ArticleJMIR mHealth and uHealth2018
Using the Habit App for Weight Loss Problem Solving: Development and Feasibility Study.
Article in JMIR mHealth and uHealth, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02192905 (Feasibility Trial of a Problem-Solving Weight Loss Mobile Application), which is not on this map. Cited by 21 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.
Feasibility Trial of a Problem-Solving Weight Loss Mobile Application
Who cites it
21 citing papers in PubMed, 40 citations in OpenAlex.
- Predicting Long-Term Engagement in mHealth Apps: Comparative Study of Engagement Indices.Journal of medical Internet research · 2024Trial
- Adherence to Behavioral Weight Management: A Scoping Review of Definitions, Measurement, and Components.Obesity reviews : an official journal of the International Association for the Study of Obesity · 2026Article
- Development of a Digital Parent Intervention to Promote Healthy Eating and Activity in Preschoolers: The eHEROs Study.Journal of nutrition education and behavior · 2025Article
- Comparing Synchronous and Asynchronous Remotely Delivered Lifestyle Interventions: Protocol for a Randomized Noninferiority Trial.JMIR research protocols · 2024Article
- A Structured Social Media Health Support Program after Bariatric Surgery.Applied clinical informatics · 2024Observational
- Digital Dietary Behaviors in Individuals With Depression: Real-World Behavioral Observation.JMIR public health and surveillance · 2024Article
- Consolidated guidance for behavioral intervention pilot and feasibility studies.Pilot and feasibility studies · 2024Article
- Acceptability of a Self-Guided Lifestyle Intervention Among Young Men: Mixed Methods Analysis of Pilot Findings.JMIR formative research · 2024Article
- Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study.Frontiers in nutrition · 2024Article
- Expert Perspectives on Pilot and Feasibility Studies: A Delphi Study and Consolidation of Considerations for Behavioral Interventions.Research square · 2023Article
- Effects of User-Reported Risk Factors and Follow-Up Care Activities on Satisfaction With a COVID-19 Chatbot: Cross-Sectional Study.JMIR mHealth and uHealth · 2023Article
- A 2.5-Year Weight Management Program Using Noom Health: Protocol for a Randomized Controlled Trial.JMIR research protocols · 2022Article
- Challenges in Participant Engagement and Retention Using Mobile Health Apps: Literature Review.Journal of medical Internet research · 2022Review
- Metabolic Surgery Supporting Aftercare via Group-Intervention (MeSSAGES): study protocol of a randomised controlled trial.BMJ open · 2021Article
- Applying Mobile Technology to Sustain Physical Activity After Completion of Cardiac Rehabilitation: Acceptability Study.JMIR human factors · 2021Article
- Problem-solving, Adherence to Lifestyle Goals, and Weight Loss Among Individuals Participating in a Weight Loss Study.International journal of behavioral medicine · 2021Article
- Applying Digital Information Delivery to Convert Habits of Antibiotic Use in Primary Care in Germany: Mixed-Methods Study.Journal of medical Internet research · 2020Article
- Persuasive System Design Principles and Behavior Change Techniques to Stimulate Motivation and Adherence in Electronic Health Interventions to Support Weight Loss Maintenance: Scoping Review.Journal of medical Internet research · 2019Article
- Development of the Top Tips Habit-Based Weight Loss App and Preliminary Indications of Its Usage, Effectiveness, and Acceptability: Mixed-Methods Pilot Study.JMIR mHealth and uHealth · 2019Article
- The history and future of digital health in the field of behavioral medicine.Journal of behavioral medicine · 2019Article
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 3 institutions in 1 country.
Funding
Abstract
backgroundReviews of weight loss mobile apps have revealed they include very few evidence-based features, relying mostly on self-monitoring. Unfortunately, adherence to self-monitoring is often low, especially among patients with motivational challenges. One behavioral strategy that is leveraged in virtually every visit of behavioral weight loss interventions and is specifically used to deal with adherence and motivational issues is problem solving. Problem solving has been successfully implemented in depression mobile apps, but not yet in weight loss apps.
objectiveThis study describes the development and feasibility testing of the Habit app, which was designed to automate problem-solving therapy for weight loss.
methodsTwo iterative single-arm pilot studies were conducted to evaluate the feasibility and acceptability of the Habit app. In each pilot study, adults who were overweight or obese were enrolled in an 8-week intervention that included the Habit app plus support via a private Facebook group. Feasibility outcomes included retention, app usage, usability, and acceptability. Changes in problem-solving skills and weight over 8 weeks are described, as well as app usage and weight change at 16 weeks.
resultsResults from both pilots show acceptable use of the Habit app over 8 weeks with on average two to three uses per week, the recommended rate of use. Acceptability ratings were mixed such that 54% (13/24) and 73% (11/15) of participants found the diet solutions helpful and 71% (17/24) and 80% (12/15) found setting reminders for habits helpful in pilots 1 and 2, respectively. In both pilots, participants lost significant weight (P=.005 and P=.03, respectively). In neither pilot was an effect on problem-solving skills observed (P=.62 and P=.27, respectively).
conclusionsProblem-solving therapy for weight loss is feasible to implement in a mobile app environment; however, automated delivery may not impact problem-solving skills as has been observed previously via human delivery.
trial registrationClinicalTrials.gov NCT02192905; https://clinicaltrials.gov/ct2/show/NCT02192905 (Archived by WebCite at http://www.webcitation.org/6zPQmvOF2).
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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.