Cannabis Use and Cognitive Impairment Among Male Adolescents: A Case-control Study
Bibliographic record
Abstract
Cannabis use by adolescents is a public health problem because it can cause cognitive impairment and educational deterioration. The objective of this study was to assess the prevalence and correlates of cognitive impairment among male adolescents with cannabis use in comparison with a control group. This is a case-control study that included 1682 adolescents who just finished their secondary school. A drug screen was made for all participants. Cognitive assessment using Montreal Cognitive Assessment (MoCA) scale was carried out for adolescents with positive urine screen for cannabis and a control group of adolescents with negative urine screen for drugs. The prevalence of cannabis use among adolescents was 2.14%. About one third of the cases started to use cannabis before the age of 15 years. Fifty-six percent used cannabis frequently (>4 times/wk). Adolescents with cannabis use were more likely to have cognitive impairment based on MoCA than controls (78% vs. 44%, P=0.004). Cases were more likely to have impairment in naming, abstraction, orientation, and total MoCA score than controls. Adolescents who started cannabis use early (below 15 y) had impairment in visuospatial/executive, attention, language, abstraction, delayed recall, and total MoCA score compared with those who started late (above 15 y). In addition, adolescents who use cannabis frequently had impairment in all cognitive domains except naming compared with those who used it occasionally. To conclude, the current study found that adolescents with cannabis use were more likely to have cognitive impairment than controls and this impairment was associated with age of onset and frequency of cannabis use.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".