Evidence map›Paper›PMID 40475951›Full record

ArticleFrontiers in psychiatry2025

Developing a digital intervention to combat fatphobia and anti-fat bias.

Agatha A Laboe, Elizabeth Sheil, Emma L Jennings, Molly F Steinhoff, Jake Goldberg, Kevin Sagat, Mahathi Gavuji, Katherine E Schaumberg

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Agatha A LaboeDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States.
Elizabeth SheilDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States.
Emma L JenningsDepartment of Psychology, Drexel University, Philadelphia, PA, United States.
Molly F SteinhoffDepartment of Psychological and Brain Science, Washington University in St. Louis, St. Louis, MO, United States.
Jake GoldbergDepartment of Psychological and Brain Science, Washington University in St. Louis, St. Louis, MO, United States.
Kevin SagatDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States.
Mahathi GavujiDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States.
Katherine E SchaumbergDepartment of Psychiatry, University of Wisconsin-Madison, Madison, WI, United States.

Funding

University of Wisconsin Institute for Clinical and Translational ResearchUL1TR002373 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI ELIZABETH S BURNSIDE, Allan R. Brasier · 2017 to 2026
$75.9M
NRSA Training CoreTL1TR002375 · NCATS · UNIVERSITY OF WISCONSIN-MADISON · PI Vivek Prabhakaran · 2017 to 2026
$8.4M
Driven exercise and risk for eating disorders: A combined genetic and longitudinal epidemiological investigationK01MH123914 · NIMH · UNIVERSITY OF WISCONSIN-MADISON · PI SCHAUMBERG, KATHERINE · 2020 to 2023
$743k
Characterizing Acute Exercise Response in Restrictive Eating DisordersR21MH131787 · NIMH · UNIVERSITY OF WISCONSIN-MADISON · PI GORRELL, SASHA CATHERINE, SCHAUMBERG, KATHERINE · 2023 to 2023
$450k
Developmental pathways and treatment of OCD and anorexia: the role heightened performance monitoring and overcontrolF31MH137979 · NIMH · WASHINGTON UNIVERSITY · PI Molly Fennig Steinhoff · 2025 to 2026
$83k
NCATS NIH HHS TL1 TR002375NCATS NIH HHS UL1 TR002373NIMH NIH HHS F31 MH137979NIMH NIH HHS K01 MH123914NIMH NIH HHS R21 MH131787
6 · The paper itself

Abstract

Introduction: The Body Advocacy Movement (BAM) is an in-person, peer-led, cognitive-dissonance-based eating disorder (ED) prevention program that reduces fatphobia and anti-fat bias. Developing a digital adaptation of BAM has the potential to increase its accessibility and fill a critical gap in existing digital ED interventions, which to date have not specifically targeted anti-fat bias or fatphobia. This study applies a human-centered design approach to inform the development of a digital version of BAM. Methods: Semi-structured interviews were conducted with 31 participants, including 17 college students with elevated ED psychopathology and 14 past BAM participants. College students with elevated ED psychopathology shared experiences with fatphobia and anti-fat bias, how they use mental health technology, and thoughts on digitizing BAM. Past BAM participants shared experiences with BAM, how they use mental health technology, and thoughts on digitizing BAM. Interviews were analyzed using reflexive thematic analysis with a critical realist lens. Results: College students with elevated ED psychopathology described pervasive and harmful experiences of anti-fat bias and fatphobia, coupled with difficulties accessing action-oriented mental health support, underscoring a gap in care that a digital adaptation of BAM could address. Both groups expressed strong interest in a hybrid digital format that combines synchronous and asynchronous components for a balance of social connection and flexibility. Discussion: Findings suggest that a digital adaptation of BAM could address unmet needs in ED prevention by providing accessible, action-oriented content focused on reducing anti-fat bias and fatphobia. Incorporating synchronous social connection within a flexible, interactive framework may promote engagement and impact. A critical next step will involve designing and pilot testing this digital adaptation of BAM to evaluate its feasibility and effectiveness.

Indexed as

anti-fat biascollege mental healthdigital interventioneating disordersfatphobiafear of weight gainhuman-centered design

Identifiers

PMID40475951
PMCPMC12138398

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.