Bridging the acceptance gap: insights from digital health tools among middle-aged and elderly chronic patients

Digital health technologies exhibit substantial potential in the management of chronic conditions, yet their uptake among middle-aged and elderly patients continues to be notably sluggish, resulting in a prominent "acceptance gap." To unravel the psychological underpinnings of this phenomenon, this study integrates the Health Belief Model (HBM) and the Technology Acceptance Model (TAM) to construct a comprehensive analytical framework. A cross-sectional survey was conducted among 409 chronic disease patients aged 45 and above in an eastern Chinese city, and the proposed integrated model was validated using structural equation modeling. The results demonstrated a good model fit (/df = 2.78, CFI = 0.93, RMSEA = 0.06). Specifically, perceived usefulness/benefits, perceived severity of disease, and self-efficacy emerged as significant positive predictors of behavioral intention, while perceived barriers exerted a marked negative influence. Social influence and perceived ease of use played crucial indirect roles by enhancing perceived usefulness/benefits and self-efficacy. Notably, the direct effect of perceived susceptibility on behavioral intention was not statistically significant. This study confirms the effectiveness of the integrated model in explaining usage intentions. To bridge the acceptance gap, multi-dimensional strategies are required: optimizing design to improve ease of use and enhance user self-efficacy, clearly conveying the core health values of digital tools in promotional efforts, and actively leveraging recommendations from healthcare professionals to drive adoption.