Factors influencing mobile platform adoption for nutritional tracking among Thai elderly: A unified UTAUT and STAM approach

The global aging population underscores the need for culturally tailored mobile health (mHealth) solutions to address nutritional challenges among older adults. This study investigates factors influencing the adoption of a culturally adapted mHealth platform for nutritional tracking among Thai elderly (aged ≥60), integrating the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Senior Technology Acceptance Model (STAM). Using Partial Least Squares Structural Equation Modeling (PLS-SEM) with data from 355 Thai elderly, the model explained 65.3 % of the variance in Behavioral Intention (BI). Performance Expectancy (β = 0.237, p < 0.001), Effort Expectancy (β = 0.239, p < 0.001), Social Influence (β = 0.257, p < 0.001), and Facilitating Conditions (β = 0.318, p < 0.001) significantly predicted BI, while Gerontechnology Self-Efficacy was non-significant (β = 0.067, p = 0.074). Notably, Gerontechnology Anxiety (GA) positively influenced BI (β = 0.078, p = 0.044), suggesting a complex emotional effect in Thailand’s collectivist culture. However, Social Influence did not moderate the GA–BI link (β = 0.002, p = 0.96), suggesting limitations in its moderating role. Post hoc analysis showed Effort Expectancy mediated the effects of Gerontechnology Self-Efficacy (β = 0.155, p = 0.007) and GA (β = −0.048, p = 0.043) on BI. These findings highlight the interplay of functional, social, and emotional factors, informing the design of anxiety-aware, localized mHealth tools. This study contributes to gerontechnology by validating the UTAUT–STAM framework in a middle-income, collectivist context.