Refining and adapting the measurement properties of evidence-based practice measures for physiotherapy students
Bibliographic record
Abstract
OBJECTIVE: There is a lack of reliable and valid evidence-based practice (EBP) measures for physiotherapy students. This study validated EBP-student (EBP-S) measures for physiotherapy students. METHODS: EBP measures developed from previous research were cross-culturally validated for use by physiotherapy students. The adapted EBP-S consisted of six measures: use of EBP, EBP activities, EBP knowledge, self-efficacy for EBP, attitudes towards EBP, and perceptions of the teaching and assessment of EBP in the curriculum. The final version was completed by physiotherapy students (n = 335). The psychometric properties for each EBP-S measure were estimated, including construct validity using Rasch model, internal consistency reliability using person separation index (PSI), test-retest reliability using intraclass correlation coefficient (ICC), and differential item functioning (DIF). RESULTS: Two formative measures (use of EBP and EBP activities) were only linguistically modified for use with students. A Rasch model was applied to the other four reflective measures. For knowledge, 55% (6/11) items fit the Rasch model with chi-square fit statistic (χ2) = 34.46, p = 0.08; PSI = 0.85. For self-efficacy, 89% (8/9) items fit the Rasch model with χ2 = 25.11, p = 0.80; PSI = 0.89. For attitudes, 62% (8/13) items fit the Rasch model with χ2 = 61.49, p = 0.00; PSI = 0.71. For perception of the teaching and assessment of EBP in the curriculum, 62% (8/13) items fit the Rasch model with χ2 = 80.99, p = 0.45; PSI = 0.92. perception of the teaching and assessment of EBP in the curriculum showed DIF in three items. The ICCs ranged between 0.80 and 0.98. CONCLUSIONS: The EBP-S measures were validated for physiotherapy students, including the testing of psychometric properties, which were not tested in the original studies. Further refinements should be considered for the use of the EBP-S with other groups of students or if changes are applied to the current curriculum.
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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 | 0.097 | 0.294 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| 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".