The association between anxiety and alcohol versus cannabis abuse disorders among adolescents in primary care settings
Bibliographic record
Abstract
BACKGROUND: Both clinical and population-based studies show that anxiety disorders and substance misuse frequently co-occur in adults, whereas among adolescents, less examination of this association has been done. Adolescence is frequently the time of substance use initiation and its subsequent interaction with anxiety disorders has not been fully explored. It is unknown in adolescents whether anxiety is more related to alcohol abuse versus cannabis abuse. In addition, as depression has been implicated in adolescents with both anxiety and substance misuse, its role in the association should also be considered. OBJECTIVE: To test the association between current anxiety with alcohol versus cannabis abuse disorders. METHOD: Cross-sectional, clinician-administered, structured assessment--using the Primary Care Evaluation of Mental Disorders--to evaluate anxiety, mood and substance abuse disorders among 632 adolescents recruited from primary care settings. RESULTS: Results show a strong association between current anxiety and alcohol [odds ratio = 3.8; 95% confidence interval (CI) 1.2-11.8], but not cannabis (odds ratio = 1.4; 95% CI 0.4-4.7) abuse. CONCLUSION: This association in adolescents reflects the importance for increased awareness of anxiety symptoms and alcohol use patterns in primary care. The lack of association of anxiety with cannabis abuse in this group may reflect differences in cannabis' anxiolytic properties or that this young group has had less exposure thus far. Given adolescence is a time of especially rapid psychosocial, hormonal and brain development, primary care may provide an opportunity for further investigation and, potentially, early screening and intervention.
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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 | 0.003 |
| 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 | 0.000 |
| Open science | 0.000 | 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".