dose, followed by three days of observation), multiple-dose period (5 days of continuous dosing per week, two days off, three weeks, one week off) and multiple-dose extension periods (3 weeks of multiple doses, one week of rest, then three weeks of additional doses, each week for five consecutive days and two days off). The dose-expansion phase consists of single-dose period and multiple-dose period. If the patient tolerates during the single-dose period, they could enter the multiple-dose period. If the patient gets clinical benefits from HK under clinical evaluation after the multiple dosing period, the patient could enter the multiple extended dosing period. Clinical safety was assessed using NCI CTCAE 4.03 criteria, and RANO criteria were used to evaluate the efficacy.
Results: A total of 24 patients were enrolled in this clinical study. The clinical symptoms of many subjects improved after the drug was administered, and the clinical effects of 10 subjects were evaluated as "Stable disease" after multiple administration periods.Long-term use is well tolerated by patients.
Conclusion: lipo-HK for injection is clinically safe and well tolerated in the treatment of patients with recurrent high-grade glioma. The recommended dose for subsequent studies is 420 mg. Objective: To observe the clinical safety, tolerability, pharmacokinetics and preliminary efficacy of lipo-HK for injection as a monotherapy in patients with recurrent high-grade glioma and to provide the basis for drug dose and method of administration. Methods: Patients with recurrent high-grade glioma were screened according to inclusion and exclusion criteria. A total of 5 experimental dose groups were included. The initial dose was 80 mg, and the dose was escalated according to the modified Fisher method, and the highest dose was 420 mg. Each patient received only one dose of administration. This clinical trial consists of two phases - a dose escalation phase and a dose expansion phase. The dose escalation phase includes a single-dose period (1 day of single dose, followed by three days of observation), multiple-dose period (5 days of continuous dosing per week, two days off, three weeks, one week off) and multiple-dose extension periods (3 weeks of multiple doses, one week of rest, then three weeks of additional doses, each week for five consecutive days and two days off). The dose-expansion phase consists of single-dose period and multiple-dose period. If the patient tolerates during the single-dose period, they could enter the multiple-dose period. If the patient gets clinical benefits from HK under clinical evaluation after the multiple dosing period, the patient could enter the multiple extended dosing period. Clinical safety was assessed using NCI CTCAE 4.03 criteria, and RANO criteria were used to evaluate the efficacy. Results: A total of 24 patients were enrolled in this clinical study. The clinical symptoms of many subjects improved after the drug was administered, and the clinical effects of 10 subjects were evaluated as "Stable disease" after multiple administration periods.Long-term use is well tolerated by patients. Conclusions: lipo-HK for injection is clinically safe and well tolerated in the treatment of patients with recurrent high-grade glioma. The recommended dose for subsequent studies is 420 mg.
Background: Men who have sex with men face high HIV prevalence globally. In Brazil, the prevalence among MSM is over 15%. Strategies such as pre-exposure prophylaxis (PrEP) are crucial to reduce HIV t...
Background: Men who have sex with men face high HIV prevalence globally. In Brazil, the prevalence among MSM is over 15%. Strategies such as pre-exposure prophylaxis (PrEP) are crucial to reduce HIV transmission. However, increasing PrEP coverage and adherence is challenging due to stigma, changes in risk perception, and difficulty in maintaining regular clinical follow-up. Objective: We analyzed the perceptions and experiences of users and healthcare professionals about PrEP clinical follow-up via asynchronous remote consultations (telePrEP) in five PrEP services in three Brazilian regions. Methods: We conducted 19 interviews with users and six interviews with healthcare professionals. The interviews addressed motivations and experiences with in-person and remote PrEP and were thematically analyzed using the QSR Nvivo® software. Results: In summary, users, primarily cisgender men, positively evaluated telePrEP and highlighted practicality, autonomy, and reduced stigma as benefits of telePrEP. They reported less embarrassment when sharing personal information remotely and the convenience of avoiding frequent trips to healthcare facilities. Healthcare professionals, on the other hand, expressed concerns about losing connection with patients and potentially reducing the quality of care due to the lack of face-to-face interactions. Conclusions: The successful implementation of telehealth services for PrEP should consider these different perceptions to adequately meet both groups' needs. Additional studies are needed to explore implementation in other contexts and improve healthcare professionals' training to deal with the specificities of PrEP care.
In response to the proposal of Tsafnat et al. to converge towards three open health data standards, this viewpoint provides a critical reflection on the proposed alignment of using openEHR, FHIR and O...
In response to the proposal of Tsafnat et al. to converge towards three open health data standards, this viewpoint provides a critical reflection on the proposed alignment of using openEHR, FHIR and OMOP as the default standards for clinical care and administration, data exchange and longitudinal analysis, respectively. We argue that open standards are a necessary but not sufficient condition to achieve health data interoperability. The ecosystem of open source implementations needs to be considered when choosing an appropriate standard for a given context. We discuss two specific contexts, namely standardization of i) health data for federated learning, and ii) health data sharing in low- and middle income countries (LMICs). Specific design principles, practical considerations and implementation choices for these two contexts are described, based on ongoing work in both areas. In the case of federated learning, we observe convergence towards OMOP and FHIR, where the two standards can effectively be used side-by-side given the availibility of mediators between the two. In the case of health information exchanges in LMICs, we see a strong convergence towards FHIR as the primary standard, with as yet limited adoption of OMOP and openEHR. We propose practical guidelines for context-specific adaptation of open standards.
Background: The greed of e-cigarette manufacturers including economic, capitalist, incentive, cultural, moral, psychological, and philosophical dimensions, contributed to the origin and development of...
Background: The greed of e-cigarette manufacturers including economic, capitalist, incentive, cultural, moral, psychological, and philosophical dimensions, contributed to the origin and development of vaping greed and shaped users' behaviors. Objective: Vaping greed is manifested in the large market share taken by the companies, but these all significantly harm users' health and the communities. Methods: This is involved via social media perception of adolescents and teenagers as an individual or in a group. The addiction could be transgenerational and can induce trauma both at an individual level and a community level Results: It is important to identify the greed and public health perceptions, and measures are taken to treat the symptoms of the greed by educating the users and making them aware of their unfulfilled needs to regain authenticity and establish an infallible authority to enforce universal morality. Conclusions: This will eradicate the complications of addiction and the root of such capitalists’ greed for tobacco/nicotine perception, addiction, and marketing.
The Metaverse is a virtual shared space that combines virtual reality (VR), augmented reality (AR) and blockchain technology to create an immersive social and interactive experience. In the medical fi...
The Metaverse is a virtual shared space that combines virtual reality (VR), augmented reality (AR) and blockchain technology to create an immersive social and interactive experience. In the medical field, Metaverse can provide simulation training, patient education, remote diagnosis and treatment and other functions to promote the interaction between doctors and patients.
Smart medical care uses advanced data analysis, artificial intelligence (AI), Internet of Things (IoT) and other technologies to improve the efficiency and accuracy of medical services. Smart medical care can achieve personalized diagnosis and treatment, real-time monitoring and predictive analysis, and improve patient health management.
The combination of the two has the potential to change the traditional medical model and make medical services more convenient, accessible and efficient. For example, patients can have virtual medical consultations in the metaverse, and doctors can use smart medical tools for diagnosis and treatment. This not only improves the utilization of medical resources, but also enhances patients' sense of participation and satisfaction. In the future, with the further development of technology, the integration of Metaverse and smart medical care will likely create a new medical experience and service model.
Background: Young adults (18-29 years) have lower COVID-19 vaccination rates than older adults, indicating a need for tailored strategies. Gamification has the potential to boost vaccine knowledge and...
Background: Young adults (18-29 years) have lower COVID-19 vaccination rates than older adults, indicating a need for tailored strategies. Gamification has the potential to boost vaccine knowledge and intentions, but its real-world impact on young adults remain underexplored. Objective: To examine the effectiveness of a digital health game, COVID Chronicles, in influencing COVID-19 vaccine intention among young adults. Methods: COVID Chronicles was advertised through QR-codes at public transit, local merchandises and online. The game was based on the Transtheoretical Model of change. Users selected statements according to their intention to be vaccinated and were directed to simple games (true/false, multiple choice, chance) using content tailored according to their vaccine intention. While anyone could play, only those who self-identified as a young adult were invited to participate in the study and asked to provide demographic information, rank their vaccination intention due to the game on a five-point Likert scale (from very unlikely to very likely) and participate in a two-month follow-up. Ordinal logistic regression model assessed the association between participants’ stated likelihood of change in vaccination intention due to gameplay with various participant characteristics. Results: Between May 2022 to July 2023, COVID Chronicles was initiated 6,295 times with 5,058 completions (80.3%) with unique completions based on submitted emails. Of these, 1,174 (26.6%) self-identified as a young adult and responded to the question on vaccine intention due to playing the game. Of those, 75.8% were fully vaccinated. Overall, 40.9% indicated COVID Chronicles either likely or very likely influenced their likelihood to be vaccinated (vaccine intention). The ordinal logistic regression showed that people who belonged to ethnic minorities, including Asian (OR 2.16, CI: 1.66-2.80), Indigenous (OR 2.69, CI:1.33-5.43) and Latinx (OR = 3.48, CI:2.20-5.51) participants were more likely to report the game influenced their willingness to be vaccinated compared to White (reference group) participants. Participants with a Bachelor’s degree (OR = 0.28, CI: 0.14-0.56), Master’s degree (OR = 0.25, CI: 0.11-0.55), and Doctorate degree (OR = 0.24, CI: 0.09-0.68), were less likely to report the game influenced their willingness to be vaccinated compared to participants with less than a high school education (reference group). Participants who agreed that vaccines are safe and effective were more likely to report that the game influenced their vaccination intentions. Conclusions: Using gamification strategies, COVID Chronicles influenced vaccine intention and was particularly effective among people who identify as members of ethnic minority groups and people with less than high school education attainments. Clinical Trial: N/A
Objective: The purpose of this article was to advance understanding of potential barriers to patient portal adoption, explore willingness to adopt an electronic portal, and examine differences between...
Objective: The purpose of this article was to advance understanding of potential barriers to patient portal adoption, explore willingness to adopt an electronic portal, and examine differences between language preferences.
Materials and Methods: English and Spanish-speaking patients (N=107) were surveyed from a community clinic. Linear and logistic regressions were performed to predict the probability that patients would adopt the patient portal.
Results: Only 65% of participants said they envisioned themselves using the patient portal. Participants reported barriers such as stronger preference for in-person communication with their physician, concerns about privacy, language difficulties, lack of comfort with portals, and poor design. Spanish-speaking patients were more willing to get e-info about medication reminders, diagnostic, and vital signs, than English speakers.
Conclusion: Understanding cultural differences and empowering patients to have more autonomy over their health and decision-making leads to a more meaningful experience with their physicians potentially overcoming low health literacy-related barriers.
Alarm fatigue, a multifactorial desensitization of staff to alarms, can harm both patients and healthcare staff in intensive care units (ICU), especially due to false and non-actionable alarms. Increa...
Alarm fatigue, a multifactorial desensitization of staff to alarms, can harm both patients and healthcare staff in intensive care units (ICU), especially due to false and non-actionable alarms. Increasing amounts of alarm and routinely collected ICU patient data are paving the way for training machine learning (ML) models that may be able to reduce the number of non-actionable alarms and thus alarm fatigue. Today, however, there exists no publicly available dataset or process that routinely collects information on alarm actionability, whether an alarm triggered a medical intervention or not—a key feature for developing meaningful ML models for alarm management. Case-based manual annotation is too slow and resource intensive for large amounts of data. In a multidisciplinary, consensus-based approach, we defined pre-processing steps and a rule-based annotation method to classify alarms as either actionable or non-actionable based on data from the patient data management system. Our annotation method will serve in the future to semi-automatically, retrospectively, and time-savingly label large amounts of alarms using patient data to generate annotated datasets for ML models in alarm fatigue research. We present our experience in developing the annotation method and provide resources that we generated, such as rule sets and data mappings. These could be used by others to prepare data for future ML projects, even beyond the topic of alarms.
Background: The growing global emphasis on combating infectious diseases has highlighted the need for detailed analyses of outbreak patterns over time. Mpox, formerly known as monkeypox, remains a cri...
Background: The growing global emphasis on combating infectious diseases has highlighted the need for detailed analyses of outbreak patterns over time. Mpox, formerly known as monkeypox, remains a critical public health challenge in Nigeria, with significant outbreaks occurring between 2017 and 2024. Understanding the trends in Mpox cases, deaths, and geographical spread provides valuable insights into the effectiveness of public health interventions, regional disparities, and demographic vulnerabilities. These findings are essential for informing ongoing and future efforts to mitigate Mpox outbreaks and improve national outbreak preparedness. Objective: This study aims to analyze the progression of Mpox outbreaks in Nigeria, focusing on trends in confirmed and suspected cases, deaths, and geographic distribution across states from 2017 to 2024. Additionally, the study explores changes in age and gender-specific vulnerabilities, evaluates the impact of public health interventions, and assesses the reduction in disease burden between 2022 and 2024. Methods: A multi-faceted approach was employed, leveraging epidemiological data on Mpox cases from 2017 to 2024. Year-on-year comparisons of confirmed and suspected cases, fatalities, and their geographical distribution were performed to identify trends in disease progression and containment. Geospatial mapping techniques were used to examine regional disparities in Mpox case distribution. Demographic analysis explored shifts in age and gender vulnerabilities, while public health intervention outcomes were assessed based on reductions in cases and geographic spread. Results: The comparative analysis from 2017 to 2024 revealed a significant 47% reduction in confirmed Mpox cases between 2023 and 2024, coupled with a notable decrease in both fatalities and geographic spread. Age-based analysis indicated a decline in disease vulnerability across younger age groups, while middle-aged males continued to show a relatively higher infection rate. A dramatic surge in cases occurred in 2022, with 762 confirmed cases, representing the peak of the outbreak. However, cases dropped significantly to 98 in 2023 and further to 40 in 2024, highlighting the success of recent public health interventions. Regional disparities remained evident, with certain states consistently showing higher case burdens, while others experienced reductions in cases, suggesting varied efficacy of local interventions. Geospatial analysis pinpointed persistent hotspots from 2017 to 2022, but a more contained spread was observed in 2023 and 2024. Additionally, gender analysis showed a consistent male predominance in cases across most age groups, with disparities becoming more pronounced in younger populations. Conclusions: The sharp reduction in Mpox cases and geographical spread from 2022 to 2024 reflects the positive impact of targeted public health interventions, including vaccination and containment strategies. However, persistent regional and gender disparities suggest that certain populations remain at higher risk, warranting continued monitoring and tailored interventions. Sustained efforts are necessary to prevent future outbreaks, maintain the progress achieved in reducing Mpox cases, and address the factors contributing to these disparities. To further reduce Mpox transmission and prevent future outbreaks, it is essential to strengthen disease surveillance systems in regions identified as consistent hotspots, ensuring rapid detection and response. Public health interventions should be tailored to address gender disparities, particularly the higher infection rates observed among males, while expanding vaccination campaigns and health education initiatives in high-burden areas. Additionally, targeted efforts must investigate the behavioral and biological factors contributing to male vulnerability, especially among younger populations. Sustained focus on these strategies will be critical to maintaining the progress achieved and closing the gaps in disease control. This study provides a comprehensive, multi-year analysis of Mpox outbreaks in Nigeria, offering critical insights into the effectiveness of public health interventions, regional disparities, and demographic trends. The findings underscore the importance of geospatial data in understanding disease distribution and controlling infectious outbreaks. The significant case reduction from 2022 to 2024 highlights the success of ongoing public health measures, while also emphasizing the need for continuous monitoring and adaptive strategies to maintain and further improve disease control.
Background: Modern healthcare systems worldwide are facing challenges, and digitalization is viewed as a means to strengthen healthcare globally. As digitalization in healthcare demands adjustments in...
Background: Modern healthcare systems worldwide are facing challenges, and digitalization is viewed as a means to strengthen healthcare globally. As digitalization in healthcare demands adjustments in practices, policies, and workflows, assessing healthcare professionals' competencies is crucial for effective integration into their work environment. Objective: The aim of this study was to analyse how the attitudes, skills and knowledge of medical student concerning eHealth and healthcare digitalization have shifted from 2016 to 2022 in connection with the development of the national healthcare information system architecture utilizing the Clinical Adoption Meta-Model framework. Methods: The research population consisted of fifth-year medical students from one University in Finland during 2016, 2021 and 2022. A survey questionnaire was administered which comprised seven background questions and 16 statements measured on a five-point Likert scale assessing students’ attitudes towards eHealth and their digital capabilities. The results were recategorized into a dichotomous scale and presented using frequencies and percentages. The statistical analysis employed a Pearson’s chi-square test. Results: The study involved 215 medical students (n = 45 in 2016, n = 106 in 2021, and n = 64 in 2022). Overall, the medical students displayed positive attitudes towards the use of digital applications in healthcare. Knowledge about the national health information exchange service has significantly improved over time. Despite positive changes in skills and attitudes among students, recent observations also indicate a more reserved stance towards healthcare digitalization. Conclusions: There has been a positive shift in the digital competence and attitudes of medical students over the years, potentially influenced by the development of the national health information system architecture. Highlighting digital health topics and interdisciplinary teaching in basic medical education is essential to foster innovation and to ensure future doctors possess a high level of digital competence.
Background: Individuals with non-Western backgrounds consistently exhibit a higher risk of type 2 diabetes (T2D) compared with ethnic Danes. Factors such as health behavior, limited healthcare access,...
Background: Individuals with non-Western backgrounds consistently exhibit a higher risk of type 2 diabetes (T2D) compared with ethnic Danes. Factors such as health behavior, limited healthcare access, and social determinants of health often contribute to this disparity. Culturally sensitive interventions are crucial, yet effective interventions for managing T2D in non-Western populations re-main limited. Objective: This study examines the effect of a one-year person-centered and culturally sensitive intervention on improving glycemic control (HbA1c) among individuals with T2D and non-Western backgrounds. The secondary objectives are to improve diabetes management and overall well-being. Methods: The present study is designed as a two-arm randomized controlled trial. 96 women and men with T2D (HbA1c≥53 mmol/mol) speaking either Arabic, Turkish, or Urdu as their native language will be randomized for one year to an intervention group (person-centered and culturally sensitive course of treatment) or a control group (usual care) in a 1:1 ratio in Denmark. Assessments are scheduled at baseline and one year. The primary outcome is HbA1c while lipids, blood pressure, and patient-reported outcomes including well-being, diabetes management, health literacy, and use of and adherence to diabetes medication are secondary outcomes. Feasibility and satisfaction are evaluated using interviews. The study is approved by the Ethics Committee of the Capital Region of Denmark (H-23042245). Results: A 5.0 mmol/mol (0.5%-DCCT) change in HbA1c is the minimally important difference, requiring 88 participants. To allow for uncertainties and dropouts, the total was increased to 96. As of October 2024, 70 participants have been recruited, with recruitment ongoing until March 2025. Data collection will continue until December 2025, with the first results expected by March 2026. Conclusions: This study will contribute to the limited knowledge regarding the effects of person-centered and culturally sensitive treatment approaches for T2D in individuals with a non-Western background. The study employs a robust methodological design and will present an alternative avenue for man-aging T2D and improving overall well-being. The study offers valuable insights into the experiences of participants and healthcare professionals, including potential obstacles and strategies for implementation in outpatient clinics. Clinical Trial: Clinicaltrials.gov NCT06147245.
Background: Individuals living with rare conditions often face unique challenges, including difficulties in access diagnosis, treatment, and support. Digital health applications present an opportunity...
Background: Individuals living with rare conditions often face unique challenges, including difficulties in access diagnosis, treatment, and support. Digital health applications present an opportunity to support self-management for these individuals. However, understanding the specific requirements and preferences for such an app is crucial to ensure its effectiveness. Objective: The primary objective of this study was to identify the needs, preferences, and concerns related to the use of digital health applications for the self-management of rare diseases. This was achieved by gathering insights from key stakeholders, including individuals with rare conditions, their informal carers, healthcare professionals, and other stakeholders. Methods: A multi-methods approach, including co-creation and co-production techniques, was employed. The study utilized an online survey and a workshop to collect data. A total of 28 participants were involved (19 survey completions and 9 workshop participants). The survey and workshop aimed to gather participant perceptions regarding personal health data collection, data sharing preferences, concerns, and potential features for a digital health app tailored to rare conditions. Ethical approval was obtained from the University Research Ethics Committee. Results: Key findings revealed a strong desire for app features such as comprehensive symptom tracking, educational resources, and a platform for community connectivity. Participants expressed a willingness to contribute their personal health data to advance research into rare diseases and improve care, but they also showed reservations about the potential misuse of their data, particularly when sharing with companies. Identified requirements included a glossary of terms for specific rare diseases, symptom logging, connectivity with others having similar conditions, mental health support, and secure data handling. Conclusions: This study underscores the potential of digital health technology to significantly improve the management and understanding of rare conditions. Despite the small sample size, the study’s methodology and survey design offer valuable insights that can be applied in larger, more diverse populations. The research highlights the importance of incorporating user and stakeholder input in designing digital health solutions, ensuring these technologies are tailored to the unique needs of the rare disease community.
Background: User Demographics are often hidden in social media data due to privacy concerns. However, demographic information on Substance Use can provide valuable insights, allowing Public Health pol...
Background: User Demographics are often hidden in social media data due to privacy concerns. However, demographic information on Substance Use can provide valuable insights, allowing Public Health policymakers to focus on specific cohorts and develop efficient prevention strategies, especially during global crises like COVID-19. Objective: Our study aims to analyze Substance Use trends in User level across different demographic dimensions; such as Age, Gender and Race/Ethnicity, focusing on COVID-19 pandemic. The study also establishes a baseline for substance use trends using social media data. Methods: The study is carried out in large scale Twitter data in the English language over a 3 year period; 2019, 2020 and 2021, which comprises 1.05 billions of posts. Following preprocessing, the substance use posts were identified using our custom trained deep learning model (RoBERTa) that resulted in identification of 9 million Substance Use posts. Then, demographic attributes like User Type, Age, Gender, Race/Ethnicity, and Sentiment types, and emotions associated with each post were extracted via a collection of natural language processing modules. Finally, various qualitative analyses were performed to get the insight of user behaviors based on the demographics. Results: The highest level of usership in SU discussions was observed in 2020, with increases of 22.18% compared to 2019 and 25.24% compared to 2021. Throughout the study period, Male and Teenagers increasingly dominated the Substance Use discussions in all substances. During the pandemic, Prescription Medication among Female usership was observed high compared to other substances. Additionally, Alcohol usership increased by 80% within two weeks after the Global Pandemic declaration in 2020. Conclusions: Our study presents a large-scale, fine-grained analysis of Substance Use on social media data by age, gender and race/ethnicity before, during, and after COVID-19 pandemic. Overall, our analysis from social media data provides a new baseline study for substance usage that can help in prevention of substance use in an efficient manner.
Misleading information has significant implications for society but can have disastrous impact for health matters. Transformative artificial intelligence (AI) tools such as large language models (LLMs...
Misleading information has significant implications for society but can have disastrous impact for health matters. Transformative artificial intelligence (AI) tools such as large language models (LLMs) have the potential for limitless content generation (including fake), soon making internet information impossible to assess using traditional human approaches. We asked if the same LLMs (GPT4 and Gemini1-5-Pro) could be part of a more scalable solution. We tested 2 publicly available LLMs for their ability to identify misinformation in HealthReleases previously labeled by human experts. We found that simple prompts lead to overall low accuracy (F1 Macro 0,45 (GPT4) and 0,49 (Gemini1-5Pro)), but very different profiles for each LLM. Adding specific criteria used by experts to critically assess the Releases enhanced Gemini (0.66) but surprisingly reduced GPT4 (0,37) performances. We therefore developed a novel approach incorporating summaries of expert feedback into prompts and then observed major improvements in performance for both LLMs(GPT4;0.63 and Gemini1-5Pro; 0.96). Our study provides the first use case of LLMs as high throughput proofing of medical text, but more importantly provides insights into LLMs’ “truth biases”. We provide a novel paradigm integrating knowledge into the prompts which may reduce the need for LLM training, and the requirement for ever larger datasets and compute power. Importantly, we show how experts could and need to be involved in LLMs used to enhance their performance and potentially minimize the data wall issue.
Background: Health and mental health digital tools have emerged as a promising and necessary future of healthcare in a post-COVID 19 pandemic era. In the preventative mental health space many smartpho...
Background: Health and mental health digital tools have emerged as a promising and necessary future of healthcare in a post-COVID 19 pandemic era. In the preventative mental health space many smartphone apps and digital tools available have either limited empirical or research support, or are limited in their ability to design to a commercial standard using iterative development methods. Objective: The current study explored the mental health and help seeking related outcomes of the iterative testing of the Monash Thrive app. It was hypothesised that there would be an improvement in all outcomes across both trials (1), and that these improvements would be observed to a greater degree in trial 2 compared to trial 1 (2). Methods: The Monash Thrive app was tested across two iterative trials in 2022, the minimum viable product (MVP) of the app was tested across 4 weeks of use, followed by the beta version of the app (redeveloped based on MVP testing feedback), tested across 12 weeks of use later that year. Mental health variables including anxiety, depression, mental health literacy and help seeking intentions were compared at pre and post app use for each trial. Results: Improvements in mental health literacy, anxiety and help seeking intentions towards smartphone apps improved in trial 1, changes in all other variables were insignificant. Trial 2 did not demonstrate any significant changes across all variables of interest. Conclusions: The initial hypothesis was partially supported by findings, the second hypothesis was not supported. The absence of observed worsening of all variables of interest across time are a promising observation given the timing of each trial during teaching semesters. The lack of predicted improvement in mental health outcomes in the second trial compared to the first highlights the importance of iterative design and testing where changes may not always result in measurable improvements. Clinical Trial: Two trials were included in the current manuscript. Trial 1 was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12622001054707). Trial 2 was registered with the Australian and New Zealand Clinical Trials Registry (ACTRN12623000131651).
Background: Mosquitoes of genera Anopheles, Aedes, and Culex transmit diseases like malaria, dengue, chikungunya, Zika, Japanese encephalitis and Lymphatic filariasis. In Odisha, malaria poses a signi...
Background: Mosquitoes of genera Anopheles, Aedes, and Culex transmit diseases like malaria, dengue, chikungunya, Zika, Japanese encephalitis and Lymphatic filariasis. In Odisha, malaria poses a significant health challenge due to the region's favorable climate and topography for mosquito breeding and Plasmodium transmission. Anopheles mosquitoes, crucial for malaria transmission, thrive in various types of water bodies. Insecticide resistance presents a major concern, necessitating effective integrated vector management strategies. Understanding mosquito diversity is vital for public health interventions. Our study in southern Odisha aimed to explore seasonal variations in Anopheles populations across 11 districts that have been traditionally hyper-endemic for malaria. Objective: Our study aimed to investigate the seasonal effects on Anopheles mosquitoes across 11 districts in southern Odisha (Rayagada, Nabarangpur, Kalahandi, Nuapada, Balangir, Boudh, Kandhamal, Gajapati, Ganjam, Malkangiri, and Koraput). Additionally, we sought to generate data on mosquito species diversity, composition (types of Anopheles present), and abundance (number of mosquitoes) across these districts, considering their distinct environmental characteristics. Methods: We conducted a comprehensive study in southern Odisha, India, targeting 11 malaria-prone districts. Mosquito collections took place from March 2021 to February 2023, totaling 11,438 Anopheles and 631 belonging to other mosquito genera (Culicines). Both indoor and outdoor sampling methods were employed, and morphological identification was performed. We performed statistical analyses, including diversity indices (Shannon's, Simpson's, and Pielou's) and Canonical Correspondence Analysis (CCA), to evaluate mosquito species distribution across districts and seasons. Results: Over the study period, 10,807 Anopheles mosquitoes were collected across all seasons. Eighteen Anopheles species were identified, with An. subpictus dominating in summer (42.99%) March-June and the rainy season (46.60%) July-Oct. of 2021, but showing a significant decline later. An. culicifacies, a known malaria vector in the region, consistently comprised 30–38% of the population during summer and the rainy season. An. varuna peaked in winter of 2021 & 2022 at 35.56%. Diversity varied among districts, with Ganjam consistently exhibiting highest diversity (1.26–2.2). Seasonal fluctuations had a significant impact on mosquito diversity (p < 0.001), highlighting the greater influence of seasonality over district-specific factors on mosquito communities. Conclusions: This study emphasizes the importance of monitoring mosquito populations in Odisha, revealing their sensitivity to seasonal and geographic factors. Such insights are crucial for developing targeted and adaptable vector control strategies to combat malaria. Continuous assessment of mosquito diversity enables policymakers to implement evidence-based interventions tailored to the unique transmission dynamics of Odisha. These efforts contribute to the broader objective of malaria elimination in the country and the protection of public health for the general good.
