Rating communication skills in dental practice: the impact of different sociodemographic factors
Bibliographic record
Abstract
BACKGROUND: Communication abilities are essential for the successful operation of a dental business and significantly influence outcomes, compliance, and patient satisfaction. AIMS AND METHODS: The aim of our study was to evaluate the knowledge and practice of doctor-patient communication among Jordanian dentists. This evaluation was conducted through a survey based on the key components of the Calgary Cambridge Observation Guides. Additionally, the impact of several sociodemographic characteristics on communication abilities was investigated. This cross-sectional study was conducted from January to June 2022. The data collection tool was an online questionnaire developed by the researchers, consisting of three sections: self-reported demographic and professional data, the practice of doctor-patient communication, and knowledge of doctor-patient communication. RESULTS: The study included 305 dentists, comprising 106 males and 199 females, with a mean age of 32.9 ± 9.0 years. The mean score for communication skills knowledge was 41.5, indicating a moderate level of communication skills knowledge. Female dentists demonstrated significantly higher communication scores compared to their male counterparts, and those working in the private sector scored significantly higher than those in the governmental sector or in both sectors (P ≤ 0.05). In general, older and more experienced dentists exhibited better communication skills. Educational level had a positive impact on certain communication skills items. 58.4% believed that communication skills can always be developed and improved through training sessions, while 48.9% reported never having attended such courses. 95.1% believed that training courses on communication skills are always necessary as part of the educational curriculum. The main obstacles that may deter dentists from considering communication skills courses were limited time (62.3%), course availability (37.7%), cost (28.2%), and perceived lack of importance (8.2%). CONCLUSION: Among a sample of Jordanian dentists, there appears to be a discrepancy between knowledge and self-reported practices regarding communication abilities. In certain crucial, evidence-based areas of doctor-patient communication, there are fundamental deficiencies. Considering the significant role dentists play in oral health and prevention, communication skills should be a top educational priority for them.
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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 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".