History of Childhood Abuse in Populations Incarcerated in Canada: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: A history of childhood abuse may affect people's health and criminal justice system involvement. Understanding the prevalence of childhood abuse among individuals in prison is important to inform effective and appropriate correctional services. OBJECTIVES: To review and summarize data on the prevalence of childhood abuse among people experiencing imprisonment in Canada. SEARCH METHODS: We searched for studies in bibliographic indexes, reference lists, and gray literature, and we consulted experts. SELECTION CRITERIA: We included studies published since 1987 that reported data on prevalence of a history of abuse before the age of 18 years among people in Canadian prisons, including any abuse, physical abuse, sexual abuse, emotional abuse, and neglect. DATA COLLECTION AND ANALYSIS: Two authors independently reviewed titles and abstracts for eligibility and reviewed full texts for eligibility. Analyses included summary estimates and meta-regression with random effects. MAIN RESULTS: The search identified 1429 records. We included 34 unique studies in our review and 29 nonoverlapping studies in our meta-analysis. The summary prevalence for any type of childhood abuse was 65.7% (95% confidence interval [CI] = 52.6, 77.7; range = 56.2% to 75.0%) among women; only one study reported the prevalence among men (35.5%). The summary prevalence of sexual abuse was 50.4% (95% CI = 33.5, 67.2; range = 9.9% to 77.3%) among women and 21.9% (95% CI = 15.7, 28.8; range = 8.3% to 55.6%) among men. The prevalence of neglect was 51.5% (95% CI = 43.1, 59.7; range = 45.5% to 65.1%) among women and 42.0% (95% CI = 12.7, 74.6; range = 6.8% to 99.0%) among men. The prevalence of physical abuse was 47.7% (95% CI = 41.3, 54.0; range = 16.3% to 83.0%), and the prevalence of emotional abuse was 51.5% (95% CI = 34.8, 67.9; range = 8.7% to 96.0%); we did not find differences according to gender. Prevalence estimates for all types of abuse showed high and unexplained variability across studies. CONCLUSIONS: Half of people in prisons in Canada experienced abuse in childhood. Public Health Implications. Prisons should incorporate trauma-informed approaches. Research is required to understand the association between a history of childhood abuse and criminal justice system involvement and to prevent childhood abuse and mitigate its adverse effects. Systematic Review Registration. PROSPERO CRD42017056192.
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How this classification was reachedexpand
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 | 0.014 | 0.046 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.015 | 0.028 |
| Bibliometrics | 0.012 | 0.016 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".