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Prevalence and associated factors of burnout & work-place stressors among Emergency Department healthcare workers in Uganda
No full textBackground
Burnout is a widely recognised occupational phenomenon, with Emergency Department (ED) healthcare workers globally facing a heightened risk. Despite this, data on the burden of burnout among ED
healthcare workers, especially in low resource settings, is limited. Our study sought to establish the prevalence and factors associated with burnout and workplace stressors among ED healthcare workers in Uganda.
Methods
An online-based survey was conducted among ED professionals across four private and public hospitals.
Burnout was assessed using the Maslach Burnout Inventory – Human Services Survey (MBI - HSS) tool. Data was analysed using univariable and multivariable logistic regression analyses.
Results
Data from 82 participants were analysed (response rate of 88%), with approximately equal numbers of males and females, just over half providing care to both adult and paediatric patients, and 61% working in public facilities. Overall, 9.7% of participants met the criteria for burnout. In total, 48.7% (n=40) reported high emotional exhaustion, 21.9% (n=18) reported high depersonalisation, and 35.4% (n=29) reported low personal accomplishment. At least 80% of participants identified key ED stressors including work-related fatigue, patients’ financial problems, work overload, equipment shortages, and challenges in balancing professional and personal responsibilities. After adjusting for covariates such as overload of health professional literature needed to be read, patients’ financial problems, educational issues, lack of sufficient
clinical skills, and ED violence, burnout was positively associated with poor communication with colleagues in the ED (Adjusted Odds Ratio [AOR]: 9.90; 95% CI: 1.60 – 61.17; p = 0.014) and with caring for the old and terminally ill patients (AOR: 7.54; 95% CI: 1.38 – 41.29; p = 0.020). These associations were consistent with the high depersonalisation domain of burnout.
Conclusion
Burnout, particularly in the emotional exhaustion domain, is notably prevalent among ED healthcare workers in Uganda. There is a pressing need for context-specific interventions aimed at improving early recognition of burnout and addressing persistent ED stressors. Such measures are essential to enhance ED healthcare workers’ wellbeing, and ultimately improve in-hospital emergency care in Uganda
Legume and soy consumption and the risk of hypertension: a systematic review and dose response meta-analysis of prospective studies
No full textBackground: Several studies have suggested that high intakes of legumes and soy products are associated with a lower risk of hypertension, however, the results have been inconsistent. We conducted a systematic review and meta-analysis to clarify the association between legumes and soy consumption and the risk of hypertension.
Methods: PubMed and Embase databases were searched up to June 14th, 2025. Random effects models were used to calculate summary relative risks (RRs) and 95% confidence intervals (CIs) for the association between legume or soy consumption and hypertension risk. Heterogeneity was evaluated using I². The likelihood of causality was evaluated using World Cancer Research Fund criteria.
Results: Eleven studies (314,018 participants, 88,424 cases) were included in the meta-analysis. The summary RR for high vs. low intake of legumes was 0.84 (0.77-0.93, I2=65%, pheterogeneity=0.003, n=10) and for soy was 0.82 (0.69-0.99, I2=82%, pheterogeneity<0.0001, n=6). In the linear dose-response analyses, the summary RR (95% CI) per 100 grams/day was 0.88 (0.80-0.97, I2=69%, pheterogeneity=0.001, n=10) for legumes and 0.76 (0.60-0.96, I2=89%, pheterogeneity<0.0001, n=6) for soy. The test for nonlinearity was not significant for legumes
(pnonlinearity=0.13), suggesting a linear reduction in risk up to ~170 g/day, while for soy there was indication of nonlinearity (pnonlinearity=0.01), and most of the reduction in risk was observed up to an intake around 60-80 grams/day. Although there was indication of publication bias with Egger's test (p=0.04) for legumes, this was explained by two outlying studies. Using WCRF
criteria, the likelihood of causality was considered probable for both legumes and soy in relation to hypertension risk.
Conclusion: In this meta-analysis of eleven prospective cohort studies, legume and soy intakes were associated with lower risk of hypertension. These findings support dietary recommendations to increase the intake of legumes in the general population
A multi-professional approach to assessing research readiness in a large NHS Trust
No full textBackground The Self-assessment of Organisational Readiness Tool (SORT) allows NHS organisations to evaluate current positions in research readiness. Here we report the experience of using this tool in a large research-active NHS Trust.
Method The scope of the SORT was expanded to include nurses, midwives, allied health professionals, pharmacists and healthcare scientists for a comprehensive assessment of organisational research readiness. Using a collective participatory reflective approach, a Trust-wide working group of colleagues representing each of the organisational directorates sought out and collated evidence that was amalgamated to provide an organisational overview.
Results The SORT can be used to gain an organisational overview of research readiness; however, difficulties emerge in assigning organisation-wide scores in an organisation with multiple professional groups and specialities involved in and contributing to research.
Conclusion Undertaking the SORT assessment and sharing results raised the profile of research healthcare professionals and supported senior leaders to prioritise future work. Using a collective reflective approach offered leaders meaningful insights into the organisation’s readiness to support research and highlighted areas for improvement. Active engagement and understanding of the scoring criteria were essential to maximise the value derived from this project
Investigating usability and acceptability of a virtual community of practice to promote self-management of chronic vascular conditions
No full textIntroduction
Virtual communities of practice (vCOPs) are a way of improving patient self-management. These inclusive online platforms can help support patients with chronic conditions to be part of a clinician-moderated virtual community of practice.
Objectives
To evaluate healthcare professionals’ perspectives on the usability & acceptability of a virtual community of practice (vCoP) for improving patient activation & self-management among those with chronic vascular conditions.
