A systematic review of strategies to improve appropriate use of opioids and to reduce opioid use disorder and deaths from prescription opioids
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Abuse of prescription opioids is a serious problem in North America. AIMS: The aim of this study was to conduct a systematic review of peer-reviewed and grey literature to examine existing strategies aimed at improving the appropriate use of prescription opioids and/or reducing the misuse, abuse, and diversion of these drugs. METHODS: The following electronic databases were searched to September 2015 without language restrictions: MEDLINE, EMBASE, PsycINFO, and CINAHL; the grey literature was searched to May 2014. Reference lists of retrieved papers were also searched. Studies were eligible if a strategy was implemented and its impact on at least one of the primary outcomes of interest (appropriate prescription opioid use; misuse, abuse, opioid use disorder, diversion; overdose) was measured. Standardized, prepiloted forms were used for relevance screening, quality appraisal, and data extraction. RESULTS: A total of 65 studies that assessed 66 distinct strategies were identified. Due to the heterogeneity of the strategies, a qualitative synthesis was conducted. Many studies combined more than one type of strategy and measured various types of outcomes. The strategies with most promising results involved education, clinical practices, collaborations, prescription monitoring programs, public campaigns, opioid substitution programs, and naloxone distribution. We also found strategies that had some unintended consequences after implementation. CONCLUSIONS: Our review identified successful strategies that have been implemented and evaluated in various jurisdictions. There is a need to replicate and disseminate these strategies where the problem of prescription opioid misuse and abuse has taken a toll on society.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it