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Record W2128217144 · doi:10.5539/gjhs.v8n5p145

Suicide Prevention and Follow-Up Services: A Narrative Review

2015· review· en· W2128217144 on OpenAlexvenueno aff
Behrooz Ghanbari, Seyed Kazem Malakouti, Marzieh Nojomi, Kaveh Alavi, Shiva Khaleghparast

Bibliographic record

VenueGlobal Journal of Health Science · 2015
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPsychological interventionSuicide preventionRandomized controlled trialMedicinePoison controlInjury preventionPhoneOccupational safety and healthPromotion (chess)Human factors and ergonomicsMedical emergencyPsychiatrySurgery

Abstract

fetched live from OpenAlex

Previous suicide attempt is the most important predictor of death by suicide. Thus preventive interventions after attempting to suicide is essential to prevent reattempts. This paper attempts to determine whether phone preventive interventions or other vehicles (postal cards, email and case management) are effective in reattempt prevention and health promotion after discharge by providing an overview of studies on suicide reattempts. The research investigated in this review conducted from 1995 to 2014. A total of 26 cases related to the aim of this research were derived from 36 English articles with the aforementioned keywords Research shows that providing comprehensive aids, social support, and follow-up after discharge can significantly prevent suicide reattempts. Several studies showed that follow-up support (phone calls, crisis cards, mails, postal cards.) after discharge can significantly decrease the risk of suicide. More randomized controlled trials (RCT) are required to determine what factors of follow-up are more effective than other methods.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.968
Threshold uncertainty score0.918

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.131
GPT teacher head0.490
Teacher spread0.359 · 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 designOther design
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

Citations54
Published2015
Admission routes1
Has abstractyes

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