Evidence map›Paper›PMID 40027849›Full record

ArticleImplementation research and practice

Application of implementation science frameworks to inform the adaptation process of an evidence-based eating disorder prevention program for high-risk perinatal individuals.

Rachel Vanderkruik, Emily C Woodworth, Caroline M Frisch, Stacey Nelson, Madison M Dunk, Marlene P Freeman, Lee S Cohen, Eric Stice, Stephen J Bartels

Abstract read
In one paragraph

Article in Implementation research and practice. 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
–field-weighted citation impact
1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Rachel VanderkruikDepartment of Psychiatry, Ammon-Pinizzotto Center for Women's Mental Health at Massachusetts General Hospital, Boston, MA, US.ORCID https://orcid.org/0000-0002-6997-7894
Emily C WoodworthCenter for Health Outcomes and Interdisciplinary Research, Massachusetts General Hospital, Boston, MA, US.
Caroline M FrischDepartment of Psychiatry, Ammon-Pinizzotto Center for Women's Mental Health at Massachusetts General Hospital, Boston, MA, US.ORCID https://orcid.org/0009-0009-2487-9404
Stacey NelsonNutrition Services, Massachusetts General Hospital, Boston, MA, US.ORCID https://orcid.org/0000-0001-8752-8227
Madison M DunkDepartment of Psychiatry, Ammon-Pinizzotto Center for Women's Mental Health at Massachusetts General Hospital, Boston, MA, US.
Marlene P FreemanDepartment of Psychiatry, Ammon-Pinizzotto Center for Women's Mental Health at Massachusetts General Hospital, Boston, MA, US.
Lee S CohenDepartment of Psychiatry, Ammon-Pinizzotto Center for Women's Mental Health at Massachusetts General Hospital, Boston, MA, US.
Eric SticeDepartment of Psychiatry and Behavioral Sciences, Stanford University, Stanford, US.
Stephen J BartelsMongan Institute, Massachusetts General Hospital, Harvard Medical School, Boston, MA, US.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The perinatal period is a high-risk time for body dissatisfaction and disordered eating. Evidence-based interventions for disordered eating have not been adapted to address the needs of this population. We describe the process of adapting the Body Project, an evidence-based eating disorder (ED) prevention program, for pregnant individuals with histories of disordered eating behaviors. Method: Our approach is informed by ADAPT, a framework offering guidance for adapting interventions to new contexts, to modify the Body Project for pregnant individuals. Following initial adaptations informed by a needs assessment and stakeholder input, we conducted a pilot trial with individuals who have lived experience relative to our target population (i.e., previously pregnant individuals with ED history, Results: Eighty percent of enrolled participants attended five or more sessions (out of six). Across sessions, average satisfaction ratings were 9.28 (1 = Conclusions: Applying implementation science frameworks to structure our process for making and summarizing planned adaptations, we adapted an empirically supported ED prevention program for pregnant individuals with histories of an ED. We made adaptation decisions based on participant feedback while weighing intervention fidelity and scalability. We will formally test the adapted intervention in a subsequent pilot randomized controlled trial versus a time- and dose-matched educational control.

Indexed as

body dissatisfactioneating disordersimplementation scienceintervention adaptationperinatal periodpreventionuser-centered design

Identifiers

PMID40027849
PMCPMC11869238

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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.