Patterns and Predictors of Resilience in Frontline Nurses Before and After Public Health Emergencies: A Latent Transition Analysis.

Abstract

To explore the stability of resilience among frontline nurses and to analyse the predictive role of internal and external factors on the patterns of resilience transformation in China during public health emergencies. The study used a longitudinal design and surveyed 258 frontline nurses at three different time points: February-March 2020 (T1), May-June 2020 (T2) and May-June 2022 (T3). The survey included the 10-item Connor-Davidson resilience scale, the Emotion Regulation Questionnaire and the Simple Coping Style Questionnaire. Latent profile analysis and latent transition analysis were used to examine the potential classes and changes. Multivariate logistic regression analysis was applied to evaluate the predictors of resilience transitions. The resilience of frontline nurses was divided into three categories: fragile group, general group and high resilience group. From T1 to T2, the general group exhibited the least stability, with a probability of maintaining its original latent state at 72.9%. Marriage and positive coping styles significantly impacted the transition between resilience categories. From T2 to T3, the fragile group showed the lowest stability, with a 74.9% likelihood of retaining its initial latent state. In this context, supportive hospital management (including psychological counselling, restful environments, and both spiritual and material incentives) and individuals' emotional regulation and sleep quality significantly affected the transition between resilience categories. These findings emphasise the necessity for early intervention. For frontline nurses, conducting initial assessments of resilience coupled with sustained hospital support is crucial for maintaining mental health and improving the quality of nursing care in public health emergencies. This study offers a fresh perspective for understanding the resilience of frontline nurses during public health emergencies. At the same time, it reveals the factors that promote or hinder the change in resilience among frontline nurses at both individual and organisational levels. This provides a theoretical basis for future resilience interventions and helps us formulate effective crisis management strategies to respond to future public health emergencies. For frontline nurses with diverse resilience characteristics and relevant transformation factors, a personalised multi-mode resilience improvement plan can be developed to mitigate public health emergencies' potential adverse psychological impact on frontline nurses, especially those in the fragile group. No patient or public contribution.