“If You Need to Light Up … You Gotta Do What You Gotta Do”: A Qualitative Study of Adolescent Attitudes Towards Cannabis Use and Comparison with Alcohol Attitudes
Bibliographic record
Abstract
Objective: Cannabis and alcohol are among the substances most frequently used by adolescents. Adolescents also frequently co-use these substances, with use of alcohol predicting subsequent initiation of cannabis use, and vice-versa. Minimal research has explored adolescents' attitudes towards cannabis use qualitatively, and how these attitudes may directly/indirectly relate to attitudes towards alcohol use and vice versa. Method: = 0.86) who had recently completed a study reporting their in-vivo exposure to substance use content in media completed follow-up interviews focused on substance depictions in media and attitudes towards substance use. Interviews were individual, semi-structured, and approximately one hour long. A priori codes were derived from the interview agenda. Interviews were transcribed and qualitatively coded by a team of three graduate students. Percent agreement across coders was 80%, suggesting substantial agreement. Results: Several themes emerged from analysis. Most adolescents reported that their approval/disapproval of cannabis use was contingent on several factors including legality, age, degree of use/problematic use, and purpose (i.e., medicinal/recreational). Participants more commonly endorsed cannabis use as more acceptable than alcohol. Common reasons for this comparative approval included perceived social and health impacts (e.g., alcohol poisoning, liver disease), perceived addictive potential, and different effects of intoxication. Conclusions: Results of the present study provide rich context to recent trends in adolescent cannabis and alcohol use and perceptions, as well as co-use and abstention. Understanding teens' attitudes towards substance use may be beneficial in developing appropriate substance prevention and intervention strategies (e.g., effectively communicating health risks 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 | 0.009 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.007 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".