Cannabis use among adolescents and young adults during the COVID-19 pandemic: A systematic review
Bibliographic record
Abstract
Background: A systematic review of the literature was performed to summarize cannabis use among adolescents and young adults during the COVID-19 pandemic. Special focus was given to the prevalence of cannabis use during COVID-19, as well as factors that may explain changes in cannabis consumption patterns. Methods: The protocol of this systematic review was registered. Articles from seven publication databases were searched in January 2022. The inclusion criteria for studies were as follows: 1) published in English; 2) study instruments needed to include items on COVID-19; 3) conducted after January 1st, 2020; 4) published in a peer-reviewed journal, dissertation, or thesis; 5) study population ≤25 years of age; 6) study designs were limited to observational analytical studies; 7) measured cannabis use. This review excluded other reviews, editorials, and conference abstracts that were not available as full text manuscripts. Independent review, risk of bias assessment, and data abstraction were performed by two authors. Results: Fifteen articles from the United States (n=11) and Canada (n=4) were included in this review. The findings of this review showed that the prevalence of cannabis use during the pandemic among adolescents and young adults were mixed. Some mental health symptoms, including depression and anxiety, were identified as the most commonly reported reasons for increased cannabis use during the pandemic. Conclusions: This review highlights the inconsistencies in the prevalence of cannabis use among adolescents and young adults during the pandemic. Therapeutic interventions for mental health and continued public health surveillance should be conducted to understand the long-term effects of cannabis use among adolescents and young adults.
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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 | 0.036 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".