Research on the Needs, Feasibility, and Intervention Effects of AI Health Coach-based Just-in-Time Adaptive Intervention (JITAI) in Weight Management for Overweight/Obese Adults

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.

Study Overview

• Status: Completed
• Conditions: Overweight , Obesity
• Intervention / Treatment: Behavioral: AI Health Coach-based Just-in-Time Adaptive Intervention

Detailed Description

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.

• Study Type: Interventional
• Enrollment (Actual): 31
• Phase: Not Applicable

Contacts and Locations

Study Locations

• China
  • Zhejiang
    • Yiwu, Zhejiang, China, 322000
      • 4th Affiliated Hospital, School of Medicine, Zhejiang University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult
• Accepts Healthy Volunteers: No

Description

Inclusion Criteria:

• Aged 18 to 60 years.
• Body mass index of 24 kg/m2 or higher, meeting the Chinese criteria for overweight or obesity.
• Able to use a smartphone, WeChat-based platform, and wearable device during the study period.
• Willing to participate in the AI health coach-based just-in-time adaptive intervention and complete study assessments.
• Provided written informed consent.

Exclusion Criteria:

• Pregnancy, lactation, or planning pregnancy during the study period.
• Severe cardiovascular, cerebrovascular, hepatic, renal, endocrine, psychiatric, or other major diseases that may affect study participation or safety.
• Medical conditions or medications that may substantially affect body weight or body composition.
• Contraindications to physical activity or inability to complete the intervention procedures.
• Current participation in another weight-management intervention or clinical study.
• Inability to understand the study procedures or complete the required assessments.

Study Plan

How is the study designed?

Design Details

• Primary Purpose: Treatment
• Allocation: N/A
• Interventional Model: Single Group Assignment
• Masking: None (Open Label)

Number of Arms

1

Arms and Interventions

Participant Group / Arm

Intervention / Treatment

Experimental: AI Health Coach-based JITAI; 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.

Behavioral: AI Health Coach-based Just-in-Time Adaptive Intervention; 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.; Other Names: JITAI

What is the study measuring?

Primary Outcome Measures

Outcome Measure	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

Secondary Outcome Measures

Outcome Measure	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	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

Collaborators and Investigators

• Sponsor: The Fourth Affiliated Hospital of Zhejiang University School of Medicine
• Investigators: Principal Investigator: Jie Yu, Master, 4th Affiliated Hospital, School of Medicine, Zhejiang University, China

Study record dates

Study Major Dates

• Study Start (Actual): March 1, 2026
• Primary Completion (Actual): May 15, 2026
• Study Completion (Actual): May 15, 2026

Study Registration Dates

• First Submitted: June 28, 2026
• First Submitted That Met QC Criteria: June 28, 2026
• First Posted (Actual): July 6, 2026

Study Record Updates

• Last Update Posted (Actual): July 6, 2026
• Last Update Submitted That Met QC Criteria: June 28, 2026
• Last Verified: June 1, 2026

More Information

Terms related to this study

• Keywords: Artificial Intelligence; Weight Management; Health Behavior Change; Just-in-Time Adaptive Intervention
• Additional Relevant MeSH Terms: Nutrition Disorders; Overnutrition; Body Weight; Pathological Conditions, Signs and Symptoms; Nutritional and Metabolic Diseases; Signs and Symptoms; Overweight; Obesity
• Other Study ID Numbers: KY-2025-344; ChiCTR2600118808 (Registry Identifier: Chinese Clinical Trial Registry)

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: NO
• IPD Plan Description: 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.

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No