Registered general nurses' health assessment practices in a tertiary hospital: A focused ethnography study.

Aim: To explore the assumptions and values that influence nursing health assessment practices among registered general nurses in general medical and surgical wards.

Design: The study was designed as a focused ethnography.

Methods: A semi-structured interview guide was used to explore prevailing nursing health assessment practices of 13 registered general nurses in an attempt to explore the assumptions and values influencing health assessment practices in the study setting.

A Simulation-Based Clinical Nursing Education Framework for a Low-Resource Setting: A Multimethod Study.

Simulation-based clinical education is a useful strategy for teaching, learning, and assessing clinical competence in health professions education. However, the use of simulation-based clinical nursing education (SBCNE) in low-resource settings such as Ghana has been hampered by the lack of a context-specific framework to guide its design, implementation, and evaluation. This study sought to develop a context-specific framework to guide the design, implementation, and evaluation of SBCNE in a low-resource setting.

Competitive Plant-Mediated and Intraguild Predation Interactions of the Invasive and Resident Stemborers and in Maize Cropping Systems in Kenya.

Following its recent invasion of African countries, fall armyworm (FAW), Spodoptera frugiperda (Lepidoptera: Noctuidae), now co-exists with resident stemborers such as Busseola fusca (Lepidoptera: Noctuidae) and Chilo partellus (Lepidoptera: Crambidae) causing severe damage to maize crops. Due to niche overlap, interspecific interactions occur among the three species, but the mechanisms and degree remain unclear. In this study, we assessed plant-mediated intraspecific and interspecific interactions, predation in laboratory and semi-field settings, and larval field occurrence of S.

Advances in data-collection tools and analytics for crop pest and disease management.

Innovative methods in data collection and analytics for pest and disease management are advancing together with computational efficiency. Tools, such as the open-data kit, research electronic data capture, fall armyworm monitoring, and early warning- system application and remote sensing have aided the efficiency of all types of data collection, including text, location, images, audio, video, and others. Concurrently, data analytics have also evolved with the application of artificial intelligence and machine learning (ML) for early warning and decision-support systems.