Evidence map›Paper›PMID 41077563›Full record

ArticlePsychological medicine2025

A network analysis of how obsessive-compulsive symptoms change during exposure and response prevention treatment.

Hyunsik Kim, Jeremy Tyler, Michael Wheaton, Saeri Park, Choong-Wan Woo, Edna Foa, Helen Blair Simpson

Abstract read
In one paragraph

Article in Psychological medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. A network analysis of obsessive-compulsive patients in intensive outpatient treatment.European psychiatry : the journal of the Association of European Psychiatrists · 2026
    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.

Hyunsik KimDepartment of Psychology, https://ror.org/056tn4839Sogang University, Seoul, South Korea.ORCID 0000-0001-9499-017X
Jeremy TylerCenter for the Treatment and Study of Anxiety, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Michael WheatonDepartment of Psychology, https://ror.org/04rt94r53Barnard College, New York, NY, USA.
Saeri ParkCenter for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, South Korea.
Choong-Wan WooCenter for Neuroscience Imaging Research, Institute for Basic Science (IBS), Suwon, South Korea.ORCID 0000-0002-7423-5422
Edna FoaCenter for the Treatment and Study of Anxiety, Department of Psychiatry, University of Pennsylvania, Philadelphia, PA, USA.
Helen Blair SimpsonCenter for OCD and Related Disorders, New York State Psychiatric Institute, New York, NY, USA.

Funding

Maximizing Treatment Outcome in OCDR01MH045404 · NIMH · UNIVERSITY OF PENNSYLVANIA · PI FOA, EDNA B · 1990 to 2016
$5.3M
Maximizing Treatment Outcome in OCDR01MH045436 · NIMH · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI SIMPSON, HELEN BLAIR · 1990 to 2015
$5.0M
Control and Reward Circuits as Targets for Repetitive Thoughts and BehaviorsR01MH104648 · NIMH · NEW YORK STATE PSYCHIATRIC INSTITUTE DBA RESEARCH FOUNDATION FOR MENTAL HYGIENE, INC · PI MARSH, RACHEL, SIMPSON, HELEN BLAIR · 2014 to 2017
$2.8M
IMPROVING THE OUTCOME OF PATIENTS WITH OCDK23MH001907 · NIMH · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI SIMPSON, HELEN B · 2000 to 2004
$837k
NIMH NIH HHS K23 MH001907NIMH NIH HHS K23 MH-01907NIMH NIH HHS R01 104648-04NIMH NIH HHS R01 MH045404NIMH NIH HHS R01 MH045436NIMH NIH HHS R01 MH104648NIMH NIH HHS R01MH 104648-04NIMH NIH HHS R01 MH45404
6 · The paper itself

Abstract

backgroundAlthough exposure and response prevention (EX/RP) is recommended as a first-line treatment for obsessive-compulsive disorder (OCD), responses vary among patients. This study was the first to use network analysis to examine how OCD symptom networks change with EX/RP and vary across different progress trajectories.

methodsData from four clinical trials with 334 adults with OCD who received manualized EX/RP were pooled. The Yale-Brown Obsessive-Compulsive Scale (Y-BOCS) was administered at baseline, midpoint, and post-treatment. OCD symptom networks were constructed using individual Y-BOCS items at these three time points, both for the entire sample and for three different progress trajectories (dramatic, moderate, and little-to-no progress) previously identified using growth mixture modeling. Network measures, including global efficiency, modularity, and weighted degree centrality, were computed to quantitatively assess network properties across treatment.

resultsNetwork analysis revealed two distinct modules at baseline: resistance/control and interference/distress. In the full sample, these two modules became integrated over time, as indicated by significant increases in global efficiency and weighted degree centrality and decreases in modularity; at post-treatment, the network shifted toward a fully connected network, and the strength of associations between nodes increased. These changes were most pronounced in the dramatic progress class.

conclusionsOur findings indicated that effective EX/RP treatment was associated with more integrated OCD symptom networks, which may serve as an indicator of treatment response. Future research should examine how these shifts in network connectivity correspond to changes in underlying brain circuitry and/or to early identification of treatment responders.

Indexed as

Implosive TherapyObsessive-Compulsive DisorderAdultFemaleHumansMaleMiddle AgedYoung Adultexposure and response preventionnetwork analysisobsessive-compulsive disordersymptom networktreatment response

Identifiers

PMID41077563
PMCPMC12551580

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.