Help seeking for self-reported alcohol problems among serving and ex-serving personnel: A cross-sectional study
Bibliographic record
Abstract
Introduction: Research has found low levels of help seeking for alcohol problems among serving and ex-serving military populations. This study aimed to understand the prevalence of, and factors associated with, help seeking for self-reported alcohol problems among serving and ex-serving UK military personnel. Methods: Regular and full-time reserve serving and ex-serving personnel in a large UK military cohort (N = 6,199) were asked whether they had an alcohol problem in the past three years and whether and where they sought help. Associations between help seeking from formal medical services (general practitioner/medical officer, hospital doctor) and socio-demographic, military, life, and health factors were examined using weighted survey methods. Results: = 0.032) were less likely to have previously accessed formal support. Discussion: Help seeking for self-reported alcohol problems among UK serving and ex-serving personnel remains low. Future research should prioritize understanding pathways into help seeking and target stigma regarding accessing clinical support among both serving and ex-serving personnel.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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; 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".