ArticleJournal of medical Internet research2017
What Matters in Weight Loss? An In-Depth Analysis of Self-Monitoring.
Article in Journal of medical Internet research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
51 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Efficacy of acupuncture and moxibustion therapy for simple obesity in adults: A meta-analysis of randomized controlled trials.Medicine · 2022Pooled it
- Self-Monitoring of Weight Loss Over Time: Secondary Data Analysis of a Randomized Controlled Trial.JMIR mHealth and uHealth · 2026Trial
- Adherence to self-monitoring and behavioral goals is associated with improved weight loss in an mHealth randomized-controlled trial.Obesity (Silver Spring, Md.) · 2025Trial
- Efficacy of providing energy expenditure information to guide weight loss interventions in people with obesity: A randomized controlled trial.Clinical obesity · 2025Trial
- Trial
- The effect of the Smart Health Continuous Feedback For Elderly Exercise (SHe CoFFEE) program on mobility: a randomized controlled pilot study.Frontiers in public health · 2024Trial
- The Effect of a mHealth App (KENPO-app) for Specific Health Guidance on Weight Changes in Adults With Obesity and Hypertension: Pilot Randomized Controlled Trial.JMIR mHealth and uHealth · 2023Trial
- Effects of a 4-month active weight loss phase followed by weight loss maintenance on adaptive thermogenesis in resting energy expenditure in former elite athletes.European journal of nutrition · 2022Trial
- Long-term Effectiveness of a Smartphone App Combined With a Smart Band on Weight Loss, Physical Activity, and Caloric Intake in a Population With Overweight and Obesity (Evident 3 Study): Randomized Controlled Trial.Journal of medical Internet research · 2022Trial
- Trial
- A Mobile Phone App Designed to Support Weight Loss Maintenance and Well-Being (MotiMate): Randomized Controlled Trial.JMIR mHealth and uHealth · 2019Trial
- Association of plasma growth differentiation factor-15 with the frailty phenotype - Evidence from the COGFRAIL study.The Journal of frailty & aging · 2026Article
- Do routinized eating behaviors support weight loss? An examination of food logs from behavioral weight loss participants.Health psychology : official journal of the Division of Health Psychology, American Psychological Association · 2026Article
- One-Year Trajectory of Step Counts and Weight Loss in Adults With Overweight/Obesity: Retrospective Cohort Study.JMIR mHealth and uHealth · 2026Article
- Article
- Long-Term Weight Loss Outcomes in a Virtual Weight Care Clinic Prescribing a Broad Range of Medications Alongside Behavior Change.Obesity science & practice · 2025Article
- The Mobile lifestyle intervention for food and exercise (mLife) study: Protocol of a remote behavioral weight loss randomized clinical trial for type 2 diabetes prevention.Contemporary clinical trials · 2025Article
- Feasibility of the flipped classroom approach for health education in a clinical weight loss program.PEC innovation · 2024Article
- A Novel Web App for Dietary Weight Management: Development, Implementation, and Usability Study.JMIR formative research · 2024Article
- App Engagement as a Predictor of Weight Loss in Blended-Care Interventions: Retrospective Observational Study Using Large-Scale Real-World Data.Journal of medical Internet research · 2024Observational
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundUsing technology to self-monitor body weight, dietary intake, and physical activity is a common practice used by consumers and health companies to increase awareness of current and desired behaviors in weight loss. Understanding how to best use the information gathered by these relatively new methods needs to be further explored.
objectiveThe purpose of this study was to analyze the contribution of self-monitoring to weight loss in participants in a 6-month commercial weight-loss intervention administered by Retrofit and to specifically identify the significant contributors to weight loss that are associated with behavior and outcomes.
methodsA retrospective analysis was performed using 2113 participants enrolled from 2011 to 2015 in a Retrofit weight-loss program. Participants were males and females aged 18 years or older with a starting body mass index of ≥25 kg/m2, who also provided a weight measurement at the sixth month of the program. Multiple regression analysis was performed using all measures of self-monitoring behaviors involving weight measurements, dietary intake, and physical activity to predict weight loss at 6 months. Each significant predictor was analyzed in depth to reveal the impact on outcome.
resultsParticipants in the Retrofit Program lost a mean -5.58% (SE 0.12) of their baseline weight with 51.87% (1096/2113) of participants losing at least 5% of their baseline weight. Multiple regression model (R
conclusionsThe self-monitoring behaviors of self-weigh-in, daily steps, high-intensity activity, and persistent food logging were significant predictors of weight loss during a 6-month intervention.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.