Since the outbreak of COVID-19, studies related to the COVID-19 pandemic have been published widely. However, there are limited qualitative studies in Ghana that explored and shed light on frontline nurses’ experiences and challenges in caring for patients diagnosed with COVID-19. This study aimed to explore frontline nurses’ experiences and challenges of providing care for COVID-19 patients in the Volta Region of Ghana. This study adopted a descriptive qualitative research design to collect data. We conducted the study among frontline nurses who provided nursing care for COVID-19 patients in the Treatment Centre for COVID-19 cases in the Volta Region of Ghana. A purposive sampling method was used to select fifteen (15) participants for this study. We collected data through individual in-depth interviews facilitated by a semi-structured interview guide. The content analysis approach was used to analyse the data. The results showed: frontline nurses received inadequate information and training during the initial stages of the pandemic; stress and burnout because of inadequate staffing; logistical challenges; stigmatisation by family members and friends; frontline nurses displeased with the decision to exclude other nurses as frontline workers; participants made some recommendations towards supporting frontline nurses for effective management of patients during pandemics. This study revealed an in-depth understanding of the experiences of frontline nurses who provided nursing care to COVID-19 patients during the pandemic. Our study concludes that the frontline nurses experienced both physical and psychological problems while caring for COVID-19 patients at the treatment centre. Some challenges frontline nurses encountered were inadequate information on COVID-19 prevention and management in the early stages of the pandemic, logistical inadequacies, and stigmatisation in providing care for COVID-19 patients during the pandemic, all of which affected the quality of nursing care, work productivity, and efficiency. Therefore, nurse managers need to provide support to frontline nurses providing care for patients with COVID-19.

Background: Diabetes is one of the major non-communicable diseases. Diabetes self-management has been identified as a key strategy to reduce complications and to improve health outcomes. Aim: This study aimed to investigate the diabetes self-management knowledge, attitude and practices among people with type-2 diabetes in Ghana. Setting: Two clinics for diabetes patients in the Ho municipality of Ghana were selected to conduct the study. Methods: An outpatient cross-sectional survey was conducted using a 57-item researcher-administered questionnaire based on the Information, Motivation, Behaviours Model adopted for Diabetes. A total of 321 patients with type 2 diabetes were randomly selected from the two outpatient clinics for diabetes in Ho, Ghana. Data were analysed using descriptive statistics and multiple linear regression modules were conducted to determine the predictors of self-management practices. Significance was set at p < 0.05. Results: The average score for knowledge was 11.37/24 ± 3.40 or 47%, indicating poor levels of diabetes self-management knowledge. Moderately positive attitudes were found (2.83/5 ± 1.57) [95% CI –1.86 to –3.80] with poor self-management practices with a median of 3.00 per week (maximum 5.20, minimum 0.60 per week). Knowledge explained 20% of variation in self-management practice. Conclusion: The findings from this study show an overall deficit in knowledge of diabetes with related low self-management practice. This suggests the need for robust self-management education programmes to improve access to diabetes self-management-related information. Contribution: This study highlights the important knowledge of diabetes in self-management.

Background: Artificial Intelligence (AI) offers transformative potential for healthcare education, yet its adoption among key frontline cadres in low-resource settings remains poorly understood. This study is the first to investigate the predictors of AI usage and knowledge among nursing and midwifery students in Ghana. Methods: An analytical cross-sectional study was conducted with 676 students from the University of Health and Allied Sciences, recruited via convenience sampling. A validated questionnaire assessed AI knowledge, usage patterns, and sources of information. Data were analyzed using descriptive statistics, binary logistic regression, and ROC analysis in STATA v17.0. Results: Most participants (78.6%) used AI, with significantly higher odds among males (aOR: 2.33, 95% CI;1.21–4.47, p = 0.011) and final-year students (aOR: 3.05, 95% CI;1.64–5.67, p = 0.001). While 73.7% demonstrated adequate knowledge, acquisition occurred primarily through informal sources (internet/media), with ChatGPT being the dominant tool. Predictive models for AI usage and knowledge demonstrated significant associations but modest discriminative power (AUC range: 0.58–0.63), indicating the role of unmeasured factors. Conclusion: A high reliance on informal, self-directed AI learning exists among students, revealing a critical gap in formal education. Despite strong adoption, significant demographic disparities and a clear “usage-knowledge disconnect” necessitate the urgent integration of structured, equitable AI curricula into Ghana’s nursing and midwifery training programs.