Evidence map›Paper›PMID 35729575›Full record

ArticleBMC nursing2022

"We are never taught anything about the elderly." Establishing the gap in elderly health care competencies in nursing education in Uganda.

Faith Nawagi, John Mukisa, Josephine Nambi Najjuma, Rose C Nabirye

Abstract read
In one paragraph

Article in BMC nursing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Article
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

4 authors.

Faith NawagiMakerere University College of Health Sciences (MaKCHS), School of Medicine, Kampala, Uganda. fnawagi@gmail.com.
John MukisaMakerere University College of Health Sciences (MaKCHS), School of Biomedical Sciences, Kampala, Uganda.
Josephine Nambi NajjumaMbarara University of Science and Technology (MUST), Faculty of Medicine, Kampala, Uganda.
Rose C NabiryeBusitema University, Faculty of Health Sciences, Kampala, Uganda.

Funding

Government of Uganda - Uganda Nurses and Midwives council 2021 UNMC Research Grants for Nurses and Midwives 1
6 · The paper itself

Abstract

backgroundNurses contribute the largest portion of Uganda's health workforce providing care to individuals of all ages and communities. However, despite the growing number of the elderly population in Uganda with improved life expectancy, there is hardly any study that has looked at the elderly health care competencies in the nursing training programs at various levels. This paper provides an overview of the gaps in elderly health care competencies in nursing education in Uganda.

methodsWe conducted a descriptive qualitative cross-sectional study that involved document review, Key Informant Interviews (KIIs) with nursing leaders, and Focus Group Discussions ( FGDs) with faculty at all levels of nursing training and nurses in practice. Data was analyzed using latent and manifest content analysis with Open Code software 4.03. Common categories were identified and incorporated into a matrix to create themes.

resultsAlmost all the curricula and minimum standards for training nurses at certificate, diploma, and degree levels lack a module and nursing competencies on elderly nursing care. This is aggravated by a lack of faculty trained in elderly health care skills, and a lack of specialized wards for nursing elderly care clinical training among others.

conclusionsThere is hardly any elderly health care training module and elderly nursing competencies at all levels of nursing training in Uganda.

Indexed as

CompetenciesElderly health careNursingTrainingUganda

Identifiers

PMID35729575
PMCPMC9210050

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.