The relationship between age and suicidal thoughts and attempted suicide among prisoners
Bibliographic record
Abstract
BACKGROUND: Suicide is a major problem across the lifespan, yet rates are highest among middle-aged and older adults; a trend which remains relatively stable across varying sociological settings, including prisons. Despite this understanding, there is limited knowledge on the nature of suicidal thoughts and attempts among older prisoners, especially with respect to how they compare to younger counterparts. The present study aimed to increase insight into the relationship between age and suicidal thoughts and attempted suicide among prisoners, with particular focus on factors that may explain age-based variability. RESULTS: Cross-sectional data were drawn from a nationally representative sample of 18,185 prisoners housed within 326 prisons across the United States. In general, analyses revealed that: (a) attempted suicide was more commonly reported among younger prisoners, while suicidal ideation was more commonly reported among older prisoners; (b) the relationship between age and probability of reporting suicidal thoughts and behavior is curvilinear; (c) younger and older prisoners exhibit somewhat differing predictive patterns of suicidal thoughts and behavior (e.g., physical illness is directly associated with suicidal history for younger prisoners, whereas the effect of physical illness on suicidal history for older prisoners is mediated by depression). CONCLUSIONS: There is evidence to suggest that suicidal thoughts and behavior may manifest differently for younger and older prisoners, with differing patterns of risk. More research is needed on age-based variability in suicidal thoughts and attempted suicide among prisoners, as well as those factors that might explain this variability. Importantly, future research must continue to investigate the nature of suicidal thoughts and behavior among older prisoners.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".