Development and validation of an approach for self-assessment of communication skills in clinical dentistry: a mixed methods evaluation in Syria
Bibliographic record
Abstract
Communication skills are universally recognised as a core competency in clinical education, yet in many Arab countries, including Syria, these skills are not formally integrated into the curriculum. This study aimed to develop and validate a self-assessment approach for communication skills, incorporating patient assessments for corrective feedback, at Damascus University Faculty of Dental Medicine, Syria. The study investigated this assessment approach's reliability, validity, and educational impact. Using the well-established Calgary Cambridge Guide, an assessment instrument was developed, translated and cross-culturally validated for the Syrian Arabic context. The assessment approach comprised six consultation sessions with six patients in clinical settings. After each consultation, students and patients completed an assessment form. Fifty-four final-year dental students completed all six sessions. A sequential mixed methods design was employed, beginning with a quantitative phase that included generalizability (G) and decision studies to assess reliability and exploratory factor analysis (EFA) to evaluate structural validity. In the qualitative phase, semi-structured interviews were conducted with a purposive subsample (n=12) from the quantitative strand. The thematic analysis explored the educational impact and factors influencing self-assessment. Findings showed a G-coefficient of 0.93 for self-assessment and 0.66 for patient assessment. Student and rater effects are conflated in self-assessment G-study, so the coefficient needs to be interpreted cautiously. EFA indicated a one-factor solution explaining 52.1% of the variance. There was a significant improvement in patient assessments over time, with a large effect size (P<0.001, Partial η²=0.184). Qualitative results supported these findings, revealing increased self-awareness and self-control due to self-assessment. Subjective self-assessment practices, patient-dentist dynamics, and self-reflection all influenced self-assessment scoring. Focusing on a context that lacks a formal communication skills curriculum, this rigorous mixed methods research makes an original and substantive contribution to the field. One original contribution of this study is the in-depth exploration of meanings and intentions underlying self-assessment results that most studies in the field overlook. Although the findings should be generalised cautiously, this research provides valuable recommendations for students, clinicians, and clinical educators on optimising self-assessment practice and using its data to facilitate communication performance improvement.
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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 | 0.098 | 0.060 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".