KNOWLEDGE,

Self-medication is a widespread public health concern, particularly in low- and middle-income countries where barriers to healthcare access persist. This study examined the prevalence, knowledge, patterns, and influencing factors of self-medication among artisans in Ovia North- East Local Government Area, Edo State, Nigeria. A descriptive cross-sectional design wasNemployed, and data were collected from 212 artisans using a structured questionnaire. The data were analyzed using descriptive statistics (frequencies, percentages, means, and standard deviations) and inferential statistics (Pearson’s correlation) at a 0.05 level of significance. The socio-demographic profile revealed that the respondents were predominantly young adults (34.0% aged 28–37 years), male (67.9%), and moderately educated, with secondary education constituting the highest proportion (41.5%). Findings on prevalence showed that 77.4% of respondents engaged in self-medication, with headaches (65.1%), malaria (57.5%), and body pain (53.8%) being the most common conditions treated. In terms of knowledge, while most respondents correctly defined self-medication (80.2%) and acknowledged its risks (90.1%), only 45.3% demonstrated awareness of drug side effects, resulting in a moderate mean knowledge score of 3.15 (SD = 1.12). The overall classification showed that 60.4% of respondents had good knowledge, while 39.6% had poor knowledge. Regarding patterns of practice, pain relievers (61.3%), antimalarials (51.9%), and antibiotics (46.2%) were the most commonly used drugs, with 66.0% of respondents adhering to full dosage. However, unsafe practices such as incomplete dosage and reliance on herbal drugs (35.4%) or informal drug sources (15.1%) were also reported. The mean pattern score was 3.73 (SD = 0.47), indicating a moderate balance between safe and unsafe practices. Factors influencing self- medication included easy access to drugs (72.6%), high cost of healthcare (67.9%), long waiting times at hospitals (60.4%), peer/family influence (40.6%), and prior experience with illness (56.6%). Hypothesis testing revealed significant relationships between knowledge and practice (r = 0.41, p = 0.001), socio-demographic factors and self-medication patterns (r = 0.312, p = 0.002), and accessibility to healthcare and frequency of practice (r = 0.46, p = 0.001). These results confirm that self-medication is influenced by a combination of knowledge, socio-economic factors, and systemic barriers. The study concludes that self-medication is highly prevalent among artisans and poses considerable health risks despite moderate knowledge levels. It highlights the need for targeted health education, regulation of drug accessibility, and improvement of healthcare affordability and efficiency to mitigate unsafe practices. The findings also have implications for nursing practice, particularly in community health education, preventive care, and patient advocacy

AI in healthcare has gained significant momentum in recent years, revolutionizing the delivery of medical services and transforming patient care processes across various specialties. Nursing, as a fundamental pillar of healthcare, is increasingly experiencing the impact of AI technologies, which range from decision support systems, robotics, predictive analytics, to personalized patient care applications. However, the successful adoption and optimal utilization of AI in nursing practice depend largely on nurses' knowledge, perceptions, and the roles they assume in its implementation. The aim of this study is to provide insights into the current knowledge and perceptions of nurses regarding AI, identifying potential gaps that could hinder effective practice. Understanding these gaps will help healthcare administrators and policy-makers design targeted interventions. This study employs a descriptive cross-sectional research design to investigate knowledge and perception of AI among nurses at the University of Benin Teaching Hospital (UBTH). A total of 257 participants were chosen using a stratified random sampling technique. A well self-structured questionnaire was used to access the knowledge, perception and roles of nurses as regards the use of AI among nurses in UBTH. The result shows, 74.3% of the respondents exhibiting correct knowledge of AI in comparison with the McDonald’s scale indicates a moderate level of knowledge regarding AI. Also with a total mean score of 2.8, the study reveals that the respondents have a good perception of AI. Of the 257 respondents, 196 (76.3%) of the respondents strongly agreed that nurses should be involved in the planning and implementation of AI systems, 15(5.8%) disagreed, 31(12.1%) agreed while 15(5.8%) strongly disagreed. The mean response of the respondents is 2.53 which is greater than the average of 2.50 for a 4-point Likert scale, hence indicating the respondents generally agree that Nurses should be involved in the planning and implementation of AI systems. This study thus concluded that there is a fair knowledge, the respondents have good perception of AI and involving in the planning and implementation of AI systems are some of the roles of nurses in the use of AI

Patient safety is central to quality healthcare delivery. Globally, unsafe care contributes significantly to morbidity, mortality, and healthcare costs. In low- and middle-income countries like Nigeria, challenges such as weak reporting systems, staff shortages, and limited training heighten risks. Doctors, as frontline caregivers, are pivotal to improving safety standards, but evidence on their knowledge, attitudes, and practices within Nigerian contexts remains limited