ArticleObesity (Silver Spring, Md.)2018
Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures: Behavioral Domain.
Article in Obesity (Silver Spring, Md.), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 2 of them syntheses that pooled it.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Essential dataset features in a successful obesity registry: a systematic review.International health · 2025Pooled it
- OBEDIS Core Variables Project: European Expert Guidelines on a Minimal Core Set of Variables to Include in Randomized, Controlled Clinical Trials of Obesity Interventions.Obesity facts · 2020Guideline
- Randomized controlled trial of a novel lifestyle intervention used with or without meal replacements in work sites.Obesity (Silver Spring, Md.) · 2023Trial
- Evaluation of PIQNIQ, a Novel Mobile Application for Capturing Dietary Intake.The Journal of nutrition · 2021Trial
- The Physiology Of the WEight Reduced State (POWERS) study: design and rationale for assessment of food intake, physical activity and other behavioral constructs.International journal of obesity (2005) · 2026Article
- The Physiology Of the WEight Reduced State (POWERS) study: assessing energy balance.International journal of obesity (2005) · 2026Article
- Article
- The relationship between sleep quantity, sleep quality and weight loss in adults: A scoping review.Clinical obesity · 2024Article
- Evidence and consensus-based clinical practice guidelines for management of overweight and obesity in midlife women: An AIIMS-DST initiative.Journal of family medicine and primary care · 2022Review
- Technical report: an online international weight control registry to inform precision approaches to healthy weight management.International journal of obesity (2005) · 2022Article
- Article
- Using psycho-behavioral phenotyping for overweight and obesity: Confirmation of the 6 factor questionnaire.Obesity science & practice · 2022Article
- Use of Natural Spoken Language With Automated Mapping of Self-reported Food Intake to Food Composition Data for Low-Burden Real-time Dietary Assessment: Method Comparison Study.Journal of medical Internet research · 2021Article
- The association between sleep health and weight change during a 12-month behavioral weight loss intervention.International journal of obesity (2005) · 2021Observational
- Minority and low-income patients are less likely to have a scale for self-weighing in their home: A survey in primary care.Clinical obesity · 2020Article
- Biobehavioural approaches to prevention and treatment: A call for implementation science in obesity research.Obesity science & practice · 2020Article
- Effectiveness of Intermittent Fasting and Time-Restricted Feeding Compared to Continuous Energy Restriction for Weight Loss.Nutrients · 2019Review
- The Accumulating Data to Optimally Predict Obesity Treatment (ADOPT) Core Measures Project: Rationale and Approach.Obesity (Silver Spring, Md.) · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
backgroundThe ability to identify and measure behaviors that are related to weight loss and the prevention of weight regain is crucial to understanding the variability in response to obesity treatment and the development of tailored treatments.
objectivesThe overarching goal of the Accumulating Data to Optimally Predict obesity Treatment (ADOPT) Core Measures Project is to provide obesity researchers with guidance on a set of constructs and measures that are related to weight control and that span and integrate obesity-related behavioral, biological, environmental, and psychosocial domains. This article describes how the behavioral domain subgroup identified the initial list of high-priority constructs and measures to be included, and it describes practical considerations for assessing the following four behavioral areas: eating, activity, sleep, and self-monitoring of weight. Challenges and considerations for advancing the science related to weight loss and maintenance behaviors are also discussed. SIGNIFICANCE: Assessing a set of core behavioral measures in combination with those from other ADOPT domains is critical to improve our understanding of individual variability in response to adult obesity treatment. The selection of behavioral measures is based on the current science, although there continues to be much work needed in this field.
Indexed as
Identifiers
What OpenQuestion holds
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.