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Background Motor vehicle crashes (MVCs) are the leading cause of child deaths in the Gulf Cooperation Council. This study aimed to investigate the effect of a social media educational campaign on parents' knowledge of child safety seats. Methods We conducted a pre-post interventional study as an online educational module in Arabic and English. The module link was shared on social media and was accompanied by a pre-post survey that included questions about demographics, knowledge, and practices of car seat use. Results A total of 303 participants completed the campaign, with 23.8% fathers and 76.2% mothers answered the survey. The majority of participants were from Saudi Arabia (95.7%), while 4.3% were from other Gulf Cooperation Council (GCC) countries. Most parents agreed on the importance of organizing awareness campaigns and having a law to enforce the use of car seats. The pre-survey mean knowledge score was 11.64, which significantly increased to 13.1 in the post-survey ( p  < 0.001). Conclusions The intervention of the educational campaign through social media resulted in a significant increase in parents' knowledge and awareness of the importance of using car seats correctly. This study highlights the potential effectiveness of social media campaigns in improving parents' knowledge and awareness of child safety seats.

Apology has been an important topic in personal relationship studies over the past three decades. This study is based on Sugimoto’s empirically derived characterization of apology strategies and explores how Saudis of both genders and of different ages use apology strategies to demonstrate their politeness. The study’s three main objectives were to identify the most commonly employed apology strategies and to determine the significance of gender and of age on how people used apology strategies. Data collection relied on the Multiple Discourse Completion Task Questionnaire, which contains questions about different real-life scenarios and multiple answers that measure the use of apology strategies. It was distributed to 102 female and 93 male participants of different ages (between 18 and 50). The study established that the most used apology strategies are self-blame and then compensation, while the least used are blaming the victim and asking the victim not to be angry. The rest of the apology strategies occur at different frequencies. The study also found that women use apology strategies significantly more than men do. Women tend to use thanking, lack of intent, asking for forgiveness, and asking the victim not to be angry, whereas men use compensation, avoiding the victim, blaming the victim, promising not to repeat, and offending the victim more than women do. In addition, the study found significant differences in which apology strategies people of different ages used.

Studies proved the existence of a pidgin used by non-Arabic speakers among themselves and when contacting Arabic speakers. However, examining the use of this pidgin by Arabic speakers is still not well covered. Thus, this paper is an attempt to examine the linguistic features employed by Arabic speakers using the pidgin while dealing with non-Arabic speakers. The data includes 78 WhatsApp voice notes created by 20 male and female Arabic speakers communicating with non-Arabic speakers living in Dammam, Saudi Arabia. The findings show that some lexifier language features are being maintained while others are pidginized. Lexifier language sounds as the pharyngeal, uvular, emphatic, and interdental sounds are maintained, while structure constituents order, affixation, number words agreement are pidginized. More studies are needed to be conducted in this field.

Artificial intelligence (AI) is revolutionizing modern dentistry by enhancing diagnostic accuracy, streamlining workflows, and enabling personalized patient care. Leveraging advanced computational models, including machine learning and convolutional neural networks (CNNs), AI applications span across dental specialties such as surgical dentistry, orthodontics, endodontics, orthodontics, and oral pathology. These technologies facilitate early disease detection, precise treatment planning, predictive modeling of restorative success, and improved clinical outcomes and patient satisfaction. Despite its transformative potential, the integration of AI into dentistry faces challenges such as data bias, limited interpretability, and ethical concerns surrounding patient privacy. This review explores the applications, limitations, and future prospects of AI in dentistry.