Evidence map›Paper›PMID 41063028›Full record

ArticleBMC public health2025

Prevalence and predictors of stress, anxiety, and depression among healthcare workers during the COVID-19 pandemic at a mental referral hospital in Kampala, Uganda.

James Otai, Newton Ekakoro, Henry Masaba, Ruth Nvumetta

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Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

James OtaiDepartment of Biological Sciences, Faculty of Science, Kyambogo University, Kampala, Uganda.
Newton EkakoroDepartment of Biological Sciences, Faculty of Science, Kyambogo University, Kampala, Uganda. ekakoronewton@gmail.com.
Henry MasabaOutpatients Department, Butabika National Mental Referral Hospital, Kampala, Uganda.
Ruth NvumettaOutpatients Department, Butabika National Mental Referral Hospital, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHealthcare workers faced immense psychological strain during the Corona Virus Disease 2019 (COVID - 19) pandemic due to increased workloads, infection risk, and limited protective equipment. This study assessed the prevalence of stress, anxiety, and depression among them and identified factors contributing to these mental health challenges during the outbreak.

methodsA cross-sectional study was done at Butabika National Mental Referral Hospital between February and March of 2023. We gave self-administered, paper-based surveys to all willing Healthcare workers (HCWs) working day shifts during this period. Sections on socio-demographics characteristics, perceived stress (PSS-10), anxiety (GAD-7), and depression (PHQ-9) were all included in the questionnaire. The SPSS version 26.0 program was used to analyse the data. To determine the variables that predict psychological distress, we employed Modified Poisson regression. When the p-value was less than 0.05, statistical significance was declared.

resultsAmong the 209 enrolled participants, 198 (94.7%) eligible subjects were included in the analysis. Majority of the participants (58.6%) were female, (73.7%) were married, (49.5%) were nurses and 58.6% had more working hours. The prevalence of symptoms of stress, anxiety and depression in healthcare workers during the COVID-19 pandemic was 91.9%, 27.3% and 57.6%, respectively. In relation to perceived stress, being female (aRR = 1.219; 95% CI: 1.010-2.922), being younger in age (aRR = 1.672; 95% CI: 1.050-5.733) and having worked for 11-15 years (aRR = 1.274; 95% CI: 1.020-2.503) were significantly associated with higher risk of perceived stress. Participants with a bachelor's degree had higher risk of generalized anxiety disorder symptoms (aRR = 2.577; 95% CI: 1.123-4.980), whereas being a nurse (aRR = 0.082; 95% CI: 0.040-0.900) showed lower risk of anxiety. Being married (aRR = 1.322; 95% CI: 1.042-2.260) and being younger in age (aRR = 1.037; 95% CI: 1.005-2.834) were significantly associated with higher risk of depressive symptoms, whereas being a technician (aRR = 0.683; 95% CI: 0.480-0.972) and having no change in work volume (aRR = 0.711; 95% CI: 0.532-0.987) were associated to lower risk of depression symptoms.

conclusionPsychological distress was high among mental health workers during COVID-19. Supportive measures such as adequate PPE, manageable workloads, mental health check-ins, and challenging societal stigma are needed to improve well-being, within study limitations.

Indexed as

AnxietyCOVID-19DepressionHealth PersonnelOccupational StressStress, PsychologicalAdultCross-Sectional StudiesFemaleHospitals, PsychiatricHumansMaleMiddle AgedPandemicsPrevalenceRisk FactorsAnxietyCOVID – 19DepressionHealthcare workersPandemicStressUganda

Identifiers

PMID41063028
PMCPMC12506417

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LicenceCC BY-NC-ND
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.