Evidence map›Paper›PMID 41006536›Full record

ArticleScientific reports2025

Exploring burnout, resilience and the coping strategies among critical healthcare professionals in post-COVID Taiwan.

Yueh-Lin Lee, Jhih-Wei Dai, Xiu-Wei Li, Yu-Chen Lin, Chien-Ho Wang

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
–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

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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

3 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

5 authors.

Yueh-Lin LeeDivision of Pulmonary and Critical Care Medicine, Chiayi Branch, Chang Gung Memorial Hospital, Chiayi, Taiwan.
Jhih-Wei DaiDepartment of Cardiology, Keelung Chang Gung Memorial Hospital, Keelung, Taiwan.
Xiu-Wei LiCollege of Medicine, Chang Gung University, Taoyuan, Taiwan.
Yu-Chen LinDepartment of Emergency Medicine, Jen-Ai Hospital, Taichung, Taiwan.
Chien-Ho WangCollege of Medicine, Chang Gung University, Taoyuan, Taiwan. Jen.y441@mail.jah.org.tw.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The mental well-being of critical healthcare professionals is a global public health issue, but its characteristics vary geographically. This study investigates the features of burnout, resilience, and coping strategies among critical healthcare professionals in Taiwan during the post-pandemic era. A survey incorporating the Maslach Burnout Inventory for Medical Professionals (MBI-MP) and the 14-item Resilience Scale (RS-14) was conducted between December 2023 and January 2024, targeting critical healthcare professionals at Chang Gung Memorial Hospital Foundation. Among 254 participants, the overall burnout rate was 35.4%, with high emotional exhaustion (EE, 70.9%), high depersonalization (DP, 56.3%), and low personal accomplishment (PA, 60.6%). The average resilience score was 70.7 ± 12.3. Younger, unmarried individuals and those with less work experience exhibited lower resilience and higher burnout scores. Resilience was significantly associated with reduced EE (p < 0.001), reduced DP (p < 0.001), and increased PA (p < 0.001). Family and friend companionship was the most common coping strategy. A high prevalence of burnout and low resilience was observed among critical healthcare professionals in Taiwan during the post-pandemic era. Identifying vulnerable populations and implementing locally tailored strategies are crucial to supporting the mental well-being of healthcare professionals.

Indexed as

Adaptation, PsychologicalBurnout, ProfessionalCOVID-19Health PersonnelResilience, PsychologicalAdultCoping SkillsFemaleHumansMaleMiddle AgedSARS-CoV-2Surveys and QuestionnairesTaiwanBurnoutCritical healthcare professionalsMental wellbeingPost-COVID-19 eraResilience

Identifiers

PMID41006536
PMCPMC12474876

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.