Evidence map›Paper›PMID 38585337›Full record

ArticleSAGE open nursing

Examining the Impact of Burnout on Hospital Nurses Engaged in Shift Work: Insights From a Nationwide Cross-Sectional Study in Malaysia.

Kun Yun Lee, Nursyahda Zakaria, Norhaniza Zakaria

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Article in SAGE open nursing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

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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.

Kun Yun LeeInstitute for Health Management, Centre of Leadership and Professional Development, Shah Alam, Malaysia.ORCID https://orcid.org/0000-0002-8606-3541
Nursyahda ZakariaInstitute for Health Management, Shah Alam, Malaysia.
Norhaniza ZakariaNational Institutes of Health, Ministry of Health Malaysia, Shah Alam, Malaysia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Shift workers follow nonstandard schedules that encompass overnight duty, rotational timetables, or permanent night work which can lead to misaligned core circadian physiology. Shift work has been associated with sleep deprivation, burnout, and metabolic syndrome among healthcare workers. Objective: We aimed to examine if shift nurses working in Malaysian public hospitals are more predisposed to burnout and to determine the predictors of burnout in this profession. Method: This national-level cross-sectional study was conducted among nurses in public hospitals in Malaysia between July and November 2019 using self-administered questionnaires. Maslach Burnout Inventory-Human Service Survey was used to determine burnout. Multistage stratified sampling was used to recruit nurses from 32 hospitals. A complex sampling analysis was performed. Results: Among the 1,491 hospital nurses, more than half (70.8%) of them followed shift work schedules. Shift nurses were mostly below 40 years old (80.9%), diploma holders (87.2%), and of lower professional grades (64.2%). The prevalence of overall burnout, as well as the domains of emotional exhaustion and depersonalization, was higher among shift nurses (27.1%) as compared to their counterparts (22.4%). Nurses who performed more than six night shifts per month were 2.6 times more predisposed to burnout. Conclusion: Shift work is integral to ensure round-the-clock nursing care for patients. However, nurses are increasingly faced with more shift duties due to heavy patient loads and staff shortages. Modified work schedules must be implemented to provide sufficient rest time for shift nurses to mitigate burnout. Additionally, proper human resource projection and distribution are imperative to prevent worsening burnout.

Indexed as

burnoutdepersonalizationemotional exhaustionhospitalnursing staff

Identifiers

PMID38585337
PMCPMC10998483

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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.