Evidence map›Paper›PMID 40050866›Full record

ArticleBMC nursing2025

The mediating role of emotional intelligence in the relationship between technostress and burnout prevention among critical care nurses a structural equation modelling approach.

Mostafa Shaban, Mohamed Ezzelregal Abdelgawad, Shimmaa Mohamed Elsayed, Haitham Mokhtar Mohamed Abdallah

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Article in BMC nursing, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

4 authors.

Mostafa ShabanGeriatric Nursing - Faculty of Nursing, Cairo University, Cairo, Egypt. mostafa.shaban2020@cu.edu.eg.ORCID http://orcid.org/0000-0001-7822-1653
Mohamed Ezzelregal AbdelgawadCritical care and emergency nursing, Faculty of Nursing, Alexandria University, Alexandria, Egypt.ORCID http://orcid.org/0000-0002-7299-4951
Shimmaa Mohamed ElsayedCritical care and emergency department, Faculty of nursing, Damanhur university, Damanhur, Egypt. Shimmaa.elsayed@nur.dmu.edu.eg.ORCID http://orcid.org/0000-0002-2065-7494
Haitham Mokhtar Mohamed AbdallahCritical care and emergency nursing, Faculty of Nursing, Alexandria University, Alexandria, Egypt.ORCID http://orcid.org/0000-0001-5044-3668

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCritical care nurses frequently experience high levels of technostress due to the increasing demands of healthcare technology, which contributes to burnout. Emotional intelligence has been shown to buffer stress in demanding environments, potentially mitigating burnout. However, its mediating role in the relationship between technostress and burnout among critical care nurses remains underexplored.

aimThis study aims to examine the mediating role of emotional intelligence in the relationship between technostress and burnout among critical care nurses.

methodsA cross-sectional study was conducted among 180 critical care nurses from two hospitals in Damnhour City, Egypt. Data were collected using the Technostress Questionnaire, Copenhagen Burnout Inventory (CBI), and Emotional Intelligence Scale. Structural Equation Modeling (SEM) was used to test the hypothesized relationships between technostress, emotional intelligence, and burnout, with bootstrapping employed to assess mediation.

resultsTechnostress was positively correlated with burnout (r = 0.56, p < 0.01), while emotional intelligence was negatively correlated with both technostress (r = -0.45, p < 0.01) and burnout (r = -0.49, p < 0.01). SEM analysis revealed that emotional intelligence significantly mediated the relationship between technostress and burnout (indirect effect = 0.23, p = 0.002), reducing burnout levels.

conclusionEmotional intelligence plays a crucial role in mitigating the effects of technostress on burnout among critical care nurses. Targeted interventions to enhance emotional intelligence may help reduce burnout in technology-driven healthcare environments.

Indexed as

BurnoutCritical care nursesEmotional intelligenceStructural equation modelingTechnostress

Identifiers

PMID40050866
PMCPMC11887162

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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.