Evidence-based practice confidence and behavior throughout the curriculum of four physical therapy education programs: a longitudinal study
Bibliographic record
Abstract
Abstract Background Evidence-based practice (EBP) is a foundational process taught in health professional education, yet it is unclear when EBP confidence and skills are obtained. Increases in EBP confidence and behaviors from the start of physical therapy programs to post graduation have been reported in studies that evaluated a single program or used non-valid questionnaires. This study aimed to describe changes in EBP confidence and behavior using validated questionnaires of students from four physical therapy education programs throughout their curriculum and one year post graduation. Methods One hundred and eighty-one students from a potential pool of 269 (67.3%) consented to participate. Students completed the Evidence-Based Practice Confidence (EPIC) Scale and the Evidence-Based Practice Implementation Scale (EBPIS) at 6 timepoints: start of the program, prior to first clinical experience, after first clinical experience, at the end of classroom instruction, graduation, and one year post. Medians (Mdn) and 25th and 75th percentiles (P25, P75) were calculated for 42 (23.2%) students with complete data across all timepoints. Change between timepoints was assessed using Friedman’s test and Wilcoxon signed rank test with a Bonferroni correction for post hoc analysis. Results There were significant changes in EPIC scores (p < 0.001) from enrollment (Mdn 50.0, P25, P75 35.5, 65.9) to prior to first clinical experience (Mdn 65.5, P25, P75 57.3, 72.5) and after the first clinical experience (Mdn 67.3, P25, P75, 58.9, 73.2) to the end of classroom instruction (Mdn 78.6, P25, P75, 72.0, 84.1). Significant increases on the EBPIS (p < 0.01) were only seen from after the first year of training (Mdn 15, P25, P75, 10.0, 22.5) to end of the first clinical experience (Mdn 21.5, P25, P75 12.0, 32.0). Conclusions EBP confidence increased significantly after classroom instruction but remained the same after clinical experiences and at one year post graduation. EBP behavior significantly increased only after the first clinical experience and remained the same through graduation. Confidence and behavior scores were higher than were previously reported in practicing professionals. Ongoing assessment of EBP confidence and behavior may help instructors build appropriate curricula to achieve their outlined EBP objectives.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".