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Record W4382400579 · doi:10.1186/s12954-023-00817-7

Impact of safer supply programs on injection practices: client and provider experiences in Ontario, Canada

2023· article· en· W4382400579 on OpenAlexafffundabout
Marilou Gagnon, Katherine Rudzinski, Adrian Guţă, Rose A. Schmidt, David T. Kryszajtys, Gillian Kolla, Carol Strıke

Bibliographic record

VenueHarm Reduction Journal · 2023
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsPublic Health OntarioUniversity of TorontoUniversity of WindsorUniversity of VictoriaCanadian Institute for Advanced Research
FundersCanadian Institutes of Health ResearchOntario HIV Treatment Network
KeywordsSAFERPsychological interventionHealth psychologyMedicineHarm reductionHydromorphoneBusinessOpioid overdoseNursingMedical emergencyPublic healthComputer securityOpioid

Abstract

fetched live from OpenAlex

OBJECTIVES: Fentanyl has contributed to a sharp rise in the toxicity of the unregulated drug supply and fatal overdoses in Canada. It has also changed injection practices. Injection frequency has increased as a result and so has equipment sharing and health-related risks. The aim of this analysis was to explore the impact of safer supply programs on injection practices from the perspective of clients and providers in Ontario, Canada. METHODS: The data set included qualitative interviews with 52 clients and 21 providers that were conducted between February and October 2021 across four safer supply programs. Interview excerpts discussing injection practices were extracted, screened, coded and then grouped into themes. RESULTS: We identified three themes, each theme corresponding to a change in injection practices. The first change was a decrease in the amount of fentanyl used and a decrease in injection frequency. The second change involved switching to injecting hydromorphone tablets instead of fentanyl. Finally, the third change was stopping injecting altogether and taking safer supply medications orally. CONCLUSION: Safer supply programs can contribute to reducing injection-related health risks in addition to overdose risks. More specifically, they have the potential to address disease prevention and health promotion gaps that stand-alone downstream harm reduction interventions cannot address, by working upstream and providing a safer alternative to fentanyl.

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 score0.354
Threshold uncertainty score0.672

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 integrity0.0000.001
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 head0.075
GPT teacher head0.372
Teacher spread0.297 · 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

Citations35
Published2023
Admission routes3
Has abstractyes

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