Negative Alcohol and Tobacco Consumption Behaviors in an Australian Army Combat Brigade
Bibliographic record
Abstract
Abstract Introduction Western militaries have consumption rates of alcohol and tobacco which are higher than the associated civilian populations, and are concerned about the negative effects on health, wellbeing, and military performance that such high rates may have. Materials and Methods A survey questionnaire which collected nonidentifiable data was distributed to all accessible members of an Australian Army Combat Brigade over the annual induction training and prefield exercise period between January and March 2019. The survey was composed of personal and demographic questions, followed by questions concerning the personal consumption habits of alcohol and tobacco. 1,606 complete and valid surveys were returned, representing 55.3% of the Brigade’s posted strength. Ethical clearance for this project was provided by the Australian Defence Force Joint Health Command Low Risk Ethics Panel (18-012). Results Almost one quarter of the Combat Brigade exceeded the Australian daily risk guideline for alcohol consumption, and over three quarters exceeded the occasion risk guideline; with 6.1% of soldiers drinking alcohol daily. 24.3% identified as tobacco smokers, with 15.9% smoking daily. Smoking rates and volumes were higher when deployed on field training exercises and on international training and operational deployments; as was the consumption of roll-your-own cigarettes. Overall, the main determinants of the negative consumption behaviors were gender (male) and age (under 25). Conclusions This study confirmed that the members of an Australian Army Combat Brigade have higher negative health consumption behaviors concerning alcohol and tobacco than the general civilian population. The results also identified a cohort of Senior Non-Commissioned Officers and Warrant Officers (E5–E9) between the ages of 35 and 44 who had high negative consumption behaviors which could result in poor health outcomes. This could be a suitable cohort for a targeted campaign to reduce tobacco and alcohol consumption and to assist to make healthy life changes.
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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 | 0.000 | 0.001 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".