Evidence map›Paper›PMID 37847013›Full record

ArticleFlorence Nightingale journal of nursing2023

Nurses' Burnout, Resilience, and Its Associated Factors in Sichuan, China, During the Peak of Coronavirus Disease 2019 Infection.

Fang Gao, Ping Lei Chui, Chong Chin Che, Xiao-Rong Mao

Open access · diamondAbstract read
In one paragraph

Article in Florence Nightingale journal of nursing, 2023. 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
1.6field-weighted citation impact, top 17% 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

4 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

4 authors at 1 institution in 1 country.

Fang GaoDepartment of Nursing Science, Universiti Malaya Faculty of Medicine, Kuala Lumpur, Malaysia; Department of Nursing, Sichuan Provincial People Hospital, Chengdu, China.
Ping Lei ChuiDepartment of Nursing Science, Universiti Malaya Faculty of Medicine, Kuala Lumpur, Malaysia.
Chong Chin CheDepartment of Nursing Science, Universiti Malaya Faculty of Medicine, Kuala Lumpur, Malaysia.
Xiao-Rong MaoDepartment of Nursing, Sichuan Provincial People Hospital, Chengdu, China.
University of Malaya · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo investigate the level of burnout and resilience, and the associated factors when the coronavirus disease 2019 infection hit a peak in the community in Sichuan, China.

methodThis was a descriptive cross-sectional design study. Data were collected from 25 to 31 December 2022, at six hospitals in Sichuan province. Using convenience sampling, a total of 717 participants were recruited, using the revised version of the Maslach Burnout InventoryGeneral Survey, and the Resilience Assessment Scale for healthcare workers.

resultsMore than half of nurses reported a moderate level of emotional exhaustion (66.50%, n = 484), cynicism (68.20%, n = 489), and personal accomplishment (68.76%, n = 493); nearly one-third and one-fourth of nurses experienced a high level of emotional exhaustion (27.48%, n = 197) and cynicism (20.78%, n = 149), respectively. In resilience, the highest scoring dimension was interpersonal connectedness, followed by decisional coping, flexible self-adaptation, and rational thinking. Satisfaction with work income, patient-nurse conflict, frequency of overtime work, age, and marital status were significant factors influencing burnout among nurses (p < .05).

conclusionThe findings of the study enlighten nursing administrators on the level of burnout and resilience and associated factors among nurses during the peak of coronavirus disease 2019 infection in China. This would be of immense help in planning a welfare program to support the nurses.

Identifiers

PMID37847013
PMCPMC10724793
OpenAlexW4387059666

What OpenQuestion holds

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LicenceCC BY-NC
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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.