Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2025 Jul 1;24(1):735.
doi: 10.1186/s12912-025-03409-x.

Emotional symptom networks in ICU nurses: a comparative network analysis of tertiary-A and tertiary-B hospitals in China

Yanchi Wang #  1   2   3 , Sha Sha #  1 , Xiangjun Lu  4 , Jian Gu  5
Affiliations

Emotional symptom networks in ICU nurses: a comparative network analysis of tertiary-A and tertiary-B hospitals in China

Yanchi Wang et al. BMC Nurs. .

Abstract

Background: Intensive Care Unit (ICU) nurses experience significant psychological distress due to the high-stakes and high-intensity nature of their work environments. This study aims to explore the differences in emotional symptom networks between tertiary-A and tertiary-B hospital ICU nurses using network analysis to identify central symptoms and inform targeted interventions.

Method: A total of 498 ICU nurses were divided into two groups based on hospital level: the tertiary-A hospital group (n = 174) and the tertiary-B hospital group (n = 324). Mood states were measured using the Profile of Mood States-Short Form (POMS-SF). Network analysis was employed to estimate and compare the symptom networks between the two groups, identify central symptoms that link distinct symptom clusters, and conduct network comparison tests to assess differences in overall and local network structures.

Results: In the tertiary-A hospital group, the most prominent symptoms were POMS4 (Depression-Dejection), POMS1 (Tension-Anxiety), and POMS2 (Anger-Hostility), with the expected influence value indicating that POMS4 (Depression-Dejection) was the most significant. In the tertiary-B hospital group, the most significant central symptoms were POMS1 (Tension-Anxiety), POMS2 (Anger-Hostility), and POMS4 (Depression-Dejection), where POMS1 (Tension-Anxiety) had the highest expected influence value. The network comparison test revealed significant differences in the network invariance test (M = 0.345, P = 0.003) and the Global expected influence invariance test (S = 0.173, P = 0.020).

Conclusion: This study identifies distinct emotional symptom networks in ICU nurses across tertiary-A and tertiary-B hospitals, with depression-dejection (POMS4) central in tertiary-A hospitals and tension-anxiety (POMS1) more prominent in tertiary-B hospitals. These findings highlight the need for tailored interventions and hospital-tier-specific mental health support to address the unique emotional challenges faced by ICU nurses, ultimately improving nurse well-being and patient care quality.

Clinical trial registration: Not applicable.

Keywords: Hospital levels; ICU nurses; Mood states; Network analysis.

PubMed Disclaimer

Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study was reviewed and approved by the Ethics Committee of the Sixth People’s Hospital of Nantong (Approval No: NTLYLL2025002). All procedures complied with the ethical standards of the Declaration of Helsinki. Written informed consent was obtained from all participants, including explicit agreement for the publication of anonymized data. Participation was voluntary with guaranteed confidentiality and the right to withdraw without penalty. Consent for publication: All participants consented to publication of anonymized data through signed informed consent forms. Competing interests: The authors declare no competing interests.

Figures

Fig. 1
Fig. 1
A: Network structure of emotional states in the tertiary-A hospital group. B: Network structure of emotional states in the tertiary-B hospital group
Fig. 2
Fig. 2
Comparison of centrality measures between the tertiary-A and tertiary-B hospital groups
Fig. 3
Fig. 3
A: Stability of Expected Influence (EI) indices in the tertiary-A hospital group using case-dropping bootstrap. B: Stability of Expected Influence (EI) indices in the tertiary-B hospital group using case-dropping bootstrap
See this image and copyright information in PMC

References

    1. Quesada-Puga C, Izquierdo-Espin FJ, Membrive-Jimenez MJ, Aguayo-Estremera R, Canadas-De La Fuente GA, Romero-Bejar JL, Gomez-Urquiza JL. Job satisfaction and burnout syndrome among intensive-care unit nurses: A systematic review and meta-analysis. Intensive Crit Care Nurs. 2024;82:103660. - DOI - PubMed
    1. Afenigus AD, Sinshaw MA. Ethical dilemmas and decision-making in emergency and critical care nursing in Western Amhara region, Northwest ethiopia: a multi-method qualitative study. BMC Nurs. 2025;24(1):295. - DOI - PMC - PubMed
    1. El Khamali R, Mouaci A, Valera S, Cano-Chervel M, Pinglis C, Sanz C, Allal A, Attard V, Malardier J, Delfino M, et al. Effects of a multimodal program including simulation on job strain among nurses working in intensive care units: A randomized clinical trial. JAMA. 2018;320(19):1988–97. - DOI - PMC - PubMed
    1. Malewska A, Serafin L, Czarkowska-Paczek B. The relationship between sleep quality and resilience among intensive care unit nurses: A cross-sectional study. Nurs Crit Care. 2025;30(2):e70010. - DOI - PubMed
    1. Haniffa R, Pubudu De Silva A, de Azevedo L, Baranage D, Rashan A, Baelani I, Schultz MJ, Dondorp AM, Dunser MW. Improving ICU services in resource-limited settings: perceptions of ICU workers from low-middle-, and high-income countries. J Crit Care. 2018;44:352–6. - DOI - PubMed

LinkOut - more resources