Objectives Behaviour management strategies involving pharmacological or non-pharmacological interventions during dental procedures should be considered to attain safe and successful treatment outcomes. This study compared the frequencies of use and the completeness of treatment with these interventions. Methods A total of 1725 dental records of patients up to 18 years old, who were treated in the King Abdulaziz Medical City in Jeddah City from October 2018 to June 2019, were used in this retrospective, cross-sectional study. Inferential analysis, Chi-square test, Kruskal–Wallis test, and regression model were used in the data analysis. Results About two-thirds of the patients were treated with attendant non-pharmacological interventions, while one-third, with pharmacological interventions. The application of General Anesthesia (GA) was the most frequently used intervention. Restorative procedures and extractions were done in higher frequencies with pharmacological interventions. Treatments with space maintainers and orthodontic appliances were carried out in higher frequencies with non-pharmacological strategies. The choice of intervention was significantly influenced by the systemic conditions of the patients. Patients treated with non-pharmacological intervention comprised the dominant type of patients, because they required treatments with less pain. Those treated with GA needed restorative treatments and extractions, or treatments that involve pain, but these treatments had higher frequencies of being completed. Conclusions The treatments with pharmacological intervention through GA have higher frequencies of being completed, compared to those with non-pharmacological interventions. Factors, such as age, potential to complete the treatment, and the type of dental treatment applied, influence the choice of treatment intervention.

The undergoing research aims to address the problem of COVID-19 which has turned out to be a global pandemic. Despite developing some successful vaccines, the pace has not overcome so far. Several studies have been proposed in the literature in this regard, the present study is unique in terms of its dynamic nature to adapt the rules by reconfigurable fuzzy membership function. Based on patient’s symptoms (fever, dry cough etc.) and history related to travelling, diseases/medications and interactions with confirmed patients, the proposed dynamic fuzzy rule-based system (FRBS) identifies the presence/absence of the disease. This can greatly help the healthcare professionals as well as laymen in terms of disease identification. The main motivation of this paper is to reduce the pressure on the health services due to frequent test assessment requests, in which patients can do the test anytime without the need to make reservations. The main findings are that there is a relationship between the disease and the symptoms in which some symptoms can indicate the probability of the presence of the disease such as high difficulty of breathing, cough, sore throat, and so many more. By knowing the common symptoms, we developed membership functions for these symptoms, and a model generated to distinguish between infected and non-infected people with the help of survey data collected. The model gave an accuracy of 88.78%, precision of 72.22%, sensitivity of 68.42%, specificity of 93.67%, and an f1-score of 69.28%.

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