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Record W4376131230 · doi:10.1136/bmjopen-2022-071379

Awareness, predictors and outcomes of drug alerts among people who access harm reduction services in British Columbia, Canada: findings from a 2021 cross-sectional survey

2023· article· en· W4376131230 on OpenAlexafffundabout
Kerolos Daowd, Max Ferguson, Lisa Liu, Jackson Loyal, Kurt Lock, Brittany Graham, Jessica Lamb, Jenny McDougall, Jane A. Buxton

Bibliographic record

VenueBMJ Open · 2023
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsSimon Fraser UniversityBC Centre for Disease ControlUniversity of British Columbia
FundersHealth Canada
KeywordsMedicineHarm reductionOddsCross-sectional studyOdds ratioHarmPoison controlPublic healthInjury preventionOccupational safety and healthPsychological interventionFamily medicineHearing lossSuicide preventionPsychiatryEnvironmental healthAudiologyLogistic regressionNursingInternal medicinePsychologySocial psychology

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess the awareness and predictors of seeing/hearing a drug alert in British Columbia (BC) and subsequent drug use behaviour after seeing/hearing an alert. METHODS: This study analysed the 2021 BC harm reduction client survey (HRCS)-a cross-sectional self-reported survey administered at harm reduction sites throughout the province and completed by participants using the services. RESULTS: In total, n=537 respondents participated and n=482 (89.8%) responded to the question asking if they saw/heard a drug alert. Of those, n=300 (62.2%) stated that they saw/heard a drug alert and almost half reported hearing from a friend or peer network; the majority (67.4%) reported altering their drug use behaviour to be safer after seeing/hearing a drug alert. The proportion of individuals who saw/heard a drug alert increased with each ascending age category. Among health authorities, there were significant differences in the odds of seeing/hearing an alert. In the past 6 months, the odds of participants who attended harm reduction sites a few times per month seeing/hearing an alert were 2.73 (95% CI: 1.17 to 6.52) times the odds of those who did not. Those who attended more frequently were less likely to report seeing/hearing a drug alert. The odds of those who witnessed an opioid-related overdose in the past 6 months seeing/hearing an alert were 1.96 (95% CI: 0.86 to 4.50) times the odds of those who had not. CONCLUSION: We found that drug alerts were mostly disseminated through communication with friends or peers and that most participants altered their drug use behaviour after seeing/hearing a drug alert. Therefore, drug alerts can play a role in reducing harms from substance use and more work is needed to reach diverse populations, such as younger people, those in differing geographical locations, and those who attend harm reduction sites more frequently.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.080

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.065
GPT teacher head0.391
Teacher spread0.326 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2023
Admission routes3
Has abstractyes

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