App and Body Fat Scale in the Management of Overweight Patients

Официальное название

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

Обзор

This study tests whether using a health app (Huawei Health) and a smart body fat scale can help overweight patients with schizophrenia or bipolar disorder lose weight and stay engaged in their health. What We're Testing: 1. Patients who use the app and scale for 4 months (Group 1) will lose more weight than those who use them for 2 months (Group 2). 2. Patients who track their weight, diet, and exercise regularly (≥3 times/week) will lose more weight than those who don't. 3. Seeing weight loss results may motivate patients to keep using the app and scale. How It Works: Patients weigh themselves weekly with the scale (auto-syncs to the app) and upload dietary log in Huawei Health app. The app will gives personalized diet/exercise tips and tracks progress. Doctors and nutritionists provide extra support through messages. Goal: To see if this digital tool + professional support combo works better for long-term weight management.

Подробное описание

The investigators will recruit the patients diagnosed with schizophrenia or bipolar disorder from Beijing Anding Hospital. Participants will use a mobile phone app (Huawei Health) to collect data on daily activities and calorie consumption. The smart body fat scale with high-precision weighing chip (Huawei Scale 2pro) will be used to collect heart rate, weight, BMI, body type, basal metabolic rate, fat rate, fat free body weight, skeletal muscle mass, bone salt content, visceral fat grade, body water (%), body protein rate and body composition, and all data will be uploaded to the app. Participants could also record their daily dietary intake (for calculation of calorie intake) in the health app. This is a 6-month, single-center, stepped wedge-shaped cluster randomized study. It is planned to recruit 204 overweight subjects from 6 units from Beijing Anding Hospital. The six clinical units comprise four inpatient wards, one day rehabilitation unit, and one outpatient department. All units (clusters) were randomly allocated to two batches (3 units each) using a computer-generated sequence. Batch 1 received the intervention from Month 3 to Month 6, while Batch 2 started from Month 5 to Month 6 (total study duration: 6 months). All units underwent baseline observation during Months 1-2, followed by a 2-week transition period for training. All clusters follow usual care prior to their assigned intervention period, with months 1-2 serving as baseline control and months 7-8 for full-intervention observation across all units. Each unit operates as an independent intervention cluster with dedicated staff teams and unit-specific WeChat-based communication groups. Intervention materials, reinforcement messages, counseling content, and technical support are synchronized with each cluster's assigned timeline. Clinical staff will be trained on intervention delivery, digital tool usage, and adherence protocols and are required to adhere strictly to the scheduled rollout sequence. Monitoring and supervision mechanisms will be implemented to track adherence, engagement, and protocol compliance in real-time. Each cluster undergoes a two-week pre-implementation transition period for device distribution, app installation, and training. The intervention combines self-weighing using using smart body fat scale, dietary logging, exercise management, and behavioral reinforcement. Behavioral reinforcement includes weekly personalized feedback messages and real-time alerts for missed self-monitoring via WeChat messages. We assess clinical, functional, and subjective outcomes at baseline and monthly intervals. Socio-demographic and clinical characteristics (age, sex, education, income, medical history) are extracted from EHRs. Body composition metrics (BMI, body fat percentage, etc.) are automatically recorded during weigh-ins. Subjective outcomes will be collected using validated scales at Month 1,2,3 and 6. Smart scale pairing success rate and weekly weigh-in adherence will be used to assess protocol feasibility. To capture user perspectives on mobile app and weighing smart scale, we will conduct 30-minute semi-structured interviews with 30 purposely selected participants (stratified by adherence and diagnosis), exploring app usability, behavioral impacts, and improvement suggestions.

Вмешательства

• Устройство Effectiveness and Feasibility of Self-Monitoring for Weight Management in Individuals with Mental Disorders Using Digital Intervention ("SWIM" trial)
  Participants receive a digital-behavioral intervention via Huawei Health App and smart scale: 1. Weekly weigh-ins (auto-synced) 2. Dietary logging (≥3x/week) with calorie-deficit targets 3. Biweekly exercise plans (150-300 min/week) 4. Weekly motivational messages Implementation: Staggered rollout: Batch 1 (Month 3-6), Batch 2 (Month 5-6). Includes 2-week training. Effectiveness monitored via app metrics and adherence. Routine care maintained.

