An integrative research framework to investigate factors influencing citizen’s intention to adopt e-health applications: post-COVID-19 perspective

The use of e-health applications has remained popular during pandemic for medical treatments. Nevertheless, adoption of e-health applications among individuals is considerably low in post-COVID-19 world. To address this issue, the current research integrates three renowned theories, namely unified theory of acceptance and use of technology model, diffusion of innovation and DeLone and McLean model and investigates individual intention to adopt e-health application.

Research design is grounded in quantitative and cross-sectional methods and uses a survey questionnaire. Survey questionnaire is administered toward smartphone users. Overall, 238 valid responses were analyzed with structural equation modeling approach.

Results indicate that altogether performance expectancy, effort expectancy, information quality, system quality, service quality, facilitating condition and social influence explained substantial variance (R² = 76.5%) in user intention to adopt e-health applications. Similarly, effect size analysis has revealed substantial impact of social influence on user intention to adopt e-health applications. Geiser and Stone’s Q² analysis discloses that research model has substantial power to predict user intention to adopt e-health applications.

This study integrates three known information system models to investigate individual behavior toward adoption of e-health applications. In practice, it suggests that managers should pay attention in improving performance expectancy, social influence, facilitating condition, system quality, service quality and information quality which develop positive behavior and encourage smartphone users to adopt e-health applications.

This study is original as it integrates three models and investigates individual intention to adopt e-health applications. To the best of the author’s knowledge, this is the first study to test the moderating impact of patient health value between user intention to adopt and actual use of e-health applications. It has established that compatibility and innovativeness are essential antecedents of performance and effort expectancy and hence make this research more unique and valuable.