Considerations for the design of overdose education and naloxone distribution interventions: results of a multi-stakeholder workshop
Bibliographic record
Abstract
Abstract Introduction Opioid overdose epidemic is a public health crisis that is impacting communities around the world. Overdose education and naloxone distribution programs equip and train lay people to respond in the event of an overdose. We aimed to understand factors to consider for the design of naloxone distribution programs in point-of-care settings from the point of view of community stakeholders. Methods We hosted a multi-stakeholder co-design workshop to elicit suggestions for a naloxone distribution program. We recruited people with lived experience of opioid overdose, community representatives, and other stakeholders from family practice, emergency medicine, addictions medicine, and public health to participate in a full-day facilitated co-design discussion wherein large and small group discussions were audio-recorded, transcribed and analysed using thematic approaches. Results A total of twenty-four participants participated in the multi-stakeholder workshop from five stakeholder groups including geographic and setting diversity. Collaborative dialogue and shared storytelling revealed seven considerations for the design of naloxone distribution programs specific to training needs and the provision of naloxone, these are: recognizing overdose, how much naloxone, impact of stigma, legal risk of responding, position as conventional first aid, friends and family as responders, support to call 911. Conclusion To create an naloxone distribution program in emergency departments, family practice and substance use treatment services, stigma is a central design consideration for training and naloxone kits. Design choices that reference the iconography, type, and form of materials associated with first aid have the potential to satisfy the need to de-stigmatize overdose response.
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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 | 0.190 | 0.167 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.005 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.004 | 0.012 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
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".