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Background Health care technologies can help improve workers’ health and productivity by supporting workplace health promotion. A personal health record app is used to manage medical data such as results from medical checkups, which facilitates decision making for medical personnel. However, an analysis of users’ technology acceptance is required to provide appropriate 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 an app in workers’ health centers and to examine differences in their perception of the main variables. Methods The study involved health experts and workers who visited 21 workers’ health centers in Korea to verify a research model in which perceived risk was added to the unified theory of acceptance and use of technology, a representative theory of information technology acceptance. After receiving ethical approval from the Korea National Institute for Bioethics Policy, 1050 questionnaires were distributed over 7 weeks with cooperation of the Korea Occupational Safety and Health Agency. A multiple linear regression analysis and multigroup path analysis were performed to verify the hypotheses, and independent samples t tests were performed to analyze differences between workers’ and health experts’ perception of the main variables. Results The analysis included data from 866 respondents (687 workers and 179 health experts). Effort expectancy (beta=.08, P=.03), social influence (beta=.43, P<.001), performance expectancy (beta=.07, P=.008), and facilitating conditions (beta=.13, P<.001) exerted significant positive effects on behavioral intention, whereas perceived risk (beta=–.29, P<.001) exerted a significant negative effect on behavioral intention. Performance expectancy had a significant effect on path differences depending on gender (critical ratio=–3.38) and age (critical ratio=1.97). 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 as well as the operational direction of community institutions such as in 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.

Background: To investigate the relationship between hand grip strength (HGS) and self-rated health in middleand old-aged Korean subjects. Methods: The data used for this study were derived from the Korean Longitudinal Study of Aging. A total of 9,132 participants were enrolled using the year 2006 as the baseline, with additional data collected throughout the followup period until 2016. Chi-square test and generalized estimating equation regression models were used for data analysis. HGS was measured in a sitting position with the elbow fixed at 90° on both sides using a dynamometer, and calculated using the values measured from both sides. Relative HGS was measured by dividing HGS by the subject's body mass index. Self-rated health was assessed with the question "How would you rate your current health in general?" and answers were categorized as "excellent, " "moderate, " or "poor. " Results: HGS was shown to be inversely associated with self-rated health (odds ratio [OR], 0.94; 95% confidence interval [CI], 0.93-0.94; P<0.0001). Patients aged 65 years or older with lower scores were more likely to report poor self-rated health. Similar results were obtained with relative HGS (OR, 0.40; 95% CI, 0.36-0.45; P<0.0001), but standard HGS had better model fitting (quasi-likelihood under independence model criteria=33,890). Conclusion: HGS may be considered an index for the diagnosis of sarcopenia and may also affect self-rated health, which is a multidimensional indicator of an individual's health status and can identify patients who may require special attention.

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