Background: Transformational leadership fosters trusting relationships; new visions; and personal, professional, and cultural growth. Effective leaders support their team’s motivational growth and organizational goals. This study aims to underscore the importance of transformational leadership and its various dimensions, focusing on its impact on job satisfaction and personal mastery among nursing leaders in healthcare organizations. Method: A cross-sectional design with convenience sampling was used. The evaluation tools included the Multifactor Leadership Questionnaire (MLQ-6S), the Satisfaction of Employees in Health Care (SEHC) questionnaire, and the Personal Mastery Scale (PMS). Results: The findings indicate that job satisfaction is influenced by transformational leadership, emphasizing the importance of tailored leadership development strategies within healthcare organizations. The laissez-faire leadership style was the only one showing no correlation with nurses’ job satisfaction. Other leadership styles showed significant positive or negative correlations with the analyzed variables. Conclusions: Transformational leaders are essential for fostering trust and enhancing job satisfaction in healthcare settings. Positive leadership styles contribute to higher levels of job satisfaction and personal mastery among nursing leaders. Conversely, laissez-faire and autocratic leadership styles can negatively impact performance and staff satisfaction. These findings highlight the critical role of leaders in creating positive work environments and supporting employee development and well-being in healthcare.

Background/Objectives: The nursing profession is expected to undergo substantial transformations in the coming years due to rapidly evolving sociocultural, environmental, and technological changes. Defining and assessing nursing competencies are essential to ensuring high-quality care and fostering professional development. This systematic review aims to explore the future nursing competencies required and the sociocultural factors influencing their evolution. Methods: A comprehensive systematic search was conducted in several indexed databases PubMed, CINAHL, Scopus, and Web of Science databases using keywords such as “nursing competencies”, “future”, “healthcare systems”, and “demographic change”. Studies published within the last five years were included, and a rigorous quality assessment was performed. Results: The findings suggest that key sociocultural and technological factors—including environmental sustainability, technological advancements, innovation, globalization, urbanization, policy uncertainty, and demographic shifts—will significantly shape the development of nursing competencies. It is projected that nearly 70% of the nursing workforce will operate in highly unpredictable environments. The review highlights the need to develop interpersonal, higher-order cognitive, and system-level competencies, alongside complementary skills in personal and customer services, decision making, technology utilization, creativity, and scientific methodologies. Conclusions: Addressing the future challenges in nursing requires a holistic and strategic approach, including a cultural shift within the profession supported by targeted policies and sustained investment in education and continuous professional development. Training systems should prioritize the development of core competencies and promote lifelong learning to ensure adaptability in an evolving healthcare landscape.

Background/Objectives: Inequalities in access to nursing professionals represent a significant challenge to achieving equity in healthcare systems. In decentralized countries like Italy, disparities in the distribution of nurses persist despite a universal national health system. This study investigates the extent and determinants of regional inequality in the distribution of the nursing workforce in Italy. Methods: A retrospective ecological analysis was conducted using administrative data from official national sources (ISTAT, Ministry of Health) concerning the number of nurses and population per region, along with Human Development Index (HDI) data from 2021. Descriptive statistics, the Gini coefficient, Lorenz curve, and Pearson correlation were used to assess inequality and identify influencing factors. Results: The national Gini coefficient was 0.136, indicating a moderate degree of inequality in the distribution of nurses across Italian regions. A strong positive correlation was observed between HDI and nurse-to-population ratio (r = 0.76, p < 0.001), suggesting that more developed regions have higher nursing density. Conclusions: Despite a universal healthcare system, Italy shows persistent regional disparities in nurse distribution. These findings emphasize the need for targeted policies and coordinated planning to reduce inequalities and ensure equitable access to nursing care across all regions.

Background/Objectives: The uneven distribution of nurses in Albania is a major problem that compromises equitable access to health services. Rural and less developed regions suffer from a chronic shortage of nursing staff, while urban areas attract health professionals. This study aims to quantify the inequalities in the distribution of nurses in Albania, analyzing the nurse-to-population ratio and its impact on the quality of healthcare. The main objective of this study is to examine the distribution of the nursing workforce in Albania and assess regional disparities, using the Gini coefficient and the Human Development Index (HDI) to measure and compare inequalities between regions. Methods: This descriptive–analytical study was conducted in 2024. The data were collected from official sources, including the Albanian Ministry of Health and the World Health Organization (WHO). The Gini coefficient and the Lorenz curve were used to analyze the distribution of nurses in relation to the population and HDI of the different regions. The analysis included data on the number of nurses, population, and regional socioeconomic conditions. Results: The average nurse-to-population ratio in Albania is 28 nurses per 10,000 inhabitants, with significant variations between regions. Tirana has the highest ratio (60 nurses per 10,000 inhabitants), while Kukës and Dibër have the lowest values (10 per 10,000 inhabitants). The calculated Gini coefficient is 0.0228, indicating a very low level of inequality in the distribution of the nursing workforce. Conclusions: Inequalities in the distribution of nurses in Albania require targeted policy interventions. Policies are needed that incentivize health workers to work in less developed regions, through economic incentives, infrastructure improvements, and lifelong learning programs. These interventions are essential to reduce disparities and ensure equitable access to health services across the country.

Background/Objectives: The uneven distribution of nurses in Albania is a major problem that compromises equitable access to health services. Rural and less developed regions suffer from a chronic shortage of nursing staff, while urban areas attract the health professionals. This study aims to quantify the inequalities in the distribution of nurses in Albania, analyzing the nurse-to-population ratio and its impact on the quality of health care. The main objective of this study is to examine the distribution of the nursing workforce in Albania and assess regional disparities, using the Gini coefficient and the Human Development Index (HDI) to measure and compare inequalities between regions. Methods: This descriptive-analytical study was conducted in 2024. The data was collected from official sources, including the Albanian Ministry of Health and the World Health Organization (WHO). The Gini coefficient and the Lorenz curve were used to analyze the distribution of nurses in relation to the population and HDI of the different regions. The analysis included data on the number of nurses, population and regional socioeconomic conditions. Results: The average nurse-to-population ratio in Albania is 28 nurses per 10,000 inhabitants, with significant variations between regions. Tirana has the highest ratio (60 nurses per 10,000 inhabitants), while Kukës and Dibër have the lowest values (10 per 10,000 inhabitants). The calculated Gini coefficient is 0.0228, indicating a very low level of inequality in the distribution of the nursing workforce. Conclusions: Inequalities in the distribution of nurses in Albania require targeted policy interventions. Policies are needed that incentivize health workers to work in less developed regions, through economic incentives, infrastructure improvements and lifelong learning programs. These interventions are essential to reduce disparities and ensure equitable access to health services across the country.

Background/Objectives: Inequalities in access to health professionals represent a significant challenge in achieving equitable health care systems. In many countries, particularly those with decentralized governance, disparities in the distribution of human health resources persist despite efforts to promote uniform access. This study investigates the extent and determinants of regional inequality in the distribution of the healthcare workforce in Italy. Methods: A retrospective ecological analysis was conducted using administrative data on physicians and nurses per 10,000 inhabitants across Italy’s regions from 2010 to 2021. The Gini coefficient was used to measure inequality in workforce distribution. Additional indicators such as average salary and health expenditure per capita were examined to identify potential drivers of disparity. Conclusions: Despite a universal national health system, Italy continues to exhibit pronounced regional disparities in the distribution of healthcare professionals. These findings highlight the need for targeted policy interventions to promote equity in health workforce allocation. A better alignment between national planning and regional implementation could help reduce inequalities and improve access to care in underserved areas.