Correlates of cannabis use and cannabis use disorder among adolescents with major depressive disorder and bipolar disorder in the National Comorbidity Survey-Adolescent Supplement (NCS-A)
Bibliographic record
Abstract
BACKGROUND: Despite evidence regarding prevalence and correlates of cannabis use (CU) and cannabis use disorder (CUD) in major depressive disorder (MDD) and bipolar disorder (BD) in adults, little is known about this topic among adolescents. METHODS: Data are from the 2001-2004 National Comorbidity Survey-Adolescent Supplement, an in-person, cross-sectional epidemiologic survey of mental disorders. Participants included adolescents, ages 13-18 years, with MDD (n = 354 with CU, n = 70 with CUD, n = 688 with no CU), BD (n = 79 with CU, n = 32 with CUD, n = 184 with no CU), or adolescents without mood disorders (n = 1413 with CU, n = 333 with CUD, n = 6970 with no CU). Analyses examined prevalence and correlates of CU and CUD within MDD and BD groups. RESULTS: CU was most prevalent in adolescents with MDD followed by adolescents with BD then controls. CUD was most prevalent in adolescents with BD followed by adolescents with MDD then controls. In covariate-adjusted ordinal logistic regression models, within MDD and BD, CU and CUD groups had significantly higher odds of lifetime suicidal ideation/attempts, as well as other significant indicators of clinical severity. LIMITATIONS: Based on changes in cannabis acceptance, potency, and availability in the two decades since this study was conducted, present findings may underestimate adverse cannabis associations. CONCLUSION: CU and CUD are both associated with adverse clinical characteristics in a community-based sample of adolescents with MDD and BD. Evidence that risks of cannabis use extend across the spectrum of use is important for adolescents with MDD and BD, in whom cannabis-related consequences tend to be more severe.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".