Coping style as a risk factor for future alcohol use disorder: A 16-year longitudinal study in a Canadian military sample
Bibliographic record
Abstract
BACKGROUND: Coping strategies used in response to stress have the potential to influence the development of mental health disorders, including alcohol use disorders. The current study investigated whether coping strategies placed an individual at greater likelihood for developing a future alcohol use disorder. METHODS: This study used data from the Canadian Armed Forces Members and Veterans Mental Health Follow-up Survey; a nationally representative 16-year follow-up survey, with initial data collected in the 2002 Canadian Community Health Survey - Canadian Forces Supplement. The total sample from the two datasets included 2941 individuals who were Regular Force members in 2002. Coping styles included problem-focused, avoidant, and self-medication. Adjusted logistic regression analyses examined relationships between coping style (in 2002) and alcohol use disorders (developed between 2002 and 2018). RESULTS: Self-medication coping in 2002 was associated with any alcohol disorder since last interview (i.e., 2002-2018) (AOR 1.26; 95 % CI, 1.02-1.57) and during the past year (adjusted odds ratios [AOR 1.26; 95 % CI, 1.08-1.47]), as well as past-year binge drinking (AOR 1.19; 95 % CI, 1.09-1.29). Problem-focused coping was protective against past-year alcohol abuse (AOR 0.84; 95 % CI, 0.71-1.00) and any alcohol use disorder (AOR 0.87; 95 % CI 0.76-1.00). CONCLUSION: Coping styles were strongly associated with future alcohol use disorders. Notably, results show the risk extended over a 16-year period. Findings suggest the use of self-medicating coping strategies places an individual at increased risk of developing alcohol use disorders, while problem-focused coping may decrease future risk of alcohol use disorders.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".