Background: Interpreting histopathology slides and scientific figures requires specialized skills and knowledge. Pathologists analyze various tissues and cells, while the general population often stru...
Background: Interpreting histopathology slides and scientific figures requires specialized skills and knowledge. Pathologists analyze various tissues and cells, while the general population often struggles with the technical information in scientific figures. Artificial intelligence-based large language models (AI-LLMs) can simplify these processes by providing clearer explanations. Objective: This study explores the capabilities AI-LLMs in interpreting histopathology slides and scientific figures. The objective is to assess the value of AI LLMs in medical applications and scientific education. Methods: The study was divided into two parts: interpreting histopathology slides and scientific figures. Six histopathology images and six scientific figures were tested on each of the three most frequently used chatbots (ChatGPT-4, Gemini Advanced, and Copilot). Responses from the chatbots were coded and blindly examined by expert raters using five parameters—relevance, clarity, depth, focus, and coherence—on a 5-point Likert scale. Statistical analysis included one-way ANOVA and multiple linear regression. Results: ChatGPT-4 outperformed Gemini Adv and Copilot in both histopathology and scientific image interpretation, with significantly higher scores across all parameters (P<.001). High homogeneity among raters validated these findings. ChatGPT-4's superior performance may be due to its advanced algorithms, extensive training data, specialized modules, and user feedback. Conclusions: ChatGPT-4 excels in interpreting histopathology and scientific images, which may lead to improving diagnostic accuracy, clinical decision-making, and reducing pathologists' workload. It also benefits education by enhancing students' understanding of complex images and promoting interactive learning. ChatGPT-4 shows a significant potential to improve patient care and enrich student learning.
Background: Cisgender Black women (CBW) account for 2% of pre-exposure prophylaxis (PrEP)-eligible people in the United States who use PrEP to prevent HIV. In correlation with low PrEP use, CBW contin...
Background: Cisgender Black women (CBW) account for 2% of pre-exposure prophylaxis (PrEP)-eligible people in the United States who use PrEP to prevent HIV. In correlation with low PrEP use, CBW continue to contract HIV more than women from every other racial group. Intervention efforts that can bridge the link between knowing that PrEP prevents HIV and support with access to PrEP are necessary for CBW. Objective: The purpose of the vlogs through the campaign was to share information about ways to prevent HIV using PrEP and fact-based education, and provide access to PrEP resources with active links to local PrEP providers at local community health centers. Methods: In Phase I, the study team formerly piloted full-length video blog posts (vlogs) (10-12 minutes each) with 26 women during an emergency department visit. Using the findings from Phase 1, Phase 2 involved a prospective 6-month social media marketing campaign, the study team led a Texas-Development CFAR (TX-DCFAR) funded pilot grant to disseminate brief vlog snippets (30 seconds) of excerpts from the full-length vlogs with a larger group of Black women in Harris County. Community members, who were aged 18 -55 years, usually consume content that is often viewed by CBW (i.e. health/beauty), and reside in neighborhoods (based on zip code) in Harris County where most residents are Black or African American, were shown a series of brief vlog snippets on their social media pages, along with a brief message about PrEP and an active hyperlink to local PrEP resources. The study team was assessed implementation outcomes including feasibility and acceptability, appropriateness of vlogs, adoption of PrEP resources at local clinics, and clinical outcomes such as increased PrEP awareness among CBW. Results: Within 6 months, the campaign reached 110.8K unique individuals who identify as women when stratified by age, video plays at 50% of the vlogs (n=30,877) were most common among women ages 18-24 years (n=12,017) and least common among women ages 45-54 years (n=658). Key performance indicators showed that 1,098,629 impressions and1,002,244 total video plays resulted in 15,952 link clicks to local PrEP resources. Conclusions: The campaign demonstrated feasibility and acceptability of this approach with CBW and illustrated preliminary effectiveness at supporting access to local PrEP resources with CBW. Further dissemination and implementation of this approach is necessary to fully assess whether vlog viewership and clicks on links to PrEP resources can meaningfully empower CBW to access to PrEP and/or help them to assess whether PrEP is personally a useful HIV prevention option. Clinical Trial: N/A
Background: We implemented a novel mobile app-based Migraine Interactive Care Plan (MICP) integrated with our EHR. The MICP facilitates remote assessment of adult migraine patients, delivery of educat...
Background: We implemented a novel mobile app-based Migraine Interactive Care Plan (MICP) integrated with our EHR. The MICP facilitates remote assessment of adult migraine patients, delivery of educational content, and care team communication. Feasibility of the MICP was demonstrated in a pilot implementation study. Objective: We aimed to assess the preferences and satisfaction of migraine patient users of a mobile app-based care plan integrated with the electronic health record (EHR). Methods: An electronic survey was administered to a single cohort of MICP users between 12/6/21 and 12/30/21. The survey assessed patient preferences for which data to track, frequency of tracking, and satisfaction with the MICP. Survey responses were compared between subsets determined by patient-reported headache frequency, treatment with and without botulinum toxin and CGRP antagonist therapy. The Wilcoxon rank-sum test was utilized for continuous variables and Chi-square test or Fisher’s exact test for categorical variables. Results: The response rate was 30.4% (n=56/184). No significant differences in age (P = 0.2579) or sex (P = 0.1944) between respondents and non-respondents were observed. Respondent median age was 42 (range, 20-72) years and 94.6% (n=53/56) were female. Headache frequency was: 1) 0 to 8 days (n=26/56, 46.4%); 2) 9 to 14 days (n=12/56, 21.4%); and 3) 15 or more days (n=18/56, 32.1%). No difference was observed in survey responses based on headache frequency or treatment.
Majority of respondents preferred to track headache days weekly (n=30/56, 53.6%) or daily (n=15/56, 26.8%) and preferred to change the frequency of headache tracking reminders (n=42/56, 75%). Respondents were somewhat or very interested in daily tracking personal observations in free text (n=41/52, 78.8%), medication treatment (n=43/52, 82.7%) and treatment response (n=39/56, 69.6%), class of medication treatment (n=36/52, 69.2%), severity of functional impairment (n=39/56, 69.6%), type of functional impairment (n=35/53, 66%), headache day (n=40/54, 74.1%), and headache pain level on a scale of 1 to 10 (n=38/53, 71.7%). Respondents agreed or strongly agreed that the education content was useful (n=31/51, 60.8%) but lacked personalization (n=25/51, 49%). Most respondents agreed or strongly agreed that they were satisfied with the MICP (n=38/50, 76%) and that it helped them communicate with their care team (n=38/53, 71.7%). Conclusions: Most MICP users were motivated to track headache frequency, medication treatment with response, functional impairment, and pain intensity. Opportunities to improve the MICP include: 1) allowing patients to change the frequency of assessments and notifications; 2) record personal observations/comments via free text which may include headache triggers; 3) assessment of headache severity using a 1 to 10 pain scale; and 4) tailoring headache education based on frequency and severity (episodic vs chronic migraine). These observations may be useful to improve usability of the MICP and similar EHR-integrated migraine care platforms that others may develop.
Background: Type 2 diabetes mellitus (T2DM) is a chronic disease that requires management of blood glucose. The Dario Digital Diabetes Solution (DDS) is a non prescription digital health intervention...
Background: Type 2 diabetes mellitus (T2DM) is a chronic disease that requires management of blood glucose. The Dario Digital Diabetes Solution (DDS) is a non prescription digital health intervention with a smartphone app that previous studies have shown to improve blood glucose control in adults with T2DM. Objective: The aim of the study was to investigate the effects of DDS on healthcare resource utilization (HCRU) rates, charges, and estimated costs for adults with T2DM. Methods: In a retrospective cohort study, patient-level claims data of adults with T2DM were obtained from the Symphony Health Integrated Dataverse, a database containing both inpatient and outpatient claims including diagnoses and procedures. Using exact- and propensity score-matching, DDS users and non-users were matched in a 1:3 ratio. For the primary outcome measure (all-cause HCRU rates [defined as inpatient hospitalization and emergency room visits]) and secondary outcome measures (all-cause outpatient visit rates, all-cause HCRU charges, diabetes mellitus-related HCRU rates and charges) baseline, follow-up and change in values were summarized using descriptive statistics and a multivariable generalized linear model (GLM) or a 2-part model (including a GLM) was applied. Additional exploratory outcome measures were analyzed. In a sensitivity analysis, a cost-to-charge ratio (CCR) was calculated and applied to medical claims to estimate medical costs. Results: Following matching, cohorts consisted of 2445 DDS users and 7334 non-users with similar baseline characteristics and demographics. The all-cause HCRU event rate was 9.3% lower in DDS users compared with non-users in the 12-month follow-up from the index date. The mean number of events was estimated to be significantly lower in DDS users (0.48, 95% CI 0.44-0.52) per patient per year [PPPY]) than non-users (0.52 PPPY, 95% CI 0.50-0.55), resulting in an incidence rate ratio of 0.91 (P=.04). Inpatient hospitalization was 23.5% lower in the DDS user cohort compared with the non-user cohort, with emergency room visit and outpatient visit rates being similar across both cohorts. DDS users were numerically less likely to incur all-cause HCRU charges than non-users (odds ratio 0.91; 95% CI 0.82-1.01; P=.07). All-cause HCRU charges were 26% lower for DDS users than for non-users ($12,552 PPPY savings; P<.001). When applying the CCR to the charges, the total estimated cost saving for DDS users was $5077, of which $4513 PPPY was attributed to all-cause HCRU and $564 to all-cause office visits. Conclusions: In a retrospective cohort study of adults in the US with T2DM, DDS users were found to have lower all-cause HCRU rates than non users, driven by significantly lower inpatient hospitalization. All-cause HCRU charges and estimated costs were shown to be lower for DDS users compared with non-users.
Background: One in ten patients die because of a diagnostic error while doctors spend two hours with paperwork for every hour they spend with patients. Medical knowledge base doubles every 73 days and...
Background: One in ten patients die because of a diagnostic error while doctors spend two hours with paperwork for every hour they spend with patients. Medical knowledge base doubles every 73 days and doctors struggling to keep up experience burnout at peak rates. Successful generative AI applications include data analytics, document generation, and question answering on medical databases, however, generative AI is yet to make its way into hospitals. Objective: We aim to accelerate this transition by offering Rhazes, an AI-Assistant for doctors to assist them with paperwork and analytical tasks in medicine. Methods: Storage, hosting, AI services and LLMs are provided by Microsoft Azure and OpenAI. Retrieval augmented generation is used to for diagnosis and billing and WebRTC protocol is used for telemedicine. Results: We made Rhazes available on the web free of charge and it is ready to help physicians with notetaking, clinical decisions and patient management starting from the initial consultation all the way to patient discharge. Conclusions: In the future we aim to pilot Rhazes in hospitals and conduct a thorough evaluation of its performance.
Background: The usage of natural language processing (NLP) in mental health research is increasing with a wide range of applications and datasets being investigated. Objective: This review aims to sum...
Background: The usage of natural language processing (NLP) in mental health research is increasing with a wide range of applications and datasets being investigated. Objective: This review aims to summarize the usage NLP in mental health research, with a special focus on the types of text datasets and the usage of social determinants of health (SDOH) in NLP projects related to mental health. Methods: The search was conducted in September 2024 using a broad search strategy in PubMed, Scopus, and CINAHL Complete. All citations were uploaded to Covidence online software. The screening and extraction process took place in Covidence with the help of a custom large language model (LLM) module developed by our team. This LLM module was calibrated and tuned to substitute human reviewers. Results: The screening process, assisted by the custom LLM, led to the inclusion of 1,768 studies in the final review. The majority of the reviewed studies (n=665, 42.8%) utilized clinical data as their primary text dataset, followed by social media datasets (n=523, 33.7%). The United States contributed the highest number of studies (n=568, 36.6%), with depression (n=438, 28.2%) and suicide (n=240, 15.5%) being the most frequently investigated mental health issues. Traditional demographic variables such as age (n=877, 56.5%) and gender (n=760, 49.0%) were commonly extracted, while SDOH factors were less frequently reported, with urban/rural status being the most used (n=19, 1.2%). Over half of the citations (n=826, 53.2%) did not provide clear information on dataset accessibility, although a sizable number of studies (n=304, 19.6%) made their datasets publicly available. Conclusions: This scoping review underscores the significant role of clinical notes and social media in NLP-based mental health research. Despite the clear relevance of SDOH to mental health, their underutilization presents a gap in current research. This review can be a starting point for researchers looking for an overview of mental health projects using text data. Discovered datasets could be used to place more emphasis on SDOH in future studies.
Background: Background: Collection of dietary behavior data is crucial in childbearing populations. In addition to observed inequities in perinatal dietary intake and quality, burdensome assessment me...
Background: Background: Collection of dietary behavior data is crucial in childbearing populations. In addition to observed inequities in perinatal dietary intake and quality, burdensome assessment methods used (e.g., 24-hour dietary recall) may limit research participation for some groups. Ecological momentary assessment (EMA) is associated with reduced recall bias and participant convenience, but there is a dearth of studies with diverse cohorts. Objective: Objective: Our aim is to describe participant completion of dietary intake items in EMA surveys, overall and across individual characteristics (e.g., pre-pregnancy body mass index). Methods: Methods: Using EMA data from participants in a longitudinal study, we report average completion rates of survey items regarding dietary behavior (e.g., number of meals eaten in a day) across demographic variables (e.g., age) and intersectional strata (e.g., race + age) during late pregnancy and throughout 12 months’ postpartum. Results: Results: In our analytic sample (N=310), average completion rates were 59.1% during pregnancy, dropping to 52.4% after giving birth. Participants who were older (>30 years), overweight before pregnancy, self-identified as white, working, or earning higher annual income (>$50,000) had higher average completion rates than their counterparts. Examining intersectional strata, we found some variation in survey completion within racial groups. Black participants using a study phone had higher average completion rates during pregnancy and postpartum, but this relationship was reversed for white participants. Conclusions: Discussion: We showed relatively stable engagement with EMA surveys in a childbearing cohort across 15 months. Increased completion rates among privileged groups (e.g., white, higher income) may demonstrate the impact of socioeconomic advantages on individual health behaviors. Investigators should consider how intersections between race and other factors (e.g., employment) may impact participation and data collection.
Background: Drug-related deaths worldwide are most commonly attributed to opioids. Opioids and other sedative drugs can cause respiratory depression and airway compromise, leading to hypoxia and death...
Background: Drug-related deaths worldwide are most commonly attributed to opioids. Opioids and other sedative drugs can cause respiratory depression and airway compromise, leading to hypoxia and death. Device technology and artificial intelligence used to detect drug overdose has potential to improve outcomes. PneumoWave Ltd have developed a small chest-worn respiratory monitoring device to detect concerning breathing patterns and alert an emergency response. Objective: The aim of this study is to investigate the feasibility of use of the PneumoWave device in hospital patients at risk of respiratory depression. Methods: This 18-month prospective observational study is performed at the Queen Elizabeth University Hospital, Glasgow. The study investigates the use of the device on three groups of patients at risk of respiratory depression due to drugs. This includes patients attending the Emergency Department (ED) due to sedative drug overdose, patients receiving procedural sedation and analgesia in the ED, and patients receiving general anesthesia in theatres. Consenting participants will have the PneumoWave sensor monitoring paired with end-tidal CO2 and regular recordings of vital signs. Usability is tested by questionnaire of the patient, the clinician, and the nurse. The primary endpoint is to determine the feasibility of gathering respiratory data from a wearable respiratory monitoring device in the ED. Statistical analysis includes comparison of biosensor data against reference physiology time course data. Results: This study will examine the use of the PneumoWave device in a variety of patient situations in which risk of respiratory depression is present, providing valuable insight into the use of device technology in individuals at risk of illicit drug-related harm within the relative safety of a hospital setting. A limitation to study procedure is exclusion of patients with intoxication after sedative drug overdose who lack capacity to provide informed consent. Conclusions: This study has been designed to acquire foundation data to demonstrate the potential for continuous respiratory monitoring to improve outcomes for patients who are at risk of drug induced respiratory depression, inform product development, and inform design of future pivotal clinical investigations. Clinical Trial: The trial was registered on the 30th of March 2022 on clinicaltrials.gov, reference: NCT05358132.
We want to know where we come from and what health risks we may face. With that in mind, modern geneticists attempted to facilitate answers to these questions by dividing humankind into demographics b...
We want to know where we come from and what health risks we may face. With that in mind, modern geneticists attempted to facilitate answers to these questions by dividing humankind into demographics by which they then cataloged genetic markers. While at first glance this seems like a rational approach to the task of answering these questions, this method has led to some of the greatest atrocities humankind has ever seen, multiple times over, by dehumanizing patients into categories which ignore their personal history, identity, as well as their genetic profile by assuming various factors to include them as part of a demographic which will never fully represent them. The goal of this paper is to analyze the ramifications of such methodologies to encourage a dialog for a more accurate along with a more patient aware method of conducting genetic studies. Statistical data on antisemitic hate crime activity from the United States Department of Justice along with the Anti-Defamation League was compared to the publication of genetic studies which have traditionally been a part of the United States national curriculum on genetics as well as private studies which attributed genetic markers and disorders to the Jewish people. These studies often ignore the scientific method to base their findings on assumptions and there is not a similar tradition of studying non-Jews who do not belong to another minority in the same manner resulting in an inherent bias within the field of study which disproportionately hectors the Jewish people in academia.
Background: Refugees often face severe mental health challenges from traumas like war, torture, genocide, and childhood abuse. These complex traumas can lead to Complex Posttraumatic Stress Disorder (...
Background: Refugees often face severe mental health challenges from traumas like war, torture, genocide, and childhood abuse. These complex traumas can lead to Complex Posttraumatic Stress Disorder (CPTSD). Traditional therapies such as Cognitive Behavioral Therapy and Eye Movement Desensitization and Reprocessing are often limited in addressing the complex, culturally specific needs of refugees. Additionally, adherence to therapeutic homework is a significant barrier. Self-tracking technology has shown promise in offering a personalized approach to mental health management in the patient’s daily life, though its active use in psychotherapy remains underexplored. Objective: This study aims to collaboratively develop a psychotherapeutic treatment concept for refugees with CPTSD that integrates a research prototype wearable, self-tracking instrument for personalized self-tracking, the One Button Tracker (OBT) to support the therapeutic process. Designed for personalized self-tracking, the OBT allows patients to track subjective experiences in the moment, bridging the gap between therapy sessions and daily life. Methods: The study was conducted at the Clinic for Trauma and Torture Survivors in Denmark, specializing in treating refugees and veterans with PTSD and CPTSD. A Participatory Action Research design was employed from November 2022 to April 2024, involving therapists, patients, clinical psychology researchers, and Human-Computer Interaction researchers. Qualitative data from interviews, peer supervision, and logbooks, as well as self-tracking data from the OBT, informed the development of the treatment concept. Results: Over a period of 17 months, 40 peer supervision sessions, two workshops, and 25 patient interviews were conducted with nine patients whose treatment durations varied from eight to 24 sessions. The use of self-tracking varied, ranging from 22 to 366 days, with patients tracking between 1 and 14 different target phenomena. Results suggest that the OBT enhanced patient engagement by facilitating active participation in symptom management. Despite some technical issues affecting data collection, therapists reported that the OBT provided valuable insights into patients' daily experiences, facilitating more personalized interventions. The flexible use of the OBT allowed patients to shift focus from distressing phenomena to alternative coping strategies, reinforcing therapeutic interventions outside sessions. Additionally, the integration of self-tracking data strengthened the therapeutic alliance by improving communication and collaboration between patients and therapists. Conclusions: This study, alongside the pilot study, is the first to use PAR methodology for collaborative development of a treatment concept integrating self-tracking technology into psychotherapy for refugees with CPTSD. The self-tracking technology shows promise in fostering patient engagement, improving adherence to therapeutic homework, and strengthening the therapeutic alliance. The broad applicability of this treatment concept suggests a transtheoretical and transdiagnostic potential, offering a personalized and flexible approach to psychotherapy. Future research should focus on refining the treatment model and exploring its applicability across diverse populations.
Background: Building prediction models of differential intervention outcomes is crucial to identifying individuals with social anxiety disorder (SAD) who are most likely to improve. Precision medicine...
Background: Building prediction models of differential intervention outcomes is crucial to identifying individuals with social anxiety disorder (SAD) who are most likely to improve. Precision medicine approaches were thus harnessed to examine prescriptive predictors of optimization to 14-day mindfulness ecological momentary intervention (MEMI) over a self-monitoring app (SM). Method: Individuals with self-reported SAD in Singapore were randomized to MEMI (n = 96) or SM (n = 95). They completed self-reports of symptoms, risk factors, treatment, and socio-demographics at baseline, post-treatment, and one-month follow-up (1MFU). Machine learning models with 17 potential predictors of post-treatment and 1MFU SAD remission were evaluated. Results: The final multivariate ML models with the top ten predictors performed well (area under the receiver operating characteristic curve = .71-.72 for both time points). These baseline variables consistently predicted optimization of MEMI over SM regarding SAD remission at post-treatment and 1MFU. They included four strengths (higher trait mindfulness, lower SAD severity, absence of psychotropic medication use, and presence of university education), three weaknesses (higher GAD severity, lower trait self-compassion, and clinician-diagnosed depression/anxiety disorder), and Chinese ethnicity. Trait emotion dysregulation and current psychotherapy predicted remission with inconsistent signs across time points. Non-significant predictors included age, gender, depression severity, treatment credibility, expectancy, attentional control, and repetitive thinking. Conclusion: Harnessing precision medicine methods that include diverse baseline transdiagnostic variables to evaluate capitalization and compensation models might enhance the accuracy of prescriptive models and optimize treatment selection for SAD within stratified models embedded in routine care.
Background: Major incident management must be both efficient and effective to save as many lives as possible. All paramedics and emergency medical technicians may unexpectedly have to respond to such...
Background: Major incident management must be both efficient and effective to save as many lives as possible. All paramedics and emergency medical technicians may unexpectedly have to respond to such incidents. However, they are infrequently, if ever, exposed to major incidents and regular training is therefore mandatory. Initial training and refresher sessions are usually based on simulations. Most major incident simulations are limited by the fact that simulated patients do not evolve during the simulation, regardless of the time elapsed and despite treatment and transport decisions. Therefore, most simulations fail to incorporate a critical temporal effect of decision-making. Objective: To develop and validate a simplified yet realistic physiological model capable of simulating the real-time evolution of several casualties. Methods: A modified version of the user-centered design framework was used to define the development process of the physiological model. This framework is based on the five modes of design thinking (empathize, define, ideate, prototype, and test), with the addition of the knowledge base mode of the information systems research framework. To validate the developed model, a validation phase was added. To determine whether the developed model was clinically realistic, 15 experienced prehospital professionals (5 advanced paramedics and 10 senior registrars working in ground and helicopter emergency medical systems) participated in a validation phase. They were asked to rate clinical and physiological parameters according to a 5-point Likert scale ranging from 1 (impossible) to 5 (absolutely realistic). Results: A collaborative development team including prehospital professionals and computer scientists agreed on the most important feature of the model: it has to be clinically realistic, include all the elements required to compute prehospital vital signs and their evolution, yet be simple enough to allow real-time computation of these parameters for several simulated patients simultaneously, on regular computers or tablets. Multiple iterations led to the development of a heart-lung-brain interaction model coupled to functional blocks representing the main anatomical body parts. These blocks enabled the management of neurovascular elements used to provide neurological information and to create hemorrhages at different levels with different blood flows. The professional prehospital providers who participated in the validation phase assessed nine simulated patients presenting pathologies devised to test the different systems and their interactions. All initial and final states of all patients had a median rating of 5 (absolutely realistic) for both clinical and physiological parameters. The overall median rating was also 5 for each individual patient. Conclusions: A simplified model of trauma patient evolution was successfully created and deemed clinically realistic by experienced clinicians. This model should now be included in computer-based simulations and its impact on the teaching of major incident management assessed through randomized trials. Clinical Trial: None
Background: With the increasing reliance on online platforms for health information, understanding user satisfaction, perceived benefits, and associated risks is critical for promoting informed health...
Background: With the increasing reliance on online platforms for health information, understanding user satisfaction, perceived benefits, and associated risks is critical for promoting informed health-seeking behaviors. This study seeks to address the gap in knowledge regarding users' perceptions of online health information and the factors influencing their trust in these sources. Objective: This study aims to evaluate users' satisfaction with online health information sources, identify the perceived benefits and risks associated with seeking health information online, and investigate the factors influencing trust in these information sources. Additionally, the study will explore how these perceptions impact users' health-seeking behaviors. Methods: A cross-sectional survey was conducted with a sample of 376 respondents, using structured questionnaires to collect data on satisfaction levels, types of health information sought, perceived benefits and risks, and trust in online health information sources. Descriptive statistics and chi-square analyses were utilized to analyze the data Results: The findings indicate that a significant proportion of respondents reported high levels of satisfaction with online health information sources, with 52.1% somewhat agreeing and 18.6% agreeing with their overall satisfaction. The most sought types of information included specific medical conditions (27.4%) and symptoms (36.7%). Benefits of online health information were primarily identified as convenience and accessibility, while risks included misinformation and lack of accountability. Trust in information sources was found to be significantly correlated with perceived reliability and the anonymity of the information source. Conclusions: Overall, users express satisfaction with online health information sources, recognizing both benefits and risks associated with their use. Trust emerges as a critical factor influencing satisfaction and health behaviors. It is recommended that health information providers improve the reliability and accountability of online health information to enhance user trust and satisfaction. Public health initiatives should also aim to educate users on evaluating online health information critically. This study underscores the importance of understanding users' perceptions of online health information, which can inform strategies to enhance the quality and effectiveness of digital health communication.
Background: Due to improvements in healthcare and rehabilitation, as well as better social conditions, individuals living with traumatic brain injury (TBI), multiple sclerosis (MS), or spinal cord inj...
Background: Due to improvements in healthcare and rehabilitation, as well as better social conditions, individuals living with traumatic brain injury (TBI), multiple sclerosis (MS), or spinal cord injury (SCI) are living longer. It is therefore necessary to ensure the presence of social and health services adapted to the realities and specific needs of these populations aging with disabilities. Social participation is a key determinant of active aging and health. However, there is limited evidence regarding the social participation of these aging populations. To support the development of more inclusive approaches promoting the health of older adults, it is essential to better understand the diversity of social participation experiences among individuals aging with neurological disabilities. Objective: 1) Explore how social participation is experienced by individuals aging with TBI, MS, or SCI; 2) Document the barriers and facilitators to their social participation; 3) Explore avenues for interventions supporting their social participation. Methods: This descriptive qualitative research is part of a larger action research project conducted in partnership with individuals aging with disabilities, researchers, and community organizations providing services to these populations who sit on the project's steering committee. Individuals aged 50 or older living with TBI (n=8), MS (n=8), or SCI (n=8) will participate in a semi-structured interview. The interviews will be transcribed verbatim, and the accuracy of the transcripts will be ensured through peer validation. Qualitative data will be analyzed using a mixed approach in alignment with the Framework methods. The use of the Human Development Model – Disability Creation Process (HDM-DCP) conceptual model will be used for deductive analysis. The coding tree will combine significant themes arising from the interview's inductive part and the themes from the HDM-DCP. Also, 12,5% of the analysis will be tested for stringency (i.e., double-blind & inter-rater reliability exercise). Results: The study will provide insights into the diversity of social participation experiences of these populations as well as the influence of individual characteristics and environmental resources on their social participation. Conclusions: This project will lay the groundwork for the co-development of health promotion programs aimed at supporting the social participation of individuals aging with neurological disabilities. This study will also help to identify the resources and strengths that support social participation for these populations, as well as the systemic barriers that need to be addressed this.
Background: Young people living with HIV (PLWH) struggle to adhere optimally to antiretroviral therapy (ART). Most mobile messaging interventions to improve ART adherence have relied on SMS, with limi...
Background: Young people living with HIV (PLWH) struggle to adhere optimally to antiretroviral therapy (ART). Most mobile messaging interventions to improve ART adherence have relied on SMS, with limited targeting of specific behavioral mechanisms.
