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| ID | Type | Description | Link |
|---|---|---|---|
| ChiCTR2600118808 | Registry Identifier | Chinese Clinical Trial Registry |
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This pilot study evaluates the needs, feasibility, and preliminary effects of an artificial intelligence (AI) health coach-based just-in-time adaptive intervention for weight management in adults with overweight or obesity.
Participants receive a wearable device and use a WeChat-based platform during the intervention period. The system collects wearable data and self-reported information, and provides timely behavior-change support related to physical activity, sedentary behavior, sleep, diet self-monitoring, and weight-management self-regulation. The AI health coach provides conversational support and personalized suggestions based on predefined intervention rules and participant inputs.
The main purpose of this study is to assess whether this AI-supported intervention is feasible and acceptable for adults with overweight or obesity. The study also explores changes in weight-related outcomes, health behaviors, self-efficacy, sleep, and quality of life before and after the intervention.
Overweight and obesity are common chronic health problems that require sustained support for daily behavior change. Digital health interventions may help extend weight-management support into everyday life, but many existing programs rely on generic education, retrospective feedback, or burdensome manual self-monitoring. This study evaluates an AI health coach-based just-in-time adaptive intervention designed to provide timely and individualized support for weight-management behaviors.
This is a single-arm pilot study conducted among adults with overweight or obesity. Participants use a wearable device and a WeChat-based intervention platform during the study period. The intervention combines passive wearable sensing, participant-reported dietary self-monitoring, rule-based just-in-time intervention triggers, and an AI conversational health coach. Intervention content focuses on physical activity, sedentary behavior, sleep-related routines, dietary self-monitoring, and self-regulation for weight management.
The AI health coach provides conversational guidance, encouragement, and behavior-change suggestions. Intervention messages are generated or selected based on participant data and predefined rules, with the goal of delivering support at moments when participants may benefit from timely prompts or feedback.
The study evaluates feasibility and acceptability indicators, including wearable use, participant engagement, dietary self-monitoring, and interaction with the AI health coach. Preliminary intervention effects are explored by comparing baseline and post-intervention measures, including weight-related outcomes, body composition, physical activity, sleep, eating-related self-efficacy, and quality of life. The findings will inform the refinement of AI-supported just-in-time adaptive interventions for future controlled trials in weight management.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| AI Health Coach-based JITAI | Experimental | Participants received an AI health coach-based just-in-time adaptive intervention for weight management. The intervention was delivered through a WeChat-based platform and supported by wearable device data and participant-reported dietary self-monitoring. |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| AI Health Coach-based Just-in-Time Adaptive Intervention | Behavioral | The intervention provided timely behavior-change support for weight management through an AI health coach delivered via a WeChat-based platform. The system used wearable device data and participant inputs to support physical activity, sedentary behavior reduction, sleep-related routines, dietary self-monitoring, and self-regulation. Participants received conversational guidance, encouragement, and personalized suggestions based on predefined intervention rules and participant data. |
| Measure | Description | Time Frame |
|---|---|---|
| Participant retention rate | Retention rate was defined as the proportion of enrolled participants who completed the post-intervention assessment. | From enrollment to post-intervention assessment, approximately 31 days |
| Valid wearable use rate | Valid wearable use rate was defined as the proportion of intervention days with valid wearable data. A valid wearable day was defined as a day with at least 10 hours of wear time or at least 180 minutes of main sleep data. | During the 31-day intervention period |
| Active engagement rate | Active engagement rate was defined as the proportion of intervention days on which participants had at least one interaction with the AI health coach or at least one dietary self-monitoring record. | During the 31-day intervention period |
| Acceptability of the AI health coach-based intervention | Acceptability was assessed using a post-intervention questionnaire evaluating participants' perceived usefulness, satisfaction, and willingness to continue using the AI health coach-based intervention. Higher scores indicate greater acceptability. | Post-intervention assessment, approximately 31 days |
| Measure | Description | Time Frame |
|---|---|---|
| Change in body weight | Body weight was measured at baseline and post-intervention. The outcome was the change in body weight from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| Change in body mass index |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Affiliation | Role |
|---|---|---|
| Jie Yu, Master | 4th Affiliated Hospital, School of Medicine, Zhejiang University, China | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| 4th Affiliated Hospital, School of Medicine, Zhejiang University | Yiwu | Zhejiang | 322000 | China |
The datasets generated and analyzed during the current study are not publicly available because they contain potentially identifiable participant-level behavioral, wearable, and interaction data, but deidentified data may be available from the corresponding author upon reasonable request and with appropriate ethical approval.
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Single-arm pilot study in which all participants received an AI health coach-based just-in-time adaptive intervention for weight management.
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Body mass index was calculated from measured body weight and height. The outcome was the change in body mass index from baseline to post-intervention. |
| Baseline and post-intervention assessment, approximately 31 days |
| Change in body fat percentage | Body fat percentage was measured at baseline and post-intervention. The outcome was the change in body fat percentage from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| Change in waist circumference | Waist circumference was measured at baseline and post-intervention. The outcome was the change in waist circumference from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| Change in visceral fat level | Visceral fat level was measured at baseline and post-intervention. The outcome was the change in visceral fat level from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| Change in physical activity | Physical activity was assessed using the International Physical Activity Questionnaire-Short Form. The outcome was the change in physical activity from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| Change in sleep quality | Sleep quality was assessed using the Chinese version of the Pittsburgh Sleep Quality Index. The outcome was the change in sleep quality score from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| Change in eating self-efficacy | Eating self-efficacy was assessed using the Chinese version of the Weight Efficacy Lifestyle Questionnaire-Short Form. The outcome was the change in eating self-efficacy score from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| Change in health-related quality of life | Health-related quality of life was assessed using the EQ-5D-5L. The outcome was the change in health-related quality of life from baseline to post-intervention. | Baseline and post-intervention assessment, approximately 31 days |
| ID | Term |
|---|---|
| D050177 | Overweight |
| D009765 | Obesity |
| ID | Term |
|---|---|
| D044343 | Overnutrition |
| D009748 | Nutrition Disorders |
| D009750 | Nutritional and Metabolic Diseases |
| D001835 | Body Weight |
| D012816 | Signs and Symptoms |
| D013568 | Pathological Conditions, Signs and Symptoms |
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