Bibliographic record
Abstract
Suicide is an important public health problem in the demographic group that forms the bulk of military populations, namely young and middle-aged men. Suicide in the military also has special significance: certain aspects of military service can lead to serious mental disorders that increase the risk of suicidal behaviour. Moreover, military organizations have control over a broad range of factors (notably the direct delivery of mental health care) that could mitigate suicide risk. This article will review the literature on suicide risk in military organizations to answer the important question: Are military personnel at increased risk for suicide? Next, Mann et al.'s (2005) model for specific suicide preventive interventions in civilian settings will be reviewed and then expanded, with an emphasis on identifying special opportunities for suicide prevention in military organizations, including: 1) organizational interventions to mitigate work stress; 2) selection, resilience training, and risk factor reduction; 3) interventions to overcome barriers to care; and 4) systematic quality improvement efforts in mental health care. Finally, the evidence behind comprehensive suicide prevention programmes will be reviewed, with a special focus on the US Air Force's benchmark programme.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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; both teacher heads agree on what is shown here.
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".