First responder attitudes and practices related to people who use drugs: exploring the impact of resource sharing
Bibliographic record
Abstract
Background First responders are critical to preventing recurrent opioid overdoses and improving overdose response. However, their attitudes and behaviors toward people who use drugs (PWUD) remain underexplored, limiting opportunities for effective intervention. This study examined first responders’ perceptions, focusing on their attitudes, crisis response behaviors, and resource-sharing practices.Methods This research is part of a larger, mixed-methods study that included pre- and post-test survey data from first responders (N = 38 and 30, respectively) piloting a mobile app designed to support overdose response and resource dissemination.Results After the intervention, first responders reported increased concern for users’ well-being and community health, along with a greater appreciation for the importance of sharing resources related to basic needs.Conclusion Training and tools that empower first responders to connect PWUD with harm reduction, treatment, and counseling resources can foster trust, enhance public health outcomes related to overdose, and reduce overdose risks in communities.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".