Prison health and public health responses at a regional prison in Western Australia
Bibliographic record
Abstract
OBJECTIVE: To describe the health of inmates in a Western Australian regional prison and evaluate the coverage of public health interventions. DESIGN: Cross-sectional audit of all paper-based and electronic medical notes of inmates at one regional prison in Western Australia. SETTING: A mixed medium-security prison in regional Western Australia. PARTICIPANTS: 185 prisoners, 170 men and 15 women. MAIN RESULTS: The prisoners were mainly young (70% < 35 years of age) and Indigenous (84%). Fifty two percent of prisoners had at least one chronic health condition. There was a significantly higher prevalence of diabetes to that found in the general Indigenous population (15% vs 6% p=0.001), and a significantly lower prevalence hepatitis C (4.5%) compared with both national (29-61%) and State (20%) data. Screening for sexually transmitted infections and blood borne viruses within the first month of incarceration was achieved for 43% of inmates. Vaccination coverage for influenza (36%) and pneumococcal disease (12%) was low. CONCLUSION: This study makes visible the burden of disease and reach of public health interventions within a largely Indigenous regional prisoner population. Our study demonstrates that the additional risks associated with being Indigenous remain in a regional Australian prison but also shows that interventions can be delivered equitably to Indigenous and non-Indigenous inmates. IMPLICATIONS: Ongoing monitoring of prisoner health is critical to take advantage of opportunities to improve public health interventions with timely STI and BBV screening and increased vaccinations rates.
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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 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".