Assessment of need for inpatient treatment for mental disorder among female prisoners: a cross-sectional study of provincially detained women in Ontario
Bibliographic record
Abstract
BACKGROUND: International studies show a consistent finding of women in prisons as having a high prevalence of mental disorder. Most will be treated within the prison however the most severely ill require transfer to a hospital facility. The primary aim of our study was to survey the total provincial female prison population in Ontario, Canada, to determine the proportion that require treatment in a psychiatric hospital, and the security level required. The secondary aim was to investigate the validity and psychometric properties of DUNDRUM-1 and DUNDRUM-2 in making these assessments. METHODS: We carried out a cross-sectional study of all remand and sentenced female inmates detained in all 16 provincial jails that hold women in Ontario. The severity of mental health need was categorised by mental health staff on a five-point scale. Two forensic psychiatrists then examined all medical files of prisoners that had been categorised in the highest two categories and a random sample of nearly a quarter of those in the third category. An overall opinion was then made as to whether admission was required, and whether a high intensity bed was needed, and files were rated using DUNDRUM-1 and DUNDRUM-2. RESULTS: There were 643 female inmates in provincial prisons in Ontario. We estimated that approximately 43 (6.7%) required admission to a hospital facility, of which 21.6 [prorated] (3.4%) required a high intensity bed such as a psychiatric intensive care bed within a secure hospital. The DUNDRUM-1 and -2 tools showed good internal validity. Total scores on both DUNDRUM-1 and DUNDRUM-2 were significantly different between those assessed as needing admission and those who did not, and distinguished the level of security required. CONCLUSION: This is the first study to determine level of need for prison to hospital transfers in Canada and can be used to inform service capacity planning. We also found that the DUNDRUM toolkit is useful in determining the threshold and priorities for hospital transfer of female prisoners.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".