Yahya Hussein Ahmed Abdalla

Aim: This study examined the relationship between transformational leadership and clinical work performance among nursing professionals within the Tabuk Health Cluster. It focused specifically on the association of leadership behaviours with nursing performance. Design: The study utilized a cross‐sectional analytical quantitative research design. Methods: Participants: A convenience sample of 280 nursing professionals (staff nurses and head nurses) from within the Tabuk Health Cluster was enrolled. Measures: Transformational leadership was measured with the Global Transformational Leadership (GTL) scale, and clinical performance through a 51‐item scale derived from Yuxiu et al. (2011). Data Collection: This was a self‐administered online questionnaire conducted over approximately 6 weeks, between November and January 2024. Analysis: Data were analysed using SPSS version 26 with descriptive statistics, independent samples t ‐tests, ANOVA, and multiple linear regression to determine the predictive value of transformational leadership. Results: Nurses perceived leadership positively (mean = 3.96/5). Overall clinical work performance was moderate (Mean = 2.70/4), with the leadership (2.75) and critical‐care (2.79) subscales scoring highest. Transformational leadership significantly predicted clinical performance ( p < 0.001), accounting for 26.9% of its variance. Nurses with 1–5 years of critical‐care experience scored significantly higher than those with more than 5 years on both leadership perception and clinical performance ( p < 0.001). Conclusion: Transformational leadership was positively associated with nurses' clinical performance and represents a modifiable target for improvement. The lower scores among more experienced nurses indicated a need to re‐engage mid‐to late‐career staff. Implications for Nursing Practice: The findings support investment in transformational leadership development, direct support for clinical performance, a stronger feedback culture, continuing professional development—particularly for mid‐ to late‐career nurses—and quality‐improvement efforts within the Health Cluster system. No patient or public contribution: While the study acknowledges the vital participation of nursing staff at the Tabuk Health Cluster, patients and members of the public were not involved in the design, conduct or reporting of this research.

Background: The primary healthcare sector has experienced significant growth globally, and the nursing workforce has also expanded in recent decades in response to health system reforms. This study aims to assess job satisfaction among primary healthcare nurses in Khartoum, Sudan. Methods: This descriptive cross-sectional study was conducted in 10 primary healthcare centers on 50 nurses who were selected using simple random sampling. Data were collected using an online questionnaire and it was analyzed using SPSS. Results: The findings of this study indicate that the job satisfaction level among nurses working at primary healthcare centers in Khartoum was high (4.4/5). Most nurses reported high satisfaction with all items including protocols, salary, environment, and relationships. The study also found a significant correlation between nurses’ sex and experience with their level of job satisfaction. Female nurses reported significantly higher job satisfaction (4.4/5) compared to male nurses (3.6/5), (p-value = 0.04). Additionally, nurses with fewer years of experience reported significantly higher job satisfaction compared to those with more years of experience (p-value = 0.03). Conclusion: The study concludes that nurses working at primary healthcare centers in Khartoum have high job satisfaction, particularly regarding the working environment, salary, relationships, and availability of guidelines. Female nurses and those with less experience have significantly higher job satisfaction.

The study sought to identify parental trends in children's self-medication, health-seeking behavior, knowledge of self-medication, antibiotic use, and antimicrobial resistance in Asir, Saudi Arabia. A web-based cross-sectional study was carried out by a survey questionnaire. Snow Ball sampling technique was used to select the Eight hundred and sixteen parents with children in the Asir region by WhatsApp and email, and 650 participants who met the inclusion criteria consented to participate in the study. There were 1809 episodes of childhood illnesses reported during the study period. The mean scores are on knowledge at 8.11 ± 2.43, favorable attitude at 17.60 ± 1.17, and practice was 7.72 ± 1.72, and a significant correlation was found between knowledge, attitude, and practice (KAP) at p = 0.01. Out of 624, the majority of parents showed strong knowledge and proficiency in antibiotics. However, the attitude scores of over 50% towards the usage of antibiotics were subpar. Around 54% of parents were self-medicating their children and 43% were unaware that skipping doses contributes to anti-microbial resistance (AMR). The facilitators for self-medication were male gender (aOR: 2.13; 95% CI: 1.26-3.98, p < 0.05), having more children (aOR: 2.78; 95% CI: 1.27-4.12 p < 0.01), professional qualification (aOR:3.07; 95% CI 1.57- 4.68; p < 0.01), residing in urban area (aOR: 3.17; 95% CI: 2.13-5.61, p < 0.05), working in health care (aOR: 5.99; 95% CI: 1.78-18.2, p < 0.01) and high income (aOR: 3.57; 95% CI: 2.08-6.34, p < 0.05). The findings indicated that the majority of parents had unfavorable views and improper practices of antibiotic usage. Strategic education programs to the targeted population, especially to the parents about side effects of antibiotics, dangerous consequences of self-medication, and crucial AMR concerns must be addressed immediately.

Background: Lung cancer is a fatal disease that kills approximately 85% of those diagnosed with it. In recent years, advances in medical imaging have greatly improved the acquisition, storage, and visualization of various pathologies, making it a necessary component in medicine today. Objective: Develop a computer-aided diagnostic system to detect lung cancer early by segmenting tumor and non-tumor tissue on Tissue Micro Array Analysis (TMA) histopathological images. Method: The prototype computer-aided diagnostic system was developed to segment tumor areas, non-tumor areas, and fundus on TMA histopathological images. Results: The system achieved an average accuracy of 83.4% and an F-measurement of 84.4% in segmenting tumor and non-tumor tissue. Conclusion: The computer-aided diagnostic system provides a second diagnostic opinion to specialists, allowing for more precise diagnoses and more appropriate treatments for lung cancer.