Take-home naloxone programs for suspected opioid overdose in community settings: a scoping umbrella review
Bibliographic record
Abstract
BACKGROUND: Opioid related overdoses and overdose deaths continue to constitute an urgent public health crisis. The implementation of naloxone programs, such as 'take-home naloxone' (THN), has emerged as a key intervention in reducing opioid overdose deaths. These programs aim to train individuals at risk of witnessing or experiencing an opioid overdose to recognize an opioid overdose and respond with naloxone. Naloxone effectively reverses opioid overdoses on a physiological level; however, there are outstanding questions on community THN program effectiveness (adverse events, dosing requirements, dose-response between routes of administration) and implementation (accessibility, availability, and affordability). The objective of this scoping review is to identify existing systematic reviews and best practice guidelines relevant to clinical and operational guidance on the distribution of THN. METHODS: Using the Arksey & O'Malley framework for scoping reviews, we searched both academic literature and grey literature databases using keywords (Naloxone) AND (Overdose) AND (Guideline OR Review OR Recommendation OR Toolkit). Only documents which had a structured review of evidence and/or provided summaries or recommendations based on evidence were included (systematic reviews, meta-analyses, scoping reviews, short-cut or rapid reviews, practice/clinical guidelines, and reports). Data were extracted from selected evidence in two key areas: (1) study identifiers; and (2) methodological characteristics. RESULTS: A total of 47 articles met inclusion criteria: 20 systematic reviews; 10 grey literature articles; 8 short-cut or rapid reviews; 4 scoping reviews; and 5 other review types (e.g. mapping review and comprehensive reviews). The most common subject themes were: naloxone effectiveness, safety, provision feasibility/acceptability of naloxone distribution, dosing and routes of administration, overdose response after naloxone administration, cost-effectiveness, naloxone training and education, and recommendations for policy, practice and gaps in knowledge. CONCLUSIONS: Several recent systematic reviews address the effectiveness of take-home naloxone programs, naloxone dosing/route of administration, and naloxone provision models. Gaps remain in the evidence around evaluating cost-effectiveness, training parameters and strategies, and adverse events following naloxone administration. As THN programs continue to expand in response to opioid overdose deaths, this review will contribute to understanding the evidence base for policy and THN program development and expansion.
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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 | 0.015 | 0.072 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.018 | 0.017 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".