ArticleDigital health
Exploring observed and instructed mHealth use in the middle-aged and elderly people (MAEP): A social learning perspective.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Authors and funding
4 authors.
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Abstract
Objective: Based on social learning theory, this study aimed to explore the intention of middle-aged and elderly people (MAEP) to engage with mobile health (mHealth) and the underlying effects of usability and utility. The goal was to garner insights that could enhance the advancement of mHealth and improve the scope of benefits of mHealth use among MAEP in the future. Methods: We employed a survey-based approach to delve into the mHealth use intentions among MAEP individuals aged 45 and above. A total of 371 valid survey responses were collected and analyzed using SmartPLS 3.0 for statistical examination and model verification. Results: Our hypotheses tests revealed that vicarious utility fully mediated the relationship between observed use and direct use intention and both indirect use intentions. Instructed usability and instructed utility were found to fully and partially mediate the relationship between instructed use and indirect use intention, respectively. Conclusions: This study demonstrates that the observed and instructed use behaviors of MAEP can promote their eventual intention to adopt mHealth through processes of observational and reinforcement learning. These findings underscore the importance of understanding the underlying effects of MAEP's intention to use mHealth is critical to increasing their adoption of mHealth, and thereby potentially improving their health outcomes.
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