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Record W4411087737 · doi:10.1002/smi.70057

Clinical and Psychosocial Stress Correlates of Self‐Harm in Women: A Retrospective Cohort Study in the Forensic Mental Health Setting

2025· article· en· W4411087737 on OpenAlexaffabout
David Joubert

Bibliographic record

VenueStress and Health · 2025
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMental healthPsychosocialPsychiatryPsychologyHarmClinical psychologyDistressCohortMedicineSocial psychology

Abstract

fetched live from OpenAlex

Para-suicidal behaviours and self-harm are commonly observed in mental health institutions, with women inpatients being particularly at risk. Little research has looked at characteristics of women engaging in self-harmful conduct beyond diagnostic and socio-demographic information. The current study investigated occurrences of self-harm over time in a large sample of women housed in forensic mental health units in the province of Ontario, Canada. Background and clinical information was obtained from staff ratings on the Resident Assessment Instrument-Mental Health at admission and every 3 months afterwards for an approximately 2-year time period. Latent class mixed models identified two distinct profiles, the first one (77.4% of sample) characterised by a low or intermittent use of self-harm, the second (22.6% of sample) showing a stable elevated risk profile. Women in the at-risk group tended to be younger, showed increased signs of subjective distress and greater occurrence of adverse life events in their history. Psychiatric diagnosis in itself was not a valid predictor of the stability of self-harm for this sample. These findings highlight the importance of addressing both clinical and stress-related distal vulnerability factors in the background of institutionalised women who engage in self-harm on a stable basis.

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

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.035
Threshold uncertainty score0.632

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.032
GPT teacher head0.420
Teacher spread0.388 · 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

Machine predicted; a candidate call from one teacher head, not a consensus.

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 routes2
Has abstractyes

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