Educational needs and preferences of adult patients with acute pain: a mixed-methods systematic review
Bibliographic record
Abstract
ABSTRACT: Many patients experience acute pain, which has been associated with numerous negative consequences. Pain education has been proposed as a strategy to improve acute pain management. However, studies report limited effects with educational interventions for acute pain in adults, which can be explained by the underuse of the person-centered approach. Thus, we aimed to systematically review and synthetize current evidence from quantitative, qualitative and mixed-methods studies describing patients' needs and preferences for acute pain education in adults. We searched original studies and gray literature in 7 databases, from January 1990 to October 2023. Methodological quality was assessed with the Mixed Methods Appraisal Tool. A total of 32 studies were included (n = 1847 patients), two-thirds of which were qualitative studies of high methodological quality. Most of the studies were conducted over the last 15 years in patients with postsurgical and posttraumatic pain, identified as White, with a low level of education. Patients expressed the greatest need for education when it came to what to expect in pain intensity and duration, as well how to take the medication and its associated adverse effects. The most frequently reported educational preferences were for in-person education while involving caregivers and to obtain information first from physicians, then by other professionals. This review has highlighted the needs and preferences to be considered in pain education interventions, which should be embedded in an approach cultivating communication and partnership with patients and their caregivers. The results still need to be confirmed with different patient populations.
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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 | 0.028 | 0.098 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 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".