Natural outcome of cannabis use disorder: a 3‐year longitudinal follow‐up
Bibliographic record
Abstract
AIMS: To assess the prevalence and correlates of remission from cannabis use disorders (CUDs), focusing on the proportion of individuals with CUDs that remit without abstaining from cannabis use. DESIGN: Three-year longitudinal study. SETTING: Wave 1 (2001) and wave 2 (2004) of the National Epidemiologic Survey on Alcohol and Related Conditions (NESARC), a nationally representative sample of US adults aged 18 years and over. PARTICIPANTS: Our sample included 444 individuals diagnosed with DSM-IV cannabis abuse and/or dependence during the 12 months prior to wave 1 of the NESARC. MEASUREMENTS: Baseline socio-demographic and clinical correlates were analysed for possible outcomes of CUDs after 3 years: abstinent remission, non-abstinent remission and sustained disorder. FINDINGS: Approximately two-thirds (67%) of individuals with baseline CUD remitted at follow-up. Approximately 37% of those who remitted were non-abstinent. Remission was associated with Hispanic ethnicity [odds ratio (OR)=2.59; 95% confidence interval (CI)=1.27-4.87], baseline daily or almost daily use of cannabis (OR=1.91; 95% CI=1.15-3.16), baseline use of other drugs (OR=1.63; 95% CI=1.04-2.56) and two or more medical conditions at baseline (OR=8.40; 95% CI=2.67-26.41). Non-abstinent remission was associated with baseline daily or almost daily use of cannabis (OR=1.92; 95% CI=1.05-3.51). CONCLUSIONS: A substantial level of remission from cannabis use disorders (CUDs), including non-abstinent remission, suggests that the nature of CUDs may be more unstable than reported previously.
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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".