Accepted for/Published in: JMIR mHealth and uHealth
Date Submitted: Oct 17, 2019
Date Accepted: Mar 30, 2020
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Factors influencing the acceptance of personal health record apps for workplace health promotion: An empirical study in Korea
ABSTRACT
Background:
Healthcare technologies can help improve a worker’s health and productivity by supporting workplace health promotion. The personal health record app manages medical data, such as the results of the medical checkups, and aids medical personnel’s decision making. The analysis of users’ technology acceptance is required to provide services based on personal health record apps.
Objective:
The purpose of this study was to analyze the factors influencing the behavioral intention of health experts and workers to use the app in workers’ health centers, and examine differences in the perception of the main variables.
Methods:
The study involved health experts and workers who visited 21 workers’ health centers, to verify a research model in which perceived risk was added to the unified theory of acceptance and use of technology, which is a representative theory of information technology acceptance. After receiving ethical approval from the Korea National Institute for Bioethics Policy, 1,050 questionnaires were distributed for 7 weeks, with the cooperation of the Korea Occupational Safety & Health Agency. A multiple linear regression analysis was performed to verify the hypotheses and an independent samples t test was performed to analyze differences in the perception of the main variables between workers and health experts. The analysis was performed using SPSS 25.0 and AMOS 22.
Results:
The number of respondents in the analysis was 866 (687 workers and 179 health experts). The results showed that effort expectancy, social influence, performance expectancy, and facilitating conditions exerted significant positive effects on behavioral intention, and perceived risk exerted a significant negative effect on behavioral intention. Workers’ mean scores for the main variables were higher, relative to those of health experts, for all remaining variables except perceived risk, and significant differences were observed for all remaining variables except facilitating condition.
Conclusions:
Social influence exerted the strongest effect on behavioral intention to use the personal health record app. Consequently, it is necessary to coordinate health promotion activities in the workplace and the operational direction of workers’ health centers, to allow workers to manage their own health via continuous use of the app. In addition, the app should be developed based on a requirement analysis of the balance between both interest groups, in consideration of differences in perspective between consumers and service providers.
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