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Record W2938012699 · doi:10.1097/nmd.0000000000000976

Recent Suicidal Ideation and Behavior in the General Population

2019· article· en· W2938012699 on OpenAlexaff
John Briere, Omin Kwon, Randye J. Semple, Natacha Godbout

Bibliographic record

VenueThe Journal of Nervous and Mental Disease · 2019
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsSuicidal ideationClinical psychologyPsychologyDepression (economics)EtiologyEmotional dysregulationSuicidal behaviorDistressPopulationPsychiatryPoison controlSuicide preventionMedicineMedical emergency

Abstract

fetched live from OpenAlex

The multivariate relationship between suicidality and three potential etiologic variables (depression, posttraumatic stress, and reactive avoidance) was examined in a stratified sample of 679 individuals from the general population. Lifetime exposure to a trauma or another very upsetting event was prevalent among those reporting suicidal behavior in the previous 6 months (58%) and those reporting recent suicidal ideation alone (40%), relative to those with no recent suicidal thoughts or behaviors (26%). Canonical correlation analysis indicated two independent sources of variance: the first loading on both suicidal ideation and behavior, predicted by depression, posttraumatic stress, and reactive avoidance, and the second indicating a unique relationship between suicidal behavior and reactive avoidance alone. Results indicate that the etiology of suicidality is likely multidimensional, and point to a significant variant of suicidal behavior that is unrelated to depression or posttraumatic stress, but may reflect emotional dysregulation and subsequent distress reduction behaviors.

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)0.001
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 score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.026
GPT teacher head0.327
Teacher spread0.300 · 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

Citations8
Published2019
Admission routes1
Has abstractyes

Explore more

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