Self-harm and suicide in prisons in low- and middle-income countries: protocol for a systematic review of prevalence and risk factors
Bibliographic record
Abstract
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).
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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 arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | low |
| gpt | no category Domain: not available · Genre: Protocol About the Canadian research system: no · About a Canadian topic: no | Systematic review | high |
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.074 | 0.089 |
| Meta-epidemiology (narrow) | 0.006 | 0.006 |
| Meta-epidemiology (broad) | 0.022 | 0.021 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.005 | 0.007 |
| Research integrity | 0.007 | 0.007 |
| Insufficient payload (model declined to judge) | 0.058 | 0.007 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedLabeled directly by 2 models reading the full record.
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".