Objective: The primary objective of this cross-sectional national study was to investigate the status of digital dental technology (DDT) adoption in Saudi Arabian undergraduate dental education. A secondary objective was to explore the impact of dental schools’ funding sources to incorporate digital technologies. Methods: A self-administered questionnaire was distributed to the chairpersons of prosthetic sciences departments of the 27 dental schools in Saudi Arabia. If any department chairman failed to respond to the survey, a designated full-time faculty member was contacted to fill out the form. The participants were asked about the school’s sector, DDT implementation in the curriculum, implemented level, their perceptions of the facilitators and challenges for incorporating DDT. Results: Of the 27 dental schools (18 public and 8 private), 26 responded to the questionnaire (response rate: 96.3%). The geographic distribution of the respondent schools was as follows: 12 schools in the central region, 6 in the western region, and 8 in other regions. Seventeen schools secure and preserve patients’ records using electronic software, whereas nine schools use paper charts. Seventeen schools (64,4%) implemented DDT in their curricula. The schools that did not incorporate DDT into their undergraduate curricula were due to not being included in the curriculum (78%), lack of expertise (66%), untrained faculty and staff (44%), and cost (33%). Conclusions: This national study showed that digital components still need to be integrated into Saudi Arabian dental schools’ curricula and patient care treatment. Additionally, there was no association between funding sources and the DDT implementation into the current curricula. Consequently, Saudi dental schools must emphasize the implementation and utilization of DDT to align with Saudi Vision 2030 for healthcare digitization and to graduate competent dentists in digital dental care.

Background: Rapid advancement in technology has provided alternatives to traditional classroom teaching. Such instructional methods have gained increasing importance during the COVID-19 pandemic when physical classroom attendance was not possible. The study evaluated faculty’s and students’ perceptions concerning the online virtual classes and recorded lectures as compared to traditional classes delivered at the College of Dentistry, King Saud bin Abdulaziz University for Health Sciences. Materials and Methods: Surveys were developed and distributed to 34 faculty members and 186 students. Perceptions about virtual classes, recorded lectures, physical attendance, the effectiveness of different teaching methods, and overall experience were evaluated. Descriptive statistics were presented using frequencies and percentages. The Chi-square test compared the students’ and the faculty members’ responses. The level of significance was set at α =0.05. Results: Thirty-one faculty members and 149 dental students participated, and the overall response rates were 91.2% and 80.1%, respectively. While there was a general agreement on the usefulness of making recorded lectures available, a statistically significant difference (p<0.001) was found between students’ and faculty members’ views on making classroom-lecture attendance optional (67.1% of students and 12.9% of the faculty agreed/strongly agreed). Statistically significant differences (p<0.001) were found between the students and faculty members concerning the effectiveness of recorded lectures and attending online virtual classes as an alternative to classroom attendance. Conclusion: Overall, students were more accepting of technology than faculty members as a substitute for traditional classroom teaching. For a more efficient and satisfactory learning experience, both teaching methods should be considered in a blended-learning module.

The aim of the study is to assess the impact of mechanical surface treatments on the shear bond strength (SBS) of orthodontic brackets bonded to three-dimensional (3D) printed and milled CAD/CAM provisional materials. Sixty cylindrical samples were fabricated for each provisional material. Samples were treated with one of the following surface treatments: aluminum oxide airborne particle abrasion, diamond bur rotary instrument roughening, and phosphoric acid etching (control). Stainless steel brackets were bonded to the samples, and then SBS was tested using a universal testing machine. SEM and digital microscopy were utilized to examine the bonding interface and the failure modes. Two-way ANOVA, one-way ANOVA, Tukey’s HSD, and independent sample t-tests were used for statistical analysis. Results revealed significant differences in SBS between 3D printed and milled samples and significant differences in SBS among most surface treatments, with rotary instrument roughening resulting in the highest values for 3D printed, while airborne particle abrasion leading for milled samples. Digital microscopy indicated that more adhesive remained on 3D-printed samples. SEM analysis revealed varying surface roughness across treatments. Based on the findings of this study, it can be concluded that different surface treatments improve the bonding of orthodontic brackets to provisional crowns.

