Comparison of Communication Skills and Empathy Levels of Physiotherapy and Rehabilitation Students According to Individual and Academic Characteristics: A Cross-Sectional Study
Bibliographic record
Abstract
Objectives: This study aimed to compare the communication skills and empathy levels of physiotherapy and rehabilitation students according to their individual and academic characteristics. Material and Methods: A total of 481 physiotherapy and rehabilitation students (mean age: 20.43±1.85 years) were included in the study. Students' individual and academic characteristics, communication skills and empathy levels were recorded with a survey form structured with the “Google Forms” application. The structured survey form consisted of a short informational text about the study and its purpose, questions about the individual and academic characteristics of the students, and questions from the Communication Skills Scale and Toronto Empathy Scale. Comparison of two independent groups and more than two independent groups means were performed with the independent samples t-test and one-way analysis of variance (ANOVA), respectively. When a significant difference was found as a result of comparing the means of more than two groups, Bonferroni correction was used to determine which group caused this difference. Results: It was observed that the communication skills of students who were female (p=0.024), had a democratic family structure (p=0.004), did not have difficulties in interpersonal relationships (p˂0.001), and had a high perceived socio-economic level (p=0.022) were higher. Also, it was concluded that the empathy levels of female students were higher (p˂0.001), while the empathy levels of the 4th grade students were lower (p=0.003). Conclusion: These results revealed that students' communication skills and empathy levels differ according to individual and academic characteristics.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".