MHealth interventions for improving ART adherence designed based on behavioral change techniques (BCT) could increase effectiveness by targeting specific drivers, such as customization. WhatsApp facilitates the uptake of BCTs through different features. To improve ART adherence, we hypothesize that WhatsApp messages self-designed by participants, with spontaneous targeting of BCTs, could be more effective than standard WhatsApp messages designed by the researchers. Objective: Evaluate the effectiveness of WhatsApp messages created by participants (self-designed) compared to WhatsApp messages created by the researchers (standardized) over adherence to ART at 16 weeks of intervention in young PLWH who receive HIV care under routine conditions at a public hospital in Lima, Peru. Methods: Two-arm randomized controlled trial (RCT) with a parallel assignment of 1:1, with no blinding of study intervention. Eligible participants are consenting PLWH aged 18-29 who receive HIV care at the study center and whose mobile phones support WhatsApp. After enrolment, participants complete a survey about general/clinical information and preferences for the weekly schedule and the number of WhatsApp messages to be received. Participants are then randomized to the control group (messages designed by the research team) or to the experimental group (messages designed by participants), stratified by sex, educational level, current ART intake, and history of ART abandonment.
In both arms, and through WhatsApp, participants receive (i) up to three weekly messages during sixteen weeks after enrolment for the delivery of the intervention; (ii) the Simplified Medication Adherence Questionnaire (SMAQ) at 4, 8, 12, and 16 weeks of intervention to analyze the primary outcome (self-reported ART adherence); and (iii) monthly questionnaires about the user’s experience. Throughout the study, the bidirectional design of WhatsApp chats enables participant-initiated communication with the medical research team.
We will compare ART adherence at 16 weeks in both study groups under the intention to treat principle; we will not conduct an interim analysis. For bilateral alpha of 0.05, study power of 78.9%, and an expected size effect of 10% difference in self-reported ART adherence after 16 weeks, the calculated sample size is 120; the final was increased to 131 to conduct a two-week pilot. Results: In March 2024, we started enrolling and randomizing participants. The study follow-up will continue until the last participant completes 16 weeks of intervention (November 2024). Blinded data analysis will be completed by December 2024. Conclusions: This trial will compare the effectiveness of standardized vs. self-designed WhatsApp messages over ART adherence measured at 16 weeks among young people living with HIV receiving routine care in a low-resource setting in Lima. Clinical Trial: ClinicalTrials.gov NCT06500013; https://clinicaltrials.gov/ct2/show/NCT06500013
Background: The wide use of smartphones offers large-scale opportunities for real-time data collection methods such as Ecological Momentary Assessment (EMA) to assess how fluctuations in contextual an...
Background: The wide use of smartphones offers large-scale opportunities for real-time data collection methods such as Ecological Momentary Assessment (EMA) to assess how fluctuations in contextual and psychosocial factors influence parents’ feeding practices and feeding goals, particularly when feeding children with a high food approach. Objective: The main objectives of this study were to: (1) assess parents/caregivers’ compliance with EMA procedures administered through a smartphone app and (2) estimate the criterion validity of the EMA to capture children’s eating occasions and parents’ feeding practices. Participant adherence, technological challenges, and data quality were used to provide an overview of the real-time dynamics of parental mood, feeding goals, and contextual factors during eating occasions. Methods: Parents living in the UK with a child aged between 3 and 5 years with avid eating behavior were invited to participate in the 10-day EMA study using a smartphone app. Of the 312 invited participants, 122 (39%) parents initiated the EMA study, of which 118 (96.7%) completed the full EMA period and the follow-up feasibility and acceptability survey. Results: Of those parents who completed the EMA study, 104 (87.4%) provided at least seven ‘full’ days of data (two signal surveys and one event survey), despite 51 parents (43.2%) experiencing technical difficulties. The parents received notifications for morning surveys (69.9% response rate), three daily mood surveys (78.7% response rate), and an end-of-day survey (84.6% response rate) on each of the ten days. Over the EMA period, a total of 2,524 child eating/food request surveys were self-initiated by the participants on their smartphones, an average of 2.1 times per day per parent (SD = 0.18, min = 1.7, max = 2.3). The majority of parents felt that the surveys made them more aware of their feelings (89%) and activities (79%). Conclusions: This paper demonstrates the feasibility of employing EMA to investigate the intricate interplay between parental mood, feeding goals, contextual factors, and feeding practices with children exhibiting an avid eating behavior profile. However, the use of EMA needs to be carefully developed and tested with parents’ involvement to ensure successful data collection.
Background: Objective We aimed to investigate the effectiveness of CGM on intensive care unit (ICU) related outcomes among frail and critically ill patients with confirmed COVID-19.
Research design a...
Background: Objective We aimed to investigate the effectiveness of CGM on intensive care unit (ICU) related outcomes among frail and critically ill patients with confirmed COVID-19.
Research design and methods This was an exploratory, prospective, randomized, open-label, parallel, single-center clinical trial. A total of 124 patients was finally analyzed. The primary outcome was 28-day in-ICU mortality. The secondary outcome included the length of ICU stay, the occurrence of hypoglycemia and severe hypoglycemia events.
Results The mean age was 78.3±11.5 years old. The mean fasting glucose level at baseline was 8.12±1.54 mmol/L. The mean HbA1c level was 7.2±0.8%. The percentage of participants with diabetes was 30.6%. The corresponding hazard ratio of the primary outcome in the isCGM group when compared with the POCT group was 0.18 (95%CI 0.04-0.79). The average length of ICU stay was 10.0±7.57 days in the isCGM group and 14.0±6.86 days in the POCT group (P < 0.05).
Conclusions We found a significant clinical benefit from the use of CGM among frail and critically ill patients with COVID-19. These findings support the use of CGM in ICU and might help with the extension of application in various in-hospital settings. Objective: We aimed to investigate the effectiveness of CGM on intensive care unit (ICU) related outcomes among frail and critically ill patients with confirmed COVID-19. Methods: This was an exploratory, prospective, randomized, open-label, parallel, single-center clinical trial. A total of 124 patients was finally analyzed. The primary outcome was 28-day in-ICU mortality. The secondary outcome included the length of ICU stay, the occurrence of hypoglycemia and severe hypoglycemia events. Results: The mean age was 78.3±11.5 years old. The mean fasting glucose level at baseline was 8.12±1.54 mmol/L. The mean HbA1c level was 7.2±0.8%. The percentage of participants with diabetes was 30.6%. The corresponding hazard ratio of the primary outcome in the isCGM group when compared with the POCT group was 0.18 (95%CI 0.04-0.79). The average length of ICU stay was 10.0±7.57 days in the isCGM group and 14.0±6.86 days in the POCT group (P < 0.05). Conclusions: We found a significant clinical benefit from the use of CGM among frail and critically ill patients with COVID-19. These findings support the use of CGM in ICU and might help with the extension of application in various in-hospital settings.
Background: The Fast Healthcare Interoperability Resources (FHIR) standard has emerged as the global interoperability standard for health information exchange. However, the uptake and implementation o...
Background: The Fast Healthcare Interoperability Resources (FHIR) standard has emerged as the global interoperability standard for health information exchange. However, the uptake and implementation of FHIR standards requires work. To speed up the process of adoption, various FHIR accelerator groups have been formed. FHIR accelerators like the Sparked program in Australia enable communities and collaborative groups to develop high-quality FHIR standards for healthcare information exchange. However, limited research exists on the development, delivery, and implementation of FHIR accelerator programs. Objective: This study sought uses qualitative methods to identify the key components of the Sparked FHIR accelerator, what factors influence implementation, and which strategies may help enhance its delivery. Methods: Semi-structured interviews were conducted with Sparked stakeholders in the early stage of the program. The Sparked FHIR accelerator intervention components were described using a standardized reporting checklist (TIDieR). The Consolidated Framework for Implementation Research (CFIR 2.0) was used to analyze factors influencing implementation (enablers and barriers). Based on the cumulative majority analysis, the top-most mentioned factors influencing implementation were identified. These factors were then mapped to the Expert Recommendations for Implementing Change (ERIC) tool to develop strategies for enhancing the implementation of the Sparked program. Results: A total of 17 participants were interviewed, including program leads, co-chairs, representatives of software industry implementers, clinicians, and consumers. Eight key CFIR influencing factors were identified: engaging, innovation design, assessing needs, local conditions, access to knowledge & information, partnerships & connections, capability, and work infrastructure. After mapping the top CFIR influencing factors to the ERIC tool, six strategy clusters were identified: adapt and tailor to context, develop stakeholder interrelations, support participants, train and educate stakeholders, and use evaluative and iterative strategies. Conclusions: The study enabled us to define the core components of the Sparked FHIR accelerator and understand what factors have the strongest influence on implementation. Using the CFIR-ERIC approach allowed us to generate expert-informed recommendations for improving the implementation of Sparked. Our research offers a systematic approach to evaluating FHIR accelerators and provides valuable insights for decision-makers and implementers. Clinical Trial: N/A
Background: Food insecurity (FI) is a risk factor for type 2 diabetes (T2D) that disproportionately affects Latinas. Objective: We propose that FI cycles over the course of a month according to disbur...
Background: Food insecurity (FI) is a risk factor for type 2 diabetes (T2D) that disproportionately affects Latinas. Objective: We propose that FI cycles over the course of a month according to disbursement of food assistance benefits and seek to understand whether this cycling is related to diabetes risk. Methods: Participants were adult Latinas living in Hartford CT, a small state capital city in northeastern, USA. They were recruited through a community agency in Hartford, CT and were invited to participate if they were receiving Supplementary Nutrition Assistance Program (SNAP) benefits, screened positive for FI, and had elevated risk factors for T2D. Using a micro-longitudinal design, we collected data twice per month for 3 months (week two which is a period of food budget adequacy and week four which is a period of food budget inadequacy). We will determine if the monthly cycling of FI is associated with near-term diabetes risk (fasting glucose, fructosamine, glycosylated albumin) and long-term risk (body mass index, waist circumference, and HbA1c). We will determine whether household food inventory, psychological distress, and binge eating mediate associations. To assess the relationship between monthly cycling of FI with diabetes risk markers, we will use repeated measures general linear mixed models (GLMMs). To assess the role of mediators, we will perform a causal pathway analysis. Participant enrollment was from April 1, 2021, to February 21, 2023. Quantitative methods and baseline demographic data for the sample are reported here. Results: Of the 845 participants screened, 685 were not eligible. The most common exclusions being because they did not receive SNAP benefits (n=229), were outside of the age range (n=155), had extant diabetes (n=90), or did not have elevated risk for type 2 diabetes (n=83). Of the n=160 that were eligible, n=73 declined with the most common reason for declining was lack of time, lack of transportation, and concerns about COVID; n=87 enrolled in the study. As can be seen in Table 1, just over half (54.0%) of the sampled self-identified as Puerto Rican, mean age was 35.1 ± 5.8 years, with 17.1 ± 11.6 years in the mainland U.S. Just under half (47.1%) spoke Spanish only, 69.0% had no formal schooling and 31.0% had <8th grade education. Modal household size was 4 including 2 children, and 44.5% were not living with a partner. About half (54.0%) were unemployed, 63.2% reported a monthly income <$1,000 and 63.2% used food pantries. Conclusions: This study will demonstrate how FI cycles over the course of the month, as well as whether and to what degree the cycling itself is related to risk for T2D. Further, the study will provide evidence for some putative mechanisms of this association that can serve as future intervention targets. Clinical Trial: Pilot study, R21. Not a registered trial.
Background: Oxidative Stress (OS) is an imbalance between the production of free radicals and the body's ability to neutralize them, leading to damages of cells, proteins and deoxyribonucleic. Objecti...
Background: Oxidative Stress (OS) is an imbalance between the production of free radicals and the body's ability to neutralize them, leading to damages of cells, proteins and deoxyribonucleic. Objective: To identify the relevant biomarkers of OS which could be associated to severity of hospitalized patients and to identify a possible correlation between OS biomarkers and clinical status of hospitalized COVID-19 patients with severe lung disease at hospital admission. Methods: All adult patients hospitalized with COVID-19 at the Infirmerie Protestante (Lyon, France) from 9th February 2022 to 18th May 2022 were included, regardless of the care service. The final sample consisted in 28 patients. Ten biomarkers were collected per patient (Zinc (Zn), Copper (Cu), Cu/Zn, Selenium, Uric acid, CRplus, Oxidized LDL, Glutathione peroxidase, Glutathione reductase and Thiols), as well as demographic variables and comorbidities. A support vector machine (SVM) model was used to predict the severity grade per patient, based on the collected data as training set. Results: : Three biomarkers of OS were associated with severity; Zn, Cu/Zn and Thiols especially for grade 0 (asymptomatic) and grade 1 (mild to moderate severity). The SVM model predicted the level of severity from the biological analysis of the OS biomarkers with only 7.14% of discrepancy in the training dataset. Conclusions: In case of COVID-19 infection, moderate to severe symptomatic patients are associated with a lowered zinc level, a lowered plasma thiol level, an increased CRPus and an increased Cu/Zn ratio among a panel of ten biomarkers of OS.
Background: The increasing reliance on the internet for health information necessitates understanding various factors influencing health information-seeking behaviors and satisfaction levels among use...
Background: The increasing reliance on the internet for health information necessitates understanding various factors influencing health information-seeking behaviors and satisfaction levels among users. These insights can inform strategies to improve the quality and accessibility of health information. Objective: This study aimed to investigate the socio-demographic factors affecting internet health information-seeking behaviors, the types of health information sought, the timeliness and trust associated with information sources, and user satisfaction regarding online health information. Methods: A quantitative cross-sectional survey was conducted among 376 participants, utilizing structured questionnaires to collect data on various aspects of health information-seeking behavior. Statistical analyses, including Chi-square tests and frequency distributions, were performed to evaluate the relationships between socio-demographic factors and health information-seeking behaviors. Results: The findings revealed significant associations between the duration of teaching, health insurance status, estimated income, and the duration of employment with health information-seeking behaviors (p < 0.05). The most sought-after health information types included specific medical conditions and treatment methods. Satisfaction levels varied across categories, with a majority of respondents expressing positive sentiments toward online searches, website information sources, and the usefulness of the information received. Conclusions: The study underscores the importance of socio-demographic factors in shaping health information-seeking behaviors and highlights the need for improved credibility and trust in online health information sources. Stakeholders in health communication should prioritize the development of reliable online health information platforms and enhance user education on navigating these resources effectively. This study contributes valuable insights into the dynamics of health information-seeking behaviors, emphasizing the critical role of socio-demographic factors and the need for high-quality, trustworthy health information in promoting informed health decisions.
Recent years have witnessed a transformative shift in the way patient-reported outcomes are captured. The increasing adoption of digital health technologies offers exciting possibilities for more effi...
Recent years have witnessed a transformative shift in the way patient-reported outcomes are captured. The increasing adoption of digital health technologies offers exciting possibilities for more efficient, engaging, and insightful electronic data collection. Electronic diaries (eDiaries) represent a paramount resource that could improve data quality, reduce costs, and limit the burden on clinical staff and trial participants. Herein, we present our perspective on how to effectively use eDiaries to optimize the data collection processes in vaccine clinical trials. We begin with with a brief description of the benefits of eDiaries in vaccine clinical trials and provide reflections on key measures such as programming the eDiary platform, training the trial staff and participants, and real-time monitoring of participant compliance, which are crucial for leveraging eDiaries for optimal data collection. By implementing the measures discussed in this paper, eDiaries can offer significant advantages for both trial participants and clinical investigators by ensuring quality and integrity of the data collected.
Background: Malnutrition is a challenge among older adults and can result in serious health consequences. However, the dietary intake monitoring needed to identify malnutrition for early intervention...
Background: Malnutrition is a challenge among older adults and can result in serious health consequences. However, the dietary intake monitoring needed to identify malnutrition for early intervention is affected by issues like difficulty remembering or needing a dietitian to interpret the results. Objective: To co-design a tool using automated food classification to monitor dietary intake and food preferences, as well as food-related symptoms and mood and hunger ratings, for use in care homes. Methods: An advisory group co-designed the tool features. A small or medium enterprise (SME) developed a prototype tool where the user takes a photo of a meal pre- and post-eating, it links to a database of foods, and associates meals with symptoms and ratings. A second version was tested with older adults/care staff. Feedback refined a third version and a new advisory group suggested design adaptations for care homes. Four care homes tested this and identified barriers to usability and features to enhance value. Systematic text condensation was used to describe themes across the different types of data. Results: Key features identified included ratings of hunger, mood, and gastrointestinal symptoms that could be associated with eating specific foods, and a traffic light system to indicate risk. Issues included staff time, Wi-Fi connectivity, recognition of pureed food, and fortification. Different models for potential use and commercialisation were identified, including peer-use between residents to support less able residents, staff-only use of the tool, care home-personalised database menus for easy photo selection, and continued measurement in highest risk residents only using the traffic light system. Conclusions: The tool was deemed useful for monitoring dietary habits and associated symptoms, but further design improvements that are needed were identified. These would need to be incorporated prior to formal evaluation of the tool as an intervention in this setting. Co-design was vital to help make the tool fit for the setting and users targeted.
Background: Alzheimer’s disease (AD) is the most common cause of dementia, accounting for 60–70% of all cases. Since there is still no treatment for dementia, early diagnosis and prevention are th...
Background: Alzheimer’s disease (AD) is the most common cause of dementia, accounting for 60–70% of all cases. Since there is still no treatment for dementia, early diagnosis and prevention are the best approaches. In this context, the cognitive reserve (CR) concept has received considerable attention in dementia researches with regard to prognosis. It originates from discrepancies between the degree of brain pathology and the clinical manifestations. Acupuncture, as a complementary intervention, has long been widely applied in neurological diseases in East Asia. At the macroscale level, how acupuncture stimulation affects neural activity concerning CR in normal aging and dementia is largely unknown. Objective: The aim of this study is to investigate the acute neural mechanisms of acupuncture stimulation concerning CR in normal aging and cognitively impaired group using neuroimaging method. Methods: This study is a randomized, placebo-controlled trial. Cognitively unimpaired (n=30) and cognitively impaired participants (n=30) will be randomly assigned to the verum or sham acupuncture groups. The verum acupuncture group will receive acupuncture stimulation at acupoints related to cognitive function and gain deqi sensation. The sham acupuncture group will receive superficial needling at non-acupoints not related to cognitive function. Each group will undergo cognitive function tests, functional near-infrared spectroscopy (fNIRS) imaging before and after acupuncture stimulation, and an assessment of CR. The primary outcomes would be differences in resting brain activities according to disease status, differences in resting brain connectivity before and after acupuncture stimulation between two groups, and changes in brain activity in relation with CR index. The secondary outcomes would be brain connectivity or network metrics associated with CR and differences in neural activity between the cognitive task and resting states. Results: The recruitment began in August 2023 and, to date, there have been the 50 participants, divided into 20 in the cognitively impaired group and 30 in the unimpaired group. The recruitment process will continue until February 2025. Conclusions: CR refers to the individual susceptibility to age-related brain changes and pathologies in cognitive impairment, thus a factor affecting the trajectories of the disease. Although acupuncture is a widely used intervention for various neurological diseases, including dementia, its mechanism associated with CR at the macroscale has not been clearly identified. This study could contribute to identify the neural mechanisms of acupuncture stimulation associated with CR using neuroimaging method and provide a basis for future longitudinal researches. Clinical Trial: Clinical Research Information Service of the Republic of Korea (CRIS), one of the WHO ICTRP Primary Registries; KCT0008719 (https://cris.nih.go.kr/cris/search/detailSearch.do/25391)
Background: Covid-19 forced psychologists and other mental health professionals to use videoconference platforms. Previous research highlights therapists’ hesitation towards adopting the medium sinc...
Background: Covid-19 forced psychologists and other mental health professionals to use videoconference platforms. Previous research highlights therapists’ hesitation towards adopting the medium since they find it hard to establish control over Videoconference Psychotherapy. Objective: This study aims to investigate whether the introduction of new technical features might improve clinicians’ control over Videoconference Psychotherapy Methods: In total, 121 mental health professionals responded to our survey, but only 86 participants provided complete data. We used Exploratory Factor Analysis to scrutinise the data collected. Three factors were identified: Challenges in providing Videoconference Psychotherapy, Features to enhance Therapeutic Relationship and Enhancing Control. Path analysis was used to observe the relationship between factors on their own and with adjustment to participants’ areas of expertise and year in practice. Results: This study highlighted a relationship between the three factors identified. It emerges that the introduction of features reduces therapists’ challenges in the provision of Videoconferencing Psychotherapy. Moreover, the additional features help therapists to enhance control over their Videoconference Psychotherapy sessions. Conclusions: This study has shown how by augmenting therapists’ control over their Videoconference Psychotherapy, clinicians would be able to impact patients’ reality, and facilitate successful therapy outcomes. Moreover, this study confirms the Video as a third agent which prevents therapists from influencing clients’ reality due to technical and relational limits. Additionally, this study supports the General System Theory which permitted to incorporate the Video in our exploration and to explain its agency in Videoconference psychotherapy.
Background: Digital health interventions show promise in supporting adults with type 2 diabetes mellitus (T2DM). Dario is a digital diabetes solution (DDS) that allows individuals with T2DM to automat...
Background: Digital health interventions show promise in supporting adults with type 2 diabetes mellitus (T2DM). Dario is a digital diabetes solution (DDS) that allows individuals with T2DM to automatically log blood glucose (BG) measurements and other variables to facilitate positive behavior changes. Objective: This retrospective cohort study compared real-world clinical outcomes of adults with T2DM using the DDS with those of adults with T2DM receiving usual care alone. Methods: Healthcare and claims data collected from the DDS, the Symphony Health Integrated Dataverse, and Quest Laboratory data were integrated into a single dataset using tokenization. DDS users were compared with a matched cohort of non-users over the period from January 2017 to October 2021. Inclusion criteria were adults ≥18 years of age with T2DM, treated with antidiabetic medications, with HbA1c ≥7.0% prior to a defined index date, and valid HbA1c measurements during follow-up. DDS users were matched 1:3 with non-users using exact-matching criteria and propensity-score matching. Difference-in-difference values were determined using a multivariable linear regression model. The primary endpoint was change in HbA1c from baseline to 6 months. Results: The two cohorts included 568 DDS users and 1699 non-users with matched baseline characteristics. At 6 months, the generalized linear model least squares mean estimate of the difference in change in HbA1c between the two cohorts was −0.23% (95% CI: −0.38%, −0.07%, P=.004). Similarly, HbA1c decreased significantly more in DDS users versus non-users in sensitivity analyses at 12 months. In four subgroups of individuals with baseline HbA1c >7.5%, >8.0%, >9.0%, and >11.0%, HbA1c decreased significantly more in DDS users than in non-users at 6 months and at 12 months. At 6 months, 47.0% of DDS users and 36.8% of non-users had a ≥1% decrease in HbA1c from baseline (P<.0001). Rates of severe hypoglycemia did not increase in either cohort between baseline over 6 months. At 6 months, more DDS users with baseline HbA1c ≥8.0% had achieved HbA1c <8.0% (P=.0021).
During 6 months’ follow-up, medication adherence rates were evaluated as an exploratory endpoint, and found to be greater for DDS users than non-users (P=.03). Engagement with DDS was also evaluated as an exploratory endpoint and was associated with a significant decrease in HbA1c from baseline to follow-up (r=−0.28, P<.0001). Engagement activities associated with reduced HbA1c were BG measurement and tagging (timing of BG measurement and meal type). Conclusions: Adults with T2DM and elevated HbA1c levels using the DDS had better outcomes at 6 months than matched non-users across various baseline HbA1c levels, with no increase in rates of severe hypoglycemia. These effects were sustained at 12 months. The results confirm that digital interventions that facilitate behavior change can potentially deliver improvements in health outcomes.
Background: Digital and web-based at-home tests are increasingly important in neuropsychological assessments, providing various advantages (e.g., automated response recording, standardization, time, a...
Background: Digital and web-based at-home tests are increasingly important in neuropsychological assessments, providing various advantages (e.g., automated response recording, standardization, time, and cost savings). Extensive comparability between standard paper-based and online testing has been demonstrated, in particular, among adults. Evidence of test-mode effects (i.e., differences between paper-based or online testing) in older adults (> 60 years), who often show minor digital adoption (e.g., affecting visual, perceptual, cognitive, and physical abilities) attributed to typical age-related changes, is limited. Objective: The present study evaluated test-mode effects in older participants for different (number) line bisection tasks. Methods: The present study compared the test-mode effects between supervised paper-based and web-based at-home testing using an unconscious but systematic neuropsychological phenomenon, the pseudoneglect, in simple (number) line bisection and number line estimation tasks in N = 77 neurologically healthy over (n = 41 males and n = 36 females over 60 years). Results: Results showed that the pseudoneglect was present in both testing environments in all (number) line bisection tasks, while test mode did not affect this systematic perceptual bias or its variance. However, web-based at-home online testing resulted in a larger skew (i.e., more s-shaped curvature) of estimation in all number line estimation tasks. Conclusions: The curvature bias can be explained by the amended response format (pencil vs. computer mouse) and the age-related inexperience with the test mode. In conclusion, we consider only online line bisection tasks in older adults to be directly comparable to paper-pencil testing, with all the advantages of online data acquisition.
Background: Resistance training is used to prevent the decrease in muscle strength associated with age. Objective: This study evaluates the effectiveness of iso-inertial training on power, physical pe...
Background: Resistance training is used to prevent the decrease in muscle strength associated with age. Objective: This study evaluates the effectiveness of iso-inertial training on power, physical performance, and risk of falls compared to gravitational training in physically active middle-older adults. Methods: Parallel-group, randomised controlled trial at Espai Esport Wellness Center (Granollers, Spain). Forty-four physically active adults (age >57) were randomised to iso-inertial (n=21) or gravitational (n=23) training groups (R software; 1:1 ratio). Participants had to complete a 6-week training program (2 sessions/week) consisting of three exercises (forward and side lunge, forward lunge with row). Primary outcome: power in the eccentric phase of each exercise evaluated with both iso-inertial and gravitational devices. Secondary outcomes: concentric power, physical performance, risk of falls. Only outcome evaluators were blinded. We used multivariate linear regression models for the analysis. Results: 27 participants completed the program (n=15 iso-inertial, n=12 gravitational). Iso-inertial training showed better eccentric power gains than gravitational training for the iso-inertial system evaluation, although the difference was only statistically significant for the side lunge. Forward lunge: between-group difference 4.50 W (95% CI: -2.94 to 11.94, p=0.23); side lunge: difference 9.24 W (95% CI: 2.99 to 15.49; p=0.00); forward lunge with row: difference 15.25 W (95% CI: -0.63 -to 31.13, p=0.06). We observed no differences for the gravitational system evaluation nor for concentric power, physical performance, and risk of falls. The two groups improved remarkably from baseline for all outcomes. Conclusions: Iso-inertial training leads to better eccentric power gains than gravitational training and therefore could be considered by clinicians when prescribing resistance training to middle-older adults. Both training systems were equally effective in improving concentric power and physical performance, and reducing risk of falls. Clinical Trial: This study was registered at Clinicaltrials.gov (NCT06160089).
Shoulder pain is prevalent in people living with spinal cord injury (pwSCI). Technology and digital rehabilitation tools are increasingly available, but this has not yet included provision of a self-g...
Shoulder pain is prevalent in people living with spinal cord injury (pwSCI). Technology and digital rehabilitation tools are increasingly available, but this has not yet included provision of a self-guided exercise intervention focused on managing shoulder pain for pwSCI. We drew on the person-based approach (PBA) to intervention development, to design a Shoulder Pain Intervention delivered over the interNet (SPIN) to address this gap. However, in preparation for the design process we found few published examples of how the PBA had been operationalized. The aim of this paper is to provide a detailed explanation of our approach and how we operationalized the PBA in the design of SPIN to maximize relevance and engagement. Our design process followed the key PBA steps, combining additional evidence and theoretical components. Each step ensured guiding principles were formulated and followed to maximize the probability that SPIN would be fit for purpose. We followed three steps: 1) we drew from themes from preparatory research (existing and primary) to identify the key behavioral issues, needs and challenges, and existing features to form the basis of SPIN design; 2) we formatted guiding principles that included articulating specific design objectives to provide a framework to identify system requirements; and 3) we selected and refined intervention features using existing literature, behavioral theory, and tools such as the ‘Behaviour Change Wheel’. We have designed SPIN by incorporating a deep understanding of the users’ needs and best available evidence, to maximize engagement and positive outcomes. In this paper we have made clear how we operationalized the PBA phases, including how existing evidence, theory, tools, and methods were leveraged to support the PBA process. In explicating our process, we have provided a blueprint to provide guidance to future researchers using this approach.
Background: Sexual and gender minority (SGM) individuals represent 2-5% of the US population, yet continue to account for more than two-thirds of new HIV infections annually. Objective: The American T...
