Evaluation of clinical communication skills of dental undergraduate students: a three-perspective approach / Puteri Nurul Adila Mohd Khairuddin
Bibliographic record
Abstract
This study is aimed to assess the Universiti Teknologi Mara (UiTM) dental student clinicians’ communication skills in four domains; caring and respectful, sharing information, tending to comfort, and interaction with team members, from three complementary perspectives; dental student clinicians’ self-assessment, patients’ feedback, and clinical instructors’ evaluation. Objectives: The objectives of the study were [1] to assess the dental student clinicians’ performance in communication from the patient’s view, self-rated and clinical instructor’s view, [2] to assess dental student clinicians’ performance in relation to patients’ socio-demography factors [3] to assess the dental student clinicians’ performances in relation to their socio-demography factors and [4] to find the correlation between the three perspectives; patients, dental student clinicians and clinical instructors. Methodology: The research was a cross-sectional study conducted using a modified-communication tool developed by the University of Manitoba; Patient Communication Assessment Instruments (PCAI), Student Communication Assessment Instruments (SCAI) and Clinical Communication Assessment Instruments (CCAI). A total of 432 questionnaires consisting of 176 patient assessment (PCAI), matching 176 students’ self-assessment (SCAI) and 80 clinical instructor assessment (CCAI) were administered. The PCAI were randomly given using random sampling technique. Three calibrated clinical instructors used CCAI to assess the dental student clinicians. Results: The response rate was 100% with 432 questionnaires answered.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".