A qualitative study of experiences among young adults who increased their cannabis use during the COVID-19 pandemic
Bibliographic record
Abstract
BACKGROUND: Young adults face unique vulnerabilities during major life disruptions like the COVID-19 pandemic. The pandemic contributed to increases in mental health challenges and substance use among young adults. This study explores the experiences of young adults who increased their cannabis use during the pandemic. METHODS: Participants were recruited from the Nicotine Dependence in Teens (NDIT) study, and qualitative data were collected through semi-structured interviews conducted via Zoom. A total of 25 participants (ages 33-34) reporting increased cannabis use during the pandemic were included. Thematic analysis and gender-based analysis was employed to extract key themes. RESULTS: Five themes emerged: (1) No disruption in cannabis use; (2) Cannabis use to manage declines in mental health; (3) Cannabis use to break up pandemic boredom; (4) Cannabis use as an expression of freedom; (5) Cannabis use as "another way to chill out." CONCLUSIONS: This research provides valuable perspectives on how major life disruptions, like the COVID-19 pandemic, influence cannabis use among young adults. The findings offer guidance for public health initiatives and highlight avenues for further investigation.
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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 | 0.006 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".