PLoS ONE· 2026Q1
Factors influencing elderly people’s intentions to use smartphone mHealth apps: Quantitative research
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- 2026year
Short summary
Elderly people's intention to use mHealth apps is positively influenced by perceived trust (β=0.427), attitude (β=0.285), and perceived quality (β=0.278), but negatively by perceived risk (β=-0.173).
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Key points
- Perceived trust (β=0.427), attitude (β=0.285), and perceived quality (β=0.278) positively impact elderly users' intention to use mHealth apps.
- Perceived risk negatively influences intention to use mHealth apps (β=-0.173).
- Perceived quality (β=0.434) and perceived ease of use directly influence perceived trust.
- Perceived convenience positively affects perceived usefulness (β=0.358) and attitude (β=0.299).
AI-generated from the title and abstract; the full text is not read.
Abstract
Smartphone mHealth apps (mHealth apps) have played a highly positive role in medical services, which provides a new direction for users’ medical services and health management. Although smartphone mHealth apps provide many benefits for users, people know little about the factors that drive elderly users to adopt this new service platform in the context of an aging population. This study aims to learn the factors that affect elderly people’s intentions to adopt smartphone mHealth apps, and use the technology acceptance model as a theoretical basis to integrate perceived convenience, perceived quality, perceived risk and perceived trust, in an attempt to construct a research model on the intentions to use smartphone mHealth apps. The elderly users’ data were collected by questionnaire survey and analyzed quantitatively by structural equation model. By analyzing the 263 valid data collected, the results showed that users’ perceived trust (β = 0.427, p < .001), attitude (β = 0.285, p < .001), and perceived quality (β = 0.278, p < .001) of mobile medical applications positively influenced users’ intention to use the applications, while perceived risk (β = −0.173, p < .001) had a negative impact on the intention to use. Perceived trust was also directly positively influenced by perceived quality (β = 0.434, p < .001) and perceived ease of use, and perceived convenience positively influenced perceived usefulness (β = 0.358, p < .001) and attitude (β = 0.299, p < .001). These findings can help us better understand the factors that influence the adoption of smartphone mHealth apps. This study further extends the technology acceptance model and its application domains to help mHealth researchers, designers, marketers, and service providers improve mHealth services and help increase users’ intentions to adopt mHealth apps.
The authors' abstract, as published at the source. PLoS ONE, 2026 · DOI ↗
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Field: Demography
DemographySocial Sciences