Enhancing depression risk assessment in critical care nurses: a call for quantitative modeling

Abstract

I am writing this letter in reference to a recent study published in Critical Care entitled “Network of job demands-resources and depressive symptoms in critical care nurses: a nationwide cross-sectional study” [1]. I would like to commend the authors for their interesting study of this important topic that explain the non-linear and multi-directional relationships between job demands-resources and depressive symptoms in critical care nurses. Despite the comprehensive and robust methodology employed by the researchers in this study, along with the intriguing results that hold significant clinical implications for nurses in critical care, it is important to note that the effectiveness and performance of the findings may be enhanced by their objectivity and higher efficiency as critical care nurses are at a heightened risk for experiencing depression, a condition that can have far-reaching consequences [2]. Not only does depression negatively impact their overall well-being, but it also significantly increases their intention to leave their positions [3]. This mental health challenge can further impair their job performance and diminish organizational productivity [4]. It is crucial to recognize that various work-related factors play a significant role in the development of depressive symptoms among these healthcare professionals. Addressing these factors is essential for the mental health of nurses, as well as for the effectiveness and efficiency of healthcare delivery in critical care settings.

The study failed to quantify the risk factors associated with the onset of depression among nurses working in critical care. Such quantification could have served as a predictive model for depression within this population to identify the variables influencing the onset of depression through multivariate analysis utilizing logistic regression. This approach would allow for the determination of the weight of each risk factor as an individual variable, ultimately leading to the development of a model capable of predicting the onset of depression in this vulnerable group. The attached article present a methodology aimed at developing the aforementioned model [5].

Although the researchers articulated that nursing managers play a crucial role in supporting critical care nurses by facilitating the identification of their sense of purpose in their work, implementing resilience-building programs, fostering meaningful relationships, and establishing a collaborative work environment that encourages mutual assistance among colleagues [1]. However, the factors discussed are predominantly qualitative and subjective, which limits their practical and objective application in clinical settings. Consequently, they provide minimal capacity for predicting the onset of depression and for implementing individualized interventions tailored to the diverse characteristics of nurses working in critical care. The proposed modeling approach allows researchers to identify the relative contributions of various risk factors associated with the onset of depression in this heterogeneous population as distinct variables. This information can subsequently be employed to develop a practical screening model for the onset and follow-up of depression. I would appreciate if authors could reflect on my comment.

No datasets were generated or analysed during the current study.

1. Li X, Tian Y, Yang J, Ning M, Chen Z, Yu Q, Liu Y, Huang C, Li Y. Network of job demands-resources and depressive symptoms in critical care nurses: a nationwide cross-sectional study. Crit Care. 2025;29(1):1–21.

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2. Zhang Y, Wu C, Ma J, Liu F, Shen C, Sun J, Ma Z, Hu W, Lang H. Relationship between depression and burnout among nurses in Intensive Care units at the late stage of COVID-19: a network analysis. BMC Nurs. 2024;23(1):224.

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3. Maddock A. The relationships between stress, burnout, mental health and well-being in social workers. British J Soc Work. 2023;54(2):668–86.

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5. Schandl A, Bottai M, Holdar U, Hellgren E, Sackey P. Early prediction of new-onset physical disability after intensive care unit stay: a preliminary instrument. Crit Care (Lond, Engl). 2014;18(4):455.

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Thanks to guidance and advice from the “Clinical Research Development Unit" of Baqiyatallah Hospital.

This research did not receive any specific grant from funding agencies in the public, commercial, or not‑for‑profit sectors.

Authors and Affiliations

1. Nursing Care Research Center, Clinical Sciences Institute, Nursing Faculty, Baqiyatallah University of Medical Sciences, Sheykh Bahayi Street, Vanak Square, P.O. Box 19575-174, Tehran, Iran

   Amir Vahedian-Azimi

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1. Amir Vahedian-AzimiView author publications

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 AVA contributed to manuscript revision, reviewed, and approved the final submitted version.

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Correspondence to Amir Vahedian-Azimi.

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Vahedian-Azimi, A. Enhancing depression risk assessment in critical care nurses: a call for quantitative modeling. Crit Care 29, 61 (2025). https://doi.org/10.1186/s13054-025-05303-z

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• Received: 25 January 2025

• Accepted: 29 January 2025

• Published: 05 February 2025

• DOI: https://doi.org/10.1186/s13054-025-05303-z

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