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Record W2790637510 · doi:10.1097/nmd.0000000000000739

Male Depression Subtypes and Suicidality

2018· article· en· W2790637510 on OpenAlexfundaboutno aff
Simon Rice, John L. Oliffe, David Kealy, John S. Ogrodniczuk

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2018
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
FundersMovember Canada
KeywordsDepression (economics)Clinical psychologyPsychologyPsychiatryMedicine

Abstract

fetched live from OpenAlex

Assessment of men's externalizing symptoms has been theorized to assist in the identification of those at risk of suicide. A nationally representative sample of Canadian men (N = 1000; mean, 49.63 years) provided data on internalizing and externalizing symptoms, and history of recent suicide planning and attempt (previous 4 weeks). Latent profile analysis indicted three classification subtypes. Robust effects were observed regarding history of recent suicide planning and attempt. Men with a marked externalizing profile (12.7% of sample), which included substance use, anger, and risk taking, were significantly more likely to have had a recent suicide plan (risk ratio, 14.47; p < 0.001) or to have attempted suicide within the previous 4 weeks (risk ratio, 21.32; p < 0.001) relative to asymptomatic men (67.7% of sample). Because recent suicide attempt was a rare event in the present sample (n = 13), findings need to be replicated in higher-risk populations. Results support primary care screening for both men's internalizing and externalizing depression symptoms.

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 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)0.002
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 score0.034
Threshold uncertainty score0.068

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.024
GPT teacher head0.315
Teacher spread0.292 · 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 source (direct Gemma or distilled Codex), 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

Citations30
Published2018
Admission routes2
Has abstractyes

Explore more

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