Individual Augmentee Deployment and Newly Reported Mental Health Morbidity
Bibliographic record
Abstract
OBJECTIVE: To investigate the association between US Navy individual augmentee (IA) deployers, who may lack the protective effects of unit cohesion and social support, and newly reported mental health. METHODS: Responses from the Millennium Cohort Study questionnaires were examined for 2086 Navy deployers in this prospective exploratory study. Multivariable logistic regression was used to evaluate IA deployment and newly reported mental health symptoms. RESULTS: After adjusting for covariates, IA deployment was not significantly associated with newly reported posttraumatic stress disorder (odds ratio = 1.02; 95% confidence interval: 0.53-1.95) or mental health symptoms (odds ratio = 1.03; 95% confidence interval: 0.66-1.60) compared with non-IA deployment. CONCLUSION: IA deployment was not associated with increased risk for posttraumatic stress disorder or mental health symptoms following deployment. It is likely that social isolation was not highly influential among Navy IAs in this study.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.003 | 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".