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Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study
被引:0
|作者:
Chew, Han Shi Jocelyn
[1
]
Achananuparp, Palakorn
[2
]
Dalakoti, Mayank
[3
]
Chew, Nicholas W. S.
[3
]
Chin, Yip Han
[4
]
Gao, Yujia
[5
]
So, Bok Yan Jimmy
[6
]
Shabbir, Asim
[6
]
Peng, Lim Ee
[2
]
Ngiam, Kee Yuan
[6
]
机构:
[1] Natl Univ Singapore, Alice Lee Ctr Nursing Studies, Yong Loo Lin Sch Med, Singapore, Singapore
[2] Singapore Management Univ, Sch Comp & Informat Syst, Singapore, Singapore
[3] Natl Univ Heart Ctr, Dept Cardiol, Singapore, Singapore
[4] Natl Univ Singapore, Yong Loo Lin Sch Med, Singapore, Singapore
[5] Natl Univ Singapore Hosp, Dept Surg, Div Hepatobiliary & Pancreat Surg, Singapore, Singapore
[6] Natl Univ Singapore Hosp, Dept Surg, Div Gen Surg Upper Gastrointestinal Surg, Singapore, Singapore
来源:
FRONTIERS IN NUTRITION
|
2024年
/
11卷
关键词:
artificial intelligence;
obesity;
implementation;
acceptability;
weight management;
behavior;
UTAUT;
perception;
FIT INDEXES;
INTERVENTIONS;
ADHERENCE;
HEALTH;
D O I:
10.3389/fnut.2024.1287156
中图分类号:
R15 [营养卫生、食品卫生];
TS201 [基础科学];
学科分类号:
100403 ;
摘要:
Introduction With 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.Methods 280 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.Results 271 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.Conclusion UTAUT2 model is recommended to guide the development of AI-assisted weight management apps among people with overweight and obesity.
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页数:9
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