Evidence map›Paper›PMID 34169176›Full record

ArticleContemporary clinical trials communications2021

Stay in treatment: Predicting dropout from pediatric weight management study protocol.

Diane C Berry, Erinn T Rhodes, Sarah Hampl, Caroline Blackwell Young, Gail Cohen, Ihuoma Eneli, Amy Fleischman, Edward Ip, Brooke Sweeney, Timothy T Houle and 1 more

Registry-linked trialAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

NCT04364282 nacompletednot on this map

War of Attrition: Predicting Dropout From Pediatric Weight Management

TypeinterventionalSponsorWake Forest University Health SciencesRan2020 to 2025Enrolled1,216ConditionsPediatric Obesity, Attrition, Family Research, Weight LossArmsCare team informed, Control
3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Trial
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  5. Article
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  7. Observational
  8. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Diane C BerryThe University of North Carolina, School of Nursing, Chapel Hill, NC, USA.
Erinn T RhodesDepartment of Pediatrics, Harvard Medical School, Boston, MA, USA.
Sarah HamplDepartment of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.
Caroline Blackwell YoungDepartment of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Gail CohenDepartment of Pediatrics, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Ihuoma EneliDepartment of Pediatrics, Ohio State University, Columbus, OH, USA.
Amy FleischmanDepartment of Pediatrics, Harvard Medical School, Boston, MA, USA.
Edward IpDepartment of Biostatistics and Data Science, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.
Brooke SweeneyDepartment of Pediatrics, University of Missouri-Kansas City School of Medicine, Kansas City, MO, USA.
Timothy T HouleDepartment of Anesthesia, Critical Care and Pain Medicine, Massachusetts General Hospital, Boston, MA, USA.
Joseph SkeltonDepartment of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Winston-Salem, NC, USA.

Funding

War of Attrition: Predicting Dropout from Pediatric Weight ManagementR01NR017639 · NINR · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI SKELTON, JOSEPH ARNOLD · 2019 to 2023
$3.0M
NINR NIH HHS R01 NR017639
6 · The paper itself

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.

Indexed as

AttritionFamilyPatientPediatric obesityPrediction

Identifiers

PMID34169176
PMCPMC8209185

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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.