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A qualitative study on perceptions and experiences of overdose among people who smoke drugs in Vancouver, British Columbia

2024· article· en· W4393320552 on OpenAlexafffundabout
Andrew Ivsins, Matthew Bonn, Ryan McNeil, Jade Boyd, Thomas Kerr

Bibliographic record

VenueDrug and Alcohol Dependence · 2024
Typearticle
Languageen
FieldMedicine
TopicSmoking Behavior and Cessation
Canadian institutionsCanadian AIDS SocietyUniversity of British ColumbiaBritish Columbia Centre on Substance Use
FundersNational Institute on Drug AbuseCanadian Institutes of Health ResearchNational Institutes of Health
KeywordsDrug overdoseMedicineThematic analysisDrugEnvironmental healthSmokePsychiatryPoison controlQualitative researchGeography

Abstract

fetched live from OpenAlex

BACKGROUND: Smoking unregulated drugs has increased substantially in British Columbia. Intersecting with the ongoing overdose crisis, drug smoking-related overdose fatalities have correspondingly surged. However, little is known about the experiences of overdose among people who smoke drugs accessing the toxic drug supply. This study explores perceptions and experiences of overdose among people who smoke drugs. METHODS: We conducted interviews with 31 people who smoke drugs. Interviews covered a range of topics including overdose experience. Thematic analysis was used to identify themes related to participant perceptions and experiences of smoking-related overdose. RESULTS: Some participants perceived smoking drugs to pose lower overdose risk relative to injecting drugs. Participants reported smoking-related overdose experiences, including from underestimating the potency of drugs, the cross-contamination of stimulants with opioids, and responding to smoking-related overdose events. CONCLUSIONS: Findings highlight the impact the unpredictable, unregulated, and toxic drug supply is having on people who smoke drugs, both among people who use opioids, and among those who primarily use stimulants. Efforts to address smoking-related overdose could benefit from expanding supervised smoking sites, working with people who use drugs to disseminate accurate knowledge around smoking-related overdose risk, and offering a smokable alternative to the unpredictable drug supply.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.977

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.026
GPT teacher head0.350
Teacher spread0.324 · 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 teacher head, 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

Citations19
Published2024
Admission routes3
Has abstractyes

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