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Record W4414545106 · doi:10.1186/s13643-025-02880-6

Self-harm and suicide in prisons in low- and middle-income countries: protocol for a systematic review of prevalence and risk factors

2025· review· en· W4414545106 on OpenAlexaboutno aff
Maha Aon, Marie Brasholt, Joanne Khabsa, Rohan Borschmann

Bibliographic record

VenueSystematic Reviews · 2025
Typereview
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
FundersNational Health and Medical Research CouncilMedical Research Council
KeywordsProtocol (science)Systematic reviewSuicide preventionHuman factors and ergonomicsPoison controlOccupational safety and healthInjury prevention

Abstract

fetched live from OpenAlex

BACKGROUND: Suicide is a leading cause of death in prisons, and documented rates of self-harm (an established risk factor for suicide) are disproportionately higher in prisons than in the general population. However, research to date has focused largely on high-income countries, and as patterns of suicide and self-harm vary across cultures, there is an urgent need for research examining these phenomena in prisons in low- and middle-income countries. This review will synthesize findings from the published literature regarding the prevalence of, and risk factors for, suicide and self-harm among incarcerated persons in prisons in low- and middle-income countries. METHODS: We will search six electronic databases (MEDLINE, Embase, Scopus, PsycINFO, the National Criminal Justice Reference Service (NCJRS), and Global Index Medicus) for studies published in any language from database inception until 1 March 2024 reporting the prevalence and/or risk factors for self-harm and/or suicide in prisons in low- and middle-income countries (as defined by the World Bank). Grey literature will be identified by searching Google, Proquest, the Networked Digital Library of Theses and Dissertations (NDLTD), and websites such as CADTH's Grey Matters. We will not restrict eligibility by age, gender, sentence type, or sentence duration. The risk of bias will be assessed using the Newcastle-Ottawa Quality Assessment Scale (NoS) and the Joanna Briggs Institute (JBI) checklists for prevalence and qualitative studies. Data addressing prevalence and incidence will be synthesized in narrative and graphic format. If sufficient data addressing risk factors for suicide and self-harm are identified, they will be meta-analyzed using the pooled adjusted odds ratio (with 95% confidence intervals). Sensitivity analysis will be conducted as appropriate. Meta-biases such as publication and outcome reporting bias will be assessed. Finally, the Grading of Recommendations Assessment, Development and Evaluation (GRADE) will be used to assess the certainty of evidence collected in this systematic review. DISCUSSION: Findings from this review will contribute to strengthening our understanding of self-harm and suicide in carceral settings in low- and middle-income countries and may be used to inform prevention efforts. SYSTEMATIC REVIEW REGISTRATION: Our systematic review protocol is registered with the International Prospective Register of Systematic Reviews (PROSPERO; CRD42022382012).

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewlow
gptno category
Domain: not available · Genre: Protocol
About the Canadian research system: no · About a Canadian topic: no
Systematic reviewhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.011
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Meta-epidemiology (broad)
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 score0.030
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0110.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0170.001
Bibliometrics0.0010.001
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 head0.083
GPT teacher head0.418
Teacher spread0.335 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.
Study designSystematic review
Domainnot available
GenreProtocol

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

Citations0
Published2025
Admission routes1
Has abstractyes

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