Background: Sexual and gender minority (SGM) individuals represent 2-5% of the US population, yet continue to account for more than two-thirds of new HIV infections annually. Objective: The American Transformative HIV Study (AMETHST) is an ongoing online cohort study of 5,364 SGM individuals from all 50 US states and Puerto Rico, enrolled in 2022 and 2023 and will be followed through 2027. Greater than half of participants are persons of color, and we oversampled persons who use methamphetamine (53.1%). Its focus on identifying multi-level (i.e., structural, psychological, and social) and bio-behavioral (i.e., rectal cytokines/chemokines) determinants of amplified HIV seroconversion risk for SGM individuals, including those who use methamphetamine, will serve to guide targeted, combination interventions to reduce HIV incidence. To be eligible, participants had to report meeting objective criteria for PrEP care, but not be taking PrEP. Methods: We used established internet-based strategies to enroll individuals aged 16-49 years at high risk of HIV acquisition via sexual networking applications. Participants complete annual online surveys (baseline, 12-, 24-, and 36-months) and are asked to provide self-collected oral fluid samples for HIV testing and two rectal swabs (the Aptima Multi-Test Swab and the Zymo DNA/RNA shield swab) following each assessment. Oral fluid samples are analyzed immediately, while rectal swabs are banked for a future nested case-cohort analysis to assess changes in inflammatory markers following a new infection. Results: Nearly all participants (84.7%) were cisgender male, 3.7% (201/5364) were transgender women, and 1.1% (61/5364) were transgender men who have sex with men. There were also n = 560 (10.4%) individuals who self-identified outside of the gender binary—all reported being assigned male sex at birth. In total, 56.5% (3031/5364) were persons of color, and 31.8% (1714/5365) were aged 16 to 29 years. In total, 4,054 baseline HIV test kits were returned, including n = 371 HIV reactive samples—3.3% were HIV-positive among those who did not report methamphetamine use, and 15.5% were HIV-positive among those reporting methamphetamine use. Based on participant’s HIV results as well as self-reporting when their most recent prior HIV-negative test was, we estimated the incidence rate in this cohort in the 12-month period leading up to study enrollment was 10.06 (95% CI 8.65 – 11.64) per 100 person-years among those reporting methamphetamine use compared with 2.04 (95% CI 1.49 -2.73) among those not reporting methamphetamine use per 100 person-years. Conclusions: A large, US national, and racially diverse online cohort of SGM individuals at high risk for HIV has been successfully enrolled and will be followed through 2027. Persons who use methamphetamine have been oversampled and demonstrated an exceptionally greater risk for HIV. Our study will offer insight for the development and implementation of new interventions, which aim to have a meaningful impact on HIV transmission. Clinical Trial: N/A
Background: Dementia is projected to impact 152 million people by 2050, making it one of the most pressing global health challenges. The neurodegenerative process initiates well before clinical sympto...
Background: Dementia is projected to impact 152 million people by 2050, making it one of the most pressing global health challenges. The neurodegenerative process initiates well before clinical symptoms manifest, advancing from subjective cognitive decline (SCD) to mild cognitive impairment (MCI) and ultimately to dementia. Despite the growing prevalence, awareness of dementia prevention is limited, and many individuals express a desire to cease living upon diagnosis. Lifestyle interventions can mitigate cognitive decline, but there is a need for effective, scalable approaches to deliver these interventions to older adults. Digital health interventions, such as app-based just-in-time adaptive interventions (JITAIs), offer a promising solution, but their application in cognitively impaired older populations remains underexplored. Objective: This study evaluated the feasibility, acceptability, and adherence to a smartphone-based JITAI delivered by a rule-based conversational agent (CA) among older adults with SCD or MCI. The primary focus was on adherence to the CA-initiated conversational turns (measured objectively via interaction logs), with secondary objectives including the perceptions of technology acceptance, the working alliance with the CA, self-reported adherence to the suggested health-promoting activity, and feedback for future improvements (through a questionnaire and short interview). Methods: This monocentric study investigated 15 participants (mean age = 70.3 years; 66.7% female and 33.3% male) with SCD (n=12) or MCI (n=3). Participants used the study app that delivered daily health-promoting activities through a CA over two weeks. Participants received notifications to engage in seven health-related activities, and adherence to the activity was self-reported. Post-intervention, participants rated their experience with the app and assessed their working alliance with the CA through the 6-item session alliance inventory. Data on smartphone usage, demographic information, and cognitive performance (via MoCA) were collected during a pre-intervention visit. Results: Participants rated the study app positively, especially regarding ease of use and a subset of the working alliance. Adherence to the CA-initiated conversational turn was measured at an average of 80.95% across 14 days. 27.14% of participants indicated as being vulnerable and 100% then responded with their state of receptivity, of which 82.65% were receptive to completing the activity, and 69.13% self-reporting adherence to the activity. There was no significant decline in adherence across the study period. Qualitative results support these findings and present two emerging themes: app enjoyment and enhancing engagement. Conclusions: This study demonstrates that smartphone-based JITAIs are feasible and generally well-accepted by older adults with SCD or MCI. However, the findings underscore the need for robust technological infrastructure and potential personal assistance to optimize adherence. Future interventions could benefit from integrating wearables to improve real-time engagement and accurately monitor adherence, ultimately supporting healthy aging and cognitive health in older populations.
Background: Intensive Care Unit (ICU) is the department with the highest incidence of hospital infection, and it is also one of the departments that the hospital infection management department focuse...
Background: Intensive Care Unit (ICU) is the department with the highest incidence of hospital infection, and it is also one of the departments that the hospital infection management department focuses on [1,2]. In recent years, the detection rate of multidrug-resistant bacteria (resistant to ≥3 kinds of antimicrobial agents) has been increasing, and they are increasingly dominating the microbial community in hospital environment. Determining effective infection control measures to prevent cross-transmission of MDRO between patients and the environment can minimize potential infection outbreaks. Zhao Lihua et al [3] found that improving the cleaning and disinfection methods in ICU plays an important role in improving the quality of cleaning and disinfection and reducing the proportion of strains causing hospital infection in MDRO. Cotton swab sampling is the gold standard for testing whether there is pathogenic microorganism pollution on the surface of high-frequency contact [4], and it has always been an important tool to judge the cleanliness of the environment. The guidelines for environmental infection control of the Centers for Disease Control and Prevention in the United States point out that medical institutions do not need routine monitoring of air, water and environmental surfaces, and the cost of routine monitoring is high and the income is insufficient. The correlation between positive results of environmental hygiene monitoring and the incidence of nosocomial infection needs to be studied [3]. In recent years, adenosine triphosphate (ATP) fluorescence monitoring method provides direct and real-time feedback. ATP fluorescence detection method is used to evaluate the cleaning and disinfection effect of environmental objects in ICU, which can provide a favorable reference for the management of environmental cleaning and disinfection in ICU. This study objectively evaluates the effect of ATP fluorescence detection method through a meta-analysis of the cleaning and disinfection effect of environmental objects in ICU, providing a basis for improving the surface cleaning of environmental objects in ICU and reducing the incidence of hospital infection. Objective: Meta-analysis method was used to evaluate the cleaning and disinfection effect of ATP bioluminescence detection on the surface of environmental objects in ICU. Methods: Search China Biomedical Literature Database, CNKI China Knowledge Resource Database, Wanfang Medical Academic Journals, VIP Chinese Journals Database, and all related literatures of PubMed, Cochrane, Embase, Web of Science, MEDLINE and CINAHL from the establishment of the database to June 18th, 2024, collect the intervention research on improving the surface cleaning and disinfection effect of environmental objects in ICU by ATP bioluminescence detection, and use RevMan 5.3 and Stata16.0 software for Meta-analysis. Results: A total of 11 articles were included, including 9 before-and-after controlled studies and 2 prospective studies. The final indicators were the qualified rate of environmental surface cleaning and disinfection. The results of meta-analysis showed that the qualified rate increased by at least 29% and at most 41% after the feedback and supervision of environmental cleaning and disinfection in ICU based on ATP fluorescence detection results, which was statistically significant (Z=11.65, P < 0.05). After the intervention measures such as guidance intervention, education and training, and optimization of environmental disinfection and cleaning process were superimposed, the qualified rate increased by at least 34% and at most 42%, with statistical significance (Z=17.41, P < 0.05). After the implementation of the cluster intervention measures, the qualified rate increased by at least 18% and at most 34%, with statistical significance (Z=4.84, P<0.05). Conclusions: The ATP fluorescence detection method is simple to operate, and the data can be directly read on site, so that potential problems can be found in time and corrective measures can be put forward, which can significantly enhance the awareness of medical staff to strengthen cleaning and disinfection and improve the qualified rate of cleaning and disinfection effects on the surface of environmental objects. Clinical Trial: NA
Background: Health information networks (HINs) are often the first stop for people seeking to understand medical conditions. When enhanced with artificial intelligence (AI), these platforms have the p...
Background: Health information networks (HINs) are often the first stop for people seeking to understand medical conditions. When enhanced with artificial intelligence (AI), these platforms have the potential to make a positive impact on health decision-making. Objective: Effective HINs must ensure that AI-generated summaries are based on reputable sources, that the platform content is regularly updated, external links are intact, and new research is integrated in a timely manner as science evolves. Methods: We conducted a qualitative study using semi-structured focus group interviews with eight key health equity experts from rural communities, immigrant populations, and those with disabilities. The goal was to explore considerations for embedding health equity principles into the design and implementation of HINs. Results: Focus groups identified four key themes that are essential for advancing health equity within AI-powered HINs: (1) Account for platform accessibility, (2) engage communities across all phases of development, (3) build in trustworthiness to avoid biases, and (4) make health information actionable. Conclusions: Our study highlights the importance of integrating health equity principles into the development of AI-powered HINs to address existing disparities and promote inclusive access to healthcare resources. By prioritizing accessibility, community engagement, trustworthiness, and actionable information, platform developers can create HINs that leverage emerging technologies and empower users to make informed decisions about their health and well-being.
Background: In the United States, the landscape of unpaid care delivery is both challenging and complex, and millions of individuals undertaking the vital role of helping family (broadly defined) mana...
Background: In the United States, the landscape of unpaid care delivery is both challenging and complex, and millions of individuals undertaking the vital role of helping family (broadly defined) manage their health care and well-being. These family care partners provide critical and often daily support for tasks such as dressing and bathing, as well as managing medications, medical equipment, appointments, and follow up care plans. Objective: To develop and implement a patient portal-based intervention designed to identify, engage, and support care partners in clinical settings. Methods: The project team collaborated with 3 health care organizations (6 primary care practices in total) to design and implement a patient portal-based intervention. Three days in advance of a visit, patients were invited to log on to their patient portal account and answer a brief questionnaire as part of the routine electronic check-in process asking them to: 1) identify themselves as the patient or someone answering for the patient, 2) report major life changes, 3) set the agenda for the upcoming visit, and 4) report on care partner responsibilities. Respondents’ answers to this brief questionnaire were available to providers ahead of the visit. Patients with care partner responsibilities were provided a link to the ARCHANGELS Caregiver Intensity Index to measure the intensity of their caregiving role and motivate care partners to connect with suggested state and local resources. Results: The intervention was launched in September 2022 at Organization A. Organization B launched in May 2023 in one clinic and June 2023 in the other. In focus groups, staff and clinicians reported that the intervention was easy to implement and did not cause workflow disruption. At 6 months post implementation, across both organizations, a total of 22,152patients had received and 13,825 had submitted completed questionnaires (62.4%). Full data will be reported at the completion of the intervention period. Conclusions: Early results suggest that the intervention could be an easily scalable and adaptable method of identifying and supporting care partners in clinical settings.
Background: Exergaming, the combination of exercise and gaming, has emerged as an important area in physical activity research. By leveraging advances in video game technology, exergaming supports bot...
Background: Exergaming, the combination of exercise and gaming, has emerged as an important area in physical activity research. By leveraging advances in video game technology, exergaming supports both physical and mental health. This growing interest in exergaming has increasingly attracted researchers over the years. Considering these developments, we believe that a comprehensive review of studies in this field will provide valuable perspectives for researchers working in this field. Objective: This study aims to identify the most researched concepts and topics in the field of exergaming, track the changes of trending topics over the years; identify the most influential journals as well as the authors who have contributed the most to the field; identify groundbreaking studies and neglected topics that shape future work; and reveal the countries, institutions and collaborations that have contributed the most to the field. It also aims to identify research gaps in the field of exergaming and provide important recommendations for future research. Methods: A bibliometric analysis was carried out using the Web of Science database, including sources up to July 2024. The R-based Bibliometrix package and the Biblioshiny web interface were used for data analysis and visualization. These analyses provided insights into research trends, citation metrics and thematic developments. Results: The results of our analysis reveal a marked increase in exergaming research since 2010, peaking in 2020-2021. High-impact journals such as Games for Health Journal and International Journal of Environmental Research and Public Health are key publishers in this field.
Researchers who have enriched the knowledge base of the exergaming field and made significant contributions include Gao Z, De Bruin ED and Zeng N. The most cited studies were divided into two different clusters. Cluster 1 focuses on concepts such as physical activity, exercise, energy expenditure and children, while Cluster 2 focuses on rehabilitation, balance, adults and aging. Medicine, information technology, dementia and disability are among the new emerging themes. The United States leads the way in terms of research productivity, with institutions such as the Swiss Federal Institute of Technology and the Karolinska Institute as major contributors. Conclusions: : Research in the field of exergaming has mainly focused on physical activity, exercise and rehabilitation. With advances in technology and the market introduction of new active video games, one of the key research gaps is to understand how these games can promote physical activity and other health-related outcomes. Also, the social impacts and community-based applications of exergaming remain critical areas of study. Future research should also investigate the cost-effectiveness, economic benefits and investment opportunities of exergaming, including economic issues and financial sustainability.
This study aims to: (1) evaluate the feasibility of collecting smartphone-based Ecological Momentary Assessment (EMA) data alongside activity and sleep tracking in adolescents with depression; (2) inv...
This study aims to: (1) evaluate the feasibility of collecting smartphone-based Ecological Momentary Assessment (EMA) data alongside activity and sleep tracking in adolescents with depression; (2) investigate the severity and variability of mood symptoms reported over time; and (3) explore the relationship between mood, activity, and sleep.
Twenty-eight participants (16 with Major Depressive Disorder (MDD), 12 unaffected controls) completed twice-daily EMA check-ins over two weeks, complemented by continuous activity and sleep monitoring using FitBit devices. The study examined feasibility, usability of EMA app, symptom severity and variability, and relationships between mood, activity, and sleep.
High compliance rates indicated the feasibility of smartphone-based EMA. MDD participants demonstrated greater symptom severity and variability compared to controls. Additionally, MDD cases exhibited more inconsistent sleep patterns, shorter total sleep times, and a higher frequency of naps. Activity levels, measured by steps per day, did not significantly differ between groups or correlate with mood variability.
This study is one of the first to integrate smartphone-based EMA and wearable activity tracking in adolescents with depression. The findings highlight the potential of these technologies to capture real-time data, providing valuable insights into the dynamic nature of depressive symptoms. Future studies should explore EMA and activity tracking methods in larger, more diverse populations to validate these findings. Clinically, the feasibility of EMA and activity tracking suggests these methods could enhance routine assessments and inform personalized interventions by accounting for individual symptom fluctuations and external factors such as environmental stressors and social interactions
Background: The COVID-19 pandemic emerged as an unprecedented challenge for healthcare systems across the world disproportionately impacting immigrant and racialized populations. Canadian African, Car...
Background: The COVID-19 pandemic emerged as an unprecedented challenge for healthcare systems across the world disproportionately impacting immigrant and racialized populations. Canadian African, Caribbean, and Black (ACB) communities representing some of the most vulnerable populations in terms of their susceptibility to health risks, receipt of adequate care, and chances of recovery. Objective: The COVID-19 ACB Providers Project (CAPP 2) aims to strengthen the ability of health care providers (HCP) to address this community’s COVID-19 related healthcare needs. Informed by CAPP 1.0 Project, a mixed-method study which examined COVID-19 pandemic impact on ACB communities in Ontario (Ottawa and Toronto), this second study seeks to develop and implement educational programs on five key areas (modules) to strengthen the capacity of HCPs working with ACB populations. Methods: An implementation science approach will guide the development, implementation, and evaluation of the evidence-informed interventions. Intersectionality lens, socio-ecological model (SEM) and community-based participatory research (CBPR) frameworks will inform the research process. To ensure active stakeholder engagement, there will be a Project Advisory Committee comprised of 16 ACB community members, health providers, and partner agency representatives. Five modules will be developed: two virtual simulation games in collaboration with leading simulation experts, and three non-simulation modules. The five modules (topics) include: 1) COVID-19 and its impacts on health, 2) social determinants of health and health inequities, 3) critical health literacy, 4) critical racial literacy, and 5) cultural competence and safety. Lastly, the ADDIE Instructional Design method will serve as a framework to design and develop the educational modules. Results: This study will strengthen policies related to HCPs capacity-building requirements, for improved African, Caribbean, and Black care. The results will be disseminated in community workshops, an online learning platform, at academic conferences and in peer-reviewed publications. Conclusions: In summary, enhancing healthcare provision and strengthening resilience during and after COVID-19 will require a whole-scale commitment to anti-racism. HCP are uniquely situated to interact with all members of the community during some of their most vulnerable moments. It is critically important to equip HCPs with the tools to provide culturally competent and equitable care to the ACB population. These five modules will enhance service provider education and build capacity for HCP by ensuring justice, equity, diversity, inclusion and accessibility in healthcare to people from ACB communities and other diverse backgrounds.
Background: Tobacco use remains a major cause of preventable deaths and the leading modifiable risk factor for cancer prevention. In Lao People's Democratic Republic (Lao PDR), approximately 60% of ma...
Background: Tobacco use remains a major cause of preventable deaths and the leading modifiable risk factor for cancer prevention. In Lao People's Democratic Republic (Lao PDR), approximately 60% of male and 15% of female cancer patients smoked cigarettes. Despite, there was no tobacco treatment program for this population. Objective: This paper describes the design, methods, and analysis plans for our pilot intervention randomized controlled trial (RCT) that is funded by the United States National Cancer Institute and that aims to adapt and evaluate the feasibility and preliminary efficacy of our mHealth intervention to help Lao cancer survivors and their caregivers quit smoking cigarettes. Methods: We utilized an intervention mixed-methods research design, which included a pilot 2-group interventional RCT and an embedded qualitative component to explain RCT outcomes. In the pilot RCT, cancer survivors or caregivers (N=80, no dyads) who smoked were recruited from national hospitals in Vientiane Capital. Recruited participants were randomized to 1 of 2 treatment groups: standard care (SC) or mHealth-based automated treatment (AT). SC consists of brief advice to quit smoking delivered by research staff, self-help written materials, and a 2-week supply of nicotine replacement therapy (transdermal patches). AT consists of all SC components plus our fully-automated interactive smartphone-based treatment program, personalized and tailored to cancer survivors or caregivers, and delivered by our Insight app. The primary RCT outcome is biochemically confirmed self-reported 7-day point prevalence abstinence at 3 months post-study enrollment. During the interventional RCT and at the 3-month follow up assessment, we used additional open-ended questions to explore why and how the participants did or did not successfully quit smoking and stay abstinent. Results: Data collection occurred from April 2022 to May 2023. Outcome analyses are ongoing. Conclusions: Our study is the first effort that uses scalable and sustainable mHealth technology to provide tobacco cessation treatment to cancer patients/survivors and their caregivers in Lao PDR. This project is built on a strong partnership with stakeholders at national institutions in Lao PDR, which will enhance the intervention’s sustainability in the future. This project and subsequent fully-powered RCT have the potential to improve cancer care and cancer survivorship research in Lao PDR. Clinical Trial: ClinicalTrials.gov ID: NCT05253573
Background: The successful conduct of health and medical research is largely dependent on participant recruitment. Effective, yet inexpensive methods of increasing response rates for all types of rese...
Background: The successful conduct of health and medical research is largely dependent on participant recruitment. Effective, yet inexpensive methods of increasing response rates for all types of research are required. Quick Response (QR) codes are now commonplace, and despite having been extensively used to recruit study participants, a search of the literature failed to reveal any randomised trial investigating the effect of adding a QR code on qualitative research response rates. Objective: To collect data regarding the impact of the addition of a QR code to a patient consent form for a qualitative research study on cancer patients’ rates of response, consent and decline, and the average time taken to respond. Methods: This was a pilot randomised controlled trial (RCT) embedded within a qualitative research study. Forty eligible patients received a recruitment pack for the qualitative study which included an information statement, a consent form, and an addressed, stamped envelope to return their consent form. Patients were randomised in a 1:1 ratio to the control (standard recruitment pack only) or intervention group (standard recruitment pack including modified consent form with a QR code). Results: Twenty-seven out of 40 patients responded to the consent form. A lower proportion of the QR code group (60%) responded, compared to 75% of the standard recruitment group. However, a higher proportion of the QR group consented (35%) compared to the standard recruitment group (20%), and a lower proportion of the QR group declined (25%) relative to the standard recruitment group (55%). The mean response time of the QR code group was 16 days compared to 19 days for the standard recruitment group. None of the age-adjusted analyses were statistically significant. Conclusions: This trial provides useful preliminary data on the potential impact of QR codes on patient response rates to invitations to participate in qualitative research and can be used to inform a fully powered randomised control trial.
Background: COVID-19 has significantly impacted cross-border movement in Eastern and Southern Africa, with border closures and containment measures affecting the region's economy and social fabric. Ob...
Background: COVID-19 has significantly impacted cross-border movement in Eastern and Southern Africa, with border closures and containment measures affecting the region's economy and social fabric. Objective: This study aimed to assess community myths, beliefs, perceptions, and information needs among Somali communities living on and near ground crossings in Tog-wajaale, Somali region, Ethiopia. Methods: A community-based cross-sectional study was conducted using a multistage sampling technique. Beliefs and perceptions of the virus's spread and control were partially adapted from WHO resources, exploring four main perception themes: perceived facilitators for the spread of the virus, perceived inhibitors, risk labeling, and socio-demographic variables. A sample size of 634 was determined using the single proportion formula, and the data were analyzed using STATA version 14.1. Results: The mean percentages of behavioral non-adherence and lack of an enabling environment as facilitators of virus spread were both high, at 62.5% and 92.2%, respectively. The highest perceived inhibitor to control the spread of Covid-19 was seen to be myth (79.3%), followed by preventive measures (46.6%) and false guarantees (40%). Conclusions: Understanding cross-border transmission dynamics, movement patterns, and the behavior of cross-border actors is crucial for developing effective, contextually appropriate risk communication and community engagement strategies to mitigate COVID-19 risk in border communities.
Background: Sexual response problems among the older adults are not inevitable consequence of aging, but rather response of sexual health. However, there is a lack of recent and multi-center data on t...
Background: Sexual response problems among the older adults are not inevitable consequence of aging, but rather response of sexual health. However, there is a lack of recent and multi-center data on this issue in China. Objective: This study aims to assess the prevalence of sexual response problems and their correlates among older adults. Methods: A multi-centre cross-sectional study on sexual well-being was conducted among individuals aged 50+ years in China between June 2020 and December 2022. Data on socio-demographics, physical health, psychological health, and sexual response problems were collected through face-to-face interviews. We included sexually active older adults who reported either vaginal, oral, or anal sex in the past 12 months for this study. Sexual response problems include lacked sex interest or enjoyment, feeling anxious or pain or no excitement during sex, desire, orgasm, and lubrication in sex. The stepwise logistic regression models were used to examine the correlates of sexual response problems. Results: A total of 1317 sexually active older adults (842 men, 475 women) were included. Older women reported a higher prevalence of sexual response problems than older men (52.0% Vs 43.1%). Common factors associated with at least one of the sexual response problems included living in rural areas (men: aOR=0.31, 95CI%: 0.22-0.43; women: 0.29, 0.19-0.43) and abnormal body mass index (BMI) (men: 1.52, 1.11-2.07; women: 2.19, 1.47-3.28). Among older men, sleep quality (1.87, 1.30-2.68), emotional connection with sex partners during sex intercourse (0.69, 0.50-0.96), frequently experienced fatigue (2.47, 1.59-3.90), anxiety (4.26, 1.12-21.27), and seeking professional help for sex life (1.58, 1.14-2.21) were associated with sexual response problems. Among older women, sexual response problems were associated with a lack of physical exercise (1.69, 1.13-2.54), poor sex-partner relationships (1.70, 1.12-2.60), and depressive symptoms (3.18, 1.18-10.24). Conclusions: Sexual response problems are common among older adults. These problems were associated with adverse physical health, mental health and poor sex-partner relationships. These findings highlight the importance for healthcare providers to take into account for the physical and mental health of older adults, as well as the quality of their relationships with sexual partners, when diagnosing and addressing sexual response problems.
Background: The COVID-19 pandemic necessitated widespread vaccination campaigns to mitigate its effects. While various strategies were employed to encourage vaccine uptake, including digital media cam...
Background: The COVID-19 pandemic necessitated widespread vaccination campaigns to mitigate its effects. While various strategies were employed to encourage vaccine uptake, including digital media campaigns, promotion efforts, and community outreach programs, there is limited understanding of the comparative effectiveness of these methods in increasing vaccination rates, particularly in Nigeria. This study aimed to examine the relationships between these strategies and COVID-19 vaccination uptake in a sample population. Objective: The objective of this study was to analyze the relationships between digital media campaigns, community outreach programs, and promotion efforts on COVID-19 vaccination uptake, and to determine which strategy had the most significant impact on increasing vaccination rates in Nigeria. Methods: A cross-sectional survey of 300 respondents was conducted using a structured questionnaire. Data were analyzed using descriptive statistics to summarize the demographic characteristics of the sample and inferential statistics, including Spearman’s correlation and regression analysis, to assess the relationships between the three strategies and vaccination uptake. Non-parametric tests were used to account for non-normal distribution of data. Results: The study found that promotion efforts had the strongest correlation with COVID-19 vaccination uptake (Spearman’s rho = 0.490, p < 0.01), followed by community outreach programs (Spearman’s rho = 0.414, p < 0.01), and digital media campaigns (Spearman’s rho = 0.239, p < 0.01). Regression analysis showed that digital media campaigns accounted for 5.7% of the variance in vaccination uptake (R² = 0.057), indicating a modest but statistically significant effect. Conclusions: All three strategies namely digital media campaigns, promotion efforts, and community outreach programs had significant positive associations with COVID-19 vaccination uptake. However, promotion efforts were found to be the most effective. Digital media campaigns, while statistically significant, had the weakest correlation. Future vaccination campaigns should prioritize promotion efforts, particularly targeted and localized strategies, to improve vaccine uptake. Community outreach programs should also be enhanced, especially for younger and less-educated populations. Digital media campaigns, though less impactful, remain a valuable tool for reaching broader audiences. This study provides critical insights into the relative effectiveness of various vaccine promotion strategies in Nigeria. The findings emphasize the importance of tailored promotion efforts and community engagement to enhance public health interventions, particularly in low-resource settings.
Background: Clinical trial success depends on efficient participant recruitment and retention, yet low enrollment and high attrition remain persistent challenges. To address these issues, we developed...
Background: Clinical trial success depends on efficient participant recruitment and retention, yet low enrollment and high attrition remain persistent challenges. To address these issues, we developed RecruitGPS, a scalable dashboard that provides investigators with timely data to improve subject participation and recruitment outcomes. Objective: This paper examines the design and effectiveness of RecruitGPS, a tool designed to monitor participant enrollment throughout the clinical trial recruitment lifecycle Methods: RecruitGPS was prototyped using Microsoft Excel for its accessibility and rapid deployment. The tool integrates with existing databases like REDCap, simplifying data import and analysis. We evaluated the dashboard effectiveness using a mixed method approach, with 12 clinical researchers. Results: The study was funded in September 2022, with data collection, completed in August 2024, revealed an average System Usability Scale score of 73.75 and 91.7% of participants rating the dashboard’s efficiency at 4 or 5 (out of 5). The presence of 25% detractors in Net Promoter Score indicates the need for improvements to the overall user experience. Conclusions: RecruitGPS enhances decision-making throughout the recruitment process, offering significant potential to improve clinical trial efficiency and ensure the validity of study outcomes.
Background: Hypothermia in young infants presenting to the emergency department (ED) may indicate a serious bacterial infection (SBI) such as a urinary tract infection, bacteremia, or bacterial mening...
