Cannabis use, addiction risk and functional impairment in youth seeking treatment for primary mood or anxiety concerns
Bibliographic record
Abstract
Cannabis use is common in youth and there is evidence that the co-occurrence of cannabis use (and other substance use) with mental illnesses predicts poorer outcomes, including suicide. The main purposes of this study were to: (i) identify rates of cannabis use and substance use disorder risk, and (ii) predictors for cannabis use among youth seeking help for mood and/or anxiety concerns in a sample population prescreened to exclude primary substance use disorders; and (iii) to determine if there was an association between cannabis use and functional impairment in this sample. We investigated substance use risk as well as hypothesized predictors of cannabis use and functional impairment including demographic characteristics, socioeconomic status, trait coping style, age of onset of several risk behaviors, current use of common addictive substances, level of functional impairment, and current psychiatric symptom severity. Results showed that approximately half of the participants were at moderate to high risk for a substance use disorder, and just over 4% appeared to have a primary substance use disorder. They also suggested an association between cannabis use and gender (male), age of first cannabis use, recent cigarette use, and functional impairment. Independently, functional impairment was predicted by inattentive coping style, depression severity, and total cannabis use score. These results confirm a high risk for addictive disorders and an association between cannabis use and functional impairment in this sample. These results support the need for substance use treatment programs to optimize care wherever youth with primary mood and/or anxiety concerns are seen.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".