ArticleContemporary clinical trials communications2021
Stay in treatment: Predicting dropout from pediatric weight management study protocol.
Article in Contemporary clinical trials communications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04364282 (War of Attrition), which is not on this map. Cited by 10 papers.
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.
War of Attrition: Predicting Dropout From Pediatric Weight Management
Who cites it
10 citing papers in PubMed.
- A Randomized Controlled Trial Comparing Loss versus Gain Incentives to Improve Adherence to an Obesity Treatment Intervention in Adolescents.Nutrients · 2024Trial
- Psychometrics of the modified family-centered care assessment short version for childhood obesity.Health and quality of life outcomes · 2024Trial
- Randomized Controlled Feasibility Trial of Late 8-Hour Time-Restricted Eating for Adolescents With Type 2 Diabetes.Journal of the Academy of Nutrition and Dietetics · 2024Trial
- Proximal and Distal Factors Associated With Obesity in Childhood: An Exploratory Structural Equation Model.Obesity science & practice · 2026Article
- Black Children's Perceptions of Parental Support and Parenting Practices: 6-Month Weight Loss and Retention in a Pediatric Weight Management Program.Obesity science & practice · 2025Article
- Psychometrics of the modified Family-Centered Care Assessment short version for childhood obesity.Research square · 2024Article
- Implementation of recommended treatment for children in weight management programs: Lessons from the stay in treatment study sites.Preventive medicine · 2024Observational
- Attrition from Face-to-Face Pediatric Outpatient Chronic Pain Interventions: A Narrative Review and Theoretical Model.Children (Basel, Switzerland) · 2024Review
- Time to act on childhood obesity: the use of technology.Frontiers in pediatrics · 2024Review
- Perceived barriers in family-based behavioural treatment of paediatric obesity - Results from the FABO study.Pediatric obesity · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
introductionChildhood obesity is a serious public health concern. Multidisciplinary pediatric weight management programs have been deemed effective. However, effectiveness of these programs is impacted by attrition, limiting health benefits to children, and inefficiently utilizing scarce resources.
methodsWe have developed a model (the Outcomes Forecasting System, OFS) that isolates variables associated with attrition from pediatric weight management, with the potential to forecast participant dropout. In Aim 1, we will increase the power and precision of the OFS and then validate the model through the consistent acquisition of key patient, family, and treatment data, from three different weight management sites. In Aim 2, external validity will be established through the application of the OFS at a fourth pediatric weight management program. Aim 3 will be a pilot clinical trial, incorporating an intervention built on the results of Aims 1 and 2 and utilizing the OFS to reduce attrition. DISCUSSION: A greater understanding of the patient, family, and disease-specific factors that predict dropout from pediatric weight management can be utilized to prevent attrition. The goal of the current study is to refine the OFS to a level of precision and efficiency to be a valuable tool to any weight management program. By identifying the most pertinent factors driving attrition across weight management sites, new avenues for treatment will be identified. This study will result in a valuable forecasting tool that will be applicable for diverse programs and populations, decrease program costs, and improve patient retention, adherence, and outcomes. CLINICALTRIALSGOV IDENTIFIER: NCT04364282.
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