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Record W4413708079 · doi:10.7717/peerj.19914

Exploration of gray matter alterations and cognitive function impairment in adolescents with first-episode non-suicidal self-injury and the associations with self-injury characteristics

2025· article· en· W4413708079 on OpenAlexaboutno aff
Rui Yu, Yuwei Chen, Xinyue Chen, Xianfu Li, Nian Liu

Bibliographic record

VenuePeerJ · 2025
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsGray (unit)CognitionCognitive impairmentClinical psychologyMedicinePsychologyPsychiatry

Abstract

fetched live from OpenAlex

Background: It remains unclear if there are potentially associated abnormalities in gray matter (GM) and cognitive function in adolescents with non-suicidal self-injury (NSSI), and if there are associations with self-injury characteristics. Therefore, exploring the alterations in GM and cognitive functions and their associations with self-injury characteristics in adolescents with first-episode NSSI can provide imaging and clinical evidence for understanding the pathogenesis of NSSI. Methods: In this cross-sectional study, we prospectively collected 29 adolescents (NSSI group) with first-episode NSSI and 28 healthy controls (HC group). Participants were scanned using a 3.0T MRI scanner. GM measures were extracted and compared between the NSSI group and the HC group using covariance analysis with total intracranial volume, age, sex, and years of education as covariates. Evaluate the cognitive functions of two groups and perform covariance analysis with years of education, age, and sex as covariates. The assessment of self-injury function was conducted using the Beck Scale for Suicide Ideation and the Ottawa Self-Injury Inventory. With years of education as the control variable, partial correlation analysis is carried out between GM volume (GMV) and cognitive functions. A mediation effect analysis was conducted on GMV, cognitive function, and NSSI to explore the relationships among them. Results: The cognitive functions of the NSSI group are poorer than those of the HC group. Compared with the HC group, the NSSI group had decreased GMV in the left putamen and left nucleus accumbens and an increased GMV in the left rostral anterior cingulate cortex. In the NSSI group, the self-injury characteristics and poorer cognitive function are associated with abnormal alternations in GMV, and the poorer cognitive functions are also associated with the self-injury characteristics. The mediation analysis showed that the volume of the left rostral anterior cingulate cortex played a partial mediating role in the relationship between NSSI behavior and cognitive decline.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
models agreeAgreement compares identical category sets and study designs across arms.

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.273
Teacher spread0.262 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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