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Record W2144120232 · doi:10.1348/135532504x15295

Screening for suicide risk factors in prison inmates: Evaluating the efficiency of the Depression, Hopelessness and Suicide Screening Form (DHS)

2005· article· en· W2144120232 on OpenAlexaff
Jeremy F. Mills, Daryl G. Kroner

Bibliographic record

VenueLegal and Criminological Psychology · 2005
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsCarleton University
Fundersnot available
KeywordsSuicide preventionPsychologyClinical psychologyDistressDepression (economics)PsychiatryPoison controlPrisonHuman factors and ergonomicsInjury preventionMedicineMedical emergency

Abstract

fetched live from OpenAlex

The Depression, Hopelessness and Suicide Screening Form (DHS; ) is a recently developed self‐report instrument to aid in screening inmates in the titled areas. Research has shown the DHS to have good internal consistency, factor structure and construct validity. The present study extends the previous validation research by comparing the disclosure of suicide risk factors on the DHS with both interview‐based and file review information. In addition, the DHS scores were used to predict psychological distress. The results indicate that despite the paper‐and‐pencil self‐report approach of the DHS it is comparably efficient in gathering suicide risk factors to other methods. In addition, the predictive accuracy of the DHS in identifying inmates experiencing psychological distress was confirmed. The current study has implications for the method of collection of suicide screening information. The discussion centres on the potential of self‐report in screening for suicide and self‐harm indicators in inmate populations.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.102
Threshold uncertainty score0.649

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.166
GPT teacher head0.414
Teacher spread0.248 · 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 teacher head, 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

Citations66
Published2005
Admission routes1
Has abstractyes

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