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Record W2750944378 · doi:10.1002/jclp.22518

Exposure to suicide in the family: Suicide risk and psychache in individuals who have lost a family member by suicide

2017· article· en· W2750944378 on OpenAlexaff
Rui C. Campos, Ronald R. Holden, Sara Santos

Bibliographic record

VenueJournal of Clinical Psychology · 2017
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyFamily memberSuicide attemptSuicide preventionClinical psychologyPortugueseIntervention (counseling)PsychiatryHuman factors and ergonomicsPoison controlMedicineMedical emergencyFamily medicine

Abstract

fetched live from OpenAlex

OBJECTIVE: The aim of the present study was to compare a sample of Portuguese individuals exposed to suicide in their families with a control group, for lifetime suicidality. This study also evaluated the incremental value of psychache (i.e., extreme psychological pain) in determining suicide risk beyond the contribution associated with having lost a family member by suicide. METHOD: A total of 225 community adults participated. Two groups were defined: a group exposed to suicide (n = 53), and a control group (n = 172). RESULTS: Results demonstrated that groups did significantly differ on the total score of the Suicide Behaviors Questionnaire-Revised (SBQ-R), on the four individual SBQ-R items, and on psychache. Results from a hierarchical multiple regression analysis demonstrated that having lost a family member by suicide and the construct of psychache each provided a significant unique contribution to explaining variance in suicide risk. The interaction between group membership and psychache also provided a further enhancement to the statistical prediction of suicide risk. CONCLUSION: Findings are discussed with regard to their implications for clinical intervention and postvention.

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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.212
GPT teacher head0.501
Teacher spread0.289 · 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

Citations12
Published2017
Admission routes1
Has abstractyes

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