A survey of educator perspectives toward teaching harm reduction cannabis education
Bibliographic record
Abstract
INTRODUCTION: Substance use is common among youth which can adversely affect youth health. Despite the legalization of cannabis in Canada and much of the United States, there is a lack of harm reduction cannabis education in schools. In addition, educators may not feel prepared to teach students about cannabis. METHODS: A cross-sectional survey explored educator perceptions toward teaching harm reduction substance use education to students in grades 4-12. Data analysis included descriptive statistics to evaluate demographic variables, ANOVAs to identify subgroup differences, and inductive thematic analysis to establish themes from open-ended responses. From the sample of 170 educators, the majority were female (77%) and worked as classroom teachers (59%). RESULTS: Ninety-two percent of educators felt harm reduction was an effective approach to substance use education, and 84% stated that they would feel comfortable teaching cannabis harm reduction education to students. While 68% of educators believed they would be able to recognize if a student was under the influence of cannabis, only 39% felt certain about how to respond to student cannabis use, and just 8% felt that their current teacher training allowed them to intervene and prevent cannabis-related harms. Most educators (89%) expressed interest in harm reduction training, particularly interactive training (70%) and instructor-led lessons (51%). Online curriculum resources were preferred by 57%. Responses differed by gender and age group, with females of any age and educators under 40 reporting greater support of harm reduction approaches and more interest in training. CONCLUSION: Educators expressed considerable support for harm reduction substance use education, but many felt unprepared to address this topic with students. The findings identified a need for educator training on harm reduction substance use education, so that educators can help students make informed choices around substance use, thereby promoting youth health and safety.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".