Evidence map›Paper›PMID 41175563›Full record

ArticleJournal of psychiatric research2026

Clinical patterns in a neuroimaging-based predictive model of self-reported dissociation.

Juliann B Purcell, Boyu Ren, Cori A Palermo, Zoe A Bair, Mollie C Marr, Rebecca L Modell, Xi Pan, Matthew A Robinson, Meghan E Shanahan, Michaela B Swee and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Journal of psychiatric research, 2026. 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

5 · Who and what money

Authors and funding

12 authors.

Juliann B PurcellDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA. Electronic address: jpurcell1@mclean.harvard.edu.
Boyu RenDepartment of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA; Laboratory for Psychiatric Biostatistics, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA. Electronic address: bren@mgb.org.
Cori A PalermoDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA. Electronic address: cpalermo@mclean.harvard.edu.
Zoe A BairDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA. Electronic address: zbair@mclean.harvard.edu.
Mollie C MarrDepartment of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA; Massachusetts General Hospital, 55 Fruit Street, Boston, MA, 02114, USA; Department of Psychiatry, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA. Electronic address: mmarr@mgb.org.
Rebecca L ModellDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA. Electronic address: rmodell@mclean.harvard.edu.
Xi PanDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA; Teacher's College, Columbia University, 525 West 120th Street, New York City, NY, 10027, USA. Electronic address: xpan@mclean.harvard.edu.
Matthew A RobinsonDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA. Electronic address: mrobinson@mclean.harvard.edu.
Meghan E ShanahanDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA. Electronic address: meshanahan@mclean.harvard.edu.
Michaela B SweeDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA. Electronic address: mswee@mclean.harvard.edu.
Milissa L KaufmanDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA. Electronic address: mlkaufman@mclean.harvard.edu.
Lauren A M LeboisDivision of Depression and Anxiety Disorders, McLean Hospital, 115 Mill Street, Belmont, MA, 02478, USA; Department of Psychiatry, Harvard Medical School, 25 Shattuck Street, Boston, MA, 02115, USA. Electronic address: llebois@mclean.harvard.edu.

Funding

Harvard Clinical and Translational Science CenterUM1TR004408 · NCATS · HARVARD MEDICAL SCHOOL · PI Lindsey Robert Baden, Lee Marshall Nadler · 2023 to 2026
$43.3M
Multimodal Approaches to Neurobiology of Traumatic DissociationR01MH119227 · NIMH · MCLEAN HOSPITAL · PI KAUFMAN, MILISSA L · 2020 to 2024
$3.7M
Characterizing the Neurobiology of Pathological Dissociation: Mechanisms of Face Perception and Self Referential ProcessingK01MH118467 · NIMH · MCLEAN HOSPITAL · PI LEBOIS, LAUREN ANN MCDONOUGH · 2019 to 2022
$679k
NCATS NIH HHS UM1 TR004408NIMH NIH HHS K01 MH118467NIMH NIH HHS R01 MH119227
6 · The paper itself

Abstract

Assessment of trauma-related dissociation has been historically challenging given its subjective nature and the lack of provider education around this topic. Recent work identified a promising neural biomarker of trauma-related dissociation, representing a significant step toward improved assessment and identification of dissociation. However, it is necessary to better understand clinical factors that may be associated with this biomarker. Participants were 65 women with histories of childhood maltreatment, posttraumatic stress disorder (PTSD), and varying levels of dissociation (e.g., co-occurring dissociative identity disorder, DID). Data were drawn from previously published work that identified a model predicting Multidimensional Inventory of Dissociation severe pathological dissociation scores on the basis of neural functional connectivity. Here, we conducted a k-means cluster analysis to explore model performance patterns in the original prediction model. We then investigated differences among the clusters in a range of clinically-relevant variables. Our clustering analysis identified four distinct groups. The original model best predicted those at the low (cluster 1, 82 % PTSD) and high (cluster 3, 86 % DID) ends of self-reported dissociation. Cluster 2 also largely included participants with DID (67 %), but the predictive model was less accurate for these individuals. Follow up analyses revealed that DID participants in cluster 2 reported lower levels of self-state intrusions, a type of DID-specific dissociation, compared to those in cluster 3. Thus, the identified model performance patterns suggest that the original prediction model may be linked to DID-specific dissociation. Our findings indicate that patterns of functional connectivity may be valuable to improve accurate assessment of DID.

Indexed as

Adult Survivors of Child AbuseDissociative DisordersStress Disorders, Post-TraumaticAdultCluster AnalysisFemaleHumansMagnetic Resonance ImagingMiddle AgedSelf ReportYoung AdultDissociationFunctional connectivityK-means clusteringNeural biomarkerPosttraumatic stress

Identifiers

PMID41175563
PMCPMC12726959

What OpenQuestion holds

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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.