Examining the relationship between entry-level physiotherapy pain curricula and pain-management competency
Bibliographic record
Abstract
Chronic pain affects one in every five Canadians, impacting physical and mental health, as well as functional capabilities. In addition to the burden on the person living with pain, the management of chronic pain is costly, and thus poses a societal burden. In response to these burdens, the Canadian Pain Task Force developed an Action Plan for Pain, which included recommendations for improved pain education in prelicensure health professional programs in Canada. The idea that better pain education will improve care for patients living with pain hinges on an underlying assumption that improved or increased amounts of pain education will lead to better clinician competency. However, this assumption has yet to be directly examined empirically. This thesis aimed to test this assumption through the administration of an online survey for pain educators to gather data about curriculum, and an online pain-management competency assessment consisting of a multiple-choice and simulation-based component for students, to measure pain management competency. This data was then analyzed to create a hierarchical linear model, wherein PT students (level 1) are nested within PT programs (level 2). This study revealed significant differences across schools in student performance on the Competency Assessment. However, the hierarchical linear model analysis showed that no program-level variables, including time dedicated to pain education, accounted for variability in pain management competency. cGPA was the only significant predictor of pain management competency. The finding that time dedicated to pain education does not predict pain management competency may imply that cultivating pain management competency is less about time dedicated to content, but the quality of that time. This theory aligns with some literature about competency-based clinical education, which suggests that time dedicated to education is less important in developing competency in students than the way in which content is delivered. Future research could investigate other curricular factors that could explain variability in pain management competency across schools
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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 | 0.004 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".