Evidence map›Paper›PMID 37077032›Full record

Trial reportClinical trials (London, England)2023

Designing a childhood obesity preventive intervention using the multiphase optimization strategy: The Healthy Bodies Project.

Lori A Francis, Robert L Nix, Rhonda BeLue, Kathleen L Keller, Kari C Kugler, Brandi Y Rollins, Jennifer S Savage

Open access · hybridAbstract readRandomized Controlled Trial
In one paragraph

Trial report in Clinical trials (London, England), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Trial
  2. Power Calculation in 2Prevention science : the official journal of the Society for Prevention Research · 2026
    Article
  3. Article
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

7 authors at 3 institutions in 1 country.

Lori A FrancisDepartment of Biobehavioral Health, College of Health and Human Development, The Pennsylvania State University, University Park, PA, USA.ORCID 0000-0002-6269-738X
Robert L NixDepartment of Human Development and Family Studies, School of Human Ecology, University of Wisconsin-Madison, Madison, WI, USA.
Rhonda BeLueDepartment of Public Health, College for Health, Community and Policy, University of Texas at San Antonio, San Antonio, TX, USA.
Kathleen L KellerDepartment of Nutritional Sciences, College of Health and Human Development, The Pennsylvania State University, University Park, PA, USA.
Kari C KuglerDepartment of Biobehavioral Health, College of Health and Human Development, The Pennsylvania State University, University Park, PA, USA.
Brandi Y RollinsDepartment of Biobehavioral Health, College of Health and Human Development, The Pennsylvania State University, University Park, PA, USA.ORCID 0000-0003-1077-3886
Jennifer S SavageDepartment of Nutritional Sciences, College of Health and Human Development, The Pennsylvania State University, University Park, PA, USA.
Pennsylvania State University · USThe University of Texas at San Antonio · USUniversity of Wisconsin–Madison · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

BACKGROUND/

aimsPreventing the development of childhood obesity requires multilevel, multicomponent, comprehensive approaches. Study designs often do not allow for systematic evaluation of the efficacy of individual intervention components before the intervention is fully tested. As such, childhood obesity prevention programs may contain a mix of effective and ineffective components. This article describes the design and rationale of a childhood obesity preventive intervention developed using the multiphase optimization strategy, an engineering-inspired framework for optimizing behavioral interventions. Using a series of randomized experiments, the objective of the study was to systematically test, select, and refine candidate components to build an optimized childhood obesity preventive intervention to be evaluated in a subsequent randomized controlled trial.

methodsA 2

resultsFour intervention components were developed, including three classroom curricula designed to increase preschool children's nutrition knowledge, physical activity, and behavioral, emotional, and eating regulation. A web-based parent education component included 18 lessons designed to improve parenting practices and home environments that would bolster the effects of the classroom curricula. A plan for analyzing the specific contribution of each component to a larger intervention was developed and is described. The efficacy of the four components can be evaluated to determine the extent to which they, individually and in combination, produce detectable changes in childhood obesity risk factors. The resulting optimized intervention should later be evaluated in a randomized controlled trial, which may provide new information on promising targets for obesity prevention in young children.

conclusionThis research project highlights the ways in which an innovative approach to the design and initial evaluation of preventive interventions may increase the likelihood of long-term success. The lessons from this research project have implications for childhood obesity research as well as other preventive interventions that include multiple components, each targeting unique contributors to a multifaceted problem.

Indexed as

Pediatric ObesityChildChild, PreschoolExerciseHumansParentsPennsylvaniaRisk Factorshealthy eatingMultiphase optimization strategyobesity preventionparentingphysical activityself-regulation

Identifiers

PMID37077032
PMCPMC10338696
OpenAlexW4366464100

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.