ArticleJMIR mHealth and uHealth2021
The Relationship Between Weight Loss Outcomes and Engagement in a Mobile Behavioral Change Intervention: Retrospective Analysis.
Article in JMIR mHealth and uHealth, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07560579 (Weight Loss and Endocrine Disrupting Chemicals), which is not on this map. Cited by 19 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Weight Loss and Endocrine Disrupting Chemicals (EDCs): Lifestyle Interventions to Lose Weight and Reduce EDC Exposure in Individuals With Overweight/Obesity
Who cites it
19 citing papers in PubMed, 24 citations in OpenAlex.
- Mobile App Intervention of a Randomized Controlled Trial for Patients With Obesity and Those Who Are Overweight in General Practice: User Engagement Analysis Quantitative Study.JMIR mHealth and uHealth · 2024Trial
- "It's Gonna Be Okay"-A Qualitative Exploration of the COVID-19 Pandemic's Effects on African American Participants During a Dietary Intervention Study.Journal of the Academy of Nutrition and Dietetics · 2023Trial
- Preventing Weight Regain After Glucagon-Like Peptide‑1 Therapy Discontinuation: A Pilot Randomized Controlled Trial.Obesity science & practice · 2026Article
- The effects of a fully subsidized behavioral weight management program among healthcare workers with pre-diabetes and diabetes.BMC public health · 2026Article
- Effectiveness and adherence in a tirzepatide-supported digital weight-loss programme in Australia: A real-world observational study.Diabetes, obesity & metabolism · 2026Observational
- Health care resource utilization and health care costs among digital weight-loss intervention participants and nonparticipants.Obesity (Silver Spring, Md.) · 2025Article
- Interactive Effects of Weight Recording Frequency and the Volume of Chat Communication With Health Care Professionals on Weight Loss in mHealth Interventions for Noncommunicable Diseases: Retrospective Observational Study.Interactive journal of medical research · 2025Article
- 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 Effect of Combining mHealth and Health Professional-Led Intervention for Improving Health-Related Outcomes in Chronic Diseases: Systematic Review and Meta-Analysis.Interactive journal of medical research · 2025Review
- A Mobile-Based Nutrition Tracker App Enhanced Dietitian-Guided 2:1:1 Diet-Induced Weight Loss: An 8-Week Retrospective Cohort Study in Taiwan.Nutrients · 2024Article
- [Process evaluation of a mobile healthcare program among employees with overweight and obesity: a 12-week intervention study investigating the role of engagement].Korean journal of community nutrition · 2023Article
- An Explainable Artificial Intelligence Software Tool for Weight Management Experts (PRIMO): Mixed Methods Study.Journal of medical Internet research · 2023Article
- The Impact of a Digital Weight Loss Intervention on Health Care Resource Utilization and Costs Compared Between Users and Nonusers With Overweight and Obesity: Retrospective Analysis Study.JMIR mHealth and uHealth · 2023Article
- Exploring Hearing Care Technology from Clinic to Capability.Seminars in hearing · 2023Review
- The Association Between Goal Setting and Weight Loss: Prospective Analysis of a Community Weight Loss Program.Journal of medical Internet research · 2023Article
- Effectiveness of a mobile health intervention on weight loss and dietary behavior changes among employees with overweight and obesity: a 12-week intervention study investigating the role of engagement.Korean journal of community nutrition · 2023Article
- Changes in Health-Promoting Behaviors and Their Association with Weight Loss, Retention, and Engagement on a Digital Program: Prospective Study.Nutrients · 2022Article
- Body Positivity and Self-Compassion on a Publicly Available Behavior Change Weight Management Program.International journal of environmental research and public health · 2021Article
- Use of mHealth interventions to enhance self-regulation and self-efficacy in individuals living with obesity: Scoping review.Digital healthReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is large variance in weight loss outcomes of digital behavior change interventions (DBCIs). It has been suggested that different patterns of engagement in the program could be responsible for this variance in outcomes. Previous studies have found that the amount of engagement on DBCIs, such as the number of meals logged or articles read, is positively associated with weight loss.
objectiveThis retrospective study extends previous research by observing how important weight loss outcomes (high weight loss: 10% or greater body weight loss; moderate weight loss: between 5% to 10%; stable weight: 0 plus or minus 1%) are associated with engagement on a publicly available mobile DBCI (Noom) from 9 to 52 weeks.
methodsEngagement and weight data for eligible participants (N=11,252) were extracted from the Noom database. Engagement measures included the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week. Weight was self-reported on the program. Multiple linear regressions examined how weight loss outcome (moderate and high vs stable) was associated with each engagement measure across 3 study time periods: 9-16 weeks, 17-32 weeks, and 33-52 weeks.
resultsAt 9-16 weeks, among the 11,252 participants, 2594 (23.05%) had stable weight, 6440 (57.23%) had moderate weight loss, and 2218 (19.71%) had high weight loss. By 33-52 weeks, 525 (18.21%) had stable weight, 1214 (42.11%) had moderate weight loss, and 1144 (39.68%) had high weight loss. Regression results showed that moderate weight loss and high weight loss outcomes were associated with all engagement measures to a significantly greater degree than was stable weight (all P values <.001). These differences held across all time periods with the exception of exercise for the moderate weight loss category at 1 time period of 33-52 weeks. Exercise logging increased from 9 to 52 weeks regardless of the weight loss group.
conclusionsOur results suggest that these clinically important weight loss outcomes are related to the number of articles read, meals logged, steps recorded, messages to coach, exercise logged, weigh-ins, and days with 1 meal logged per week both in the short-term and long-term (ie, 1 year) on Noom. This provides valuable data on engagement patterns over time on a self-directed mobile DBCI, can help inform how interventions tailor recommendations for engagement depending on how much weight individuals have lost, and raises important questions for future research on engagement in DBCIs.
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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.