Currently submitted to: Journal of Medical Internet Research
Date Submitted: Jan 16, 2026
Open Peer Review Period: Jan 18, 2026 - Mar 15, 2026
(currently open for review)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
AI-Powered Health Chatbot and Plate Recognition: Impact on Weight Loss and Health Literacy in Adults with Overweight
ABSTRACT
Background:
Obesity remains a pressing global health issue. Research suggests that better health literacy can support obesity management. This study tested digital interventions combining healthy eating guidelines with AI and mobile tools, including a ChatGPT-powered Line chatbot for daily education and an AI food plate recognition system for calorie tracking and meal suggestions.
Objective:
This study aims to evaluate the efficacy of an integrated digital intervention, combining YOLOv5-based AI food plate recognition and a ChatGPT-powered LINE chatbot, on weight reduction (BMI) and health literacy among overweight and obese adults.
Methods:
The study used a quasi-experimental design-intervention case-control design. Both the case and intervention groups received basic health education through app notifications and used an AI food plate recognition tool to estimate their nutritional intake. Only the intervention group could access an AI weight-loss chatbot for timely suggestions. Questionnaire data were collected from users at several points during the intervention.
Results:
Eighty participants were enrolled. The intervention group demonstrated significantly greater reductions in BMI (β = −1.32; 95% CI, −1.56 to −1.09; P < .001) and improvements in health literacy (β = 4.71; 95% CI, 3.86 to 5.56; P < .001) versus controls. Physical activity (step count β = 1,926.5; 95% CI, 1,209.3 to 2,643.7; P < .001) and weekly exercise time (β = 0.56; 95% CI, 0.21 to 0.92; P = .002) also increased, while late-night snacking decreased (β = −0.45; 95% CI, −0.81 to −0.08; P = .017). The intervention group consistently outperformed the control group across key health measures. However, the AI chatbot alone lacked significant effects on primary outcomes.
Conclusions:
This integrated digital intervention effectively promotes weight loss and health literacy. Given the strong short-term efficacy, future research should employ randomized designs, larger sample sizes, and longer follow-ups to establish long-term weight maintenance and address potential influences such as the Hawthorne effect. It also highlights the need to further develop interactive, personalized health education tools and optimize AI food plate recognition systems to improve health literacy and weight management.
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