Understanding factors that facilitate the inclusion of pain education in undergraduate curricula: Perspectives from a UK survey
Bibliographic record
Abstract
BACKGROUND: Studies in Europe, North America and Australasia suggest that one in five adults suffer from pain. There is increasing recognition that pain, particularly chronic pain, represents a global health burden. Many studies, including two national surveys exploring the content of undergraduate curricula for pain education, identify that documented pain education in curricula was limited and fragmentary. METHODS: The study design used a questionnaire which included an open text comment box for respondents to add 'further comments' as part of larger study previously published. The sample consisted of 19 UK universities that offered 108 undergraduate programmes in the following: dentistry, medicine, midwifery, nursing (adult, child, learning disabilities and mental health branches), occupational therapy (OT), pharmacy, physiotherapy and veterinary science. An inductive content analysis was performed, and the data were managed using NVivo 10 software for data management. RESULTS: A total of 57 participants across seven disciplines (dentistry, medicine, midwifery, nursing, pharmacy, physiotherapy and OT) completed the open text comment box (none were received from veterinary science). Analysis revealed two major themes of successes and challenges. Successes included expansion (extending coverage and/or increased student access), multidimensional curriculum content and diversity of teaching methods. Challenges included difficulties in identifying where pain is taught in the curriculum, biomedical versus biopsychosocial definitions of pain, perceived importance, time, resources and staff knowledge, and finally a diffusion of responsibility for pain education. CONCLUSION: This study identifies new insights of the factors attributed to successful implementation of pain education in undergraduate education. Many of the challenges previously reported were also identified. This is one of the first studies to identify a broad range of approaches, for pain education, that could be deemed as 'successful' across a range of health disciplines.
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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 | 0.008 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| 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".