Background: Hypothermia in young infants presenting to the emergency department (ED) may indicate a serious bacterial infection (SBI) such as a urinary tract infection, bacteremia, or bacterial meningitis. Improved understanding of the epidemiology of SBI in hypothermic infants and the development of prediction models can help avoid unnecessary invasive procedures and antimicrobial exposure. The objectives of this multicenter study are to (1) describe the epidemiology of SBI and HSV among hypothermic infants, (2) assess the role of biomarkers in predicting SBI, and (3) derive and internally validate a multivariable predictive model for SBI among hypothermic infants. Objective: The objectives of this multicenter study are to (1) describe the epidemiology of SBI and HSV among hypothermic infants, (2) assess the role of biomarkers in predicting SBI, and (3) derive and internally validate a multivariable predictive model for SBI among hypothermic infants. Methods: The study is being conducted through the Pediatric Emergency Medicine Collaborative Research Committee (PEMCRC) as a retrospective nested case-control study. We will include infants with hypothermia (rectal temperature <36.5 °C) presenting to one of 30 pediatric EDs in the United States between January 1, 2013, and December 31, 2022. Exclusion criteria will include (1) fever in the ED or prior to ED arrival, (2) transfer from another healthcare facility, (3) technology dependence, (4) trauma, (5) skin and soft tissue infections, and (6) presentation in cardiac arrest. The primary outcomes will be culture-confirmed SBI (objectives 1-3) and HSV-positivity (objective 1). The analytic approach for each objective will be to (1) use descriptive statistics to summarize the epidemiology of SBI and HSV and clinical outcomes, (2) compare biomarker parameters of infants with and without SBI and determine optimal cut-off values using a receiver operator characteristic curve, and (3) develop a multivariable predictive model using penalized mixed effects logistic regression within a 1:3 case-control sample among infants in the cohort who had a blood culture obtained. Results: Data collection for this study is ongoing, with collection of data from 13 hospitals at the time of protocol submission. Conclusions: We will use a consensus-based outcome measure for SBI with an established data acquisition pathway. We will use a multicenter sample from 30 U.S. children's hospitals, employing a consensus-based outcome measure for SBI and a case-control approach to effectively evaluate rare outcomes to improve the management of young infants with hypothermia in the emergency department.
Background: There is breast cancer-related medical information on social media, but there is no established method for objectively evaluating the quality of this information. PRHISM is a newly develop...
Background: There is breast cancer-related medical information on social media, but there is no established method for objectively evaluating the quality of this information. PRHISM is a newly developed tool for objectively assessing the quality of health-related information on social media; however, there have been no reports evaluating its reliability and validity. Objective: The purpose of this study is to statistically examine the reliability and validity of PRHISM using videos about breast cancer treatment on YouTube. Methods: Sixty YouTube videos were selected on January 5, 2024, with the Japanese words for “breast cancer”, “treatment”, and “chemotherapy”, and assessed by six Japanese breast cancer experts. These evaluators independently evaluated the videos using PRHISM and an established tool for assessing the quality of health-related information, DISCERN, as well as through subjective assessments. We calculated inter-rater and intra-rater agreement among evaluators with confidence intervals, measuring agreement using weighted Cohen's kappa. Results: The inter-rater agreement for PRHISM overall quality was κ=0.52 (90% CI: 0.49, 0.55), indicating that the expected level of agreement, statistically defined by the lower limit of the 90% confidence interval exceeding 0.53, was not achieved. However, PRHISM demonstrated higher agreement compared to DISCERN overall quality, which had a κ=0.45 (90% CI: 0.41, 0.48). In terms of validity, the intra-rater agreement between PRHISM and subjective assessments by breast experts was κ=0.37 (95% CI: 0.14, 0.60), while DISCERN showed an agreement of κ=0.27 (95% CI: 0.07, 0.48), indicating fair agreement and no significant difference in validity. Conclusions: PRHISM has demonstrated sufficient reliability and validity for evaluating the quality of health-related information on YouTube, making it a promising new metric.
The VISIA camera is a novel device that captures images of the skin using a rotating camera with both UV and polarized light to assess the condition of the skin by imaging the surface and beneath it....
The VISIA camera is a novel device that captures images of the skin using a rotating camera with both UV and polarized light to assess the condition of the skin by imaging the surface and beneath it. It provides patients with an easy-to-understand analysis helping them understand their skin’s problem areas to target further treatment. Actinic Keratoses (AKs) are precancerous lesions that are diagnosed by use of the naked eye and the dermatoscope. We believe it would be beneficial to use the VISIA camera for AK patients to get an indepth look at the effects of sun exposure on their skin, providing motivation to undergo field treatment of AKs using 5-Fluorouracil (5-FU) for patients with hesitancy. We are conducting an observational study with results reported here on a male patient diagnosed with diffuse AKs who was prescribed and had consented to go through 5-FU treatment on the scalp. An initial photo was taken on the VISIA prior to treatment, 5-FU was applied twice daily to the scalp for 4 weeks and a follow up photo was obtained 1 week and 3-months post-treatment. Results using the UV spot filter, feature count decreased from 706 to 631 and percentile reduced from 83% to 39%. Spot filter produced the same percentile of 9% for all photos affirming the VISIA’s efficacy in detecting UV damage-related areas. This study enhances patients’ understanding of 5-FU’s effectiveness on their AKs and provides a positive example of treatment success for future patient education and treatment adherence.
Background: Traumatic brain injury (TBI) is a major cause of death and disability in all age groups, placing a heavy burden on society and families，serum albumin levels have a significant impact on...
Background: Traumatic brain injury (TBI) is a major cause of death and disability in all age groups, placing a heavy burden on society and families，serum albumin levels have a significant impact on mortality and length of hospitalization patients. This study was made to develop a predictive model based on Computed Tomography (CT) and clinical parameters to explore the predictable power of the model in the development of hypoproteinemia with TBI patients. Objective: To explore the predictable power of the model in the development of hypoproteinemia with TBI patients. Methods: A total of 72 TBI patients were prospectively recruited and confirmed as hypoproteinemia in 26 cases. A cranial CT and clinical parameters such as age, gender, admission Glasgow score were collected to establish the clinical model. The least absolute shrinkage and selection operator (LASSO) was applied to extract radiological features. Then a total of five different machine learning methods (RF, SVM, GNB, XGB, KNN) were used to establish the prediction model of radiomics. Finally, a combined model: clinical-radiological was constructed. The average area under the curve (AUC) were used to evaluate the performance of each model. Results: Comparing these three different models, we found that the radiomic models combined with clinical parameters showed the best performance, which had an AUC with 0.8704 compared with clinical model only AUC=0.8512 and radiomics model only AUC=0.7040, respectively. Conclusions: The model of radiomics features combined with clinical parameters is superior to the radiomics model and clinical model alone, and the model of radiomics combined with clinical parameters is a useful tool for predicting the occurrence of hypoproteinemia in patients with traumatic brain injury.
Background: Case studies have shown ChatGPT can run clinical simulations at the medical student level. However, no data have assessed ChatGPT’s reliability in meeting desired simulation criteria suc...
Background: Case studies have shown ChatGPT can run clinical simulations at the medical student level. However, no data have assessed ChatGPT’s reliability in meeting desired simulation criteria such as medical accuracy, simulation formatting, and robust feedback mechanisms. Objective: To quantify ChatGPT’s ability to consistently follow formatting instructions and create simulations for preclinical medical student learners according to principles of medical simulation and multimedia educational technology. Methods: Using ChatGPT-4 and a pre-validated starting prompt, the authors ran 360 separate simulations of an acute asthma exacerbation. 180 simulations were given correct answers and 180 were given incorrect answers. ChatGPT was evaluated for its ability to adhere to basic simulation parameters (stepwise progression, free response, interactivity), advanced simulation parameters (autonomous conclusion, delayed feedback, comprehensive feedback), and medical accuracy (vignette, treatment updates, feedback). Significance was determined with chi-squared analyses using 95% confidence intervals for odds ratios. Results: 100% of simulations met basic simulation parameters and were medically accurate. For advanced parameters, 55% of all simulations delayed feedback, while the Correct arm (87%) delayed feedback significantly more than the Incorrect arm (24%) (p<0.001). 79% of simulations concluded autonomously, and there was no difference between the Correct and Incorrect arms in autonomous conclusion (81%, 77%; p=0.364). 78% of simulations gave comprehensive feedback, and there was no difference between the Correct and Incorrect arms in comprehensive feedback (76%, 81%; p=0.306). ChatGPT-4 was significantly more likely to conclude simulations autonomously (p<0.001) and provide comprehensive feedback (p<0.001) when feedback was delayed compared to when feedback was not delayed. Conclusions: ChatGPT simulations performed perfectly on medical accuracy and basic simulation parameters. It performed well on comprehensive feedback and autonomous conclusion. Delayed feedback depended on the accuracy of user inputs. A simulation meeting one advanced parameter was more likely to meet all advanced parameters. These simulations have the potential to be a reliable educational tool for simple simulations and can be evaluated by a novel nine-part metric. Further work must be done to ensure consistent performance across a broader range of simulation scenarios.
Background: Artificial intelligence (AI) has advanced significantly in various fields, including medicine, where tools like ChatGPT (GPT) have demonstrated remarkable capabilities in interpreting and...
Background: Artificial intelligence (AI) has advanced significantly in various fields, including medicine, where tools like ChatGPT (GPT) have demonstrated remarkable capabilities in interpreting and synthesizing complex medical data. Since its launch in 2019, GPT has evolved, with version 4.0 offering enhanced processing power, image interpretation, and more accurate responses. In medicine, GPT has been used for diagnosis, research, and education, achieving significant milestones like passing the USMLE board exam. Recent studies show that GPT 4.0 outperforms its earlier versions and medical students on medical exams. Objective: This study aimed to evaluate and compare the performance of GPT versions 3.5 and 4.0 on Brazilian Progress Tests (PT) from 2021 to 2023, analyzing their accuracy compared to medical students. Methods: A cross-sectional observational study was conducted on 333 multiple-choice questions from the PT, excluding questions with images, nullified, or repeated items. All questions were presented sequentially, without any modification to their structure. The performance of GPT versions was compared using statistical methods, and medical students' scores were included for context. Results: GPT 4.0 showed a significant improvement in accuracy, achieving an 87.2% accuracy rate compared to 68.4% for GPT 3.5 (p-value = 0.028), representing a relative improvement of 27.4%. Despite these differences, both GPT 3.5 and 4.0 achieved a higher score than students from all years of medical school. Conclusions: GPT 4.0 demonstrates superior accuracy compared to its predecessor in answering medical questions on the PT. The results of this article are similar to other researches, indicating that we are getting closer to new revolution in Medicine.
Background: Virtual Reality (VR) has emerged as a promising, low-risk strategy to manage many forms of psychological stress and may be a modality to improve cardiovascular health. Recent scientific st...
Background: Virtual Reality (VR) has emerged as a promising, low-risk strategy to manage many forms of psychological stress and may be a modality to improve cardiovascular health. Recent scientific statements on the mind-heart-body connection call for better adherence to psychological screening and adoption of more holistic, “behavioral cardiology” interventions that improve overall health of patients with or at risk for cardiovascular disease (CVD). Objective: The aim of this study is to explore how a VR experience can aid in stress reduction among patients with/at risk for CVD. Methods: A convergent mixed-methods approach was used for this single-arm prospective pilot study. 20 patients were recruited from UCLA adult cardiology clinics & cardiac rehabilitation. Surveys and physiologic parameters were collected before, during, and after a 30-minute VR experience aimed at relaxation. The primary outcome was the State-Trait Anxiety Inventory-State scale (STAI-S). They participated in a 90-minute visit during which they completed surveys, including the STAI-S, before & after a 30-minute VR experience. Physiological parameters were also collected before, during, and after the experience. Visits concluded with semi-structured interviews analyzed with inductive thematic analysis to add depth and nuance to our analysis. Results: STAI-S scores after the VR experience were significantly decreased from baseline (P<0.001). Verbal feedback revealed that participants experienced a relaxing sense of “distance from stress” moderated by unexpected, intense audiovisual components. Heart rate significantly decreased (P<0.001) while blood pressure (systolic: P=0.75, diastolic: P=0.60) & galvanic skin response (P=0.5) remained the same. Changes in heart rate variability parameters were consistent with increased vagal tone over time but were only statistically significant at certain timepoints. Survey results and interviews generally indicated safety, tolerability, and openness to using VR again. Conclusions: This sample of patients with cardiovascular disease or risk of cardiovascular disease had above-average stress, supporting epidemiological data and the need for increased awareness of the mind-heart-body connection; the statistically and clinically significant decrease in subjective perception of stress partially converged with physiologic data. Overall, the VR intervention was a safe, viable stress reduction method. This study can help inform future research utilizing this immersive therapeutic (or others) to reduce cardiovascular risk profiles. Clinical Trial: UCLA Institutional Review Board (#21-000705) and the ClinicalTrials.gov registry number was NCT04984655 https://clinicaltrials.gov/study/NCT04984655
Background: Deep Brain Sound Stimulation (DBSS) is an innovative, non-invasive neuromodulation technique that aims to enhance neural synchronization and neuroplasticity by using precision-targeted aud...
Background: Deep Brain Sound Stimulation (DBSS) is an innovative, non-invasive neuromodulation technique that aims to enhance neural synchronization and neuroplasticity by using precision-targeted auditory stimuli. Unlike traditional brainwave entrainment methods, DBSS employs monaural and isochronic tones that are carefully modulated to activate specific brain regions through frequency-following responses (FFRs). This approach addresses limitations found in established techniques such as Transcranial Magnetic Stimulation (TMS) and Transcranial Direct Current Stimulation (tDCS). Objective: The study aims to assess the therapeutic impact of DBSS across a broad range of neurological and psychological conditions, including anxiety, depression, ADHD, Parkinson’s disease, and PTSD. It further evaluates DBSS’s user-reported safety, satisfaction, and adaptability as a self-administered neuromodulation method. Methods: DBSS was applied across 134 therapy applications, targeting specific brain regions associated with various conditions. This report examines feedback from over 6,400 users engaging with 50 specific DBSS therapies, out of a total user base of more than 500,000 worldwide. User data was collected to assess safety, effectiveness, and satisfaction rates. Results: Preliminary findings reveal a high satisfaction rate of 98.52% among users, with a minimal refund rate of 1.48%. User feedback and case studies indicate notable improvements in cognitive, emotional, and motor functions across the studied conditions, underscoring the adaptability and therapeutic potential of DBSS. The report also confirms a high safety profile, with minimal adverse effects reported. Conclusions: These initial findings suggest that DBSS holds promise as a versatile neurotherapeutic tool. However, further research and controlled clinical trials are essential to validate its long-term efficacy, optimize treatment protocols, and establish standardized usage guidelines for broader therapeutic applications. Clinical Trial: Not applicable.
Background: Mass displacement is a grand public health challenge. Refugees experience a disparate hypertension (HTN) burden and disparities in self-management. Successful HTN self-management is key fo...
Background: Mass displacement is a grand public health challenge. Refugees experience a disparate hypertension (HTN) burden and disparities in self-management. Successful HTN self-management is key for improving outcomes, but research on its feasibility in refugee healthcare settings is limited. Objective: Our aim was to assess the perspectives of refugee health providers on telemonitoring home BP management using connected BP monitors. Methods: Primary care physicians (PCPs) and medical assistants (MAs) that care for refugees in San Diego were interviewed using human-centered semi-structured methods (n=18). Interviews were analyzed using an inductive approach. Usability testing for the BP software (Med Pro Care) was conducted with participants (n=15) to test the feasibility of real-time tracking of BP home readings. Providers rated their satisfaction on a System Usability Scale and the NASA Task Load Index which measures mental workload. Results: For refugee patients self-managing HTN, providers identified the following as facilitators: 1) family support, 2) language resources, and 3) trust. The following barriers were identified: 1) life stressors, 2) language barriers, 3) cultural differences, 4) socioeconomic status, 5) lack of awareness, and 6) unavailability of equipment. PCPs completed 90% and MAs completed 83% of the tasks successfully. The majority of providers found the software system for self-management of HTN to be easy to use with an average score for usability of 3.59 out of 5 (SD ± 0.76). Conclusions: Identified barriers and facilitators of self-management of HTN are crucial to designing effective interventions in real-world refugee healthcare settings. Telemonitoring interventions using software that transfers BP readings to providers in real time may be feasible from the perspective of healthcare providers and can address hypertension disparities in marginalized populations.
Background: Urinary incontinence affects around 7-10% of children during the day and 9-12% during the night. Once anatomical and neurogenic causes are ruled out, treatment mainly involves lifestyle ad...
Background: Urinary incontinence affects around 7-10% of children during the day and 9-12% during the night. Once anatomical and neurogenic causes are ruled out, treatment mainly involves lifestyle advice and behavioral methods. However, motivation and adherence to these methods, essential for success, are often low. Traditional tools, such as pen-and-paper solutions, may feel outdated to today’s ‘digital native’ children. As healthcare evolves with technology, traditional UI management tools may no longer meet children’s needs, potentially affecting their motivation and adherence. Objective: Our objective was to identify innovative, tech-driven and digital tools for managing pediatric urinary incontinence as alternatives to traditional methods and provide an overview of their supporting evidence. Methods: This scoping review followed PRISMA-ScR guidelines, with a search conducted in March 2022 across PubMed, Web of Science, and Cochrane Library, without date limits. The review focused on innovative, tech-driven and digital tools for pediatric urinary incontinence management, covering a wide range of dysfunctions and behavioral methods. Articles involving adults, lacking results, not in English, or missing full texts were excluded. From 2030 articles retrieved, 60 were included after screening, with 6 additional articles identified through cross-references, resulting in a total of 66 included articles. Results: The field of pediatric urinary incontinence demonstrates a considerable level of innovation, as evidenced by the inclusion of 66 studies, with nearly one-third (38%, n=25/66) focusing on nocturnal enuresis. Most studies were randomized controlled trials (n=14) or validation studies (n=13), and over one-third (38%, n=25/66) assessed patient experience outcomes such as satisfaction, motivation, and usability. Our analysis led to the identification and classification of six main categories of tools: (i) mobile health (n=7), (ii) serious games (n=7), (iii) reminder technology (n=6), (iv) educational media (n=12), further divided into video (n=5) and other media (n=7), (v) telehealth and remote patient monitoring (n=13), with subcategories of communication (n=5) and technological advances (n=8), and (vi) enuresis alarm innovations (n=21), further divided into novel configurations (n=8) and pre-void alarms (n=13). Conclusions: Many of the tools identified in this review show great promise as feasible and effective alternatives to traditional methods. They engage children well, improving compliance and leading to high satisfaction and preference, while also having the potential to save time for healthcare providers. However, their superiority over traditional methods remains unclear due to study limitations and conflicting results. Additionally, managing pediatric UI is complex due to its multifaceted nature, requiring accurate diagnosis and tailored interventions that consider clinical signs, child characteristics, and stakeholder involvement. We propose that future tools evolve into holistic, adaptive, and personalized ecosystems that align with stakeholders' needs by integrating diverse strategies for urinary incontinence management. Combining different tool categories identified in this review may provide a framework for creating these ecosystems.
This paper aims to describe the co-creation and development processes of an educational ecosystem-centered BSc degree in Digital Health and Biomedical Innovation (SauD InoB). This program is shaped by...
This paper aims to describe the co-creation and development processes of an educational ecosystem-centered BSc degree in Digital Health and Biomedical Innovation (SauD InoB). This program is shaped by a multidisciplinary, intersectoral and collaborative framework, involving over 60 organizations in teaching activities and/or internship supervision/hosting, most of which collaborated in needs assessment, curriculum design and public promotion of the degree. In the context of healthcare digital transformation, this comprehensive BSc degree will respond to unmet demands of the labor market by training students with technological, research and management skills, as well as with basic clinical and biomedical concepts. Graduates will become transdisciplinary, creative professionals capable of understanding and integrating different "languages," and reasoning, clinical processes, and scenarios.
Background: Functional dyspepsia is a common gastrointestinal condition characterised by symptoms such as epigastric pain or burning, early satiety, or postprandial fullness, that negatively impacts q...
Background: Functional dyspepsia is a common gastrointestinal condition characterised by symptoms such as epigastric pain or burning, early satiety, or postprandial fullness, that negatively impacts quality of life, work productivity and healthcare costs. A lack of well-defined causes for the condition limits effective treatment options. Consumers around the world report using mānuka honey as a treatment for gastrointestinal symptoms, including dyspepsia, although clinical evidence supporting such use is limited. Pre-clinical studies indicate that unique compounds in mānuka honey may have bioactive properties that could prevent gastrointestinal inflammation. Recently, a 3,6,7 trimethyllumazine (Lepteridine™), a natural pteridine compound in mānuka honey, was shown to inhibit enzymes involved in gastrointestinal inflammation in in vitro studies. Therefore, Lepteridine™ standardised mānuka honey may deliver digestive health benefits. Objective: The aim of this feasibility study is to gather data required to estimate sample size and support study logistics to design future trials. The primary objective will be preliminary assessments of the impact of Lepteridine™ standardised mānuka honey on digestive symptom severity and quality of life in subjects with mild to moderate functional dyspepsia. Other feasibility objectives include assessing the biological responses to mānuka honey standardised to medium and high levels of Lepteridine™, and concentrations of mānuka honey-derived metabolites in blood and urine following consumption. Methods: This is a three-arm, parallel, controlled, double-blind, randomised feasibility study. Seventy-five healthy adults with symptoms of functional dyspepsia (Rome IV Criteria) and mild-to-moderate severity of dyspepsia (Short Form Leeds Dyspepsia Questionnaire) were recruited between October 2022 and September 2023. Participants were randomised into one of three groups: 1) mānuka honey standardised to contain 10 mg/kg Lepteridine™; 2) mānuka honey standardised to contain 40 mg/kg Lepteridine™; or 3) honey maple flavoured syrup control. After a two-week lead-in period, participants consumed 10 g of their respective intervention twice daily for six weeks. Throughout the study, participants completed daily bowel movement diaries and validated weekly questionnaires about their gastrointestinal symptoms and quality of life. Three-day diet records and stool samples were collected at baseline and end of the intervention. Blood samples were collected at baseline, weeks two and four, and at the end of the intervention. In addition, six healthy participants without symptoms of functional dyspepsia were recruited to undergo an acute five-hour assessment for the appearance of Lepteridine™ and related metabolites in plasma and urine following consumption of Lepteridine™ standardised mānuka honey. The study was approved by the Northern B Health and Disability Ethics Committee. Results: At the time of writing, laboratory and data analyses are being undertaken. The results of the primary and secondary outcomes will be published in peer-reviewed journals. Conclusions: This study will provide essential information on the potential efficacy and suitability of Lepteridine™ standardised mānuka honey to design future clinical trials investigating the effect of Lepteridine™ standardised mānuka honey for the treatment of symptoms of functional dyspepsia. Clinical Trial: Australian New Zealand Clinical Trials Registry, Trial Number ACTRN12622001140741p
Background: The healthcare sector's digital transformation has accelerated, yet adverse drug events (ADEs) continue to rise, posing significant clinical and economic challenges. Clinical Decision Supp...
Background: The healthcare sector's digital transformation has accelerated, yet adverse drug events (ADEs) continue to rise, posing significant clinical and economic challenges. Clinical Decision Support Systems (CDSS), particularly those related to medication, are crucial for improving patient care, identifying Drug-Related Problems (DRPs) and reducing ADEs. Hospital pharmacists play a key role in utilizing CDSS for patient management and safety. Human Factors and Ergonomics (HFE) methods are essential for designing effective, human-centered CDSS. HFE involves three phases: exploration, design, and evaluation, with exploration being critical yet often overlooked in literature. For medication-related CDSS, understanding hospital pharmacists' tasks and challenges is vital for creating user-centered solutions. Objective: The aim of this study is to explore the actual practices and identify the needs of hospital pharmacists analyzing electronic prescriptions. This study focuses on the preliminary stage of user-centered design of a pharmacist-centered CDSS. Methods: The study involved observing 16 pharmacists across five hospitals in mainland France, including a university hospital, two large general hospitals, a smaller general hospital, and a specialized clinic. Pharmacists were selected regardless of expertise. The observation method used systematic in situ observation with shadowing posture, following pharmacists as they analyzed prescriptions. Researchers recorded activities, tools used, verbalizations, behaviors, and interruptions, using an observation grid. Data analysis focused on modeling pharmacists' cognitive work, categorizing activities by action type, specificity, and information source. Sequential time data analysis and distance matrices were employed to generate hierarchical clustering and identify similarity groups among the pharmacists' analysis. Each group is described using its typical sequences of analysis and related covariates. Results: 16 pharmacists analyzed and validated electronic prescriptions for 140 patients, averaging 5.48 minutes per patient. They spend 91% of their time searching for information rather than transmitting it. Most information comes from the list of prescriptions but it's the time spent in the Electronic Medical Record (EMR) that dominates at the heart of the analysis. Pharmaceutical interventions are most frequently transmitted in the last third of the sequence.
The pharmaceutical analysis were grouped into four clusters:
A (22%): Interventionist clinical analysis with extensive crossing of various sources of information and almost systematic pharmaceutical interventions.
B (52%): Most common clinical analysis focusing on EMR and biology results.
C (13%): Logistical analysis, focusing on the pharmacy workflow and the medication circuit.
D (13%): Quick, trivial analyses based exclusively on the list of prescriptions. Conclusions: The pharmaceutical analysis process is complex and multifaceted. Pharmacists are detectives, accessing a wealth of information in order to discriminate DRPs and respond accordingly. They also carry out different types of analysis, which lead to different needs and require different solutions from CDSS. This exploratory study is an essential prerequisite for meeting the challenge of designing tools to support pharmaceutical analysis and pharmacists.
Background: Chronic pain in adolescents is a significant and growing concern, as it can have negative implications on physical and psychosocial development. Management can be complicated by the increa...
Background: Chronic pain in adolescents is a significant and growing concern, as it can have negative implications on physical and psychosocial development. Management can be complicated by the increasing risks associated with opioid misuse, highlighting the need for effective non-pharmacological interventions. Biofeedback is an empirically supported behavioral intervention for chronic pain that targets the self-regulation of physiological responses. Virtual reality (VR) is a novel delivery method for biofeedback that could serve as an engaging and effective platform for adolescents. Objective: The goal of this study was to assess the feasibility, acceptability, and preliminary effectiveness of integrating a VR-delivered respiratory biofeedback intervention into an outpatient pediatric pain rehabilitation program (PPRP) for adolescents with chronic pain. Methods: In this pilot study, we recruited nine participants (age 13-18 years old, 89% female, 33% non-Hispanic white) from those enrolled in the PPRP at Nemours Children’s Hospital. Participants underwent 2 VR respiratory biofeedback sessions per week over a 4-week period using AppliedVR’s “RelieVRx” program. Feasibility was defined as: >60% of eligible patients enrolling with at least 80% of VR sessions completed. Acceptability was assessed via validated acceptability questionnaires, with high acceptability defined as an average acceptability rating score >3 on a 5-point Likert scale. Open-ended responses were analyzed via qualitative analysis. Preliminary effectiveness was assessed with questionnaires measuring the quality of life (PedsQL) and level of pain interference in daily activities (FDI) before and after participation in the pain program. Lastly, heart rate (HR) and blood pressure (BP) were measured before and after each VR session. Results: Of 14 eligible PPRP patients, 9 (64%) enrolled in the VR respiratory biofeedback study, and 7 (77% of study participants) completed at least 80% of biofeedback sessions. Participants reported high acceptability with average session ratings ranging from 3.89 to 4.16 on post VR program questionnaires. Of 224 open-ended responses, participants reported changes in stress and somatic symptoms (i.e. pain distraction, breathing regulation). There was a statistically significant increase in the average physical functioning score of the PedsQL among participants (p=0.009) from pre- to post- participation in the overall pain program. The cohort’s average emotional functioning score of the PedsQL also increased, though this change was not statistically significant (p=0.176). Participant FDI scores significantly decreased from an average of 25.1 to 11 from before to after the pain program (p=0.002). There were no significant differences between pre vs. post BP or HR for any session. However, decreased BP and HR was observed across most sessions. Conclusions: AppliedVR respiratory biofeedback demonstrated initial feasibility, acceptability, and preliminary effectiveness when implemented as part of a PRPP. This study underscores the need for future larger-scale studies analyzing the use of VR biofeedback in adolescent populations with chronic pain.
Background: Mental health problems and adverse health behaviors are enriched in individuals with obesity, and need to be considered in weight-loss interventions. Regarding weight-loss, hybrid interven...
