Predictors of Clinical Reasoning Using the Reasoning 4 Change Instrument With Physical Therapist Students
Bibliographic record
Abstract
BACKGROUND: Although physical therapist students must be well prepared to integrate biopsychosocial and behavioral perspectives into their clinical reasoning, there is a lack of knowledge regarding factors that influence such competence. OBJECTIVE: This study explored the associations among the independent variables-knowledge, cognition, metacognition, psychological factors, contextual factors, and curriculum orientation vis-à-vis behavioral medicine competencies-and the dependent variables-outcomes of input from client (IC), functional behavioral analysis (FBA), and strategies for behavior change (SBC) as levels in physical therapist students' clinical reasoning processes. DESIGN: This study used an exploratory cross-sectional design. METHODS: The Reasoning 4 Change instrument was completed by 151 final-semester physical therapist students. Hierarchical multiple regression analyses for IC, FBA, and SBC were conducted. In the first step, curriculum orientation was inserted into the model; in the second step, self-rated knowledge, cognition, and metacognition; and in the third step, psychological factors. RESULTS: All independent variables except contextual factors explained 37% of the variance in the outcome of IC. Curriculum orientation explained 3%, cognitive and metacognitive factors an additional 22%, and attitudes another 15%. Variance in the outcomes of FBA and SBC were explained by curriculum orientation only (FBA change in R2 = 0.04; SBC change in R2 = 0.05). Higher scores of the dependent variables were associated with a curriculum having behavioral medicine competencies. LIMITATIONS: The limitations of this study are that it was cross-sectional. CONCLUSIONS: Cognitive and metacognitive capabilities and skills and positive attitudes are important predictors of physical therapist students' clinical reasoning focused on behavior change at the IC level. Curricula with behavioral medicine competencies are associated with positive outcomes at all clinical reasoning levels.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".