Injectable opioid agonist treatment: An evolutionary concept analysis
Bibliographic record
Abstract
Canada is currently in the midst of an overdose crisis. With new and innovative approaches desperately needed, injectable opioid agonist treatment (iOAT) should be considered as an integral treatment option to prevent even more fatalities. These programs provide injectable diacetylmorphine or hydromorphone to clients with severe opioid use disorders. Currently, they remain an under-executed and under-studied treatment modality. To better understand why this may be, we performed an evolutionary concept analysis as described by Rodgers. The attributes, antecedents, consequences, and surrogate terms of iOAT were unpacked and explored. Further, four themes were identified within the literature: (1) physical and mental health, (2) illicit drug use, (3) criminal behavior, and (4) ethical considerations. Recommendations surrounding the need for additional studies that focus on the perspectives of people who use opioids (PWUO), the necessity of nursing advocacy in iOAT, and the consideration of a changing illicit drug supply were explored. Further, theoretical analysis coupled with direct input from PWUO was discussed as a necessity to move forward with iOAT.
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.004 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| 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".