Rating communication skills in dental practice: the impact of different sociodemographic factors
Notice bibliographique
Résumé
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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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,020 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».