Background: Mental health problems and adverse health behaviors are enriched in individuals with obesity, and need to be considered in weight-loss interventions. Regarding weight-loss, hybrid interventions combining digital and in-person elements have proven superior compared to eHealth-only interventions. However, it remains unclear whether a minimal group or individual enhancement could bring additional benefits to mental health and health behavior domains in individuals with obesity. Objective: The study explored whether minimal group or individual enhancements could offer additional benefits to an eHealth intervention, specifically in relation to mental health, perceived work ability, and health behavior. Additionally, the study sought to examine the overall effects of the health behavior-focused intervention, which combined ACT and behavioral components, across these domains. Methods: This study was a randomized controlled trial (RCT) with a 12-month intervention with selected variables followed for another 12-months without additional support. Recruited from occupational health care, 111 working-age adults with BMI 30–40 kg/m2 were randomized to one of the three treatment arms: eHealth, eHealth+Group, or eHealth+Individual. All treatment arms received a web-administrated, coach-assisted eHealth program based on ACT and, additionally, the eHealth+Group and eHealth+Individual arms received three remotely facilitated group or individual meetings. The participants were assessed for depression (BDI-21), burnout (BBI-18), perceived work ability, eating behavior (ecSatter2.0, TFEQ and BES) and physical activity (BPAQ). Results: Neither of the treatment arms showed superiority over another. Across all participants, depression showed an estimated mean decrease of 2.5 BDI-21-points, with older participants experiencing a greater reduction in depressive symptoms. Furthermore, there were increases in eating competence, controlled restraint and physical activity, and decreases in uncontrolled eating and binge eating tendency. However, the 24-month measurements showed an adverse effect in eating competence, especially in attitudes towards eating and food, during the follow-up without further support. Conclusions: Minimal enhancement through either group or individual virtual meetings did not provide additional benefits in mental health or eating habit domains compared to the eHealth intervention alone. However, the eHealth intervention effectively reduced depression symptoms, uncontrolled eating, and binge eating tendencies, while also improving eating competence and physical activity across the study population. Future research should explore the effect of providing additional support during the follow-up period to sustain the positive outcomes achieved during the intervention. Clinical Trial: ClinicalTrials.gov Identifier: NCT04785586 (March 8, 2021)
RR2-10.1016/j.conctc.2020.100638
Background: Long COVID is characterised by an array of physical and psychological symptoms that can be debilitating. Given the enormous number of individuals affected by long COVID, it presents a sign...
Background: Long COVID is characterised by an array of physical and psychological symptoms that can be debilitating. Given the enormous number of individuals affected by long COVID, it presents a significant, and poorly understood emerging long-term medical and socioeconomic challenge. As such, there is a pressing need to develop and test new holistic and efficient approaches to whole-person treatment and rehabilitation at scale for patients with long COVID. Objective: To evaluate the effectiveness of a new human-centred, digital-first health platform - Avid - for the management of long COVID by examining its impact on participants quality of life scores and symptom severity in the short-term, and the platform’s usability and acceptability for end-users. Methods: 37 participants (35 female, mean age 46.5 years, 8.1% previously hospitalised with acute COVID) with long Covid were recruited into the Avid program. Avid is a human-centred, digital-first platform that delivers a 6-week program providing structured, personalised health coaching and tailored digital content aligned to specific weekly goals. The approach facilitates a standardised approach through evidenced-based treatment strategies, whilst simultaneously supporting personalised, adaptable care at scale. A quasi-experimental single arm pre-post intervention design was employed to evaluate the platform. The primary outcome measures were C19-YRSm and EQ5D-5L quality of life scores. Usability and acceptability of the program for participants was examined through Net Promoter Scores (NPS) and qualitative semi-structured interviews. Results: The Avid program led to significant and sustained improvements in C19-YRSm scores at week 6 (5.57 (SD 1.79) vs. 3.95 (SD 1.35), p=0.0001, mean improvement 41.0%); week 10 (5.07 (SD1.78) vs. 3.93 (1.18), p=0.0003, mean improvement 29.0%); and week 22 (5.08 (SD 1.68) vs. 3.88 (SD 1.13), p=0.0001, mean improvement 30.9%). The program also led to significant improvements in EQ5D-5L Index scores at week 6 (0.54 (SD 0.25) vs. 0.44 (SD 0.23) p=0.0005, mean improvement 25.0%); week 10 (0.51 (SD 0.25) vs. 0.44 (SD 0.24), p=0.0382, mean improvement 15.9%); and week 22 (0.54 (SD 0.23) vs. 0.46 (SD 0.23), p=0.0103, mean improvement 17.4%. The program was well received with 100% engagement and completion at 6 weeks. NPS scores showed 70% of participants were promoters of the program with a mean individual score of 8.64. Conclusions: The pilot study indicates that the Avid platform is safe, feasible and effective. It produces significant and sustained improvements in the symptoms and severity of long COVID, and wider measures of quality of life in the short-term. These findings suggest that the approach may provide a clinically impactful, cost-effective, and scalable platform that can successfully manage the challenges of long COVID. The modular approach of the platform also readily facilitates its rapid development and expansion to address other health challenges and long-term conditions in the future.
Background: Mental health issues are prevalent and challenging both on a personal and societal level. Art therapy has been a recognized method of treatment, offering patients an expressive and non-ver...
Background: Mental health issues are prevalent and challenging both on a personal and societal level. Art therapy has been a recognized method of treatment, offering patients an expressive and non-verbal way to process emotions. With advancements in digital technologies, integrating artificial intelligence (AI) into therapeutic practices has the potential to enhance accessibility and effectiveness. However, the application of generative AI within art therapy remains underexplored, necessitating further investigation into its technical and ethical challenges. Objective: This study aims to develop and showcase a novel technical design that integrates generative AI into art therapy, specifically focusing on the use of text-to-image models. The goal is to provide a supportive tool that enhances patient expression and creative customization, while preserving the role of the therapist in guiding the therapeutic process. Methods: We define a simplified art therapy session process and demonstrate how it can be augmented with generative AI. Our technical implementation leverages edge detection, sketch-to-image models, and inpainting techniques to enable patients to refine their artwork through text prompts. We qualitatively evaluate the system using three illustrative examples: a digital sketch, a painted image, and a photograph of a sculpture. Results: The system successfully generated, refined and adapted versions of the exemplary artworks for all three cases, demonstrating its ability to maintain the essence of the original input. Conclusions: The integration of generative AI into art therapy offers significant potential for enhancing accessibility and expressive possibilities for patients. While this proof-of-concept highlights technical feasibility, future research is required to assess therapeutic efficacy, user acceptance, and address ethical concerns, such as bias in AI-generated content. Our approach offers a foundation for further investigation into combining AI with traditional therapeutic practices, supporting the development of extended applications in clinical settings. Our implementations are publicly available at https://github.com/BFH-AMI/sds24.
Background: Compassion has been a topic of growing scientific interest, including in the field of Applied Behavior Analysis (ABA). To improve socially relevant behaviors, it is essential to explore ho...
Background: Compassion has been a topic of growing scientific interest, including in the field of Applied Behavior Analysis (ABA). To improve socially relevant behaviors, it is essential to explore how behavior analysts can provide maximum support to clients and promote significant changes through compassionate care. Although compassion skills have been studied by ABA researchers, the literature still presents gaps.
Research question: "What has been widely published in the scientific literature about the compassion skills of the Behavior Analyst?"
Source of evidence: The electronic databases to be searched include Embase, Index Psicologia, Lilacs, PubMed, Scopus, and Web of Science. The search strategy will use combinations of descriptors and their synonyms according to the Health Sciences Descriptors (DeCs) and Medical Subject Headings (MeSH), using the PCC mnemonic (population, concept, and context), combined with the Boolean operators AND and OR. Objective: The aim of this review is to map, identify, and provide data available in the existing literature on compassion skills and applied behavior analysis. Methods: The framework of Arksey and O'Malley guides the design of this scoping review, and the elements reported use the recommended guidelines of the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews). The study will follow established methodological framework standards to provide a systematic approach to mapping existing literature and identifying knowledge gaps. The protocol has been registered on the Open Science Framework (OSF) platform. Results: This scoping review is expected to provide:1. A comprehensive overview of the definitions and conceptualizations of compassion in the context of ABA.
2. A detailed mapping of specific compassionate skills reported in the ABA literature.
3. A synthesis of existing interventions or training programs for developing compassionate skills in behavior analysts.
4. An analysis of reported outcomes associated with compassionate practice in ABA.
5. An identification of barriers and facilitators for implementing compassionate practices in ABA.
6. Directions for future research and practice development in the area. Conclusions: Expected Implications
The results of this scoping review have the potential to inform the development of compassion training programs for behavior analysts, improve clinical practices, and influence care policies in ABA. It is expected that the synthesis of existing evidence may highlight the importance of compassionate skills in ABA practice and promote a more holistic and client-centered approach.
Strengths and Limitations
A significant strength of this study is its comprehensiveness, including a wide range of study types and not being limited to a specific geographical context. This will allow a global view of compassionate practices in ABA. However, a potential limitation is the possibility of missing relevant studies due to differences in terminology or inadequate indexing. To mitigate this, a comprehensive search with varied terms and consultation with experts in the field will be conducted.
Background: Virtual reality (VR) gaming is growing in popularity but little is known about physical activity (PA) during gameplay. Two popular VR games are Gorilla Tag (GT) and Beat Saber (BS). Little...
Background: Virtual reality (VR) gaming is growing in popularity but little is known about physical activity (PA) during gameplay. Two popular VR games are Gorilla Tag (GT) and Beat Saber (BS). Little is known about these games in youth. Objective: The purpose of this study was to investigate the enjoyment, intensity, and amount of PA while playing GT and BS in early adolescent youth. Methods: Sixteen participants played two VR games (GT and BS) randomly in a single session. Both games followed the same procedure: 10-minute familiarization period, 5 minutes of rest, 15 minutes of gameplay, and 10 minutes rest. Participants wore a heart rate (HR) monitor to track heart rate reserve (% HRR) and accelerometers to monitor time in sedentary, light physical activity (LPA), and moderate to vigorous physical activity (MVPA) of the arm and whole-body. The Physical Activity Enjoyment Scale-child version (PACES) and ratings of perceived exertion were completed after each game. Dependent t-tests compared measures between games. Results: The results revealed that average and maximum %HRR were significantly higher during GT than BS, with PA intensity reaching light for both games and moderate for GT. Arm MVPA and whole-body MVPA and LPA were greater during GT than BS. Arm and whole-body sedentary time were significantly lower during GT than BS. GT and BS were rated as highly enjoyable. Conclusions: These results suggest that BS produced light intensity PA and GT produced light to moderate-intensity PA in early adolescent youth, with both games rated as highly enjoyable.
Background: Atrial fibrillation (AF) is a chronic cardiovascular condition that requires long-term adherence to medications and self-monitoring. Clinical trials for AF have had limited diversity by se...
Background: Atrial fibrillation (AF) is a chronic cardiovascular condition that requires long-term adherence to medications and self-monitoring. Clinical trials for AF have had limited diversity by sex, race and ethnicity, and rural residence, thereby compromising integrity and generalizability of trial findings. Digital technology coupled with remote strategies has potential to increase recruitment of individuals from underrepresented demographic and geographic populations, resulting in increased trial diversity, and improvement in the generalizability of interventions for complex diseases such as AF. Objective: To summarize the successful architecture of a research program that used remote methods to enhance recruitment and engagement of diverse participants. Methods: We developed a programmatic architecture to conduct remote recruitment and assessments of individuals with AF in 2 complementary randomized clinical trials, funded by the National Institutes of Health, to test the effectiveness of a smartphone-based relational agent on adherence to oral anticoagulation. The study team engaged individuals with either rural or metropolitan residence receiving care for AF at health care settings who then underwent consent, baseline assessments, and randomization during a remotely conducted, telephone visit. Participants were randomized to the receive the relational agent intervention or control and subsequently received by mail a study smartphone with installed applications. Participants received a telephone-based training session on device and application usage accompanied by a booklet with pictures and instructions accessible for any level of health or digital literacy. The program included virtual methods to promote retention at 4-, 8-, and 12-month visits and incentivized return of the smartphone following study participation. The program demonstrated excellent participant engagement and retention throughout the duration of the clinical trials. Results: In total, 513 participants were enrolled, surpassing recruitment goals for the rural (n=270; target enrollment, 264) and metropolitan (n=243; target enrollment, 240) studies. Of those enrolled, 62% of participants were women; 30% of participants in the metropolitan study were non-white race, in contrast to 5% in the rural study. Among all participants, 45% had less than an associate’s degree and 44% were characterized as having limited health literacy. Intervention recipients receiving the relational agent used the agent median 95-98 (IQR, 56-109) across both studies and reported excellent satisfaction with it. Retention exceeded 85% at 12 months with study study phones used for median 3.3 (IQR, 1-5) participants. Conclusions: We report here the development and implementation of a programmatic architecture for the remote conduct of clinical trials. Our program successfully enhanced trial diversity and composition and applied while providing an innovative mobile health intervention to improve anticoagulation adherence in individuals with AF. Our methods provide a model for enhanced recruitment and engagement of diverse participants in cardiovascular trials. Clinical Trial: ClinicalTrials.gov ID NCT04076020
ClinicalTrials.gov ID NCT04075994
Background: The pervasive influence of social media on consumer behavior and marketing strategies necessitates a comprehensive understanding of its impact on the hospitality industry. As hotels increa...
Background: The pervasive influence of social media on consumer behavior and marketing strategies necessitates a comprehensive understanding of its impact on the hospitality industry. As hotels increasingly leverage digital platforms for engagement and reputation management, examining the effectiveness of various social media strategies and their implications becomes crucial for optimizing marketing efforts and enhancing brand identity. Objective: This study aims to investigate the impact of social media on hotel management, branding, engagement, and reputation in the hospitality sector. Methods: A mixed-methods approach was employed, involving quantitative surveys of hotel customers and qualitative interviews with hotel marketing managers. Data on demographic characteristics, social media usage patterns, primary purposes of social media usage, perceptions of hotel branding, and reputation management practices were collected and analyzed to identify trends and insights. Results: The data reveals that promotional offers and discounts (100%), user reviews (90%), and visual content (80%) are critical factors influencing consumer hotel choices. Collaboration with influencers, user-generated content, live video content, and social media advertising all demonstrated 100% effectiveness in engaging audiences and building brand identity. Pre-social media, 40% of hotels promptly addressed issues, while post-social media, this decreased to 20%, with private resolutions increasing from 20% to 30%. Conclusions: : Social media significantly influences consumer behavior in hotel selection and booking decisions. The shift in reputation management practices underscores the need for hotels to balance transparency with effective conflict resolution strategies. Social media strategies that leverage influencers, user-generated content, and dynamic visual content are crucial for enhancing engagement and brand identity. Hotels should prioritize influencer collaborations, encourage user-generated content, and invest in high-quality visual media. Implementing regular updates, engaging contests, and targeted promotional offers can drive bookings and enhance customer satisfaction. Proactive reputation management and transparent communication are essential for maintaining a positive public image. This study provides valuable insights into the transformative impact of social media on the hospitality industry, offering evidence-based strategies and policy recommendations for optimizing digital marketing efforts. The findings underscore the importance of a strategic and multifaceted approach to social media, highlighting its role in shaping consumer behavior, enhancing brand identity, and driving business growth.
Summary: This study highlights the rise of cardiology’s presence on social media, specifically on the platform X (formerly Twitter) and explores the impact of social media on gender representation a...
Summary: This study highlights the rise of cardiology’s presence on social media, specifically on the platform X (formerly Twitter) and explores the impact of social media on gender representation and existing gender gaps.
Background: Chronic hepatitis B (CHB) remains a significant health burden for at least a hundred thousand Canadians. The government of Canada has endorsed the Global Strategy to eliminate hepatitis as...
Background: Chronic hepatitis B (CHB) remains a significant health burden for at least a hundred thousand Canadians. The government of Canada has endorsed the Global Strategy to eliminate hepatitis as a public health threat by 2030, but effectively targeting public health interventions is complicated by the silent nature of the disease, which can remain asymptomatic for decades. Objective: This study develops a framework to estimate the prevalence of chronic hepatitis B and the proportion of the infected population that remains undiagnosed. We apply the proposed method to national data from Canada, from 2007 to 2021. Methods: We infer the prevalence and undiagnosed proportion of CHB by fitting a mathematical state-transition model, based on the natural history of chronic hepatitis B, to observed CHB-related events. Results: We estimate the national prevalence of CHB in Canada in 2021 to be 0.308% (95% CI: 0.252% - 0.363%). The corresponding percentage of undiagnosed cases was estimated to be 33.9% (95% CI: 22.7% - 45.1%). Conclusions: The estimates of CHB prevalence obtained via our method are in line with previous estimates obtained from national seroprevalence studies. More specialized estimates, stratified by province or age cohort, may be achievable with detailed health administrative data.
Background: Granular control over medical record sharing empowers patients to manage access to sensitive information, like substance use disorders (SUD), often withheld due to stigma. Although federal...
Background: Granular control over medical record sharing empowers patients to manage access to sensitive information, like substance use disorders (SUD), often withheld due to stigma. Although federal and state laws protect this data, manual segmentation processes remain error-prone, complicating care coordination. Integrating contextual EHR data into segmentation technologies could enhance accuracy, better aligning sensitivity classifications with providers’ assessments. Objective: This is the first study to examine the influence of context, specifically pertinent health data availability, on how physicians categorize potentially sensitive health data items. The goal is to increase the accuracy of automated sensitive data segmentation technologies. Methods: 1,000 data items from deidentified EHRs from patients receiving behavioral health care were distributed across 12 surveys. These data items were randomly assigned to 12 pairs of physicians to categorize into a sensitive data taxonomy. During a follow-up interview, participants categorized 120 survey data items and could use the medical record to support their answers. Survey and interview results were compared. Results: Educational materials provided during surveys and interviews for the sensitive data taxonomy were helpful (75.0% and 70.8%, respectively), but the provided data sensitive taxonomy may require further revisions and validations. 62.5% of the participants used the provided patient EHR data to justify their categorizations during the interview. Some participants felt they needed access to more patient data (50%) or speak with the patient (8.3%) to best categorize a data item. When considering the 240 survey and interview responses, accessing additional patient health data led to multiple (72.1%) changes in categorizations. When comparing the survey and interview categorizations of data items, disagreements decreased by 20.1%, partial agreements increased by 26.4%, but agreements decreased by 6.4%. Conclusions: Incorporating context using additional data from a patient’s EHR impacted how physicians categorize potentially sensitive health data. As future work, this study's results will open new research discussions in physician-validated data segmentation methods.
Background: Patient-reported outcome measures (PROMs) are standardized tools for assessing symptoms and the quality of care. Despite their growing use, conventional data collection methods limit wides...
Background: Patient-reported outcome measures (PROMs) are standardized tools for assessing symptoms and the quality of care. Despite their growing use, conventional data collection methods limit widespread PROM implementation. In orthopaedics, pain is a frequent patient complaint and a common PROM, especially following total knee arthroplasty (TKA). Although TKA is generally successful, some patients still report post-operative pain, potentially due to tourniquet use. Using an improved PROM data-gathering technique may help to address tourniquet use during a TKA procedure and its impact on post-operative pain. The PainPad, an automated self-logging device, was developed to capture patient pain levels accurately. Objective: To assess the feasibility and effectiveness of the PainPad device in quantifying in-hospital post-operative pain following TKA with or without tourniquet use. Methods: A retrospective study with 234 patients who underwent TKA from 2018 to 2021 at Milton Keynes University Hospital was conducted. Patients were categorized as receiving TKA with an intra-operative tourniquet (tourniquet group) or TKA without a tourniquet (non-tourniquet group). Twenty-four-hour post-operative pain was collected bi-hourly and was self-reported using the PainPad device. From both groups, data on hospital length of stay (LOS), total tourniquet time, and the presence of post-operative deep vein thrombosis were also collected. Results: There were 115 TKAs with tourniquets (63% females, mean age 69.2 years) and 119 TKAs without tourniquets (76% females, mean age: 71 years). When assessing 24-hour mean post-operative pain scores, the PainPad device data indicated no significant difference (P = .53, 95% CI: -0.76 to 0.39) between the tourniquet (mean pain score: 3.31 ± 2.34) and non-tourniquet groups (mean pain score: 3.12 ± 2.15). There was no correlation between tourniquet times and the pain scores retrieved from the PainPad device. A subgroup analysis comparing longer (>90 minutes) vs. shorter (<90 min) tourniquet times showed no significant difference in terms of pain and LOS. Conclusions: The PainPad device is a feasible and effective method for collecting and evaluating in-hospital postoperative pain following total knee arthroplasty (TKA), allowing for the quantification of individual pain levels. This study aligns with the current healthcare trend towards leveraging innovative technologies and personalized data to enhance patient-centered care. Clinical Trial: N/A
Background: Childhood trauma is pervasive, with approximately 50% of adolescents experiencing at least one potentially traumatic event (PTE) before adulthood. Of PTE-exposed adolescents, 8-33% develop...
Background: Childhood trauma is pervasive, with approximately 50% of adolescents experiencing at least one potentially traumatic event (PTE) before adulthood. Of PTE-exposed adolescents, 8-33% develop posttraumatic stress disorder (PTSD). PTSD can cause extreme suffering and coincides with a high number of comorbid illnesses and high-risk behaviors. PTSD can be effectively treated in adolescents through weekly sessions of eye movement desensitization and reprocessing (EMDR) or trauma-focused cognitive behavioral therapy (TF-CBT). Despite the availability of these treatments, a substantial amount of severely traumatized adolescents do not receive the available treatment options due to high treatment avoidance. In adolescents who do receive care, a large group youth does not experience sufficient symptom decrease after regular treatment. In addition, dropout rates during prolonged treatment are substantial, varying between 10% and 30%. This underscores the need for innovative and brief trauma treatment. Pilot studies show that Brief Intensive Trauma Treatment (BITT) can be a safe and effective treatment for adolescents with PTSD. However, randomized controlled trials (RCTs) on its effectiveness are crucial and urgently needed. Objective: This is the first study to test the effectiveness of a one-week BITT in adolescents with PTSD and comorbid symptoms and their caregiver(s). Methods: This multicenter, single-blinded RCT, will be conducted in five youth care centers in the European and Caribbean Netherlands: Levvel, Karakter, Leef! Jeugdzorg, Fornhese-GGz Centraal, and Mental Health Caribbean (Bonaire). We will randomly allocate adolescents (12-18 years old) with PTSD to a BITT (n=50) or waitlist control group (WLCG; n=50). BITT consists of a one-week (i.e., five consecutive workdays) intensive trauma treatment, encompassing daily 90-minute manualized sessions of TF-CBT and EMDR. The day begins and ends with psychomotor therapy. The caregiver(s) receive daily parental counseling sessions consisting of psycho-education and social support skill training. We will conduct measurements at similar time intervals for both groups: at baseline, directly after BITT or WLCG, and at 3, 6, and 9 months follow-up. The WLCG will receive BITT after the 3-months follow-up assessment. We will assess all study parameters using digital/face-to-face questionnaires and (semi) structured interviews conducted by a research psychologist blinded to randomization. We will assess the primary outcome PTSD symptoms using the Child and Adolescent Trauma Screen (CATS-2) and the Clinician-Administered PTSD Scale for Children and Adolescents DSM-5 (CAPS-CA-5). Results: . Conclusions: This first, innovative study on the effectiveness of BITT may enhance treatment outcomes for PTSD by preventing dropout, reducing avoidance, shortening therapy duration, and empowering therapists by working together intensively. This research will provide valuable insights across cultures for effective treatment of severely traumatized adolescents who do not benefit sufficiently from regular treatment. Clinical Trial: NCT06143982
Background: Gold mining activities in Osun State, Nigeria, have led to significant environmental changes that may pose health risks to both miners and non-miners in the surrounding communities. Given...
Background: Gold mining activities in Osun State, Nigeria, have led to significant environmental changes that may pose health risks to both miners and non-miners in the surrounding communities. Given the growing concern about the health implications of exposure to environmental hazards associated with mining, it is crucial to assess these impacts to develop targeted health and environmental interventions. Objective: This study aims to evaluate the relationships between exposure to environmental hazards resulting from gold mining activities and the prevalence of associated health problems among miners and non-miners in Osun State, Nigeria. The study uses quantitative data analysis to identify key risk factors influencing health outcomes and inform appropriate public health strategies and policy actions. Methods: A cross-sectional study design was employed, involving the collection of quantitative data from both miners and non-miners in Osun State. A structured questionnaire was used to assess exposure to environmental hazards, including polluted water sources, noise, ground vibrations, and dust inhalation. Health outcomes such as joint pain, malaria, and general weakness were also recorded. The data were analyzed using statistical techniques, including correlation and regression analysis, to identify significant relationships between exposure and health outcomes. Demographic variables such as age and duration of residence were included to evaluate their influence on vulnerability to environmental risks. Results: The findings reveal that environmental hazards such as drinking from polluted water bodies (R = 0.172, p = 0.003), exposure to noise and ground vibrations (R = 0.220, p = 0.000), and inhalation of dust (R = 0.288, p = 0.000) are significantly correlated with various health issues, including joint pain (77.3%), malaria (73.0%), and general weakness (69.0%). The presence of particles in surrounding water bodies (R = 0.354, p = 0.000) was the strongest predictor of health problems. Key demographic factors, such as age and duration of residence, further influence vulnerability to these environmental risks. Conclusions: The study concludes that multiple environmental hazards associated with gold mining activities significantly impact the health of both miners and non-miners in Osun State, Nigeria. Although some correlations are moderate to weak, their significance underscores the cumulative risk posed by different environmental exposures. Urgent interventions are needed to address water quality, reduce particulate matter, and enhance safety regulations in mining operations to protect public health. The study recommends implementing stringent regulations for mining operations, including monitoring and controlling water and air quality. Community awareness programs should be launched to educate residents about the risks associated with exposure to mining-related hazards. Additionally, providing alternative safe water sources, establishing better ventilation practices in mines, and enforcing occupational safety standards can help mitigate the identified health risks. This study highlights the critical health risks posed by environmental hazards associated with gold mining activities in Osun State, Nigeria. By identifying key risk factors such as water and air pollution, noise, and unsafe mining practices, the study provides essential insights for developing targeted interventions to protect public health. The findings emphasize the need for a coordinated approach involving policy enforcement, community education, and sustainable mining practices to mitigate the adverse health effects on both miners and non-miners in the affected communities.
Background: As a crucial component of the modern healthcare system, pre-hospital medical services have become increasingly significant with the advancements in medical technology and evolving medical...
Background: As a crucial component of the modern healthcare system, pre-hospital medical services have become increasingly significant with the advancements in medical technology and evolving medical concepts. However, pre-hospital medical services face numerous challenges and difficulties. To enhance the quality of pre-hospital medical services, it is essential to identify the current deficiencies from the perspective of the demand side, analyze and monitor their concerns, and provide data support for future improvements. Objective: This study aims to conduct text mining on the content of complaint work orders related to pre-hospital medical services recorded in the 12320 Health Hotline, with the goal of gaining an in-depth understanding of the key concerns and issues expressed by the public regarding these services. Methods: We obtained complaint work orders related to pre-hospital medical service from the 12320 health hotline, spanning from June 1, 2016 to December 31, 2019. Using the Latent Dirichlet Allocation (LDA) topic model, we identified the themes mentioned in these complaint work orders and analyzed their prevalence. The themes identified by the LDA model were further refined and categorized through manual verification. Detailed analyses and discussions were conducted for each complaint theme. Results: Among the 2287 complaint hotline orders related to pre-hospital medical services, the LDA model identified 12 distinct themes, each with specific subject terms and prevalence values. Through manual verification and summarization, we consolidated these into 6 main complaint themes: (1) ambulance response and dispatch, (2) service quality and attitude, (3) Poor coordination between pre-hospital and in-hospital medical services, (4) pre-hospital medical services cost issues, (5) medical documentation issues, and (6) hotline management. Conclusions: Utilizing an intelligent LDA topic model combined with manual thematic summarization, this study successfully identified the primary concerns of public complaints regarding pre-hospital medical service in Shanghai from the 12320 Health Service Hotline. These findings highlight key challenges within the service process and provide data support for future improvements. By analyzing and monitoring hotline data, we gained a deeper understanding of public expectations and the difficulties they encounter with pre-hospital medical services.
Background: Background: Goals for ending the HIV epidemic prioritize implementation of trauma-informed care (TIC), an operating paradigm for fostering multi-level resilience and empowerment. However,...
