Evidence map›Paper›PMID 35184031›Full record

ArticleInternational emergency nursing2022

Emergency trauma care during the COVID-19 pandemic: A phenomenological study of nurses' experiences.

Mohammed Al-Sheikh Hassan, Kay De Vries, Jane Rutty

Open access · hybridAbstract read
In one paragraph

Article in International emergency nursing, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
1.3field-weighted citation impact, top 21% of its field
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

3 citing papers in PubMed, 5 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Mohammed Al-Sheikh HassanFaculty of Health and Life Sciences, De Montfort University, Gateway House, Leicester LE1 9BH, United Kingdom. Electronic address: P17236771@my365.dmu.ac.uk.
Kay De VriesFaculty of Health and Life Sciences, De Montfort University, Gateway House, Leicester LE1 9BH, United Kingdom.
Jane RuttyFaculty of Health and Life Sciences, De Montfort University, Gateway House, Leicester LE1 9BH, United Kingdom.
De Montfort University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThis study aimed to explore nurses' experiences in delivering emergency trauma care during the COVID-19 pandemic at a level I trauma centre in Saudi Arabia.

methodsA qualitative, descriptive phenomenological design was utilised, in which face-to-face, unstructured interviews were carried out with emergency and trauma nurses at a level I trauma centre in Saudi Arabia. The study included nine registered emergency and trauma nurses who were interviewed twice from February to April 2021. The collected data were analysed using Colaizzi's descriptive phenomenological method.

resultsThe analysis of the data revealed an overarching theme that was about the inevitable change on the ground due to the pandemic and two primary themes, each containing two subthemes: 1 dealing with an interrupted path of care; 1.1 experiencing additional complexity; 1.2 encountering extra demands; 2 optimising the path of care; 2.1 modifying the steps; and 2.2 transforming the system.

conclusionThe COVID-19 pandemic imposed change on how trauma patients would be handled and treated. Nurses took an active and critical role in creating another form of change, which helped optimise the path of trauma care and accommodate urgent treatment needs of the injured patients.

Indexed as

COVID-19Emergency Medical ServicesNursesHumansPandemicsQualitative ResearchSARS-CoV-2COVID-19EmergencyNursingPandemicPhenomenologySaudi ArabiaTrauma

Identifiers

PMID35184031
PMCPMC8801308
OpenAlexW4210617516

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.