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Record W2789914404 · doi:10.1111/cpsp.12227

Do neurocognitive abilities distinguish suicide attempters from suicide ideators? A systematic review of an emerging research area

2018· review· en· W2789914404 on OpenAlexaff
Boaz Y. Saffer, E. David Klonsky

Bibliographic record

VenueClinical Psychology Science and Practice · 2018
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsNeurocognitivePsychologyClinical psychologySuicide attemptPoison controlSuicide preventionInjury preventionSuicide methodsHuman factors and ergonomicsCognitionPsychiatryMedicineSuicide ratesMedical emergency

Abstract

fetched live from OpenAlex

Recent findings suggest that neurocognitive deficits may hasten progression from suicidal thoughts to behavior. To test this proposition, we examined whether neurocognitive deficits distinguish individuals who have attempted suicide (attempters) from those who have considered suicide but never attempted (ideators). A comprehensive literature search yielded 14 studies comparing attempters to ideators on a range of neurocognitive abilities. In general, attempters and ideators scored comparably across neurocognitive abilities (median Hedges' g = −.18). An exception was a moderate difference for inhibition and decision making (median Hedges' g = −.50 and g = −.49, respectively). Results suggest that some neurocognitive abilities might help explain the transition from suicidal thoughts to suicide attempts. However, findings are regarded as suggestive, given the small number of studies, few cross-study examinations of neurocognitive domains, and variability in sample characteristics. Recommendations for future research are included.

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)0.006
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.006
Bibliometrics0.0120.009
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.596
GPT teacher head0.646
Teacher spread0.050 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations73
Published2018
Admission routes1
Has abstractyes

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