The COVID-19 government public health measures are necessary to prevent the spread of COVID-19, however, their efficacy is largely dependent on adherence. This study utilized the Health Belief Model (HBM) to explain the public’s adopted prevention practices during the COVID-19 outbreak in Saudi Arabia. This study used “COVID-19 Snapshot MOnitoring (COSMO): monitoring knowledge, risk perceptions, preventive behaviours, and public trust in the current coronavirus outbreak” research protocol which is developed by the WHO Regional Office for Europe and the COSMO group. The COSMO questionnaire was translated into Arabic and distributed as an online survey via WhatsApp instant messaging application from May 2nd to May 26th, 2020. The dependent variable was the mean of adopting ten COVID-19 preventive practices. These practices were hand washing, avoiding touching eyes, nose and mouth, use of hand sanitizer, covering mouth and nose when coughing/sneezing, staying home when sick, avoiding close contact with infected persons, social distancing, wearing masks, home isolation, and lockdown. The independent variables included the HBM constructs (susceptibility to and severity of COVID-19, benefits of and barriers to adopting preventive behaviors, cues to action, health motivation, and self-efficacy), sociodemographic factors, presence of chronic illness, and perceived and actual knowledge. We conducted bivariate and multivariate analyses and reported significant findings (P ≤ 0.05). We analyzed 1027 surveys. About 38% adhered to all COVID-19 preventive behaviors and the mean for adherence was 9. The HBM perceived benefits (p = 0.001), perceived barriers (p = 0.004), and cues to action (p = 0.046) were associated with adherence to COVID-19 preventive behaviors after adjusting for all other factors. Respondents with the highest levels of education and income were less likely to adopt COVID-19 preventive behaviors compared to those in the lower ranks of education and income. Our findings suggest that the HBM can be applied to understand adherence to COVID-19 prevention practices. The recognition of perceived health beliefs and practices is important for developing effective COVID-19 health intervention strategies.

The recent coronavirus disease of 2019 (COVID-19) pandemic led to major lifestyle changes. The present study sought to assess factors associated with fear to seek dental care during COVID-19 pandemic in Saudi Arabia. This cross-sectional study was conducted during the COVID-19 outbreak in 2020. An online questionnaire was filled by a convenient sample of adult Saudi residents through mobile instant messaging application. The following measures were collected: sociodemographic characteristics, fear of COVID-19 using validated Fears of Illness and Virus Evaluation scale, fear to seek dental care, perceived health status, and COVID-19 experience. There were 826 participants involved in this study (541 females and 285 males, mean age: 38.8 ± 13.29 years). Fear to seek dental care was significantly higher among females, younger age groups, people who perceived poor general and oral health, and people who perceived high risk of contracting the virus in dental clinics. After controlling for confounders, fear to seek dental care was significantly higher among the age group of 35–44 years, those who perceived high and moderate risk of COVID-19 infection in dental clinics, and among participants who reported untreated dental conditions. Fear that Others Get Sick, Fear of the Impact on Social Life, and Behaviors Related to Illness and Virus Fears were significantly associated with high levels of fear to seek dental care. Within the study’s limitations, fear of COVID-19 negatively impacted the study population’s willingness to seek dental treatment. Factors such as age, perceived risk of COVID-19 infection in dental clinics, and untreated dental conditions were associated with fear to seek dental care.

Background: Artificial Intelligence (AI) and its subset, Machine Learning (ML), have emerged as pivotal tools in dental public health by enhancing diagnostic accuracy, optimizing resource allocation, and personalizing patient care. AI offers significant opportunities, particularly in predictive analytics, personalized interventions, and expanding access to underserved areas. Objective: This review presents a broad evaluation of AI’s applications in dental public health, emphasizing their roles in diagnostics, discussing ethical considerations, and outlining future directions to enhance public health practice and policy. Methods: We conducted a literature review of published articles from major databases (e.g., PubMed, Scopus, Web of Science) between 2015 and 2024. We used relevant search terms (e.g., “Artificial Intelligence,” “Machine Learning,” “Dental Public Health,” “Ethical Considerations,” “Predictive Analytics”). We applied inclusion and exclusion criteria based on relevance to diagnostics, epidemiological data analysis, health promotion, and ethical/legal frameworks. Results: The findings indicate that AI technologies enhance diagnostics (e.g., interpreting dental radiographs), support predictive analytics for disease monitoring, and enable targeted health interventions. However, significant challenges include data privacy risks, algorithmic biases, and compatibility with existing infrastructures. Ethical considerations, such as transparency, accountability, and equitable access are essential for responsible AI integration. Conclusion: AI holds the potential to revolutionize dental public health by improving patient outcomes, especially in underserved populations. Further interdisciplinary research, clear policy frameworks, and strong data protection measures are required to ensure the ethical and effective deployment of these technologies. Future investigations should also foster interprofessional collaboration to maximize the benefits of AI in dental public health.

OBJECTIVES: The objective of this study was to evaluate the use of survival analysis in cyclic fatigue testing in orthodontic bracket bonding. MATERIALS AND METHODS: We used 100 extracted bovine lower incisors (50 orthodontic brackets and 50 eyelet brackets). Each set of brackets was further divided by etching technique (25 total-etch and 25 self-etch). Cyclic fatigue testing was performed at a crosshead speed of 2 mm/min using an up-and-down method. Kaplan–Meier survival data analyses and Cox regression analyses were performed. RESULTS: Survival analysis proved to be a simple methodology and revealed that the etching technique was not a statistically significant predictor for survival of orthodontic bracket bonding with either tensile or shear cyclic forces at P > 0.05. In tensile cyclic loading, high mechanical loading after controlling for the etching technique is a statistically significant predictor for lower survival of the orthodontic bracket bond at P < 0.001. CONCLUSIONS: Both etching techniques (total-etch and self-etch) are equally efficient in bonding orthodontic brackets. High mechanical loading is an important predictor of bond failure when applying tensile cyclic forces. Finally, survival analysis is a simpler alternative method to analyze orthodontic bracket bonding subjected to cyclic tensile and shear forces and gives similar results to other complicated methods.

Objective: This study was aimed to evaluate the dental age in Saudi children from panoramic radiographs using the Demirjian method to estimate their chronological age. Materials And Methods: This retrospective cross-sectional study consisted of 1902 panoramic radiographs of 955 boys and 947 girls between the ages of 3–17 years. All children were placed in the age group closest to their chronological age. The dental age was scored on all seven left mandibular teeth by calibrated examiners. Bivariate analyses using the t-test and Pearson correlation were performed. Results: There was significant difference in both boys and girls in all the age groups between their chronological age and dental age. Even though there was a slight overestimation in boys in some age groups and slight underestimation in girls in some groups, correlation analysis showed that there was a highly significant correlation between the chronological age and dental age for both boys (r² = 0.96, P < 0.001) and girls (r² = 0.98, P < 0.001). Moreover, correlation analyses for each age group showed a significant correlation between the chronological age and the dental age, using the Demirjian method, in most age groups (P < 0.01). When comparing the maturation score between boys and girls, the Student's t-test showed that there were no statistical differences between boys and girls in most age groups. Conclusion: Saudi boys and girls living in the western region of Saudi Arabia exhibited similar pattern of dental development when compared to the Demirjian method. Hence, the Demirjian method could be used as reference in children from the western region of Saudi Arabia.