Virtual health coach acceptance in point-of-care settings among community-dwelling older adults: a mixed-method proof-of-concept study

Introduction Population aging increases the need for accessible, technology-assisted interventions that promote the wellbeing of older adults. Tai Chi and Qigong (TCQ) demonstrate benefits for balance, mobility, and mental health, but limited evidence exists regarding older adults’ acceptance of mixed reality-based virtual coaching technologies. This proof-of-concept mixed method study aimed to (1) describe the profile of older adult participants, (2) develop and evaluate a parsimonious model integrating Unified Theory of Acceptance and Use of Technology (UTAUT) constructs and perceived benefits as point-of-care technology (BEPOCT) variables in explaining behavioral intention to use the Mixed Reality-Oriented Virtual Coach Experience–Qigong and Tai Chi Module (MOVE-QTM), and (3) explore the experiences of the older adult participants in relation to the study’s quantitative outcomes. Methods An explanatory-sequential mixed-methods design was employed with 38 community-dwelling older adults from a senior center. Results and Discussion Most participants were female (97.37%), aged 60–64 years (50.00%) and classified as low income (55.26%). Structural equation modeling showed significant direct effects of Facilitating Conditions on Behavioral Intention (β = 0.278, p = 0.030), Social Influence on Behavioral Intention (β = 0.287, p = 0.026), and BEPOCT on Behavioral Intention (β = 0.249, p = 0.048). Social Influence also demonstrated a strong direct effect on BEPOCT (β = 0.656, p < 0.001), representing the strongest relationship in the model. However, Effort Expectancy (β = 0.190, p = 0.105) and Performance Expectancy (β = −0.099, p = 0.263) did not significantly predict BEPOCT. Furthermore, the effects of Social Influence (β = 0.163, p = 0.067), Effort Expectancy (β = 0.338, p = 0.338), and Performance Expectancy (β = −0.025, p = 0.414) on BI through BEPOCT were not significant. Quantitative findings were aligned with qualitative outcomes and suggest that multiple factors are critical determinants of older adults’ acceptance of MOVE-QTM as a point-of-care technology.