Abstract
Obesity management demands scalable and personalized approaches. This study evaluates a novel AI-driven framework, NExGEN-ChatGPT, integrating dietary and exercise guidance for obese adults. By analyzing pre-post outcomes and adherence patterns over three months, this research addresses gaps in cost-effective, scalable, and personalized interventions compared to traditional methods. [1,2]. A one-group pre-post pilot design assessed NExGEN-ChatGPT feasibility in weight management. 44 obese adults (BMI: 27.5–32.4 kg·m-2) [3] from Universiti Teknologi MARA, Malaysia, participated. Dietary adherence was tracked via chat-logged food records analyzed with Nutritionist Pro™, while exercise adherence used metabolic equivalents from accelerometers. Eligibility ensured no severe medical conditions or recent weight loss. Adherence data were scored weekly for analysis.
Metadata
Item Type: | Book Section |
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Creators: | Creators Email / ID Num. Reezal, Rose Mylia UNSPECIFIED Mohd Dan, Azwa Suraya UNSPECIFIED Sazali, Razif UNSPECIFIED Md Yusoff, Yusandra UNSPECIFIED Zulqarnain, Muhammad UNSPECIFIED Haziq, Amrun UNSPECIFIED Linoby, Adam UNSPECIFIED |
Subjects: | G Geography. Anthropology. Recreation > GV Recreation. Leisure > Sports |
Divisions: | Universiti Teknologi MARA, Negeri Sembilan > Seremban Campus |
Keywords: | Artificial Intelligence, weight management, dietary adherence, physical activity, obesity intervention |
Date: | February 2025 |
URI: | https://ir.uitm.edu.my/id/eprint/116263 |