Currently submitted to: JMIR Human Factors
Date Submitted: Nov 13, 2025
Open Peer Review Period: Nov 24, 2025 - Jan 19, 2026
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TrainBo: A Pilot Study of Developing an Interactive Robot-assisted Scenario Training System for Older Adults
ABSTRACT
Background:
With the ability to provide instant feedback and assistance, social robotic systems have been proven effective in enhancing learning experiences across various age groups, ranging from kids to young adults. Robot-assisted training environment may also enhance the learning experience of older adults, compared with traditional instructional environment. However, the strength of interactive robots in promoting learning engagement for older adults has not been well investigated.
Objective:
This study focuses on the design of an interactive robot-assisted scenario training system (TrainBo), derives design requirements and user experience themes through formative research and evaluation.
Methods:
The pilot test was conducted with 11 older adults in an elderly care center in Hong Kong, employing observations and training interviews. It included three phases. Phase 1: Formative research involved face-to-face surveys and semi-structured interviews to identify DRs. Phase 2: Conducted few rounds of iterations based on the identified DRs. Following evidence-based user experience principles and the Self-Determination Theory, we developed TrainBo. We utilised multi-sensory components to improve usability, including automatic speech recognition, visual aids and human-like interactions. Phase 3: We recruited participants in a 4-week training session covering supermarket, restaurant, and transportation scenarios for a evaluation of participants’ engagement and motivation.
Results:
The formative research has identified 5 key Design Requirements (DR): DR1) visual-based instructions, DR2) encouragement and positive feedback, DR3) large and readable fonts, DR4) relatable content, DR5) customizable response time. During the evaluation, participants demonstrated high engagement with TrainBo, with no signs of frustration. They prefer TrainBo to read questions aloud, respond with gestures and provide encouraging responses. We also observed the colour preference, familiarity of equipment usage, the need for visual aids and scenario preference, as well as gaining insights into their communication challenges, levels of patience and engagement.
Conclusions:
This study demonstrates the promising role of interactive robot-assisted scenario training systems in enhancing engagement and motivation among older adults. By leveraging the principles of Self-Determination Theory, the system has shown potential in fostering intrinsic motivation and improving user satisfaction. The positive feedback from participants regarding the usability and interactive features of TrainBo suggests that such an interactive robot-assisted scenario training system may be a valuable tool for improving elderly care.
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