Provisional restoration is essential for function, esthetics, occlusion, and tissue health. However, when multiple teeth are involved, making a direct splinted provisional restoration could be challenging due to the combined undercuts between the prepared teeth. This article describes a dental technique using polytetrafluoroethylene (PTFE) tape as a spacer to fabricate a splinted provisional restoration for multiple prepared teeth. The PTFE tape spacer will compensate for discrepancies in the path of insertion between prepared teeth, thus facilitating the removal of the direct splinted provisional restoration intact.

Background: Artificial intelligence (AI) has shown promise in improving the detection of proximal caries on dental radiographs; however, its educational value in enhancing undergraduate students’ independent radiographic interpretation remains unclear. Therefore, this study aimed to evaluate the effect of AI–assisted radiology training on undergraduate dental students’ diagnostic competence in assessing proximal caries extension when compared with conventional radiology training. Methods: This randomized experimental study included 82 undergraduate dental students. After completing a pre-test using 20 conventional bitewing radiographs, from which students evaluated three proximal surfaces per radiograph, students were randomly allocated to either conventional radiology training or AI-assisted training using Second Opinion ^® software. Both groups received a one-hour training session. A post-test using 20 conventional bitewing radiographs without AI assistance was conducted one day later, with students again evaluating three proximal surfaces per radiograph. Diagnostic performance was assessed using total exact-match scores (0–60) and absolute average error (0–5 scale). Completion time in minutes was also recorded for pre- and post-tests. Mixed-design ANOVA was used to evaluate group, time, and interaction effects (α = 0.05). Results: Seventy-nine students completed both tests, with 41 trained using AI assistance and 38 trained using conventional radiography. No significant differences were found between training groups or across time points (pre- and post-intervention, p > 0.05). However, absolute average errors increased significantly in the conventional group from pre- to post-test ( p < 0.05), indicating a greater deviation from the correct answers. Post-test completion time was significantly shorter in the AI group compared with the conventional group, and both groups demonstrated significant reductions in completion time from pre- to post-test ( p < 0.05). Conclusions: AI-assisted training did not significantly improve students’ diagnostic competency in proximal caries detection compared with conventional radiology training. However, AI training improved diagnostic efficiency, as indicated by the lower absolute average errors, and did not impair students’ independent radiographic interpretation when AI support was removed. AI may serve as a supportive adjunct in undergraduate dental education, particularly for improving efficiency and consistency in lesion depth estimation.

Background/Objectives: Early diagnosis and interceptive orthodontic treatment can prevent or correct developing skeletal and dental discrepancies. Parental awareness and acceptance of interceptive orthodontic appliances remain limited, particularly in Saudi Arabia; therefore, this study assessed parents’ awareness and acceptance of commonly used appliances in early orthodontic treatment. Methods: A cross-sectional study was conducted in Saudi Arabia from December 2023 to August 2024 using a structured web-based questionnaire assessing awareness and acceptance of 10 orthodontic appliances. Awareness and acceptance were categorized into poor/moderate/good and low/high, respectively, and associations with sociodemographic factors, dental/orthodontic history, and sources of knowledge were analyzed. Results: Overall appliance awareness was moderate (8.32 ± 4.29/20), while acceptance was high (6.31 ± 3.19/10). Twin-block had the highest awareness (88.6%) and acceptance (85.5%), while hyrax/quad helix and tongue crib had the lowest. Awareness and acceptance were significantly associated with sociodemographic factors and children’s dental/orthodontic history, particularly previous orthodontic treatment (81.7% vs. 52.6%, p < 0.001). Dentists, orthodontists, social media, and personal experience were key sources influencing awareness and acceptance. Conclusions: Parental awareness was moderate, while acceptance was high. Greater awareness and acceptance were associated with higher education, income, and previous dental and orthodontic treatment, highlighting the need for reliable professional information to promote evidence-based early orthodontic intervention.