Evidence map›Paper›PMID 42094893›Full record

ArticleFrontiers in public health2026

The prevalence and predictors of burnout among employees of the national emergency medical services system: evidence from Poland.

Mateusz Szczupak, Jacek Kobak, Anna Ingielewicz, Paulina Domańska-Gruszczyńska, Sabina Krupa-Nurcek

Abstract read
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Article in Frontiers in public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Mateusz SzczupakDepartment of Anaesthesiology and Intensive Therapy of the Nicolaus Copernicus Hospital in Gdańsk, Gdańsk, Poland.
Jacek KobakDepartment of Otolaryngology, Faculty of Medicine, Medical University of Gdańsk, Gdańsk, Poland.
Anna IngielewiczDepartment of Emergency Medicine, Faculty of Health Sciences, Medical University of Gdańsk, Gdansk, Poland.
Paulina Domańska-GruszczyńskaDepartment of Emergency Medicine, St. Adalbert's Hospital, Copernicus Healthcare Entity, Gdańsk, Poland.
Sabina Krupa-NurcekDepartment of Surgery, Faculty of Medicine, Collegium Medicum, University of Rzeszów, Rzeszów, Poland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Burnout, classified in ICD-11 as a phenomenon associated with chronic workplace stress, represents a major challenge in emergency medicine. Employees of the State Emergency Medical System (SEMS) in Poland are exposed to high job demands, time pressure, traumatic events, and shift work, which may increase the risk of burnout. The aim of this study was to assess burnout severity and identify its determinants among SEMS employees using the Oldenburg Burnout Inventory (OLBI), within the framework of the Job Demands-Resources (JD-R) model and in accordance with STROBE recommendations. Methods: A cross-sectional study was conducted using an anonymous online survey between October 2025 and January 2026. Of 302 individuals who initiated participation, 261 completed the questionnaire (86.4% completion rate). Burnout was assessed in two dimensions: exhaustion and disengagement. Confirmatory factor analysis indicated limited separability between these dimensions. Due to non-normal data distribution, nonparametric tests (Mann-Whitney U and Kruskal-Wallis) were applied, with effect sizes reported. Multivariate regression analysis was performed to identify independent predictors of exhaustion, and k-means clustering was used to identify burnout profiles. Results: The study included 261 respondents (68.2% men, 31.8% women). Mean OLBI scores indicated a moderate level of burnout (disengagement: 2.508 ± 0.425; exhaustion: 2.657 ± 0.453), with exhaustion predominating. Salary satisfaction was significantly associated with both burnout dimensions ( Conclusion: Moderate burnout, dominated by exhaustion, was observed among SEMS employees in Poland. Organizational factors, particularly salary satisfaction and workplace setting, were key correlates. These findings highlight the need for system-level interventions to improve working conditions and workforce sustainability, while acknowledging the cross-sectional design and psychometric limitations.

Indexed as

Burnout, ProfessionalEmergency Medical ServicesAdultCross-Sectional StudiesEmotional ExhaustionFemaleHumansMaleMiddle AgedPolandPrevalenceRisk FactorsSurveys and QuestionnairesWorking Conditionsburnoutemergency departmentemergency medical serviceshealthcare workforceoccupational stressOldenburg Burnout Inventory

Identifiers

PMID42094893
PMCPMC13139351

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.