Youth cannabis use in Canada post-legalization: service providers’ perceptions, practices, and recommendations
Bibliographic record
Abstract
BACKGROUND: In 2018, Canada legalized recreational cannabis use with the purpose of protecting youth and restricting access. However, concerns have been raised that this objective has not been met as rates of cannabis use among youth aged 16-24 have not declined. Youth cannabis use is associated with various adverse effects including psychosis, anxiety, depression, suicidality, respiratory distress, cannabinoid hyperemesis syndrome, and intoxications. Service providers play a crucial role in addressing youth cannabis use. This study aimed to understand Ontario service providers' perceptions, practices, and recommendations on youth cannabis use. METHODS: This mixed method study included a survey and two focus groups. The survey was distributed to mental health service providers serving youth aged 16-24 across Ontario who were given the option to participate in a focus group. The survey included closed and open-ended questions regarding perceptions, practices, and recommendations, while the focus groups explored these categories in greater depth. Descriptive statistics were used to analyze close-ended questions and interpretative content analysis was applied for open-ended questions. Focus group data were analyzed using thematic analysis. RESULTS: The survey was completed by 160 service providers and 12 participated in two focus groups. Regarding perceptions, 60% of survey participants agreed with legalization, 26% had a strong understanding of medical versus recreational cannabis, 84% believed that cannabis has physical and mental health risks, and 49% perceived stigmatization. Less than half of the survey participants reported screening or assessing cannabis use, 16% stated they are highly familiar with treating cannabis use, and 67% reported that they rarely work with families. Subthemes identified in the focus groups under perceptions included normalization and stigmatization, harms for youth, and stigma, racism, and discrimination. Subthemes under practice included cannabis not being the primary focus, challenges with screening, assessment, and intervention, and referral to specialized services. Both the survey and focus group participants recommended increasing public education, enhancing service provider training, improving regulation and policies, reducing stigma and minimization, improving service access, and providing more culturally responsive services. CONCLUSION: Youth cannabis use in Canada remains a significant public health concern, necessitating a more comprehensive plan to protect Ontario youth and reduce associated harms.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".