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Record W4411628949 · doi:10.1371/journal.pone.0326495

The opportunity to save a life: A qualitative study of a point-of-care overdose education and naloxone distribution intervention

2025· article· en· W4411628949 on OpenAlexafffundabout
Janet Parsons, Benjamin Markowitz, Rekha Thomas, Mercy Charles, Kate Sellen, Douglas M. Campbell, Pamela Leece, Michelle Klaiman, Leigh Chapman, Shaun Hopkins, Rita Shahin, Curtis Handford, Vicky Stergiopoulos, Laurie J. Morrison, Carol Strıke, Aaron Orkin

Bibliographic record

VenuePLoS ONE · 2025
Typearticle
Languageen
FieldMedicine
TopicOpioid Use Disorder Treatment
Canadian institutionsSt Joseph's Health CentreHealth Sciences CentreSunnybrook Health Science CentreOntario College of Art and DesignPublic Health OntarioUniversity of TorontoCentre for Addiction and Mental HealthToronto Public HealthSt. Michael's Hospital
FundersCanadian Institutes of Health Research
KeywordsOpioid overdoseThematic analysis(+)-NaloxoneQualitative researchMedicineIntervention (counseling)OpioidPsychologyPsychiatryNursingSociology

Abstract

fetched live from OpenAlex

Canada's opioid crisis continues to escalate. Naloxone can effectively reverse the effects of opioid overdose. We planned a randomized trial on the effectiveness of a point-of-care overdose education and naloxone distribution (OEND) intervention on participants' performance in a simulated opioid overdose scenario. In preparation for the trial, we conducted a feasibility study which included a qualitative process evaluation aimed at eliciting participants' perspectives of the study's OEND tool and procedures, and how their lived experiences of the opioid crisis intersected with their experiences of the study. Twenty-three participants were interviewed, including people with lived experiences of opioid use or overdose, and people living in neighbourhoods or working in services where they were likely to encounter overdose. Thematic analysis of interview transcripts was informed by stigma theory. Participants' accounts depicted challenges faced by people who take opioids in their everyday lives, deep losses experienced, negative attitudes encountered, and systemic barriers to care. Participation in the study itself was portrayed as meaningful. We explored participants' experiences through three key themes: (1) who were the participants - describing their experiences related to opioid overdose, opioid use and attendant stigma; (2) why did they participate - recounting their motivations to join the study; and (3) what they thought about study processes - reflecting on the OEND materials and study procedures. Accounts revealed a sense of agency as participants confronted the opioid crisis. Our results demonstrate that people experiencing opioid use and overdose and people who care about them are eager and willing to be approached about research at point of care; participants were eager to learn overdose prevention skills and to return for follow-up study sessions. They recounted a range of motivations for participating, the most important of which is the opportunity to actively intervene, save lives and raise awareness. Trial Registration: ClinicalTrials.gov registry (NCT03821649).

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)0.025
metaresearch head score (Gemma)0.035
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.025
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0250.035
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0190.017
Scholarly communication0.0060.006
Open science0.0040.008
Research integrity0.0040.008
Insufficient payload (model declined to judge)0.0050.001

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 head0.043
GPT teacher head0.361
Teacher spread0.318 · 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 designQualitative
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
Published2025
Admission routes3
Has abstractyes

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