PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
February 2, 2026Digital Health0 citationsOpen Access

Feasibility and usability of a ChatGPT-based app to support physical activity: A pilot study

View Full Paper
DLDillys LarbiPZPaolo ZanaboniEÅEirik Årsand

Key Points

  • The study aims to evaluate the feasibility and usability of FysBot, a ChatGPT-based app designed to promote physical activity among adults with obesity.
  • Conducted a 6-week single-arm pilot study at an obesity rehabilitation clinic in Norway.
  • Utilized questionnaires and semi-structured interviews to gather data on physical activity and user experiences.
  • Included tools such as the Godin Leisure-Time Exercise Questionnaire, Behavioral Regulation in Exercise Questionnaire-2, Relative Autonomy Index, and System Usability Scale.
  • Fifty-three participants were eligible, with 17 completing the final follow-up.
  • Mean System Usability Scale score was 51.3, indicating below-average usability.
  • Self-reported leisure-time physical activity showed small, non-significant increases, while identified regulation significantly increased and self-efficacy decreased.

Abstract

Background FysBot is a ChatGPT-based mobile app developed to promote physical activity among adults living with obesity. This pilot study aimed to evaluate the feasibility and usability of FysBot. Methods A 6-week single-arm pilot study was conducted in which patients from an obesity rehabilitation clinic in Norway used FysBot. This pilot study employed an explanatory sequential mixed-methods design combining questionnaires and post-intervention interviews. Participants completed questionnaires at baseline and weeks 2, 4, and 6, assessing leisure-time physical activity (Godin Leisure-Time Exercise Questionnaire (GODIN)), motivation (Behavioral Regulation in Exercise Questionnaire-2 and relative autonomy index (RAI)), Self-Efficacy for Exercise (SEE), and System Usability Scale (SUS). Semi-structured interviews were conducted to explore user experiences further. Quantitative data were analyzed descriptively, with multiple imputations for missing data, while qualitative data were analyzed thematically. Results Fifty-three participants were eligible, 36 completed baseline, and 17 completed the final follow-up. App engagement declined steadily, with most participants ceasing use after week 2. The mean SUS score was 51.3, indicating below-average usability. The median of self-reported leisure-time physical activity (GODIN: 34–40) and overall motivation (RAI: 8.3–9.8) showed small, non-significant increases, while identified regulation increased significantly (2.8–3.3; p = 0.04) and SEE decreased (58–49). Qualitative findings supported these results, showing that participants valued the chatbot's motivational potential but experienced technical problems and limited personalization. Conclusions This study offers insight into the potential of a ChatGPT-based physical activity app for adults living with obesity and highlights key areas for refinement. Future iterations should incorporate user-requested features through iterative co-design, with enhanced personalization and guidance to improve relevance and engagement.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Larbi et al. (2026) studied this question.

synapsesocial.com/papers/6980fd81c1c9540dea80f3fchttps://doi.org/10.1177/20552076261417860
Ask AI
Helpful
Bookmark
Share
View Full Paper