Methods and Analysis
A cross-sectional observational study using convenience sampling was employed. Data were collected during the 2022 Vascular Society Conference held in the United Kingdom. Participants completed a structured questionnaire evaluating vCoP usability, accessibility, perceived patient benefits, & areas for improvement. Descriptive statistics, including percentages, were calculated to summarise the findings.
Results
A total of 42 healthcare professionals, comprising 16 vascular nurse specialists (VNS) & 26 consultant vascular surgeons (CVS), voluntarily participated in the study. Sixty percent of participants found the vCoP platform accessible. The majority agreed or strongly agreed that the platform could enhance patient activation, self-management, the consent process, & the patient journey. Most participants rated the platform’s readability, interactiveness, usability, & overall benefit as either excellent or good. Seventy-six percent of participants identified no major drawbacks, though concerns were raised regarding accessibility for patients with limited internet access or technical skills. Suggested improvements included modifying the layout & creating a mobile app.
Conclusion
Healthcare professionals viewed the vCoP platform as both usable & acceptable, with potential benefits for patient engagement & self-management. Future research is required to assess its effectiveness in improving patient outcomes
TorchCor: high-performance cardiac electrophysiology simulations with the finite element method on GPUs
Get PDFCardiac electrophysiology (CEP) simulations are increasingly used for under standing cardiac arrhythmias and guiding clinical decisions. However, these simulations typically require high-performance computing resources with numerous CPU cores, which are often inaccessible to many research groups and clinicians. To address this, we present TorchCor, a high-performance Python library for CEP simulations using the finite element method on general-purpose GPUs. Built on PyTorch, TorchCor significantly accelerates CEP simulations, particularly for large 3D meshes. The accuracy of the solver is verified against manufactured analytical solutions and the N version benchmark problem. TorchCor is freely available for both academic and commercial use without restrictions
A sparse hp-finite element method for piecewise-smooth differential equations with periodic boundary conditions
No full textWe develop an efficient hp-finite element method for piecewise-smooth differential equations with periodic boundary conditions, using orthogonal polynomials defined on circular arcs. The operators derived from this basis are banded and achieve optimal complexity regardless of h or p, both for building the discretisation and solving the resulting linear system in the case where the operator is symmetric positive definite. The basis serves as a useful alternative to other bases such as the Fourier or integrated Legendre bases, especially for problems with discontinuities. We relate the convergence properties of these bases to regions of analyticity in the complex plane, and further use several differential equation examples to demonstrate these properties. The basis spans the low order eigenfunctions of
constant coefficient differential operators, thereby achieving better smoothness properties for time-evolution partial differential equations
Shale gas development, energy justice and human rights in the Global South
No full textExamines how international, regional, and national legal frameworks hold corporations operating in the natural resource sector accountable for human rights violations in the Global South
Two-stage Bayesian factor analysis for air pollution source apportionment and health risk assessment
No full textAir pollution, especially particulate matter (PM), presents significant public health challenges and is associated with several Sustainable Development Goals (SDGs), notably SDG 3 (Good Health and Well-being) and SDG 11 (Sustainable Cities and Communities). Effective policy development requires robust statistical approaches to identify pollution sources and quantify their health impacts with appropriate uncertainty. This study develops a novel two-stage Bayesian framework for air pollution source apportionment and health risk assessment, with the aim of quantifying the contribution of distinct particle sources to respiratory health outcomes in children, using particle number size distribution (PNSD) data from London. In the first stage, we construct a Bayesian dynamic factor model with autoregressive components to infer latent pollution sources, incorporating non-negativity constraints and accounting for temporal dependence. In the second stage, we assess the relationship between source-specific exposures and respiratory hospital admissions in children via a Poisson regression model, explicitly propagating uncertainty from the source apportionment stage to the health model. The model identifies four main sources: nucleation, traffic, urban activities, and secondary aerosols. Among these, traffic and secondary sources exhibit the strongest and most consistent associations with increased respiratory hospital admissions. Importantly, models that do not account
for uncertainty propagation tend to overestimate health risk associations, underscoring the value of the proposed Bayesian framework. This work illustrates the advantages of integrating Bayesian methods for source apportionment and health effect estimation, with formal uncertainty propagation across model stages. The proposed framework enhances interpretability and supports evidence-based public health and environmental policy. It is readily extensible to other pollutants and settings, contributing to improved air quality management and progress toward global sustainability goals
A counterfactual analysis of the dishonest casino
No full textThe dishonest casino is a well-known hidden Markov model (HMM) often used in education
to introduce HMMs and graphical models. A sequence of die rolls is observed with the
casino switching between a fair and a loaded die. Instead of recovering the latent regime through filtering, smoothing, or the Viterbi algorithm, we ask a counterfactual question: how much of the gambler’s winnings are caused by the casino’s cheating? We introduce a class of structural causal models (SCMs) consistent with the HMM and define the expected winnings attributable to cheating (EWAC). Because EWAC is only partially identifiable, we bound it via linear programs (LPs). Numerical experiments help to develop intuition using benchmark SCMs based on independence, comonotonic, and countermonotonic copulas. Imposing a time homogeneity condition on the SCM yields tighter bounds, whereas relaxing it produces looser bounds that admit an explicit LP solution. Domain knowledge such as pathwise monotonicity or counterfactual stability can be incorporated through additional linear constraints. Finally, we show the time averaged EWAC becomes fully identifiable as the number of time periods tends to infinity. Our work is the first to develop LP bounds for counterfactuals in a HMM setting, benefiting educational contexts where counterfactual inference is taught