Light Cannabis Use and the Adolescent Brain: An 8-years Longitudinal Assessment of Mental Health, Cognition, and Reward Processing
Bibliographic record
Abstract
RATIONALE: For decades, cannabis has been the most widely used illicit substance in the world, particularly among youth. Research suggests that mental health problems associated with cannabis use may result from its effect on reward brain circuit, emotional processes, and cognition. However, findings are mostly derived from correlational studies and inconsistent, particularly in adolescents. OBJECTIVES AND METHODS: Using data from the IMAGEN study, participants (non-users, persistent users, abstinent users) were classified according to their cannabis use at 19 and 22 years-old. All participants were cannabis-naïve at baseline (14 years-old). Psychopathological symptoms, cognitive performance, and brain activity while performing a Monetary Incentive Delay task were used as predictors of substance use and to analyze group differences over time. RESULTS: Higher scores on conduct problems and lower on peer problems at 14 years-old (n = 318) predicted a greater likelihood of transitioning to cannabis use within 5 years. At 19 years of age, individuals who consistently engaged in low-frequency (i.e., light) cannabis use (n = 57) exhibited greater conduct problems and hyperactivity/inattention symptoms compared to non-users (n = 52) but did not differ in emotional symptoms, cognitive functioning, or brain activity during the MID task. At 22 years, those who used cannabis at both 19 and 22 years-old n = 17), but not individuals that had been abstinent for ≥ 1 month (n = 19), reported higher conduct problems than non-users (n = 17). CONCLUSIONS: Impairments in reward-related brain activity and cognitive functioning do not appear to precede or succeed cannabis use (i.e., weekly, or monthly use). Cannabis-naïve adolescents with conduct problems and more socially engaged with their peers may be at a greater risk for lighter yet persistent cannabis use in the future.
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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 | 0.001 | 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".