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Record W4387380541 · doi:10.1177/00220426231205520

Factors Influencing Attitudes Towards Safer Supply Programs for People Who Use Drugs: Findings From an Atlantic Canadian Province

2023· article· en· W4387380541 on OpenAlexaffabout
Adrienne N. Thornton, Amy L. MacQuarrie, Caroline Brunelle

Bibliographic record

VenueJournal of Drug Issues · 2023
Typearticle
Languageen
FieldMedicine
TopicHIV, Drug Use, Sexual Risk
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsOpenness to experienceSAFERHarmStigma (botany)Harm reductionMedicineEnvironmental healthPsychologyBusinessPublic healthPsychiatrySocial psychologyNursing

Abstract

fetched live from OpenAlex

Safer supply programs (SSPs) are harm reduction services where people who use drugs can access regulated pharmaceutical drugs (e.g., hydromorphone). Public attitudes, and factors that influence attitudes towards SSPs must be considered as they impact policy and funding decisions. A total of 384 participants were recruited from the community ( n = 160, 41.7%) and an Atlantic Canadian University ( n = 224, 58.3%) to complete an online survey. The majority of the sample was supportive of SSPs ( n = 316, 82.3%). Being of European origin, a younger age, identifying as female, displaying higher levels of Openness to Experience, and reporting less stigma towards people who use drugs were predictive of more positive attitudes towards SSPs. Openness to Experience mediated the relationship between stigma levels and attitudes towards SSPs. The findings of the current study suggest that when developing public awareness campaigns, considering the impact of demographic and psychological factors is important.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.053
GPT teacher head0.351
Teacher spread0.298 · 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.

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

Citations1
Published2023
Admission routes2
Has abstractyes

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