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Sickle cell disease (SCD) is a hereditary blood condition characterized by abnormal hemoglobin, leading to chronic hemolysis and vaso-occlusive complications. Caregivers of children with SCD often experience significant distress, akin to post-traumatic stress disorder (PTSD). This study aimed to measure the degree of trauma and post-traumatic growth among parents (caregivers) of children with SCD in the Kingdom of Saudi Arabia. A total of 294 primary caregivers were recruited for this study, through direct phone calls and online outreach using contact information obtained from their primary treating physician in Maternity and Children Hospitals and the Hereditary Blood Diseases Center in Al-Ahsa. Inclusion criteria required caregivers not to be receiving professional mental health care and to have a child with SCD below the age of 18. Results indicate that caregiver gender significantly affected IESR scores, with mothers reporting higher scores than fathers. Family income had a significant effect on IESR as well. In terms of education level, higher-educated caregivers were less likely to experience severe trauma. Significant differences emerged between online and phone interview participants, with online respondents reporting higher post-traumatic growth and higher trauma levels. This study represents a crucial step in understanding the challenges faced by caregivers of children with SCD in Al-Ahsa, Saudi Arabia. However, the study has limitations, including a substantial portion of the sample being from a single clinic and a cross-sectional design.

In today’s data-driven world, we are constantly exposed to a vast amount of information. This information is stored in various information systems and is used for analysis and management purposes. One important approach to handle these data is through the process of clustering or categorization. Clustering algorithms are powerful tools used in data analysis and machine learning to group similar data points together based on their inherent characteristics. These algorithms aim to identify patterns and structures within a dataset, allowing for the discovery of hidden relationships and insights. By partitioning data into distinct clusters, clustering algorithms enable efficient data exploration, classification, and anomaly detection. In this study, we propose a novel centroid-based clustering algorithm, namely, the morphological accuracy clustering algorithm (MAC algorithm). The proposed algorithm uses a morphological accuracy measure to define the centroid of the cluster. The empirical results demonstrate that the proposed algorithm achieves a stable clustering outcome in fewer iterations compared to several existing centroid-based clustering algorithms. Additionally, the clusters generated by these existing algorithms are highly susceptible to the initial centroid selection made by the user.

Objective: The objective of this study is to assesses the preparedness of primary care centers (PHCs) in Aseer region, KSA, for the coronavirus disease 2019 (COVID-19) pandemic. Methods: This survey was conducted during April 2020 in PHCs. The questionnaire was developed by the investigators and sent via e-mail to health care providers of primary health care centers (PHCCs). The questionnaire consisted of five parts to assesses readiness of PHCs, knowledge, attitude, and practice of health care providers (HCPs) concerning the COVID-19 pandemic. Data entry and analysis were managed by SPSS version 20. Results: Three hundred and seventy-one HCPs participated in this study. Most of them were males (58%), doctors or nurses (81%). Almost all PHCCs have adequate infection control resources, with some shortage in sterilization rooms. Most of participants received on-job training (85%) and had good knowledge about COVID-19. Attitudes of participants showed variation toward COVID-19; 74% were afraid to be infected, 54% were afraid to care for infected patients, 58% were ready for vaccination, and 80% thought that COVID-19 has a huge negative impact on the health care system. Compliance with preventive measures ranged from 66% for keeping social distance to 90% for using personal protective equipment. Most of the participants had positive contributions regarding health education of individuals and communities using different methods including the new social media (80%). Conclusion: This study revealed that PHCCs in Aseer region were well equipped and HCPs were well prepared to deal with the COVID-19 pandemic. There are some shortage in a few items of infection control at PHCCs and gaps in knowledge and practice among HCPs which need continuous assessment and monitoring to overcome such barriers.