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Record W2046351839 · doi:10.3109/14659891.2013.784369

Nonfatal overdose from alcohol and/or drugs among a sample of recreational drug users

2013· article· en· W2046351839 on OpenAlexafffundabout
Gina Martin, Kate Vallance, Scott Macdonald, Tim Stockwell, Andrew Ivsins, Clifton Chow, Warren Michelow, Cameron Duff

Bibliographic record

VenueJournal of Substance Use · 2013
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsUniversity of British ColumbiaVancouver Coastal HealthUniversity of VictoriaCentre for Addiction and Mental Health
FundersCanadian Institutes of Health Research
KeywordsPolysubstance dependenceRecreational DrugMedicineRecreationRecreational drug useDrugEnvironmental healthDrug overdosePsychiatrySubstance abusePoison control

Abstract

fetched live from OpenAlex

The purpose of this study was to examine nonfatal overdose events experienced among a sample of recreational drug users. We sought to determine predictors of nonfatal overdose from alcohol and/or drugs among a sample of recreational drug users. In addition, we examined the substance(s) used at the last overdose event. Methods: Participants were 637 recreational illicit drug users (had used illicit drugs other than marijuana, in a club or party setting), aged 19 or older, from Victoria or Vancouver, British Columbia, Canada. Data were obtained in structured interviews conducted from 2008 to 2012 as part of the Canadian Recreation Drug Use Survey (CRDUS). Results: In the 12 months prior to interview, 19.3% (n = 123) of the participants had experienced an overdose. In multivariate analysis, younger age, unstable housing, and usually consuming eight or more drinks containing alcohol, when drinking, significantly increased overdose risk. In addition, polysubstance use was reported by 67.5% (n = 83) participants at their last overdose event. Conclusions: Intervention and prevention measures seeking to reduce overdoses among recreational drug users should not only address illicit drug use but also alcohol and polysubstance use. In addition, measures may target those who usually consume high amounts of alcohol when drinking are younger and who experience housing instability.

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 score0.013
Threshold uncertainty score0.639

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 communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.022
GPT teacher head0.267
Teacher spread0.245 · 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

Citations10
Published2013
Admission routes3
Has abstractyes

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