Abstract
Mobility represents a vital health challenge for the inevitably aging population. Technology-driven interventions, such as virtual coaches, may offer innovative and promising solutions to promote physical activity and wellness among community-dwelling older adults. Guided by the Universal Theory of Acceptance and Use of Technology (UTAUT) framework and the Conical Model of Mobility, the Mixed Reality-Oriented Virtual Coach Experience (MOVE) Project was conceptualized by a multidisciplinary team. The study examined the usability, acceptability, feasibility, and impact of virtual coaches on older adults, using physiological metrics (balance and fall risk score, cardio fitness score, heart rate variability) and psychological metrics (mobility efficacy). A mixed-method proof-of-concept study was adopted. A purposively selected group of community-dwelling older adults (n = 26) was exposed to experimental (mixed-reality physical exercise with a virtual coach; MOVE) and control (physical exercise with a human coach) interventions for 3 weeks. Empirical data were collected using valid and reliable methods (e.g., cognitive walkthrough via eye-tracking) and devices (e.g., research management platform, Fitbit Inspire 3™, BTrackS Balance Plate ) . Descriptive and comparative statistics (independent samples T-test and RM-ANOVA) were generated from the pilot research data using SPSS version 25. The older adult participants who received the MOVE intervention rated the virtual coaches satisfactorily, with only minor adjustments to the user interface. The health impact of virtual coaches for physical exercise is not statistically significantly different from a control intervention in this small proof-of-concept sample. Developing cost-effective, customized, and inclusive innovations via a human-centered approach is necessary to maximize the benefits of technologies.
| Original language | English (US) |
|---|---|
| Article number | 101115 |
| Journal | Computers in Human Behavior Reports |
| Volume | 22 |
| DOIs | |
| State | Published - May 2026 |
All Science Journal Classification (ASJC) codes
- Neuroscience (miscellaneous)
- Applied Psychology
- Human-Computer Interaction
- Computer Science Applications
- Cognitive Neuroscience
- Artificial Intelligence
Keywords
- Fall risk
- Feasibility
- Mixed reality
- Mobility
- Older adults
- Proof-of-concept
- Usability
- Virtual coach
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