Measuring the Prevalence of Current, Severe Symptoms of Mental Health Problems in a Canadian Correctional Population
Bibliographic record
Abstract
This study measured the prevalence of current, severe symptoms of a mental health problem in an adult population of inmates in Ontario, Canada. The Resident Assessment Instrument-Mental Health was used to measure the prevalence of symptoms among a sample of 522 inmates. Propensity score weighting was used to adjust for nonrandom selection into the sample. Prevalence estimates were derived for the total inmate population, remand and sentenced, males and females, and Aboriginal and non-Aboriginal inmates. It is estimated that 41.1% of Ontario inmates will have at least one current, severe symptom of a mental health problem; of this group, 13.0%, will evidence two or more symptoms. The number of symptoms is strongly associated with presence of a psychiatric diagnosis and level of mental health care needs. Female (35.1%) and Aboriginal (18.7%) inmates are more likely to demonstrate two or more current, severe symptoms. Greater efforts must be made to bridge the gap between correctional and mental health care systems to ensure inmates in correctional facilities can access and receive appropriate mental health care services.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".