Exploring confidence in recognizing oral cancer among dentists and dental students.
Abstract
To explore correlation between ability of dentists and dental students to recognise the clinical presentation of oral cancer and their self-rated confidence. A cross-sectional, analytical design was used for this study. A validated oral disease recognition scale (ODRS) encompassing a range of benign, premalignant, and malignant oral conditions was used for data collection. For each of the seven patient cases, the participants were asked to provide a diagnosis and rate their self-perceived confidence. Confidence ratings were used as a predictor in a logistic regression model to determine its value as a predictor of diagnosis accuracy, controlling for other factors. A total of 252 participants completed the online survey. All correlations between pairs of Cases are positive and statistically significant (p < 0.001). An ordinal logistic regression model predicting Correct vs. Incorrect based on Confidence, Case, participant status, participant gender, and participant age group (and a random effect for participant) suggests that each unit increase in confidence results in a 0.235 unit increase in log-odds of a correct response (an Odds Ratio of 1.265, p < 0.001). Overall, confidence ratings appear to predict diagnosis accuracy, after controlling for case and participant characteristics. Notwithstanding the limitations of the current study, the oral disease recognition scale may serve as a useful tool to assess clinicians' ability to recognize oral cancer and identify potential cognitive biases in their clinical assessment skills. This study highlights the correlations between diagnostic accuracy and confidence of dentists and dental students in identifying oral cancer, which is crucial for timely referral and improved patient outcomes. By identifying gaps in diagnostic confidence and potential cognitive biases, the findings can inform targeted educational interventions for reliable oral cancer screening in general dental practice.
Collections
- Dental Medicine Research [471 items ]


