Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study
IntroductionWith in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity.Methods280 participants were recruited between May and Novemb...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2024-02-01
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| Series: | Frontiers in Nutrition |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnut.2024.1287156/full |
| _version_ | 1797322458378797056 |
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| author | Han Shi Jocelyn Chew Palakorn Achananuparp Mayank Dalakoti Nicholas W. S. Chew Yip Han Chin Yujia Gao Bok Yan Jimmy So Asim Shabbir Lim Ee Peng Kee Yuan Ngiam |
| author_facet | Han Shi Jocelyn Chew Palakorn Achananuparp Mayank Dalakoti Nicholas W. S. Chew Yip Han Chin Yujia Gao Bok Yan Jimmy So Asim Shabbir Lim Ee Peng Kee Yuan Ngiam |
| author_sort | Han Shi Jocelyn Chew |
| collection | DOAJ |
| description | IntroductionWith in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity.Methods280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression.Results271 participant responses were analyzed, representing participants with a mean age of 31.56 ± 10.75 years, median (interquartile range) BMI, and waist circumference of 27.2 kg/m2 (24.2–28.4 kg/m2) and 86.4 (80.0–94.0) cm, respectively. In total, 188 (69.4%) participants intended to use AI-assisted weight loss apps. UTAUT2 explained 63.3% of the variance in our intention of the sample to use AI-assisted weight management apps with satisfactory model fit: CMIN/df = 1.932, GFI = 0.966, AGFI = 0.954, NFI = 0.909, CFI = 0.954, RMSEA = 0.059, SRMR = 0.050. Only performance expectancy, hedonic motivation, and the habit of using AI-assisted apps were significant predictors of intention. Comparison with existing literature revealed vast variabilities in the determinants of AI- and non-AI weight loss app acceptability in adults with and without overweight and obesity. UTAUT2 produced a good fit in explaining the acceptability of AI-assisted apps among a multi-ethnic, developed, southeast Asian sample with overweight and obesity.ConclusionUTAUT2 model is recommended to guide the development of AI-assisted weight management apps among people with overweight and obesity. |
| first_indexed | 2024-03-08T05:13:41Z |
| format | Article |
| id | doaj.art-f1560cd2a4d74988b4fec80a8ded60b0 |
| institution | Directory Open Access Journal |
| issn | 2296-861X |
| language | English |
| last_indexed | 2024-03-08T05:13:41Z |
| publishDate | 2024-02-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Nutrition |
| spelling | doaj.art-f1560cd2a4d74988b4fec80a8ded60b02024-02-07T05:04:37ZengFrontiers Media S.A.Frontiers in Nutrition2296-861X2024-02-011110.3389/fnut.2024.12871561287156Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional studyHan Shi Jocelyn Chew0Palakorn Achananuparp1Mayank Dalakoti2Nicholas W. S. Chew3Yip Han Chin4Yujia Gao5Bok Yan Jimmy So6Asim Shabbir7Lim Ee Peng8Kee Yuan Ngiam9Alice Lee Centre for Nursing Studies, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, SingaporeSchool of Computing and Information Systems, Singapore Management University, Singapore, SingaporeDepartment of Cardiology, National University Heart Centre, Singapore, SingaporeDepartment of Cardiology, National University Heart Centre, Singapore, SingaporeYong Loo Lin School of Medicine, National University of Singapore, Singapore, SingaporeDivision of Hepatobiliary and Pancreatic Surgery, Department of Surgery, National University Hospital, Singapore, SingaporeDivision of General Surgery (Upper Gastrointestinal Surgery), Department of Surgery, National University Hospital, Singapore, SingaporeDivision of General Surgery (Upper Gastrointestinal Surgery), Department of Surgery, National University Hospital, Singapore, SingaporeSchool of Computing and Information Systems, Singapore Management University, Singapore, SingaporeDivision of General Surgery (Upper Gastrointestinal Surgery), Department of Surgery, National University Hospital, Singapore, SingaporeIntroductionWith in increase in interest to incorporate artificial intelligence (AI) into weight management programs, we aimed to examine user perceptions of AI-based mobile apps for weight management in adults with overweight and obesity.Methods280 participants were recruited between May and November 2022. Participants completed a questionnaire on sociodemographic profiles, Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), and Self-Regulation of Eating Behavior Questionnaire. Structural equation modeling was performed using R. Model fit was tested using maximum-likelihood generalized unweighted least squares. Associations between influencing factors were analyzed using correlation and linear regression.Results271 participant responses were analyzed, representing participants with a mean age of 31.56 ± 10.75 years, median (interquartile range) BMI, and waist circumference of 27.2 kg/m2 (24.2–28.4 kg/m2) and 86.4 (80.0–94.0) cm, respectively. In total, 188 (69.4%) participants intended to use AI-assisted weight loss apps. UTAUT2 explained 63.3% of the variance in our intention of the sample to use AI-assisted weight management apps with satisfactory model fit: CMIN/df = 1.932, GFI = 0.966, AGFI = 0.954, NFI = 0.909, CFI = 0.954, RMSEA = 0.059, SRMR = 0.050. Only performance expectancy, hedonic motivation, and the habit of using AI-assisted apps were significant predictors of intention. Comparison with existing literature revealed vast variabilities in the determinants of AI- and non-AI weight loss app acceptability in adults with and without overweight and obesity. UTAUT2 produced a good fit in explaining the acceptability of AI-assisted apps among a multi-ethnic, developed, southeast Asian sample with overweight and obesity.ConclusionUTAUT2 model is recommended to guide the development of AI-assisted weight management apps among people with overweight and obesity.https://www.frontiersin.org/articles/10.3389/fnut.2024.1287156/fullartificial intelligenceobesityimplementationacceptabilityweight managementbehavior |
| spellingShingle | Han Shi Jocelyn Chew Palakorn Achananuparp Mayank Dalakoti Nicholas W. S. Chew Yip Han Chin Yujia Gao Bok Yan Jimmy So Asim Shabbir Lim Ee Peng Kee Yuan Ngiam Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study Frontiers in Nutrition artificial intelligence obesity implementation acceptability weight management behavior |
| title | Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study |
| title_full | Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study |
| title_fullStr | Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study |
| title_full_unstemmed | Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study |
| title_short | Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study |
| title_sort | public acceptance of using artificial intelligence assisted weight management apps in high income southeast asian adults with overweight and obesity a cross sectional study |
| topic | artificial intelligence obesity implementation acceptability weight management behavior |
| url | https://www.frontiersin.org/articles/10.3389/fnut.2024.1287156/full |
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