Opiate addiction and overdose: experiences, attitudes, and appetite for community naloxone provision
Bibliographic record
Abstract
Background More than 200 opiate overdose deaths occur annually in Ireland. Overdose prevention and management, including naloxone prescription, should be a priority for healthcare services. Naloxone is an effective overdose treatment and is now being considered for wider lay use. Aim To establish GPs’ views and experiences of opiate addiction, overdose care, and naloxone provision. Design and setting An anonymous postal survey to GPs affiliated with the Department of Academic General Practice, University College Dublin, Ireland. Method A total of 714 GPs were invited to complete an anonymous postal survey. Results were compared with a parallel GP trainee survey. Results A total of 448/714 (62.7%) GPs responded. Approximately one-third of GPs were based in urban, rural, and mixed areas. Over 75% of GPs who responded had patients who used illicit opiates, and 25% prescribed methadone. Two-thirds of GPs were in favour of increased naloxone availability in the community; almost one-third would take part in such a scheme. A higher proportion of GP trainees had used naloxone to treat opiate overdose than qualified GPs. In addition, a higher proportion of GP trainees were willing to be involved in naloxone distribution than qualified GPs. Intranasal naloxone was much preferred to single (P<0.001) or multiple dose (P<0.001) intramuscular naloxone. Few GPs objected to wider naloxone availability, with 66.1% (n = 292) being in favour. Conclusion GPs report extensive contact with people who have opiate use disorders but provide limited opiate agonist treatment. They support wider availability of naloxone and would participate in its expansion. Development and evaluation of an implementation strategy to support GP-based distribution is urgently needed.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".