Cross-Sectional Study to Examine Evidence-Based Practice Skills and Behaviors of Physical Therapy Graduates: Is There a Knowledge-to-Practice Gap?
Bibliographic record
Abstract
BACKGROUND: Curricula changes in physical therapist education programs in Canada emphasize evidence-based practice skills, including literature retrieval and evaluation. Do graduates use these skills in practice? OBJECTIVES: The aim of this study was to evaluate the use of research information in the clinical decision making of therapists with different years of experience and evidence-based practice preparation. Perceptions about evidence-based practice were explored qualitatively. DESIGN: A cross-sectional study with 4 graduating cohorts was conducted. METHODS: Eighty physical therapists representing 4 different graduating cohorts participated in interviews focused on 2 clinical scenarios. Participants had varying years of clinical experience (range=1-15 years) and academic knowledge of evidence-based practice skills. Therapists discussed the effectiveness of interventions related to the scenarios and identified the sources of information used to reach decisions. Participants also answered general questions related to evidence-based practice knowledge. RESULTS: Recent graduates demonstrated better knowledge of evidence-based practice skills compared with therapists with 6 to 15 years of clinical experience. However, all groups used clinical experience most frequently as their source of information for clinical decisions. Research evidence was infrequently included in decision making. LIMITATIONS: This study used a convenience sample of therapists who agreed to volunteer for the study. CONCLUSIONS: The results suggest a knowledge-to-practice gap; graduates are not using the new skills to inform their practice. Tailoring academic evidence-based activities more to the time constraints of clinical practice may help students to be more successful in applying evidence in practice. Academic programs need to do more to create and nurture environments in both academic and clinical settings to ensure students practice using evidence-based practice skills across settings.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".