Actively Recruiting

Phase Not Applicable
Age: 18Years - 60Years
All Genders
ID05866107

Effectiveness and Feasibility of Self-Monitoring for Weight Management in Individuals With Mental Disorders Using Digital Intervention ("SWIM" Trial)

Led by Capital Medical University · Updated on 2025-06-05

204

Participants Needed

1

Research Sites

N/A

Total Duration

On this page

Sponsors

C

Capital Medical University

Lead Sponsor

M

Merck Sharp & Dohme LLC

Collaborating Sponsor

AI-Summary

What this Trial Is About

Researchers are evaluating the use of a digital health app called Huawei Health combined with a smart body fat scale to help overweight patients diagnosed with schizophrenia or bipolar disorder manage their weight. The study focuses on whether longer use of these tools leads to better weight loss and whether regular tracking motivates sustained engagement. The trial aims to improve long-term weight management through this digital and professional support approach. Participants will use the Huawei Health app and Huawei Scale 2pro smart body fat scale for self-monitoring. The intervention is rolled out in two batches: one group starts using the tools from Month 3 to Month 6, and the second group from Month 5 to Month 6. Patients weigh themselves weekly, log their diet at least three times per week, and follow biweekly exercise plans. They also receive weekly motivational messages and support from doctors and nutritionists via WeChat. During the 6-month study, participants undergo baseline observation, training, and intervention phases. Data collected include weight, BMI, body composition, heart rate, and dietary intake. Monthly assessments use validated scales to measure subjective outcomes. Adherence to self-monitoring and protocol compliance are tracked through the app and scale metrics. Researchers also conduct interviews to explore user experiences and assess the feasibility and effectiveness of this combined digital and multidisciplinary intervention.

CONDITIONS

Brief Title

App and Body Fat Scale in the Management of Overweight Patients

Who Can Participate

Age: 18Years - 60Years
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • Age 18-60 years old, no gender restriction
  • Diagnosed with bipolar disorder or schizophrenia per ICD-10 and currently in remission or stable
  • Currently using at least one antipsychotic or mood stabilizer medication
  • Overweight or obese with body mass index of 24 kg/m2 or higher and willing to use health app and smart scale
  • Education level of primary school or above, able to understand scale content and proficient in smartphone use
  • Voluntarily agree to participate and sign informed consent
Not Eligible

You will not qualify if you...

  • Planning to lose weight by other methods during the study (dieting, vomiting, diet pills, surgery)
  • Self-reported weight loss of 7% or more in past 6 months
  • Weight over 150 kg
  • Secondary obesity due to other medical conditions (eg, hypothyroidism, Cushing's syndrome)
  • Currently pregnant, lactating, less than 6 months postpartum, or planning pregnancy during study
  • Self-reported cardiac discomfort or chest pain during activity or rest
  • Serious medical condition posing safety risk for exercise
  • Unable to walk 30 minutes without stopping
  • Conditions affecting protocol compliance (eg, end-stage disease, substance abuse, uncontrolled medical issues)
  • Any other conditions deemed inappropriate by investigator

AI-Screening

AI-Powered Screening

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Your Study Journey

Screening

Duration - 2 to 4 weeks

Participants are screened for eligibility to participate in the trial.

1 visit (in-person)

Baseline Observation

Duration - 2 months

Participants undergo baseline observation using usual care with no intervention to collect initial data on body composition and health status.

Monthly visits for assessments

Pre-implementation Transition

Duration - 2 weeks

Participants receive training on using the mobile app and smart body fat scale, including device distribution and installation.

1 to 2 visits for training and device setup

Intervention Period

Duration - Up to 4 months depending on cluster assignment

Participants use the digital behavioral intervention involving weekly weigh-ins with the smart scale, dietary logging at least three times per week, biweekly exercise plans, and weekly motivational messages.

Monthly visits for clinical, functional, and subjective outcome assessments; weekly remote monitoring through the app

Full-Intervention Observation

Duration - 2 months

All participants receive the digital intervention concurrently across all units, with continued self-monitoring and behavioral reinforcement.

Monthly visits for assessments and ongoing app-based monitoring

Trial Site Locations

Total: 1 location

1

Beijing Anding Hospital

Beijing, Beijing Municipality, China

Actively Recruiting

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Research Team

L

Le Xiao

How is the study designed?

Study Type

INTERVENTIONAL

Masking

NONE

Allocation

RANDOMIZED

Model

SEQUENTIAL

Primary Purpose

TREATMENT

Number of Arms

2

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Published Research Related To This Trial

Antipsychotic-induced weight gain in first-episode psychosis patients: a meta-analysis of differential effects of antipsychotic medications.

Cenk Tek, Suat Kucukgoncu, Sinan Guloksuz...

https://pubmed.ncbi.nlm.nih.gov/25962699

Antipsychotic-associated weight gain: management strategies and impact on treatment adherence.

Madhubhashinee Dayabandara, Raveen Hanwella, Suhashini Ratnatunga...

https://pubmed.ncbi.nlm.nih.gov/28883731

Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity.

Michele L Patel, Lindsay N Wakayama, Gary G Bennett

https://pubmed.ncbi.nlm.nih.gov/33624440

Self-Administered Auricular Acupressure Integrated With a Smartphone App for Weight Reduction: Randomized Feasibility Trial.

Lorna Suen, Wenru Wang, Kenneth King Yip Cheng...

https://pubmed.ncbi.nlm.nih.gov/31144666

Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis.

Gemma Flores Mateo, Esther Granado-Font, Carme Ferré-Grau...

https://pubmed.ncbi.nlm.nih.gov/26554314