Comparison of physical therapy anatomy performance and anxiety scores in timed and untimed practical tests
Bibliographic record
Abstract
Students in health care professional programs face many stressful tests that determine successful completion of their program. Test anxiety during these high stakes examinations can affect working memory and lead to poor outcomes. Methods of decreasing test anxiety include lengthening the time available to complete examinations or evaluating students using untimed examinations. There is currently no consensus in the literature regarding whether untimed examinations provide a benefit to test performance in clinical anatomy. This study aimed to determine the impact of timed versus untimed practical tests on Master of Physical Therapy student anatomy performance and test anxiety. Test anxiety was measured using the State-Trait Anxiety Inventory (STAI). Differences in performance, anxiety scores, and time taken were compared using paired sample Student's t-tests. Eighty-one of the 84 students completed the study and provided feedback. Students performed significantly higher on the untimed test (P = 0.005), with a significant reduction in test anxiety (P < 0.001). Students who were unsuccessful on the timed test showed the greatest improvement on the untimed test ( x¯ = 20.4 ±10%). Eighty-three percent (n = 69) of students preferred the untimed test, 8.4% (n = 7) the timed test, and 8.4% (n = 7) had no preference. Students took on average eight minutes longer on the untimed test. This study found that physical therapy students perform better on untimed tests, which may be related to a reduction in test anxiety. If the intended goal of evaluating health care professional students is to determine fundamental competencies, these factors should be considered when designing future curricula.
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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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".