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Record W2017748051 · doi:10.2466/pr0.101.2.561-564

Suicide Intervention Trainees' Knowledge of Myths about Suicide

2007· article· en· W2017748051 on OpenAlexaboutno aff
Michael G. Macdonald

Bibliographic record

VenuePsychological Reports · 2007
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsIntervention (counseling)Suicide preventionCommitPsychologySpousePoison controlInjury preventionPsychiatryOccupational safety and healthHuman factors and ergonomicsSuicide RiskSuicide methodsClinical psychologyMedical emergencyMedicineSuicide rates

Abstract

fetched live from OpenAlex

The responses of 70 trainees in suicide intervention to 10 Suicide Opinion Questionnaire items were evaluated for accuracy of their knowledge about suicide myths. Participants were Canadian adults (62 women, 8 men, M (age) = 35 yr.) representing a wide variety of occupations and educational backgrounds. Analysis indicated knowledge for most items was high but less accurate for items concerning the most common method of suicide and suicide risk across the lifespan. Those trained in suicide intervention were more knowledgeable on four items than those awaiting training; they more frequently knew that most suicides are not triggered by an argument with a spouse, people who are depressed are more likely to commit suicide, a person whose parent has committed suicide is at greater risk for suicide, and that shooting is the most common method of suicide in Canada.

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)0.002
metaresearch head score (Gemma)0.014
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 score0.146
Threshold uncertainty score0.290

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.070
GPT teacher head0.420
Teacher spread0.350 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

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