Accuracy and predictive value of incarcerated adults' accounts of their self-harm histories: findings froman Australian prospective data linkage study
Bibliographic record
Abstract
BACKGROUND: Self-harm is prevalent in prison populations and is a well-established risk factor for suicide. Researchers typically rely on self-report to measure self-harm, yet the accuracy and predictive value of self-report in prison populations is unclear. Using a large, representative sample of incarcerated men and women, we aimed to examine the level of agreement between self-reported self-harm history and historical medical records, and investigate the association between self-harm history and medically verified self-harm after release from prison. METHODS: During confidential interviews with 1315 adults conducted within 6 weeks of expected release from 1 of 7 prisons in Queensland, Australia, participants were asked about the occurrence of lifetime self-harm. Responses were compared with prison medical records and linked both retrospectively and prospectively with ambulance, emergency department and hospital records to identify instances of medically verified self-harm. Follow-up interviews roughly 1, 3 and 6 months after release covered the same domains assessed in the baseline interview as well as self-reported criminal activity and contact with health care, social and criminal justice services since release. RESULTS: Agreement between self-reported and medically verified history of self-harm was poor, with 64 (37.6%) of 170 participants with a history of medically verified self-harm disclosing a history of self-harm at baseline. Participants with a medically verified history of self-harm were more likely than other participants to self-harm during the follow-up period. Compared to the unconfirmed-negative group, the true-positive (adjusted hazard ratio [HR] 6.2 [95% confidence interval (CI) 3.3-10.4]), false-negative (adjusted HR 4.0 [95% CI 2.2-6.7]) and unconfirmed-positive (adjusted HR 2.2 [95% CI 1.2-3.9]) groups were at increased risk for self-harm after release from prison. INTERPRETATION: Self-reported history of self-harm should not be considered a sensitive indicator of prior self-harm or of future self-harm risk in incarcerated adults. To identify those who should be targeted for preventive strategies, triangulation of data from multiple verifiable sources should be performed whenever possible.
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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 | 0.001 |
| Open science | 0.002 | 0.002 |
| 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".