{"title":"通过关系型人工智能聊天机器人增强身体活动:可行性和可用性研究。","authors":"Yoo Jung Oh, Kai-Hui Liang, Diane Dagyong Kim, Xuanming Zhang, Zhou Yu, Yoshimi Fukuoka, Jingwen Zhang","doi":"10.1177/20552076251324445","DOIUrl":null,"url":null,"abstract":"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Clinical trial registrations: </strong>ClinicalTrials.gov; NCT05794308; https://clinicaltrials.gov/ct2/show/NCT05794308.</p>","PeriodicalId":51333,"journal":{"name":"DIGITAL HEALTH","volume":"11 ","pages":"20552076251324445"},"PeriodicalIF":2.9000,"publicationDate":"2025-03-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11877463/pdf/","citationCount":"0","resultStr":"{\"title\":\"Enhancing physical activity through a relational artificial intelligence chatbot: A feasibility and usability study.\",\"authors\":\"Yoo Jung Oh, Kai-Hui Liang, Diane Dagyong Kim, Xuanming Zhang, Zhou Yu, Yoshimi Fukuoka, Jingwen Zhang\",\"doi\":\"10.1177/20552076251324445\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objective: </strong>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.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Conclusions: </strong>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.</p><p><strong>Clinical trial registrations: </strong>ClinicalTrials.gov; NCT05794308; https://clinicaltrials.gov/ct2/show/NCT05794308.</p>\",\"PeriodicalId\":51333,\"journal\":{\"name\":\"DIGITAL HEALTH\",\"volume\":\"11 \",\"pages\":\"20552076251324445\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2025-03-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11877463/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"DIGITAL HEALTH\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/20552076251324445\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q2\",\"JCRName\":\"HEALTH CARE SCIENCES & SERVICES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"DIGITAL HEALTH","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/20552076251324445","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
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 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.