Core competencies of peer workers who use pulse oximeters to supplement their overdose response in British Columbia
Bibliographic record
Abstract
INTRODUCTION: Peer workers (those with lived/living experience of substance use) are at the forefront of overdose response initiatives in British Columbia, Canada. The onset of the coronavirus disease pandemic has significantly compounded the impact of the overdose crisis. Peer workers are integral in supporting people who use substances. However, despite the important work they do, peer workers often lack formalized credibility and do not have the same resources available to them as service providers without lived experience. The peer-led project titled the Peer2Peer Project implemented several support programs for peer workers, including providing pulse oximeters to peer workers to supplement their overdose response procedures. MATERIALS AND METHODS: This study was a component of a larger evaluation of the pulse oximeter program at two organizations in BC. The study aims to highlight the competencies of peer workers who use pulse oximeters. Telephone interviews were conducted with seven peer workers who were given pulse oximeters. The transcripts were thematically coded using Covert et al.'s framework of core competencies of community health workers to compare our sample with other widely recognized professions. FINDINGS: We found that peer workers who used pulse oximeters described several core competencies in their work and these were aligned with Covert et al.'s core competencies for community health workers, including assessment, community health practice, communication, diversity and inclusion, professional practice, and disease prevention and management. CONCLUSION: By aligning peer workers' skills to those of community health workers, we create awareness on the competencies of peer workers in using oximeters to supplement overdose response and advocate for them to receive more recognition and respect within the workplace. Further, our findings act as groundwork for future research in identifying the professional proficiencies of peer workers.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".