A Dynamic Analysis of the Demand for Health Care in Post-Apartheid South Africa

The Daily Basic Psychological Need Satisfaction and Work Engagement of Nurses: A ‘Shortitudinal’ Diary Study

Nurses’ satisfaction and work engagement have been linked to patient outcomes. Nightshift nurses provide healthcare to the population and experience unique challenges in performing their healthcare tasks. Therefore, the current study aimed to investigate the daily basic needs satisfaction and work engagement of nightshift nurses in accordance with the satisfaction of three basic psychological needs as indicated by the Self-Determination Theory. A quantitative, ‘shortitudinal’ design (diary study; over a few days) with a multi-level research approach using a daily diary survey method was completed by a convenience sample of nurses working the nightshift in a public hospital (n = 33). The results revealed that the daily need for autonomy and need for relatedness did not significantly predict variance in daily work engagement. However, need for competence did significantly predict variance in daily work engagement, and general emotional load explained significant variability in daily need satisfaction of competence. Lastly, general role clarity had a negative impact on the daily variability in work engagement. This study provides healthcare organisations with explanations for variance in nursing performance and suggests possible interventions to address nursing outcomes in accordance with the three basic needs of nightshift nurses in daily activity.

The Role of Artificial Intelligence and Machine Learning Amid the COVID-19 Pandemic: What Lessons Are We Learning on 4IR and the Sustainable Development Goals

The COVID-19 pandemic came with disruptions in every aspect of human existence, with all the sectors of the economies of the world affected greatly. In the health sector, the pandemic halted and reversed progress in health and subsequently shortened life expectancy, especially in developing and underdeveloped nations. On the other hand, machine learning and artificial intelligence contributed a great deal to the handling of the pandemic globally. Therefore, the current study aimed to assess the role played by artificial intelligence and machine learning in addressing the dangers posed by the COVID-19 pandemic, as well as extrapolate the lessons on the fourth industrial revolution and sustainable development goals. Using qualitative content analysis, the results indicated that artificial intelligence and machine learning played an important role in the response to the challenges posed by the COVID-19 pandemic. Artificial intelligence, machine learning, and various digital communication tools through telehealth performed meaningful roles in scaling customer communications, provided a platform for understanding how COVID-19 spreads, and sped up research and treatment of COVID-19, among other notable achievements. The lessons we draw from this is that, despite the disruptions and the rise in the number of unintended consequences of technology in the fourth industrial revolution, the role played by artificial intelligence and machine learning motivates us to conclude that governments must build trust in these technologies, to address health problems going forward, to ensure that the sustainable development goals related to good health and wellbeing are achieved.