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Record W2135902079 · doi:10.1192/bjp.bp.107.037382

Psychosocial and clinical correlates of suicidal acts: Results from a national population survey

2008· article· en· W2135902079 on OpenAlexafffundabout
Emma Robertson Blackmore, Sarah Munce, Iris Weller, Brandon Zagorski, Stephen Stansfeld, Donna E. Stewart, Eric D. Caine, Yeates Conwell

Bibliographic record

VenueThe British Journal of Psychiatry · 2008
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsSunnybrook Health Science CentreUniversity of TorontoHealth Sciences CentreUniversity Health Network
FundersNational Institute of Mental HealthCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsPsychosocialPsychologyPopulationClinical psychologyPsychiatryMedicineEnvironmental health

Abstract

fetched live from OpenAlex

BACKGROUND: Clinical samples have identified a number of psychosocial risk factors for suicidal acts but it is unclear if these findings relate to the general population. AIMS: To describe the prevalence of and psychosocial risk factors for suicidal acts in a general adult population. METHOD: Data were obtained from a Canadian epidemiological survey of 36,984 respondents aged 15 years and older (weighted sample n=23,662,430). RESULTS: Of these respondents, 0.6% (weighted n=130,143) endorsed a 12-month suicidal act. Female gender (OR=4.27, 95% CI 4.05-4.50), being separated (OR=37.88, 95% CI 33.92-42.31) or divorced (OR=7.79, 95% CI 7.22-8.41), being unemployed (OR=1.70, 95% CI 1.50-1.80), experiencing a chronic physical health condition (OR=1.70, 95% CI 1.67-1.86) and experiencing a major depressive episode in the same 12-month period as the act (OR=9.10, 95% CI 8.65-9.59) were significantly associated with a suicidal act. CONCLUSIONS: The psychosocial correlates of suicidal acts in this sample are consistent with those previously reported in clinical and general population samples. These findings reinforce the importance of the determination of suicide risk and its prevention not only of psychiatric illness but of physical and psychosocial factors as well.

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)0.001
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 score0.045
Threshold uncertainty score0.801

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.059
GPT teacher head0.355
Teacher spread0.295 · 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

Citations114
Published2008
Admission routes3
Has abstractyes

Explore more

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