Awareness and knowledge of the Good Samaritan Drug Overdose Act among people at risk of witnessing an overdose in British Columbia, Canada: a multi-methods cross sectional study
Bibliographic record
Abstract
INTRODUCTION: Bystanders to drug overdoses often avoid or delay calling 9-1-1 and cite fear of police involvement as a main reason. In 2017, the Good Samaritan Drug Overdose Act (GSDOA) was enacted by the Canadian government to provide people present at an overdose with legal protection from charges for simple drug possession, and conditions stemming from simple possession. Few studies have taken a multi-methods approach to evaluating the GSDOA. We used quantitative surveys and qualitative interviews to explore awareness, understanding, and perceptions of the GSDOA in people at risk of witnessing an overdose. METHODS: Quantitative cross-sectional surveys and qualitative telephone interviews were conducted with adults and youth at risk of witnessing an overdose across British Columbia. Cross-sectional survey participants were recruited at 19 Take Home Naloxone sites and online through Foundry. Multivariable logistic regression models were constructed hierarchically to determine factors associated with GSDOA awareness. Telephone interview participants were recruited by research assistants with lived/living experience of substance use. Deductive and inductive thematic analyses were conducted to identify major themes. RESULTS: Overall, 52.7% (n = 296) of the quantitative study sample (N = 453) reported being aware of the GSDOA. In multivariable analysis, cellphone possession (adjusted odds ratio [AOR] = 2.19; 95% confidence interval [CI] 1.36, 3.54) and having recently witnessed an opioid overdose (AOR = 2.34; 95% CI 1.45, 3.80) were positively associated with GSDOA awareness. Young adults (25 - 34 years) were more likely to be aware of the Act (AOR = 2.10; 95% CI 1.11, 3.98) compared to youth (16-24 years). Qualitative interviews (N = 42) revealed that many overestimated the protections offered by the GSDOA. To increase awareness and knowledge of the Act among youth, participants recommended adding the GSDOA to school curricula and using social media. Word of mouth was suggested to reach adults. CONCLUSION: Both awareness and knowledge of the GSDOA remain low in BC, with many overestimating the protections the Act offers. Dissemination efforts should be led by people with lived/living experience and should target those with limited awareness and understanding of the Act as misunderstandings can erode trust in law enforcement and harm reduction policy.
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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".