Conectar
Values and preferences are key determinants of optimal care, and variability in patient values and preferences often dictates differences in patient management. Clinicians’ views of patients’ values and preferences may differ across cultural aspects and stage of training, but the extent to which this is the case remains uncertain. One key value and preference issue is the trade-off between quantity and quality of life, and this issue is particularly prominent among patients with dementia. We therefore propose to investigate the extent to which physicians’ perceptions of optimal management for patients living with advanced dementia may differ due to cross-cultural factors and stage of medical training.
We will conduct a sequential explanatory mixed-methods study (QUAN -> qual). First, we will administer paper-based or electronic surveys during educational sessions, conferences and rounds to medical students, residents and physicians in ten countries, either in person or online. Following that, a qualitative inquiry, guided by the findings of the quantitative study and the principles of the interpretive description design, will inform an in-depth exploration of the predictive factors identified in the quantitative data analysis.
The Hamilton Integrated Research Ethics Board at McMaster University has approved this study (approval number 2024-17651). We will disseminate our findings in peer-reviewed publications and present results at conferences as oral and poster presentations.
Type 2 diabetes (T2D) is a complex disease with a heterogeneous clinical presentation. Recently, five distinct clusters of T2D have been identified in the Emirati population of long-standing T2D with complications. This study aimed to validate these clusters in newly diagnosed T2D patients without any complications and determine whether severe and mild phenotypes are detectable early in the disease course.
Retrospective, cross-sectional, non-interventional study.
Primary healthcare centres in Dubai, UAE.
A total of 451 adults, including both Emiratis and expatriates, diagnosed with T2D in the last 5 years and without T2D-related complications at the time of visit, were enrolled. Patients with complications, incomplete clinical data or higher duration of T2D were excluded from the study.
Identification of distinct T2D clusters using machine learning-based clustering analysis. Five clinical variables: age at diagnosis, body mass index, glycated haemoglobin, fasting serum insulin and fasting blood glucose served as predictors. Overlap between clusters was assessed via the Silhouette Index and Bayesian probability.
Five clusters were identified, replicating prior findings: severe insulin-resistant diabetes (SIRD), severe insulin-deficient diabetes (SIDD), mild age-related diabetes (MARD), mild obesity-related diabetes (MOD) and mild early-onset diabetes (MEOD). As confirmed by a Silhouette Index and Bayesian probability of 1, 55.43% of the patients showed cluster-exclusiveness, while 44.56% of the cohort showed overlap between clusters. The highest overlap was recorded for mild forms of T2D in the order MOD>MARD>MEOD.
The study confirms that both severe and mild T2D phenotypes are present in newly diagnosed, complication-free patients, supporting the applicability of cluster-based classification early in disease. These results highlight the potential for personalised treatment strategies to optimise management and prevent complications. Future studies should investigate longitudinal outcomes and therapeutic response across clusters.
Nurses' burnout, work instability (WI), and job satisfaction (JS) in their practice environment (PE) are well established in the literature. However, perinatal missed care (PMC), a subset of missed nursing care, remains underreported among maternity nurses.
To examine the mediating role of PE and burnout in the associations of WI, JS, and PMC among maternity nurses.
A cross-sectional and correlational study employed consecutive sampling to recruit maternity nurses (n = 312) from five hospitals in Saudi Arabia (three government and two private hospitals in Hail and Makkah regions, respectively). Maternity staff nurses, regardless of their sex, years of professional nursing experience, or nationality, who met inclusion criteria were included in this study. Data was collected from July to September 2024 using four standardized self-report scales. Structural equation modeling was utilized for statistical analyses.
Maternity nurses' WI negatively influenced PE (β = −0.23, p = 0.014), while positively affected PMC (β = 0.15, p = 0.031). The PE positively affected JS (β = 0.24, p = 0.034) but had a negative effect on burnout (β = −0.24, p = 0.007) and PMC (β = −0.21, p = 0.038). Burnout negatively affected JS (β = −0.25, p = 0.028), while positively associated with PMC (β = 0.20, p = 0.022). PE mediated the associations between WI and burnout (β = 0.05, p = 0.019), JS (β = −0.07, p = 0.020), and PMC (β = −0.06, p = 0.008). Meanwhile, burnout mediated between PE and JS (β = 0.05, p = 0.030) and PMC (β = −0.04, p = 0.023).
Understanding the relationships among maternity nurses' burnout, JS, PE, and PMC is key to improving the quality of perinatal care and ensuring the patients' well-being. By focusing on strategies to enhance the PE (e.g., adequate staffing and resources, improved nurse–patient ratio), reduce burnout (e.g., meditation and mindfulness programs, coping intervention programs), and improve JS (e.g., work schedule flexibility, facilitate work-life balance, staff professional development), healthcare organizations can mitigate the occurrence of PMC.
FreshRSS 