Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study

Objective This study presents a pilot randomized controlled trial to assess the usability, feasibility, and initial efficacy of a mobile app-based relational artificial intelligence (AI) chatbot (Exerbot) intervention for increasing physical activity behavior. Methods The study was conducted over a...

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Main Authors: Yoo Jung Oh, Kai-Hui Liang, Diane Dagyong Kim, Xuanming Zhang, Zhou Yu, Yoshimi Fukuoka, Jingwen Zhang
Format: Article
Language:English
Published: SAGE Publishing 2025-03-01
Series:Digital Health
Online Access:https://doi.org/10.1177/20552076251324445
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author Yoo Jung Oh
Kai-Hui Liang
Diane Dagyong Kim
Xuanming Zhang
Zhou Yu
Yoshimi Fukuoka
Jingwen Zhang
author_facet Yoo Jung Oh
Kai-Hui Liang
Diane Dagyong Kim
Xuanming Zhang
Zhou Yu
Yoshimi Fukuoka
Jingwen Zhang
author_sort Yoo Jung Oh
collection DOAJ
description Objective This study presents a pilot randomized controlled trial to assess the usability, feasibility, and initial efficacy of a mobile app-based relational artificial intelligence (AI) chatbot (Exerbot) intervention for increasing physical activity behavior. Methods The study was conducted over a 1-week period, during which participants were randomized to either converse with a baseline chatbot without relational capacity (control group) or a relational chatbot using social relational communication strategies. Objectively measured physical activity data were collected using smartphone pedometers. Results The study was feasible in enrolling a sample of 36 participants and with a 94% retention rate after 1 week. Daily engagement rate with the AI chatbot reached over 88% across the groups. Findings revealed that the control group experienced a significant decrease in steps on the final day, whereas the group interacting with the relational chatbot maintained their step counts throughout the study period. Importantly, individuals who engaged with the relational chatbot reported a stronger social bond with the chatbot compared to those in the control group. Conclusions Leveraging AI chatbot and the relationship-building capabilities of AI holds promise in the development of cost-effective, accessible, and sustainable behavior change interventions. This approach may benefit individuals with limited access to conventional in-person behavior interventions. Clinical trial registrations ClinicalTrials.gov; NCT05794308; https://clinicaltrials.gov/ct2/show/NCT05794308 .
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spelling doaj-art-191173419d4e4cd3941b1a8a99111e732025-08-20T03:15:56ZengSAGE PublishingDigital Health2055-20762025-03-011110.1177/20552076251324445Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability studyYoo Jung Oh0Kai-Hui Liang1Diane Dagyong Kim2Xuanming Zhang3Zhou Yu4Yoshimi Fukuoka5Jingwen Zhang6 Department of Communication, , East Lansing, Michigan, USA Department of Computer Science, , New York, USA Department of Communication, , California, USA Department of Computer Science, , New York, USA Department of Computer Science, , New York, USA Department of Physiological Nursing, , California, USA Department of Communication, , California, USAObjective This study presents a pilot randomized controlled trial to assess the usability, feasibility, and initial efficacy of a mobile app-based relational artificial intelligence (AI) chatbot (Exerbot) intervention for increasing physical activity behavior. Methods The study was conducted over a 1-week period, during which participants were randomized to either converse with a baseline chatbot without relational capacity (control group) or a relational chatbot using social relational communication strategies. Objectively measured physical activity data were collected using smartphone pedometers. Results The study was feasible in enrolling a sample of 36 participants and with a 94% retention rate after 1 week. Daily engagement rate with the AI chatbot reached over 88% across the groups. Findings revealed that the control group experienced a significant decrease in steps on the final day, whereas the group interacting with the relational chatbot maintained their step counts throughout the study period. Importantly, individuals who engaged with the relational chatbot reported a stronger social bond with the chatbot compared to those in the control group. Conclusions Leveraging AI chatbot and the relationship-building capabilities of AI holds promise in the development of cost-effective, accessible, and sustainable behavior change interventions. This approach may benefit individuals with limited access to conventional in-person behavior interventions. Clinical trial registrations ClinicalTrials.gov; NCT05794308; https://clinicaltrials.gov/ct2/show/NCT05794308 .https://doi.org/10.1177/20552076251324445
spellingShingle Yoo Jung Oh
Kai-Hui Liang
Diane Dagyong Kim
Xuanming Zhang
Zhou Yu
Yoshimi Fukuoka
Jingwen Zhang
Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study
Digital Health
title Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study
title_full Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study
title_fullStr Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study
title_full_unstemmed Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study
title_short Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study
title_sort enhancing physical activity through a relational artificial intelligence chatbot a feasibility and usability study
url https://doi.org/10.1177/20552076251324445
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