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Record W2791422107 · doi:10.1111/sltb.12437

An Empirical Test of the Three‐Step Theory of Suicide in U.K. University Students

2018· article· en· W2791422107 on OpenAlexaff
Katie Dhingra, E. David Klonsky, Vojna Tapola

Bibliographic record

VenueSuicide and Life-Threatening Behavior · 2018
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsSocial connectednessSuicidal ideationIdeationPsychologySuicide attemptTest (biology)Clinical psychologyEmpirical researchSuicide ideationSample (material)Suicide preventionSocial psychologyPoison controlMedicineMedical emergency

Abstract

fetched live from OpenAlex

The purpose of this study was to further our understanding of how individuals move down the pathway from first thinking about suicide to ultimately attempting to take their own lives by empirically testing the Three-Step Theory (3ST) in a sample of university students (n = 665). Results largely support the theory's central propositions. First, an interactive model of pain and hopelessness accounted for substantial variance in suicidal desire. This result replicated in both men and women, and across age groups (i.e., below 35 and at or above 35). Also, as predicted, connectedness was protective against ideation in those high on both pain and hopelessness. However, contrary to our prediction, connectedness was similarly protective among everyone else. Finally, suicide capacity predicted suicide attempt history over and above current and lifetime suicide ideation. These findings provide further support to the 3ST.

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)0.007
metaresearch head score (Gemma)0.039
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 score0.012
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.039
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0020.002
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.061
GPT teacher head0.362
Teacher spread0.301 · 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

Citations109
Published2018
Admission routes1
Has abstractyes

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