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This study aimed to investigate the caries diagnosis performances of dental students after training with an artificial intelligence (AI) application utilizing deep learning techniques, a type of artificial neural network. A total of 1200 bitewing radiographs were obtained from the institution's database and two specialist dentists labeled the caries lesions in the images. Randomly selected 1000 images were used for training purposes and the remaining 200 radiographs were used to evaluate the caries diagnostic performance of the AI. Then, a convolutional neural network, a deep learning algorithm commonly employed to analyze visual imagery problems, called “You Only Look Once,” was modified and trained to detect enamel and dentin caries lesions in the radiographs. Forty dental students were selected voluntarily and randomly divided into two groups. The pre‐test results of dental caries diagnosis performances of both groups were recorded. After 1 week, group 2 students were trained using an AI application. Then, the post‐test results of both groups were recorded. The labeling duration of the students was also measured and analyzed. When both groups’ pre‐test and post‐test results were evaluated, a statistically significant improvement was found for all parameters examined except precision score (p< 0.05). However, the trained group's accuracy, sensitivity, specificity, and F1 scores were significantly higher than the non‐trained group in terms of post‐test scores (p< 0.05). In group 2 (trained group), the post‐test labeling time was considerably increased (p< 0.05). The students trained by AI showed promising results in detecting caries lesions. The use of AI can also contribute to the clinical education of dental students.

The limited number of programs of tested efficacy in the literature such as cognitive-behavioural therapy and family-based prevention of internet addiction is striking. The aim of this study was to analyse the effect of reality therapy-based group counselling on college students’ problematic internet use and life satisfaction. In order to determine who would participate in the counselling program, screening tests were administered to 418 students. Twenty students who met the inclusion criteria eventually took part. The Online Cognition Scale and Life Satisfaction Scale were used pre- and posttests in order to evaluate the counselling program. Results show that reality therapy-based group counselling significantly reduces the level of problematic internet use among college students and increases their life satisfaction levels.

Dental education consists of both theoretical and practical learning for students to develop competence in treating patients clinically. When dental students encounter practical courses in their first year as a new educational experience, they must also learn to evaluate themselves. Self‐evaluation is an essential skill to learn for dental professionals to keep increasing their competence over the course of their careers. The aim of this study was to compare the assessment scores of second‐ and third‐year dental students and the faculty in two consecutive preclinical practical exams in restorative dentistry courses in a dental school in Turkey. Faculty‐ and student‐assigned scores were calculated from two consecutive preclinical examinations on tooth restorations performed on both artificial casts and phantom patients. The students were formally instructed on grading procedures for tooth preparations, base and restoration placement, and polishing criteria. After each step, each item was assessed by faculty members, the student, and another student. The results indicated that the initial differences between second‐year students’ assessments of their own preclinical practical ability and that of the faculty decreased among the third‐year students. Self‐evaluation scores did not indicate whether the third‐year students tended to over‐ or underestimate the quality of their own work. However, the second‐year students not only overestimated themselves but thought they were above average. The results point to the need to develop students’ self‐insight with more exercises and practical training.

The aim of this study was to investigate the relationship between problematic internet use and eating attitudes in a group of university students. The study sample consisted of 314 students attending programs at the faculties of education, medicine and communications at the Karadeniz Technical University in Turkey. One hundred forty-seven (46.8 %) were male and 167 (53.2 %) female. The Problematic Internet Use Scale was used to measure problematic internet use levels among university students and the Eating Attitudes Test to determine anorexia nervosa symptoms. Additionally, a Personal Data Form was used to determine age, gender, faculty attended and computer ownership. Data were analyzed on SPSS 15.00. Pearson’s product moments correlation coefficient, multiple linear regression analysis, the independent ttest and one-way ANOVA were used for data analysis. The research findings showed that 46.8 % of students were female and 53.2 % male. Mean age was 20.65 (SD 1.42). Analysis showed a significant positive correlation between problematic internet use and eating attitudes (r= 0.77, p< 0.01). Problematic internet use was found to be a significant predictor of eating attitudes. The results also showed a significant difference in problematic internet use with regard to program variables [F(2,311)= 102.79]. There were no significant differences in problematic internet use in terms of gender or computer ownership. The results of this study indicate that problematic internet use is significantly correlated with eating disorders, that problematic internet use does not vary on the basis of gender or computer ownership and that variations arise in problematic internet use depending on the faculty attended.