Author(s): LI, C., YANG, Y., Institution: SHANGHAI JIAO TONG UNIVERSITY, Country: CHINA, Abstract-ID: 1771

INTRODUCTION:
Health and fitness apps are widely used to support physical activity and health management among older adults. Although prior research has identified numerous age-friendly features among various contexts (Amouzadeh et al., 2025), little is known about how older adults prioritize these features in health and fitness. This study aims to quantify older adults’ prioritization of age-friendly features in health and fitness apps.
METHODS:
Two studies were conducted. Study 1 applied a PRISMA-guided systematic review to identify age-friendly health and fitness app features from 98 articles, which were selected and further categorized based on user experience theory and relevant standards (MIIT, 2021). Based on study 1, study 2 employed a direct-anchored, incentive-aligned Maximum Difference (Max-Diff; Schramm & Lichters 2025) experiment via Credamo (n=683 Chinese older adults, mean age=63.5 [SD=3.86], 50.5% females) to quantify older adults’ prioritization of the selected features. We used hierarchical Bayes modeling to estimate utilities and derive individual-level preference scores.
RESULTS:
Study 1 identified 12 core age-friendly health and fitness app features, and they were categorized into five clusters: (i) entry usability (large fonts, icons, and buttons; clear visual contrast; concise and intuitive interface), (ii) operational usability (simple navigation; error prevention and prompts; voice interaction), (iii) health support (remote health and activity monitoring; exercise and health habit reminders), (iv) engagement and experience (personalized services; elderly social interaction; gamification elements), and (v) trust and safety (data and privacy protection). The inclusion frequency of these features by prior literature ranges from 9 (error prevention and prompts) to 42 (large fonts, icons, and buttons) times. Furthermore, study 2 reveals a clear preference hierarchy: Remote health and activity monitoring showed the strongest positive utility (β = 1.41), whereas elderly gamification elements (β = −2.03) were weakly or negatively valued. Anchored Max-Diff further indicated that concise and intuitive interface, large fonts, icons, and buttons, and remote health and activity monitoring were most frequently identified as truly needed.
CONCLUSION:
This study integrated a systematic review and online incentive-aligned Max-Diff experiment and prioritized a set of 12 age-friendly health and fitness app features. We found that features related to clear interaction, monitoring and reminders are consistently prioritized, whereas gamification and social interaction are deprioritized. The findings provide a clear basis for the age-friendly design and implementations in health and fitness.
References:
Amouzadeh et al., 2025. https://doi.org/10.1007/s40520-025-03157-7
Ministry of Industry and Information Technology of the People’s Republic of China, 2021.
Schramm & Lichters, 2025. https://doi.org/10.1007/s11002-023-09714-2