Background: Background: Goals for ending the HIV epidemic prioritize implementation of trauma-informed care (TIC), an operating paradigm for fostering multi-level resilience and empowerment. However, a dearth of literature explores strategies for collaboratively conducting TIC implementation. Research co-production could be an effective strategy for facilitating collaborative TIC adoption, but formative research is needed to explore this potential. Objective: Objective: We present findings from a longitudinal study to co-produce TIC implementation at an adolescent-focused HIV clinic in a nationally prioritized jurisdiction in the Southern United States. Results will contribute to a deeper understanding of local context and be used to tailor TIC implementation for the specific needs of the clinic. Methods: Methods: This study builds on our multi-phase, pre-implementation stage research and applies mixed methods to explore potential barriers and facilitators to collaborative TIC implementation in the HIV care clinic. We employed purposive sampling to conduct semi-structured interviews and surveys with clinic personnel. Thematic analysis was conducted using two implementation science frameworks in order to support locally-responsive and effective TIC implementation. The Consolidated Framework for Implementation Research (CFIR) 2.0 was used to explore general features of the implementation environment, and the Research Quality Plus for Co-Production (RQ+ 4 Co-Pro) framework was used to explore the context for co-producing the implementation strategy at and for the clinic. Results: Results: Twenty personnel completed interviews and nine completed surveys. Facilitators included clinic cohesiveness, equity focus, and prioritization/compatibility of TIC. Barriers included perceived disconnect between the clinic and larger hospital, perceived stigma, sustainability, leadership championship, insufficient mental health protocols, a lack of formal patient feedback procedures, and protected time for personnel activity engagement. Survey responses suggest the clinic environment is supportive of collaborative research and empowers participation among personnel. Evidence is seen as prioritized in the environment, with an openness for new approaches and a focus on health disparities. However, there was an identified need to develop a clear path and capacities for systematic collaborative TIC research (e.g., designated time for personnel to devote to research). Conclusions: Conclusions: Collaborative TIC implementation was seen as a strategy likely to be supported by the clinic, but several areas of need were highlighted. Future research will be conducted to adapt a multi-level TIC intervention by addressing and leveraging the identified implementation determinants and test the application of co-production as an implementation strategy.
Background: Hypertension is a Non-Communicable Disease (NCD) where this disease cannot be transmitted through any form. The development of this disease takes a relatively long time. In this case, non-...
Background: Hypertension is a Non-Communicable Disease (NCD) where this disease cannot be transmitted through any form. The development of this disease takes a relatively long time. In this case, non-communicable diseases are one of the leading causes of death in the world. Hypertension is often referred to as a silent killer. Hypertension is also a major risk factor for sudden death due to heart disease, left ventricular hypertrophy, chronic kidney disease, diabetes mellitus, metabolic syndrome, vascular dementia, Alzheimer's disease, and eye disease. Efforts to prevent hypertension sufferers can be done by carrying out primordial prevention, namely, avoiding hypertension by doing physical activity and not smoking. Primary prevention by following counseling related to hypertension, secondary prevention in the form of routine treatment for hypertension sufferers who have been diagnosed with hypertension, and carrying out tertiary prevention by carrying out behaviors to prevent complications in hypertension sufferers Objective: This study aims to determine how the behavior of preventing hypertension in the elderly in the working area of the Cendana Putih Health Center, Mappedeceng District, North Luwu Regency Methods: This study uses a descriptive qualitative method with a content analysis approach. Data collection through observation, in-depth interviews, and documentation. Field observations or observations are carried out first with the aim of observing the habits carried out by informants. In-depth interviews are carried out with the aim of digging deeper information carried out by researchers to informants. And the last stage is to document the results of observations and interviews that have been conducted. Other supporting data is carried out by obtaining primary data and secondary data. Results: Overall, this study found that the behavior of preventing hypertension in the elderly is diverse, such as some informants doing physical activities such as gymnastics, other activities such as gardening, walking, routinely taking hypertension medication, having regular health checks, and also consuming herbal plants obtained around the informant's home environment. The role of the family in supporting or motivating the elderly to prevent hypertension is also needed, such as helping to remind the elderly to take medication or simply taking the elderly to have a check-up at the nearest health facility. Conclusions: Hypertension prevention behavior in the elderly can be done independently by the elderly by doing light activities such as walking and exercise at home, routinely taking hypertension medication, avoiding foods that can trigger high blood pressure, and carrying out traditional medicine by utilizing plants around the house that are already trusted to be one of the herbal plants for treating hypertension. Clinical Trial: Hypertension, Prevention, Physical Activity, Gymnastics, Examination, Hypertension Medication, Herbal Plants
Background: Cardiovascular diseases are one of the leading causes of mortality globally. Cardiac rehabilitation (CR) programs are crucial for patients recovering from cardiac events, as they help redu...
Background: Cardiovascular diseases are one of the leading causes of mortality globally. Cardiac rehabilitation (CR) programs are crucial for patients recovering from cardiac events, as they help reduce the risk of recurrent events and support patient recovery. The patient’s journey in CR spans the stages before, during, and after the program. Patients have to progress through each stage of CR programs successfully to complete the entire CR journey and get the full benefits of CR programs, but numerous barriers within this journey can hinder patient progression. Objective: To explore the barriers to progression at all stages of the CR patient journey from the perspectives of healthcare providers involved in CR care. Methods: This qualitative study involved semi-structured interviews with healthcare providers involved in CR care from July 2023 and January 2024. A purposive maximal variation sampling method was used to target providers with diverse demographics and specialties. Snowball sampling was used to recruit participants, leveraging the existing networks of participants. Each interview lasted between 30 and 45 minutes. Interviews were recorded, transcribed verbatim, and analyzed using an inductive thematic analysis approach. Data analysis was conducted from August 2023 to February 2024. Results: Ten healthcare providers, comprising seven females and three males, were interviewed. Their roles included physician, program director, nurse manager, clinical manager, nurse coordinator, nurse, physiotherapist, and kinesiologist. The analysis identified four overarching themes related to barriers to progression in the CR journey: (1) patients not being referred to CR programs, (2) patients not enrolling in CR programs, (3) patients dropping out of CR programs, and (4) patients’ lack of adherence to lifestyle changes post-CR programs. Conclusions: In light of the growing interest in technological interventions in CR programs, we proposed four potential technological solutions to address the barriers to progression identified in our analysis. These solutions aim to provide a foundation for future research and guide the development of effective technologies to enhance patient progression within the CR journey.
Background: Numerous reviews have explored specific aspects of violence prevention apps, but given the rapid development of new apps, increased violence during COVID-19, and gaps in understanding func...
Background: Numerous reviews have explored specific aspects of violence prevention apps, but given the rapid development of new apps, increased violence during COVID-19, and gaps in understanding functionalities and geographical distribution, an updated review is needed. Objective: Therefore, we aimed to systematically evaluate the trends, geographical distribution, functional categories, available features, and feature evolution of mobile apps designed to prevent violence against women and girls (VAWG). Methods: We conducted a systematic search on app reselling platforms and search engines from April 24, 2024, to May 28, 2024, using terms related to violence against women and girls in multiple languages. We included apps meeting our criteria for addressing VAWG, without restrictions on date or language. We conducted content analysis of app and apps were categorized by functionality and feature type. We performed descriptive analyses, trend analysis, and co-occurrence network analysis, and geographical mapping. Results: Out of 432 apps initially identified, 178 were included in the final analysis. Of these, 99 apps were available on both Google Play and the App Store, 64 were exclusive to Google Play. Most apps were implemented in the North America (27%), followed by South Asia (17%) and the Europe and Central Asia (17%). Emergency and support applications were most prevalent across regions. Most apps (74%) originated from the private sector and designed for victims (68%), were free without in-app purchases (56%), had a website (83%), and offered GPS features (80%), but only 15% provided offline functionality. App releases peaked in 2020 (19%), followed by a decline. Regression analysis indicated a significant trend (p=0.01) increase in app release, with a 2.40 unit increase per year before 2020 and a 7.01 unit decrease after, showing a post-2020 decline of 4.61 units per year. Apps were primarily categorized as emergency (n=110) or support (n=81), with most emergency apps in the 10,000 to ≥100,000 downloads range. Network analysis showed that emergency services (degree=10, clustering coefficient=0.911), location sharing (degree=10, clustering coefficient=0.911), SOS alerts (degree=10, clustering coefficient=0.911), and educational resources (degree=10, clustering coefficient=0.911) features highly co-occurred in the same app. We found a gradual shift towards more sophisticated and comprehensive safety tools, evolving from basic GPS tracking and SOS alerts to advanced features like real-time communication, panic buttons, peer support, and group communication, culminating in multi-functional platforms offering personalized safety, community engagement, and proactive risk identification Conclusions: Most apps to prevent VAWG emphasize emergency and support functions, and although initial releases increased, there has been a recent decline, with a shift towards integrating more comprehensive safety solutions like communication, reporting, and community engagement. Future app development should prioritize cross-platform availability, offline functionality, public sector collaboration, and the integration of advanced technologies like artificial intelligence. Clinical Trial: PROSPERO ID: CRD42024500431
Background: Population aging underlines the critical need for improving health professional training to adequately care for older adults (over 60 years old). Objective: Develop and validate a serious...
Background: Population aging underlines the critical need for improving health professional training to adequately care for older adults (over 60 years old). Objective: Develop and validate a serious game on older adult health for undergraduate nursing students. Methods: This quantitative and descriptive methodological study, conducted between February and December 2023 at a public university in the Federal District, involved the active participation of 27 8th-year undergraduate nursing students. The game, 'Unidade de Saúde em Foco' ('Health Unit in Focus'), was developed and validated with their input. It features 75 clinical cases distributed across three themes: pharmacology, metabolic syndrome, and semiology. The application was validated using the SUS, and the students' feedback. Results: Of the 40 students initially enrolled, 27 completed the study. The game received an average SUS score of 85.75 (median: 86.57), classified as excellent—all evaluated items scored above 75. Participants considered the game easy to use, accessible, practical, and rich in well-founded, useful content. This high usability score, coupled with the overwhelmingly positive feedback from the students who found the game easy to use, accessible, practical, and rich in well-founded, useful content, instills confidence in the game's effectiveness. Furthermore, 100% of students agreed that learning through games is effective and expressed interest in incorporating more interactive games into their training. Conclusions: The Serious Game' Unidade de Saúde em Foco' ('Health Unit in Focus') is not just a valid and reliable tool for training nursing students, but also an engaging and interactive approach to learning. Its ability to captivate and involve students in the learning process is a testament to its potential to revolutionize nursing education.
Background: A comprehensive evaluation of short-term effects of antihypertensive medicines is important for informing guidelines and clinical practice. Objective: We aimed to develop a database of Dou...
Background: A comprehensive evaluation of short-term effects of antihypertensive medicines is important for informing guidelines and clinical practice. Objective: We aimed to develop a database of Double-blind Randomised trials of Effects of Antihypertensive Medicines (DREAM) to facilitate a series of meta-analyses evaluating the short-term effects of antihypertensive medicines. Methods: We searched the Cochrane Central Register of Controlled Trials, MEDLINE, and Epistemonikos from inception until December 2022 to identify relevant randomized clinical trials (RCTs). We included RCTs in the DREAM database if they were double-blind, enrolled adult participants, evaluated the five major classes of antihypertensive medicines over a duration of 2 to 26 weeks, and were published in the English language. Screening of records for inclusion and data collection were both conducted in duplicate. Results: A total of 1,659 RCTs (3,997 eligible groups) were included: 44% were placebo-controlled, 71% had parallel-group allocation, and 37% had three or more randomized groups. A total of 277,749 participants were included: the mean age was about 54 years, about 40% were female, 86% RCTs had participants with hypertension, and 11% RCTs had participants with cardiovascular disease at baseline. RCTs with at least one group randomized to monotherapy accounted for 78%, at least one group randomized to combination therapy accounted for 23%, and at least one group randomized to calcium channel blockers (as the most evaluated class) were 35%. The median duration of treatment was 8 weeks. Most, 91%, RCTs reported data on effects on blood pressure. Meta-analyses planned in the first round of outputs include effects of antihypertensive medicines on blood pressure, safety, headache, cardiovascular events, and blood pressure variability. Conclusions: The planned meta-analyses from the DREAM database will produce important evidence to inform clinical practice guidelines and practice. Clinical Trial: Not applicable
Background: Accessibility barriers contribute to low participation in center-based cardiac rehabilitation. We developed an innovative, comprehensive, dual-phase telerehabilitation program to address t...
Background: Accessibility barriers contribute to low participation in center-based cardiac rehabilitation. We developed an innovative, comprehensive, dual-phase telerehabilitation program to address this gap (Smartphone Cardiac Rehabilitation Assisted Self-Management; SCRAM). Objective: To determine the effectiveness of SCRAM for increasing maximal aerobic exercise capacity (VO2max). Methods: A multi-center, parallel two-arm randomized controlled trial recruited clinically stable adults (aged 18+ years) with diagnosed coronary heart disease at three hospitals in Victoria, Australia (Melbourne, Geelong, Bendigo) from 2018-2021. Participants were randomized (1:1), stratified by sex and study site, to receive SCRAM plus usual cardiovascular care (intervention), or usual cardiovascular care alone (control). SCRAM intervention provided 24 weeks of remote exercise supervision, coaching, and behavior change support via smartphone. Usual cardiovascular care included standard medical care and advice to seek a referral to centre-based cardiac rehabilitation (CR), which was heavily impacted during the COVID-19 pandemic. Due to the nature of the treatments, participants were not blinded to allocation; primary outcome assessors and biostatisticians were blinded. The primary outcome was VO2max at 24 weeks, analyzed on the principle of intention-to-treat, using linear regression adjusted for baseline and stratification factors on multiple imputed data. Results: Recruitment and data collection were heavily impacted by COVID-19, although SCRAM delivery was sustained throughout. Of 220 required participants, only 123 (56%) were recruited and randomized (intervention n=63, control n=60); 45% had missing VO2max at 24 weeks—largely due to enforced COVID-19 restrictions. VO2max at 24 weeks favored SCRAM, but this was not statistically significant (mean difference=1.61 ml/kg/min; 95% CI [-1.38, 4.61], P=.28). Among secondary outcomes, patients receiving SCRAM had lower diastolic blood pressure at 24 weeks (mean difference=-5.54 mmHg; 95% CI [-10.01, -1.06]). Conclusions: SCRAM was resilient to COVID-19-related disruptions to CR delivery but, while findings were inconclusive, it did not lead to a clinically important difference in VO2max. Further research is needed to conclusively assess treatment effects and understand how virtual CR delivery models can be translated into routine practice. Clinical Trial: Australian New Zealand Clinical Trials Registry (ACTRN): 12618001458224
With artificial intelligence (AI) playing an increasingly prominent role in healthcare, patients are arguably the most impacted. For patients to be empowered in the many ways in which AI impacts their...
With artificial intelligence (AI) playing an increasingly prominent role in healthcare, patients are arguably the most impacted. For patients to be empowered in the many ways in which AI impacts their care, rather than remaining passive recipients, they need awareness, understanding, and trust in AI. We evaluate the current state of AI in healthcare from the all-important patient perspective, and consider future directions supporting a more equitable future with enhanced care for the wide variety of patient needs.
Background: Challenges in emergency medicine include overcrowding, insufficient emergency care resources and extended Emergency Department (ED) waiting times. These issues contribute to delays in trea...
Background: Challenges in emergency medicine include overcrowding, insufficient emergency care resources and extended Emergency Department (ED) waiting times. These issues contribute to delays in treatment and unfavorable outcomes. Particularly worsened during the Covid-19 pandemic and events with large crowds. The integration of augmented reality (AR) smart glasses could potentially enhance patient care in the ED. Objective: To compare the duration of patient care in ED between the use and non-use of Augmented reality (AR) smart glasses during The 19th Asian Games and 4th Asian Para Games Hangzhou 2022 (HAG2022). Methods: This retrospective study was conducted between September 13, 2023, and October 28, 2023, during HAG2022. The data was gathered from AR smart glasses at the HAG2022 village and electronic health records at Sir Run Run Shaw Hospital, China. The study included two groups: teleconsultation by AR telemedicine system (ARTS) group and no teleconsultation by AR telemedicine system (non-ARTS) group. The main data assessed were pre-preparation time (PPT) and consult response time (CRT) in ED. Results: During the research period, 80 patients were divided into two cohorts: the ARTS cohort (n=10) and the non-ARTS cohort (n=70). Gender and age demographics showed no significant differences between the cohorts. The ARTS cohort had a significantly lower average PPT of 23.0 minutes compared to the non-ARTS cohort's 40.3 minutes (P<.001). Additionally, CRT in the ARTS cohort was significantly lower at 15.6 minutes compared to the non-ARTS cohort's 164.8 minutes (P=.03). The outcomes suggest that smart glasses are effective in decreasing PPT and CRT. Conclusions: Augmented reality smart glasses in the EDs can improve patient admissions efficiency and care time in ED. More research is needed to confirm their effectiveness in emergency medicine. Clinical Trial: approval no.srrsheca2023-0597
Background: Tetraplegia imposes significant challenges on individuals, caregivers, and healthcare systems. Assistive technologies (AT) like assistive robot arms have shown to improve the quality of li...
Background: Tetraplegia imposes significant challenges on individuals, caregivers, and healthcare systems. Assistive technologies (AT) like assistive robot arms have shown to improve the quality of life of persons with tetraplegia, fostering independence in daily activities and reducing caregiver burden. Despite potential benefits, the integration of AT innovations into daily life remains difficult. Implementation science offers a systematic approach to bridge this know-do gap. Objective: The objective of this review was to (1) identify and involve relevant stakeholders, (2) identify relevant contextual factors (barriers and facilitators), and (3) suggest a general outlook for the implementation of AT, specifically an assistive robot arm, within the everyday private life for persons with tetraplegia in Switzerland. Methods: A qualitative design, involving three semi-structured online focus group interviews with eight stakeholder groups (affected person, engineering/technology, legal perspective, nursing/care, therapy, social counselling, social insurers, political perspective), was used. The interviews were analysed using the Focus Group Illustration Mapping (by Pelz et al. (2004)), and data aligned with the domains of the Consolidated Framework for Implementation Research (CFIR). Results: Three focus group interviews, comprising 22 participants, were conducted and data was mapped onto 21 constructs of CFIR domains. Identified barriers were the customisation to the users’ needs, safety concerns and financing issues of high AT costs. The collaboration with different stakeholders including political engagement proved crucial. Identified facilitators included the enhancement of autonomy for persons with tetraplegia, improvement of quality of life, reduction of caregiver dependency, and addressing healthcare labour shortages. The implementation outlook involved the formation of an experienced team, and the development of an implementation plan using Hybrid Type 1 and Type 2 designs incorporating qualitative and quantitative implementation and innovation outcomes. Conclusions: The robot arm offers promising benefits in terms of improved participation for the users, while high costs and regulatory complexities for the assumption of costs limit its implementation. These findings highlight the complexities involved in implementing AT innovations and the importance of addressing contextual factors. A specific framework for the implementation of AT is needed to ensure the successful integration into the Swiss and comparable social and health insurance systems.
Background: The COVID-19 pandemic has had a profound impact on healthcare professionals, particularly nurses, who have faced increased stress, burnout, and health challenges. Post-pandemic, it has bec...
Background: The COVID-19 pandemic has had a profound impact on healthcare professionals, particularly nurses, who have faced increased stress, burnout, and health challenges. Post-pandemic, it has become critical to provide these frontline workers with tools that support their well-being and self-health management. Gamification, the application of game-design elements in non-game contexts, has emerged as a promising approach to engage users in health-related behaviors. This study explores the effectiveness of a gamified mobile application designed to empower post-COVID nurses in managing their self-health. Objective: This study aims to evaluate the effectiveness of a gamified mobile application in promoting self-health management among nurses who have experienced the COVID-19 pandemic. The primary objective is to assess whether the use of gamification within the app can enhance engagement, improve health outcomes, and support sustained behavior change in managing personal health among this specific group of healthcare professionals. Methods: This study utilized a user-centered design approach to develop and evaluate a gamified mobile application aimed at enhancing self-health management among post-COVID nurses. The app was developed using the Octalysis framework and goal-setting theory, incorporating personalized exercise prescriptions and health tracking features. The target users were nurses from a specific hospital in Hsinchu, Taiwan, who participated voluntarily. Data were collected through in-depth interviews, surveys, and app usage analytics to assess the effectiveness and usability of the application. The analysis focused on understanding the impact of the app on nurses' health behaviors and engagement. Results: The study included a total of 234 participants, all of whom completed the intervention, resulting in a response rate of 100%. Participants' physical activity levels showed significant improvement after the intervention. The average daily step count increased from baseline levels, indicating enhanced engagement with the gamified mobile application. Additionally, the Body Mass Index (BMI) measurements of participants revealed a shift towards healthier weight categories, with a notable decrease in the number of participants classified as overweight or obese. These findings suggest that the gamified approach was effective in promoting physical activity and encouraging weight management among post-COVID nurses. Conclusions: This study demonstrates the potential of a gamified mobile application to enhance self-health management among post-COVID nurses. By integrating key gamification principles, the app successfully engaged users and promoted increased physical activity, as evidenced by the significant improvements in step count and BMI. These findings suggest that gamification can be a powerful tool in addressing the unique health challenges faced by healthcare professionals, particularly in the demanding post-pandemic environment.
However, the study also highlights the need for further exploration into the most effective gamification elements and the potential for personalized interventions. The limitations of the study, including the specificity of the sample and the voluntary nature of participation, suggest that while the results are promising, they may not be universally applicable.
Overall, the findings contribute valuable insights into the design of digital health interventions and underscore the importance of continuing to develop innovative approaches to support the health and well-being of healthcare workers in the post-COVID era. Clinical Trial: This study was not a Randomized Controlled Trial (RCT) and therefore did not require registration in a WHO-accredited trial registry. The research focused on the development and evaluation of a gamified mobile application for post-COVID nurses, using a pre-post study design to assess its impact on self-health management. As the study did not involve the random allocation of participants to different interventions or control groups, it falls outside the scope of studies requiring formal trial registration.
Background: Patients' conditions continue to change after diagnosis, with each patient exhibiting a unique time course of progression. This variability complicates the prediction of clinical outcomes,...
Background: Patients' conditions continue to change after diagnosis, with each patient exhibiting a unique time course of progression. This variability complicates the prediction of clinical outcomes, particularly for diseases with acute exacerbations like coronavirus disease (COVID-19). Objective: This study aimed to perform risk classification at initial diagnosis to predict the maximum severity of COVID-19 patients, and implement dynamic risk monitoring during hospitalization to continuously assess mortality risk using longitudinal data. Methods: This retrospective cohort study included 382 COVID-19 patients treated at Tokyo Shinagawa Hospital between January and September 2020. Patients under 18 years old or with unknown clinical outcomes were excluded. The dataset was divided into training and validation sets (2:1 ratio) using stratified sampling. Risk classification at initial diagnosis utilized 84 variables, including symptoms, background factors, and blood/urine biomarkers. Gradient Boosting Decision Trees (GBDT) were employed to predict the highest severity level at diagnosis, and risk factors were interpreted in SHAP (SHapley Additive exPlanations). For dynamic risk assessment during hospitalization, longitudinal data from 182 inpatients were used, including 72 variables such as blood/urine biomarkers, vital signs, and background data. Random Survival Forests were applied to predict daily mortality risk, with the 7-day cumulative hazard function as the measure. SurvSHAP(t) was applied to provide a time-dependent explanation of the contribution of each variable to the prediction. Results: The cohort had a median age of 39 years, with 233 males and 149 females. Of the 51 inpatients requiring oxygen, 30 required low-flow oxygen, 3 high-flow oxygen, and 8 were treated with invasive ventilation or extracorporeal membrane oxygenation. Ten patients died. The GBDT model predicted COVID-19 severity with area under the receiver operating characteristic curves ranging from 0.717 to 0.970 across severity thresholds. Pneumonia was the most significant predictor for moderate cases, while age and biomarkers such as lymphocyte count, creatinine, C-reactive protein (CRP), and prothrombin time were key for severe outcomes. The dynamic mortality risk assessment during hospitalization could discriminate between deceased and surviving patients 1–2 weeks before the outcome. Early in hospitalization, CRP was an important risk factor for mortality, while in the middle period peripheral oxygen saturation increased its importance and platelets and β-D-glucan were the main risk factors immediately before death. Conclusions: The machine learning-based framework developed in this study demonstrated the ability to predict the maximum severity of COVID-19 at initial diagnosis with reasonable accuracy. However, the risk of deterioration for some patients evolved during hospitalization, highlighting the importance of continuous monitoring. The dynamic risk monitoring framework, which updates mortality risk predictions daily using longitudinal data, achieved high predictive performance and offered explainable predictions through SurvSHAP(t). This approach can provide healthcare professionals with real-time guidance for clinical decision-making, enabling timely interventions and better resource allocation. Clinical Trial: This study was approved by the local institutional review board of RIKEN and Tokyo Shinagawa Hospital (approval number: 20-A-06).
Background: Atherosclerotic cardiovascular disease poses a heavy burden on the population’s health and healthcare costs. Identifying apparently healthy individuals at-risk of developing cardiovascul...
Background: Atherosclerotic cardiovascular disease poses a heavy burden on the population’s health and healthcare costs. Identifying apparently healthy individuals at-risk of developing cardiovascular diseases using clinical prediction models raises awareness, facilitates shared decision-making, and supports tailored management of disease prevention. In the CARRIER project, a personalized cardiovascular risk management (CVRM) eCoach approach is co-created, in which identified individuals receive education, guidance, and monitoring to prevent atherosclerotic cardiovascular disease through existing interventions. In this approach, an AI-driven clinical prediction model calculates the 10-year risk for atherosclerotic cardiovascular disease, which supports informed decision making. Objective: Our primary aim is to assess the effectiveness of our CVRM eCoach approach through a 10-year risk calculation of atherosclerotic cardiovascular disease, including risk factors contributing to this risk. Methods: This pretest-posttest interventional study provides the CVRM eCoach approach for six months to 100 apparently healthy individuals visiting their General Practitioner for primary CVRM. The CVRM eCoach approach is a multicomponent eHealth solution, including a clinical prediction under intervention model that not only calculates the 10-year risk of cardiovascular disease through conventional risk factors (smoking, blood pressure, lipid profile), and individual characteristics (age, gender, socioeconomic status, physical activity and diet), but also calculates how the risk changes after hypothetical lifestyle or medical interventions. The CVRM eCoach approach include features that encourage behavioral change. Most of these features include goal setting, decision cards to help decide on an intervention, intervention monitoring, remote communication, education, all accessible from one dashboard. A practice nurse consults the individuals after risk calculation with the clinical prediction model, and uses behavioral change features, such as the decision cards to support shared decision-making. Data are primarily collected via the eCoach, after which the 10-year risk for atherosclerotic cardiovascular disease and its components are analyzed using paired sample analyses. Results: Recruitment began in March 2024 and will continue until 100 participants have been recruited, which is expected in 2025. Conclusions: We anticipate that our CVRM eCoach approach will be valuable in the primary prevention setting. During the crucial initial first months of habit formation, factors like education, regular check-ups via the eCoach, and clear risk communication could support individuals in sustaining their medical or lifestyle interventions. We hypothesize that there will be a slight to moderate reduction in the 10-year risk of atherosclerotic cardiovascular disease, which over time will lead to significant health improvements on a larger scale. Clinical Trial: https://onderzoekmetmensen.nl/nl/trial/56578; NL84584.096.23
Background: Participation has moved from political protest to active engagement in various areas, including health. Patient engagement has transformed healthcare, and mHealth has positioned mobile tec...
Background: Participation has moved from political protest to active engagement in various areas, including health. Patient engagement has transformed healthcare, and mHealth has positioned mobile technology as a tool for health promotion. Research indicated that user engagement is crucial for effective mHealth interventions. Objective: This paper aims to explore the attributes, methods and barriers to user engagement in mHealth. Methods: For this scoping review, a systematic approach was used to map the evidence on mHealth interventions for health promotion and prevention, following PRISMA-ScR guidelines. Scopus, Web of Science and PubMed databases were searched using tailored keywords. A two-stage selection process was implemented, focusing on participation attributes, methods, and barriers/facilitators. Results: The study analyzed mHealth interventions for health promotion and prevention. Out of 1,533 articles identified, 782 were screened and 41 met the inclusion criteria for analysis. Participation definitions and attributes varied by discipline and author, with scales and gradations qualifying participation by intensity or within the mHealth. User engagement methods included theory-based interventions, behavior change techniques, user-centered design, personalization, autonomy, peer support, motivation and gamification. Challenges included barriers to technology adoption, lack of theory-based interventions, personalization, autonomy, peer support, motivation and gamification. Conclusions: The understanding of user participation in digital interventions is complex and diverse, lacking consensus. Definitions vary among intervention providers, reflecting distinct objectives and methodologies. The absence of clear concepts and attributes highlights the need to refine definitions in digital health, which is essential for guiding intervention evaluation and development methodologies.
Background: Co-design is a collaborative approach involving end users, stakeholders, and designers in creating digital tools for healthcare. This study focuses on the co-design and evaluation of Behav...
