Evidence map›Paper›PMID 37789285›Full record

ArticleBMC nursing2023

"We felt so proud by the president calling us my heroes." An exploration of the nurse's experiences in the management of COVID-19 patients in Uganda.

Faith Nawagi, Martin Lubega, Aidah Ajambo, John Mukisa, Rose Nabirye

Abstract read
In one paragraph

Article in BMC nursing, 2023. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Faith NawagiCollege of Health Sciences, Makerere University, Kampala, Uganda. fnawagi@gmail.com.
Martin LubegaCollege of Health Sciences, Department of Nursing, Makerere University, Kampala, Uganda.
Aidah AjamboUganda Prisons Service, Kampala, Uganda.
John MukisaSchool of Biomedical Sciences, Makerere University College of Health Sciences (MaKCHS), Kampala, Uganda.
Rose NabiryeFaculty of Health Sciences, Department of Nursing, Bustiema University, Kampala, Uganda.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionAdequate and intensive nursing care was a key characteristic of recovery of the COVID-19 patients globally and in Uganda. However, there is limited literature on the experiences of nurses who participated in the care of COVID-19 patients in Uganda, East Africa, and Africa at large, yet imperative in designing approaches to increase the efficiency of the health systems' response to future pandemics. To address this gap, this study aimed to explore the experiences of the nurses who managed COVID-19 patients at Mulago National Referral Hospital in Uganda.

methodsThis was an exploratory qualitative study that used purposive sampling to identify 21 nurses who treated COVID-19 patients at Mulago National Referral Hospital in Uganda. Focus Group Discussions were used to collect data. Thematic Analysis was used to analyze the data. Common codes were identified and grouped to create subthemes and major themes.

resultsSix themes were identified: 1) Motivation to work on COVID-19 patients, 2 ) Roles performed by nurses, 3) High workload and professional role strain, 4) Challenges with maintaining personal health and relationships, 5) Institutional and government support, 6) Acquired professional knowledge and skills to manage critical patients and epidemics. Most of the nurses faced work burnout, social isolation, stress, and psychological trauma. However, interprofessional collaboration, financial incentives, government recognition, and provision of personal protective equipment, were key motivators for the nurses. The majority reported to have gained new knowledge and skills in the management of pandemics and highly infectious diseases.

conclusionThe nurses experienced negative scenarios like work burnout due to high workload, social isolation, and psychological stress. Therefore, there is a need for health systems to develop approaches and policies that support nurses' well-being. Nevertheless, key attributes like resilience, adaptability, and diligence to serve enabled them to persevere despite the hardships faced.

Indexed as

AfricaCOVID-19ExperiencesNursesUganda

Identifiers

PMID37789285
PMCPMC10548748

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LicenceCC BY
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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.