Первичные конечные точки

• Percent weight loss [Срок оценки: At the end of Months 1, 2, 3, and 6]
• Adherence to self-monitoring [Срок оценки: At the end of Months 1, 2, 3, and 6]

Вторичные конечные точки (4)

• Longitudinal adherence to self-monitoringcompliance to app + scale protocol and the participants who have bad compliance is compared by percent weight loss. [Срок оценки: At the end of Months 1, 2, 3, and 6]
• Weight loss by adherence level [Срок оценки: At the end of Months 1, 2, 3, and 6]
• Association between adherence and weight loss [Срок оценки: At the end of Months 1, 2, 3, and 6]
• Prediction of future adherence by prior weight loss [Срок оценки: At the end of Months 1, 2, 3, and 6]

Критерии участия

Критерии включения

• Age 18-60 years old, no gender restriction.
• According to ICD-10 to diagnose bipolar disorder or schizophrenia, the researcher judges that the patient is currently in remission, or the condition is stable and can cooperate with the research.
• Currently using at least one antipsychotic or mood stabilizer (e.g. lithium, magnesium valproate, sodium valproate, lamotrigine).
• Currently overweight or obese (body mass index ≥ 24kg/m2) and willing to use health app and smart scales to lose weight.
• The education level of primary school or above, able to understand the content of the scale, and be able to use smart phone proficiently.
• Understand and voluntarily participate in this study, and sign the informed consent form.

Критерии исключения

• Plan to lose weight by other methods during the study period (such as dieting, inducing vomiting, taking diet pills, surgery).
• Self-reported weight loss ≥ 7% in the past 6 months.
• Weight over 150 kg.
• Other secondary obesity (such as hypothyroidism, Cushing's syndrome, hypothalamic obesity, etc.).
• Currently pregnant, lactating, < 6 months postpartum or planning to become pregnant during the study period.
• Self-reported cardiac discomfort or chest pain during activity or at rest.
• There is a serious medical condition, and the researchers believe that there may be safety risks when participating in sports.
• Be unable to walk 30 minutes without stopping.
• There are problems that may affect compliance with the protocol (eg, end-stage disease, planning to move travel to the field, history of substance abuse, other uncontrolled or untreated medical conditions);
• Any other conditions deemed inappropriate by the investigator.

Participants include approximately 50% with schizophrenia and 50% with bipolar disorder, distributed across all clusters.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Распределение

Рандомизированное

Модель

Последовательный дизайн

Маскирование

Открытое

Основная цель

Лечение

Центры проведения

Китай · 1 центр

• Beijing Anding Hospital — Пекин

Публикации

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• Dayabandara M, Hanwella R, Ratnatunga S, Seneviratne S, Suraweera C, de Silva VA. Antipsychotic-associated weight gain: management strategies and impact on treatment adherence. Neuropsychiatr Dis Treat. 2017 Aug 22;13:2231-2241. doi: 10.2147/NDT.S113099. eCollection 2017. PMID 28883731
• Brockmann AN, Eastman A, Ross KM. Frequency and Consistency of Self-Weighing to Promote Weight-Loss Maintenance. Obesity (Silver Spring). 2020 Jul;28(7):1215-1218. doi: 10.1002/oby.22828. Epub 2020 May 21. PMID 32437055
• Patel ML, Wakayama LN, Bennett GG. Self-Monitoring via Digital Health in Weight Loss Interventions: A Systematic Review Among Adults with Overweight or Obesity. Obesity (Silver Spring). 2021 Mar;29(3):478-499. doi: 10.1002/oby.23088. PMID 33624440
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• Flores Mateo G, Granado-Font E, Ferre-Grau C, Montana-Carreras X. Mobile Phone Apps to Promote Weight Loss and Increase Physical Activity: A Systematic Review and Meta-Analysis. J Med Internet Res. 2015 Nov 10;17(11):e253. doi: 10.2196/jmir.4836. PMID 26554314
• Goldstein SP, Goldstein CM, Bond DS, Raynor HA, Wing RR, Thomas JG. Associations between self-monitoring and weight change in behavioral weight loss interventions. Health Psychol. 2019 Dec;38(12):1128-1136. doi: 10.1037/hea0000800. Epub 2019 Sep 26. PMID 31556659

Идентификаторы

NCT: NCT05866107 · MISP#100150

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

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