The cost of caring

Understanding occupational stress among nurses at Mulago National Referral Hospital

Bibliographic Data

ID22089381
AuthorsEdward Tumusiime (RMIT University), Evas Atuhaire (RMIT University), Eliot Namanya (Uganda Martyrs University), Abraham Muhwezi (0009-0005-9757-0978, Mbarara University of Science and Technology), Steward Mudenda (0000-0003-1692-8981, University of Zambia), Ronald Ouma Omolo (Mbarara University of Science and Technology), Nathan Mugenyi (Mbarara University of Science and Technology)
Year2026
Volume14
Pages1748547-1748547
Publication date2026-04-14
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueFrontiers in Public Health (JOURNAL)
Journal identifiersISSN: 2296-2565 • E-ISSN: 2296-2565
PublisherFrontiers Media SA (PUBLISHER • CH)
DOI10.3389/fpubh.2026.1748547
PMID42058079
OpenAlexW7154364740
LanguageEN
References cited26

Background: Occupational stress is prevalent among nurses, particularly in resource-constrained settings, where high patient volumes, limited institutional support, and societal pressures exacerbate strain. In Uganda, nurses at tertiary referral hospitals face compounded challenges, yet empirical evidence on multilevel determinants of stress is limited. This study applied the Job Demands-Resources-Support (JDRS) framework to examine health system, patient-related, and community-level factors influencing occupational stress among nurses at Mulago National Referral Hospital (MNRH). Methods: A facility-based cross-sectional study was conducted from April to June 2024, enrolling 231 nurses through availability sampling. Occupational stress was measured using a self-reported binary indicator, and explanatory variables captured job demands, control, and support per the Job Demand-Control-Support (JDCS) framework. Descriptive statistics summarized variables, while bivariate and domain-specific multivariable logistic regression analyses were used to examine adjusted associations with occupational stress within health system, patient-related, and community-level domains. Results: Occupational stress prevalence was 64.5%. In domain-specific multivariable analyses, caregiver-related challenges were associated with higher odds of stress (aOR = 1.3, 95% CI: 1.02-1.57), while participation in continuous professional development-based programs (aOR = 0.3, 95% CI: 0.12-0.98) and lack of hospital accommodation (aOR = 0.2, 95% CI: 0.04-0.80) were associated with lower odds. Counterintuitive inverse associations were also observed for inadequate staffing and exposure to aggressive patient behavior, likely reflecting adaptation, selection effects, or residual confounding. Gender-related stressors were similarly inversely associated with stress (aOR = 0.7, 95% CI: 0.52-0.88). Conclusion: Nurses at MNRH experience high occupational stress driven by complex interactions of job demands, limited resources, and societal pressures. Effective stress mitigation requires integrated interventions addressing structural capacity, professional development, and social valuation of nursing. Future research should employ longitudinal and mixed-methods designs to disentangle the dynamics of occupational stress in high-demand, resource-limited environments

Bivariate analysis · Descriptive statistics · Health care · Logistic regression · Occupational stress · Odds · Referral · Staffing · Stressor · Workforce · Healthcare professionals’ stress and burnout · Nursing education and management · Workplace Health and Well-being

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