دورية أكاديمية

Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study

التفاصيل البيبلوغرافية
العنوان: Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study
المؤلفون: 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
المصدر: Frontiers in Nutrition, Vol 11 (2024)
بيانات النشر: Frontiers Media S.A., 2024.
سنة النشر: 2024
المجموعة: LCC:Nutrition. Foods and food supply
مصطلحات موضوعية: artificial intelligence, obesity, implementation, acceptability, weight management, behavior, Nutrition. Foods and food supply, TX341-641
الوصف: 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.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2296-861X
Relation: https://www.frontiersin.org/articles/10.3389/fnut.2024.1287156/full; https://doaj.org/toc/2296-861X
DOI: 10.3389/fnut.2024.1287156
URL الوصول: https://doaj.org/article/f1560cd2a4d74988b4fec80a8ded60b0
رقم الأكسشن: edsdoj.f1560cd2a4d74988b4fec80a8ded60b0
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:2296861X
DOI:10.3389/fnut.2024.1287156