Evidence map›Paper›PMID 40720145›Full record

ArticleAddiction biology2025

Grey Matter Volume in Substance Use: A Preregistered, Dimensional Approach to Disentangle Substance Use and Disorder Severity.

Kristina Schwarz, Malin K Hildebrandt, Nele Sauer, Raoul Wüllhorst, Tanja Endrass

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Addiction biology, 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. 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

5 authors.

Kristina SchwarzDepartment of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0003-3820-655X
Malin K HildebrandtDepartment of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Nele SauerDepartment of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Raoul WüllhorstDepartment of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.
Tanja EndrassDepartment of Clinical Psychology and Psychotherapy, Technische Universität Dresden, Dresden, Germany.

Funding

Else Kröner-Fresenius-Stiftung 2020_EKEA.70Transregio Collaborative Research Center TRR 265, B01
6 · The paper itself

Abstract

This preregistered study investigates whether altered grey matter volume (GMV) in the insula and ventromedial prefrontal/anterior cingulate cortex (vmPFC/ACC) - regions commonly implicated in substance use disorder (SUD) - is associated with the degree of substance use or with the severity of substance-related problems, two distinct but correlated facets of SUD. Baseline structural MRI and behavioural assessment of substance use, substance-related problems (i.e., DSM-5 disorder severity) and negative urgency were conducted in 134 (poly-)substance users. At 1-year follow-up, behavioral assessments were repeated in 120 participants. Linear regression analyses tested associations between GMV in predefined regions (insula, vmPFC and ACC) and (1) degree of use, (2) substance-related problems and (3) substance-related problems controlled for use. Mediation analyses tested whether negative urgency mediated the problem-specific associations. GMV in all regions negatively related to substance-related problems and use (p

Indexed as

Gray MatterPrefrontal CortexSubstance-Related DisordersAdultFemaleGyrus CinguliHumansInsular CortexMagnetic Resonance ImagingMaleMiddle AgedOrgan SizeSeverity of Illness IndexYoung Adultaddictiondimensionalgrey matter volumesubstance‐related problemsventromedial prefrontal cortex

Identifiers

PMID40720145
PMCPMC12302895

What OpenQuestion holds

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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.