Self-harm and suicidal behaviour among incarcerated adults in the Australian Capital Territory
Bibliographic record
Abstract
BACKGROUND: Suicide is the leading cause of death in prisons worldwide. Improved understanding of the factors associated with suicide is necessary to inform targeted suicide prevention and interventions. Here we aim to (a) document the prevalence of suicide attempts, suicidal ideation, self-harm, and mental disorder; and (b) identify demographic, mental health, and criminal justice correlates of suicidal ideation, in a sample of incarcerated adults in Australia. METHODS: Data were obtained from the 2016 Detainee Health and Wellbeing Survey conducted in the Alexander Maconochie Centre, the Australian Capital Territory's only adult prison. Interviews with 98 incarcerated adults were conducted in October 2016. Descriptive statistics were calculated for all measures. Crude differences between participants who reported experiencing suicidal ideation in their lifetime and those who did not were compared using Fisher's exact test. RESULTS: Nearly half of the participants (48%, n = 47) reported lifetime suicidal ideation and 31% (n = 30) reported attempting suicide at some point in their lives. Eighteen participants (18%) reported a lifetime history of having engaged in self-harm. Factors significantly associated with suicidal ideation included lifetime history of mental disorder, self-harm, experiencing a drug overdose, and being hospitalized in the past 12 months. CONCLUSION: The burden of suicidal ideation and prior suicide attempts among people in prison is substantial. Incarceration is a pivotal opportunity to identify people with a history of mental health problems and target interventions aimed at reducing adverse outcomes including suicide mortality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".