Factors influencing nurses’ knowledge and attitudes toward patients in chronic pain with opioid use disorder: A literature review
Bibliographic record
Abstract
Background and objective: Chronic pain is a common symptom among patients worldwide. This issue leads health care professionals to manage patients’ chronic pain by using opioids. However, some patients tend to abuse these medications and develop opioid use disorder. The aim of the study was to identify and explore factors that influence nurses’ knowledge and attitudes toward patients in chronic pain with opioid use disorder.Methods: A literature review was conducted. CINAHL, Medline, and PsychINFO databases were used to search for relevant articles. A total of 12 articles that met the inclusion criteria were retrieved.Results: This literature review showed several factors that influence nurses’ knowledge and attitudes. These factors were nurses’ education, role support, demographic factors, nurses’ experiences, and nurses’ beliefs and culture.Conclusions: The findings of this literature review will inform the development of an educational program to promote nurses’ knowledge and attitudes toward patients in chronic pain with opioid use disorder.
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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 | 0.003 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".