Background: Co-design is a collaborative approach involving end users, stakeholders, and designers in creating digital tools for healthcare. This study focuses on the co-design and evaluation of Behavior Emotion Therapy System and You (BETSY), a mental health chatbot and digital human for mild to moderate anxiety. Objective: To develop and evaluate BETSY through a co-design process involving potential users. Methods: The study employed a mixed-methods approach across three phases. Phase 1 involved recruiting 87 volunteer participants through social media for initial end-user requirements. Phase 2 focused on the design process based on end-user requirements employing the expertise of 10 stakeholders in healthcare and health service user. Phase 3 evaluated of the two prototyped interfaces (text-only chatbot and voice-interactive digital human chatbot) through 45 healthy volunteers. Results: For phase 1, 60.7% of participants had previous experience with chatbots and 85.7% expressed a willingness or potential willingness to use a chatbot for mental health support. Thematic analysis in phase 2 revealed key user preferences for a personalized, non-judgmental chatbot with a clear identity and focus on empathy. Privacy concerns and the need for clear interaction guidelines were highlighted. In phase 3, the users showed a strong preference for discussing anxiety related to work, relationships, and health. Both text-only and voice-interactive digital human users considered BETSY valuable for managing mild to moderate anxiety and providing self-help exercises. Conclusions: The co-design process yielded valuable insights for developing BETSY. While users recognized its potential as an accessible first step before seeking professional help, they also identified areas for improvement, including more nuanced conversation capabilities and a broader range of exercises. BETSY's potential as a screening tool for healthcare was consistently acknowledged, suggesting its capability for alleviation of healthcare system burdens. Clinical Trial: No trial registration
Background: : In healthcare settings, especially in high-pressure environments like Emergency situations, the ability to document and communicate patient information rapidly and accurately is crucial....
Background: : In healthcare settings, especially in high-pressure environments like Emergency situations, the ability to document and communicate patient information rapidly and accurately is crucial. Traditional methods for manual documentation are often time-consuming and prone to errors, which can adversely affect patient outcomes. To address these challenges, there is growing interest in integrating advanced technologies, especially Large Language Models (LLMs), into medical communication systems. However, deploying LLMs in clinical environments presents unique challenges, including the need to ensure the accuracy of medical content and to mitigate the risk of generating irrelevant or misleading information. Objective: This paper aims to address these challenges by developing a Natural Language Processing (NLP) pipeline for the extraction of text from German rescue services treatment dialogues. The objectives are twofold: (1) to generate realistic, medically relevant dialogues where the ground truth is known, and (2) to accurately extract essential information from these dialogues to populate emergency protocols. Methods: This study utilizes the MIMIC-IV-ED dataset, a de-identified, publicly available resource, to generate synthetic dialogue data for emergency department scenarios. By selecting and anonymizing data from 100 patients, we created a baseline for generating realistic dialogues and evaluating an NLP pipeline. We applied the Post Randomization Method (PRAM) for non-mechanical data perturbation, ensuring patient privacy and data utility. Dialogue generation was conducted in two stages: initial generation using the "Zephyr-7b-beta" model, followed by refinement and translation into German using GPT-4 Turbo. A Retrieval-Augmented Generation (RAG) approach was developed for extracting relevant information from these dialogues, involving chunking, embedding, and dynamic prompt templates. The model's performance was evaluated through manual review and sentiment analysis, ensuring that the generated dialogues maintained clinical relevance and emotional accuracy. Results: The data generation pipeline produced 100 dialogues, with initial English dialogues averaging 2,000 tokens and German dialogues 4,000 tokens. Manual evaluation identified certain redundancies and formal language in the German dialogues. Sentiment analysis revealed a reduction in negative sentiment from 67% to 59% and an increase in positive sentiment from 27% to 38%, which may negatively impact text extraction, as positive sentiments may not align well with identifying critical topics such as suicidal thoughts. The RAG-based extraction system achieved high precision and recall in both nominal and numerical features in the initial dialogues, with F1-scores ranging from 86.21% to 100%. However, performance declined in the refined dialogues, with notable drops in precision, particularly for "Diagnosis" (60.82%) and "Pain Score" (57.61%). Conclusions: The results of the study underscore the system's robust capabilities in processing structured data efficiently, demonstrating its strength in managing well-defined, quantitative information. However, the findings also reveal limitations in the system’s ability to handle nuanced clinical language, particularly when it comes to non-English and non-Chinese languages.
Background: Diabetic retinopathy (DR), a leading cause of preventable blindness among working-aged adults.
Black, Latine, and individuals living in poverty are screened less for DR, diagnosed later,...
Background: Diabetic retinopathy (DR), a leading cause of preventable blindness among working-aged adults.
Black, Latine, and individuals living in poverty are screened less for DR, diagnosed later, treated
less often, and go blind more than wealthy white individuals. Objective: Through a community-led research approach, this project engaged community members directly
to co-design a digital health tool that is accessible, user-friendly, and culturally relevant. Methods: Using a qualitative approach, we conducted 4 semi-structured focus groups with 19 individuals
from the Greater New Haven area, aged 18 years or older, and diagnosed with diabetes. We
transcribed and coded contextual interviews and categorized them into themes using affinity
mapping. The study has two specific aims: (1) to complete a comprehensive needs assessment
aimed at (2) developing a community-responsive digital health tool to increase access to and
knowledge of diabetic retinopathy (DR) screening in high-risk populations. We transcribed the
focus group interviews, used rapid qualitative analysis to generate themes, and completed
affinity mapping to identify content and features for a digital health tool for preventing blindness
from diabetic retinopathy. Results: We interviewed 19 individuals (68% female, 47% Black, 26% Hispanic,11% indigenous) in 4
focus groups. Over 80% had access to smart devices. Participants’ self-reported mean [SD] A1c
was 6.77 [1.93]. Age mean [SD] was 58.79 [19.54]. Almost half (48%) of participants completed
some college. The principal themes obtained from coding contextual interviews were desired app
attributes, mental impact, informal support, content knowledge related to diabetes, barriers, diet-related topics, and receiving notifications. Conclusions: DR is one of the leading causes of blindness, and many treatments exist. Despite the existence of
treatments, historically marginalized populations experience poor health outcomes, including
blindness. Our community-based approach empowers the creation of a culturally sensitive digital
health tool that will engage more of the patient population with DR.
Background: Tailored interventions are needed to contain Ukraine’s HIV epidemic, especially in wartime. The CASI-Plus study sought to develop and test a mHealth tool to support HIV testing targeted...
Background: Tailored interventions are needed to contain Ukraine’s HIV epidemic, especially in wartime. The CASI-Plus study sought to develop and test a mHealth tool to support HIV testing targeted to people most at risk of HIV exposure, namely the sexual and needle-sharing partners of people who have been newly-diagnosed with HIV. The tool provides client-facing information on how HIV index testing works and uses a standardized self-guided questionnaire with non-judgmental language for clients to list partners who would benefit from HIV testing. The tool also enables healthcare workers (HCWs) to see summarized data about named partners, to facilitate their tracking and follow-up. Given wartime population displacement, trauma, and disruption of health services, it was important to gather both client and healthcare worker input on the designs of this mHealth CASI-Plus tool to ensure acceptability, feasibility, and usability. Objective: This formative research study sought to gather input to prioritize features and test usability of CASI-Plus with healthcare workers and clients living with HIV who are engaged with HIV services in public health clinics in wartime Ukraine. Methods: The CASI-Plus study’s formative phase, carried out in May 2023-July 2024, utilized adapted, human-centered design (HCD) methods grounded in principles of empathy, iteration, and creative ideation. The study included three steps: 1) human centered design, including in-depth individual interviews with 10 clients, including men who have sex with men (MSM) and people who inject drugs (PWID), and virtual design workshops with 22 HCWs from rural and urban HIV clinics in Chernihiv and Dnipro; 2) formative development and heuristic evaluation, including assessment of open-source mHealth platforms against CASI-Plus requirements, prototype development, and testing of the REDCap prototype based on usability heuristics; and 3) usability walk-throughs, including simulated cases with HCWs and clients. Results: The formative research phase of the CASI-Plus study demonstrated how simplified HCD methods, adapted to the wartime context, gathered rich input on the prioritized features and design of the CASI-Plus tool. The CASI-Plus design reflected features that are both culturally sensitive and align with the constraints of Ukraine’s wartime setting. Prioritized features included information about benefits of HIV index testing, a non-judgmental self-guided questionnaire to report partners, client stories, and bright images to accompany text. Two-way SMS messaging between clients and HCW was not considered feasible to integrate within the workflow of understaffed public health clinics. Conclusions: It was feasible to conduct HCD research in Ukraine even in a wartime setting, and the CASI-Plus mHealth tool was acceptable to both HCW and clients. The next step for the research is a randomized clinical trial of the effect of the REDCap-based CASI-Plus on the number of partners named and the rate of partners completing HIV testing. Clinical Trial: This trial is registered via ClinicalTrials.gov # NCT05826977.
Background: Clinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often la...
Background: Clinical reasoning is a critical skill for physical therapists, involving the collection and interpretation of patient information to form accurate diagnoses. Traditional training often lacks the diversity of clinical cases necessary for students to develop these skills comprehensively. Large Language Models (LLMs) like GPT-4 have the potential to simulate a wide range of clinical scenarios, offering a novel approach to enhance clinical reasoning in physical therapy education. Objective: The aim of this study is to explore the main barriers and facilitators that could be encountered in conducting a randomised clinical trial to study the effectiveness of the implementation of LLM models as tools to work on the clinical reasoning of physiotherapy students. Methods: This pilot randomized parallel-group study involved 46 third-year physiotherapy students at La Salle Centre for Higher University Studies. Participants were randomly assigned to either the experimental group, which received LLM training, or the control group, which followed the usual curriculum. The intervention lasted for four weeks, during which the experimental group used LLM to solve weekly clinical cases. Digital competences, satisfaction, and costs were evaluated in order to explore the feasibility of this intervention. Results: The recruitment and participation rates were high, but active engagement with the LLM was low, with only 5.75% of the experimental group actively using the model. No significant difference in overall satisfaction was found between the groups and the cost analysis reflected an initial cost of 460€ for completing the study. Conclusions: While LLMs have the potential to enhance specific digital competences in physical therapy students, their practical integration into the curriculum faces challenges. Future studies should focus on improving student engagement with LLMs and extending the training period to maximize benefits.
Background: Post-stroke spasticity (PSS) is a frequent sequela in patients who have suffered a stroke. This form of paralysis is more prevalent compared to other post-stroke sequelae and is among the...
Background: Post-stroke spasticity (PSS) is a frequent sequela in patients who have suffered a stroke. This form of paralysis is more prevalent compared to other post-stroke sequelae and is among the most challenging and complex symptoms to manage. Surface electromyography (sEMG) can reflect the physiological information of muscles in real time and is highly beneficial in diagnosing neuromuscular diseases in clinical medicine. This study aimed to investigate the timing of post-stroke limb spasms using a nested case-control study combined with sEMG and to identify and predict factors of PSS at an early stage. Objective: This clinical study aimed to improve the prognosis of patients with PSS by exploring the time of PSS occurrence through a nested case-control study, early identification, and prediction of PSS factors. Methods: This was a nested case-control study. Participants were assessed within 24 h of the onset of hospitalization using a standardized case report form to evaluate general patient information and clinical data related to cerebral infarction and imaging. Upon inclusion, patients were assessed after 1, 2, 4, 8, and 12 weeks, using the Modified Ashworth Scale (MAS) for spasticity severity, root mean square (RMS) values from (sEMG) for limb spasm severity, and the simplified Fugl-Meyer Assessment (S-FM) for limb motor function. Patients who experienced spasticity within 12 weeks were assigned to the spasticity group, whereas those who did not experience spasticity were assigned to the control group. Unmatched case grouping was implemented. Data with normal distribution was analyzed using the t-test, while data with non-normal distribution was analyzed using the rank-sum test; categorical data was analyzed using the chi-square test, rank-sum test, or Fisher's exact test. Logistic regression analysis was used to investigate factors affecting treatment outcomes. Data processing, analysis, and visualization were conducted using Statistical Package for the Social Sciences software (version 26.0). Results: The patient is still being recruited Conclusions: The patient is still being recruited Clinical Trial: Ethics and dissemination: The study has been approved by the Ethics Committee of the Affiliated Hospital of Hunan Academy of Traditional Chinese Medicine (approval number: [202371]). All patients were required to provide a written informed consent before enrollment. The findings of this investigation were mandated for publication in peer-reviewed journals.
Clinical trial registration: ClinicalTrials.gov ChiCTR2300077121.
Background: Virtual reality (VR) is a rapidly developing technology that has gained significant traction in the medical domain, particularly in the treatment and rehabilitation of individuals with str...
Background: Virtual reality (VR) is a rapidly developing technology that has gained significant traction in the medical domain, particularly in the treatment and rehabilitation of individuals with stroke. The growing use of VR in stroke management has led to a notable increase in clinical investigations. Objective: The aim of this study is to present a bibliometric analysis of VR for stroke studies to identify prevailing research trends and guide future scientific research. Methods: Articles and reviews on the topic of virtual reality for stroke were retrieved from the Science Citation Index Expanded of Web of Science Core Collection database. The data related to publications, countries, institutions, authors, journals, citations, and keywords in the studies were systematically analyzed using VOSviewer 1.6.20 and Citespace 6.3.1 software. Results: A total of 1171 papers on the topic of VR for stroke between 1999 and 2023 were analyzed and visualized to identify research hotspots and trends in the field. The number of annual publications in this field of study has increased gradually over the past 20 years, with the number of annual publications peaking in 2022 (n=154). In terms of publications and total citations, countries, institutions, and authors from North America and Western Europe were found to make significant contributions to the field. The current hotspot is concentrated on evaluating the effectiveness of VR for improving upper limb and balance functions in stroke patients. The keyword analysis indicates that the latest research is oriented to investigate the effectiveness of VR in combination with rehabilitation techniques such as physiotherapy and occupational therapy for the treatment of stroke, and the advancements in VR technology are increasingly gaining focus. Conclusions: Our study offers insights into the current hotspots and emerging trends of VR in the treatment of stroke. These findings may serve as a guide for future research and the application of VR for stroke.
Background: The transition to parenthood is a memorable yet vulnerable time for mothers' physical and mental health, placing women after giving birth at risk of postpartum depression. Prevalence of co...
Background: The transition to parenthood is a memorable yet vulnerable time for mothers' physical and mental health, placing women after giving birth at risk of postpartum depression. Prevalence of common perinatal mental disorders or postpartum depression among Vietnamese women after giving birth remains high, with potential long-term consequences for mothers' mental health, children's development, and family relationships. Supportive programs to prevent mental illness and promote mental health are, therefore, essential. Objective: The 12-week women's wellness after giving birth program aims to provide evidence-based knowledge and support for women after giving birth to reduce risk of postpartum depression while improving overall quality of life. This protocol guides a pilot study to evaluate the effectiveness and feasibility of a health education package for Vietnamese women after giving birth. Methods: Following ethical approval, 30 Vietnamese women after giving birth will be invited to participate in a wellness program. Participants will be able to access a free online platform featuring evidence-based information delivered through infographics, podcasts, pop-up key messages and videos. They can provide feedback and request professional help while receiving daily reminders via emails. Results: Qualitative outcome measures will include participants' feedback and experience regarding feasibility and usability of the program while results from self-reported online survey using Edinburgh Postnatal Depression Scale (EPDS) will reveal the risk of postpartum depression and the 12-Item Short-Form Health Survey (SF-12) will indicate quality of life of participants at week 6 and week 12. Conclusions: This innovative intervention is the first of its kind in Vietnam to support women's wellness after giving birth. Findings will help refine and optimize the program and provide valuable information on its effectiveness in promoting mental health, improving quality of life, and reducing the risk of postpartum depression among Vietnamese women after giving birth.
Background: Although much progress has been made in AI, several challenges remain substantial obstacles to the development and translation of AI systems into clinical practice. Even the LLMs (Large La...
Background: Although much progress has been made in AI, several challenges remain substantial obstacles to the development and translation of AI systems into clinical practice. Even the LLMs (Large Language Models) which show excellent performance on various tasks, have progressed slowly in clinical practice task. Providing precise and "explainable" treatment plans with personalized details remains a big challenge for AI systems due to both the highly professional medical knowledge and the patient’s complicated condition. In this study, we develop a knowledge graph-enhanced and explainable automatic decision support system based on multiple-center data, named H-SYSTEM, hoping provide substantial assistance for neurosurgeons in dealing with HICH cases. Objective: During the past decade, much progress has been made in artificial intelligence (AI), but there are still two main challenges represent substantial obstacles to the development and translation of medical AI systems into clinical practice. The first important challenge is access to large and well-annotated datasets. The second important challenge is that the inner workings and decision-making processes of machine-learning algorithms remain opaque, which is also "black-box" effects. Therefore, in this study, we developed a novel clinical decision support system (CDSS) based on multiple-center data, called H-SYSTEM, attempting to address the two main challenges. Methods: The H-SYSTEM consists of three main modules, the key-named entity identification module, the semantic analysis and representation module, and the reasoning module. Furthermore, we constructed a medical domain knowledge graph for HICH, named HKG, which is served as an “external knowledge brain” of H-SYSTEM to enhance its text recognition and automated decision-making capability. The HKG is exploited to guide the training of semantic analysis and representation module and reasoning module, which makes the output of H-SYSTEM more “explainable”. To assess the performance of the H-SYSTEM, we compared it with doctors and different LLMs. Results: The outputs based on HKG showed a reliable performance as compared with the neurosurgical doctor (ND). The BERT-IDCNN-BiLSTM-CRF model was used as the key-named entity identification module of H-SYSTEM because of its excellent performance in terms of fast convergence and efficient extraction of key named entities. Furthermore, the H-SYSTEM showed high reliability and efficiency when compared to doctors, ChatGPT and ChatDoctor. Additionally, it also demonstrated both high accuracy and generalization capacity in the cases from diffrent medical centers. Conclusions: The H-SYSTEM shows significantly high efficiency and generalization capacity in processing EMRs, and provides explainable and elaborate treatment plans. Therefore, it has the potential to provide neurosurgeons with rapid and reliable decision support, especially in emergency conditions. The knowledge graph enhanced deep-learning model can exhibit excellent performance in the clinical practice task. Clinical Trial: This research is not an clinical trial.
You may have come across the term “personalized medicine” before, but what is it? Genetic testing has become commonplace for investigating ancestry and disease risk. There are a myriad of genetic...
You may have come across the term “personalized medicine” before, but what is it? Genetic testing has become commonplace for investigating ancestry and disease risk. There are a myriad of genetic tests available for sale online claiming to offer meal plans and exercise routines tailored to your genetic code. After all, what could be more personalized than DNA? As health information has become more accessible online, another question arises: what information is reliable and what is not? This open educational resource explores 6 questions that can be used by anyone to evaluate the trustworthiness of online health information: Who runs the website? What is the website about? Where are the sources of health information? When was the website last updated? Why was the website made? How is the website funded? Asking these questions is key for the public and medical professionals alike.
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, begi...
Background: Abstract (237 words)
The American Civil War has been commemorated with a great variety of monuments,
memorials, and markers. These monuments were erected for a variety of reasons, beginning with
memorialization of the fallen and later to honor aging veterans, commemoration of significant
anniversaries associated with the conflict, memorialization sites of conflict, and celebration of
the actions of military leaders. Sources reveal that during both the Jim Crow and Civil Rights
eras, many were erected as part of an organized propaganda campaign to terrorize African
American communities and distort the past by promoting a ‘Lost Cause’ narrative. Through
subsequent decades, to this day, complex and emotional narratives have surrounded interpretive
legacies of the Civil War. Instruments of commemoration, through both physical and digital intervention approaches, can be provocative and instructive, as the country deals with a slavery legacy and the commemorated objects and spaces surrounding Confederate inheritances.
Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question. Objective: I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Methods: This article addresses several elements within the purview of the Journal: questions of contemporary society, diversity of opinion, recognition of complexity, subject matter of interest to non-specialists, international relevancy, and history. Drawing from the testimony of scholars and artists, I address the contemporary conceptual landscape of approaches to the presentation and evolving participatory narratives of Confederate monuments that range from absolute expungement and removal to more restrained responses such as in situ re-contextualization, removal to museums, and preservation-in-place. In a new era of social justice surrounding the aftermath of dramatic events such as the 2015 Charleston shooting, the 2017 Charlotteville riot, and the murder of George Floyd, should we see them as symbols of oppression, inviting expungement, or selectively as sites of conscience and reflection, inviting various forms of re-interpretation of tangible and intangible relationships?
I describe monuments as symbols in the “Lost Cause” narrative and their place in enduring Confederate legacies. I make the case, and offer documented examples, that remnants of the monuments, such as the “decorated” pedestals, if not the original towering statues themselves, should be left in place as sites of reflection that can be socially useful in public interpretation as disruptions of space, creating disturbances of vision that can be provocative and didactic. I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Results: I argue that we should see at least some of them as sculptural works of art that invite interpretations of aesthetic and artistic value. I point out how, today, these internationally relevant factors and outcomes of retention vs. removal are engulfed in swirls of social and political contention and controversy within processes of remembering and forgetting and changing public dialogues. Conclusions: Today, all of these potential factors and outcomes, with internationally relevance, are surrounded by swirls of social and political contention and controversy, including the remembering/forgetting dichotomies of cultural heritage. The modern dilemma turns on the question: In today’s new era of social justice, are these monuments primarily symbols of oppression, or can we see them, in select cases, alternatively as sites of conscience and reflection encompassing more inclusive conversations about commemoration? What we save or destroy and assign as the ultimate public value of these monuments rests with how we answer this question.
Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations
at various levels to limit public mobility. This paper analyzes the complex associatio...
Background: The COVID19 pandemic has caused a large number of infections and fatalities, causing administrations
at various levels to limit public mobility. This paper analyzes the complex association between the
stringency of restrictions, public mobility, and reproduction rate (R-value) on a national level for Germany. Objective: The goals were to analyze; a) the correlation between government restrictions and public mobility and b)
the association between public mobilities and virus reproduction. Methods: In addition to correlations, a Gaussian
Process Regression Technique is used to fit the interaction between mobility and R-value. Results: The main
findings are that: (i) Government restrictions has a high association with reduced public mobilities,
especially for non-food stores and public transport, (ii) Out of six measured public mobilities, retail,
recreation, and transit station activities have the most significant impact on COVID19 reproduction rates. Conclusions: A mobility reduction of 30% is required to have a critical negative impact on case number dynamics,
preventing further spread.
This paper discusses the specific characteristics of any hypothetical cognitive space that may be modelled in
order to automate (or partially automate) the kind of mental health clinical reasoning -...
This paper discusses the specific characteristics of any hypothetical cognitive space that may be modelled in
order to automate (or partially automate) the kind of mental health clinical reasoning - clinical or psychological
case formulation - that is used by mental health professionals. It argues that work into the use of generative
artificial intelligence (AI) in the field of mental health needs to consider three components of this kind of
clinical reasoning. Firstly, heterotopy. When mental health clinical reasoning statements are made, parsing them
does not result in the same representation when the same words are used, due to the fact that mental health
ontologies contain multiple meanings for the same words. Secondly, orthogonality. Variables relevant to mental
health may not causally intersect but may both be relevant for clinical case formulation and treatment
determination. Thirdly, veridicality. The truth of a clinical case formulation may not be determined by any
testable observations. Even treatment response may not allow for a determination of truth., The truth status of a
clinical case formulation may hinge principally on the degree to which it confers meaning or understanding of a
mental state on the person who is experiencing that mental state, and that truth may be different to the truth
judgements of a mental healthcare clinician. Automated clinical case formulation models need to accommodate
for these features of the cognitive space of mental health clinical case formulation.
Background: Exercise intervention is effective in managing diabetes when delivered in a personalized manner. Personalization of exercise intervention following a systematic fitness assessment can lead...
Background: Exercise intervention is effective in managing diabetes when delivered in a personalized manner. Personalization of exercise intervention following a systematic fitness assessment can lead to better health outcomes Objective: This study aimed to analyze the effect of digitally delivered fitness assessments and exercise prescriptions on the fitness and health outcomes of people with diabetes. Methods: Participants diagnosed with type 2 diabetes (n=86) enrolled in the Fitterfly Diabetes program which included interventions in nutrition, fitness, and mental health delivered via a digital platform. The participants underwent a video call-based fitness assessment consisting of the 1-minute push-up test, wall sit test, 1-minute sit-up test, V-sit and reach test, and 6-minute walk test. Trained physiotherapists conducted the assessments, developed personalized exercise plans, and shared them with the participants via the app. Regular follow-ups were taken. The participants were re-assessed after 90 days. Results: There was a statistically significant improvement in the fitness-related outcome measures (p<0.05), the anthropometric measures (p<0.05), and HbA1c (p<0.05) post-intervention. Improvement in exercise duration was associated with better outcomes in fitness tests and anthropometric measures. Conclusions: Personalized exercise intervention delivered digitally can help achieve better health outcomes in people with type 2 diabetes.
Background: The burgeoning volume of scientific literature being generated today places a great burden on evidence reviewers. On average, only 2% to 8% of articles yielded by a search strategy are ult...
Background: The burgeoning volume of scientific literature being generated today places a great burden on evidence reviewers. On average, only 2% to 8% of articles yielded by a search strategy are ultimately included in a systematic review. Due to the burden of increasing information loads, there is a demand for methods that improve efficiency while maintaining accuracy in performing evidence reviews. Objective: This systematic review aims to determine the accuracy and efficiency of AI-assisted abstract selection compared to manual abstract selection, as assessed by diagnostic performance and workload saved over sampling (WSS). Methods: Two reviewers searched PubMed, Proquest, and Cochrane Library for studies evaluating the diagnostic performance and/or workload savings achieved by any AI tool, whether through full or semi-automation, in the title and abstract screening phase of literature review. Variance-weighted random effects meta-analysis was done to generate univariate measures of sensitivity, specificity, and WSS for the studies using RevMan verson 4.3 and the ‘meta’ and ‘mada’ packages on R version 4.3.1. Bivariate analysis was also performed for the measures of diagnostic accuracy and a hierarchal summary operating characteristics curve (HSROC) was generated. Results: Twenty-two studies were included in this review, where 13 reported diagnostic performance, 14 reported WSS, and five studies reported both outcomes. In fully automated workflows, AI tools had a sensitivity of 85.6% (95% CI: 60.8%-95.8%) and a specificity of 88.7% (95% CI: 58.7%-97.7%) with considerable heterogeneity, which likely stems from the differences in the SRs and AI techniques used. In semi-automated workflows, sensitivity was 87.6% (95% CI: 77.2%-93.6%) and specificity was 94.1% (95% CI: 60.0%-99.4%) also with considerable heterogeneity. Among studies on full automation, the median workload savings for 100% recall was 50.0% (IQR: 10.2), while for studies on semi-automation, the median workload savings was 55.6% (IQR: 16.4). Conclusions: Given the findings of this review, the diagnostic performance of AI tools appeared to be superior when used in semi-automated workflows rather than fully automated ones. This suggest that AI tools hold great potential in augmenting the accuracy and efficiency of human reviewers during study selection in literature review.
Infrapubic penile implant surgery is a viable option for patients with severe penile curvature, shortening, and impaired penile rigidity due to fibrosis of the corpora cavernosa (Sadeghi-Nejad, 2007)....
Infrapubic penile implant surgery is a viable option for patients with severe penile curvature, shortening, and impaired penile rigidity due to fibrosis of the corpora cavernosa (Sadeghi-Nejad, 2007). Studies have shown that patients who undergo penile implant surgery, particularly the infrapubic approach, experience significantly better erectile function and treatment satisfaction compared to those receiving other treatments such as sildenafil citrate and intracavernous prostaglandin E1 (Rajpurkar & Dhabuwala, 2003). The infrapubic approach offers advantages such as ease of reservoir placement, rapid implantation, and direct vision during the procedure, as well as avoiding an extra incision on the scrotum, which can hinder rehabilitation (Montague & Angermeier, 2000; Vollstedt et al., 2017). Additionally, it has been noted that the infrapubic approach can be quickly learned by urologists who are already comfortable with the trans‐scrotal approach (Kramer & Chason, 2010). However, it is important to consider the drawbacks associated with the infrapubic approach, such as the higher risk of surgical errors during the placement of the device in the corpora (Kramer et al., 2010).
Background: The research reports the development of a behavioral satisfaction questionnaire (BSQ) for the use in cognitive-behavioral therapies (CBTs). Objective: It is purposed for semi-structured ps...
Background: The research reports the development of a behavioral satisfaction questionnaire (BSQ) for the use in cognitive-behavioral therapies (CBTs). Objective: It is purposed for semi-structured psychoanalytic interviews, but can also be used for self-report. The design of BSQ seeks to organize a referential scale with a psychodynamic perspective, in order to bridge the gaps among neurological / psychiatric therapies, psychological therapy, and patient / visitor autonomy. Methods: The psychometric evaluations are dissected into different dimensions in the questionnaire design, with a paradigmatic conceptual framework. Results: The test trial has demonstrated high affinity with other major psychometric methods. Conclusions: The BSQ design is valid in overall assessments on complicated psychological case. Clinical Trial: The test trial is registered on ClinicalTrials.gov with the identifier NCT05930912.
