Heterogeneity in Psychological Resilience and Mental Health among Newly Graduated Nursing Students: A Latent Profile and Generalized Additive Model Analysis

Xiao Xiao Mei; Xiao Na Wu; Hui Yuan Wang; Jie Yi Wu; Xin Qin Wang; Zeng Jie Ye

doi:10.2147/PRBM.S348661

Heterogeneity in Psychological Resilience and Mental Health among Newly Graduated Nursing Students: A Latent Profile and Generalized Additive Model Analysis

Psychol Res Behav Manag. 2022 Mar 10:15:597-606. doi: 10.2147/PRBM.S348661. eCollection 2022.

Authors

Xiao Xiao Mei¹, Xiao Na Wu¹, Hui Yuan Wang¹, Jie Yi Wu¹, Xin Qin Wang¹, Zeng Jie Ye¹

Affiliation

¹ Guangzhou University of Chinese Medicine, Guangzhou, Guangdong, 510006, People's Republic of China.

Abstract

Background: Psychological resilience is important to mental health and professional development in newly graduated nursing students (NGNSs). However, the association between psychological resilience and mental health in NGNSs is less explored.

Purpose: The current study was designed to determine mental health profiles measured by the Kessler 10 scale (K10) and evaluate the non-linear association between psychological resilience and mental health in NGNSs.

Methods: A total of 472 NGNSs from the Be Resilient to Nursing Career program were assessed using the K10 and ten-item Connor-Davidson Resilience Scale (CD-RISC 10). Latent profile analysis and generalized additive model analysis were performed.

Results: A four-class model based on the K10 was identified: lowest (28.0%), lower-middle (36.4%), upper-middle (26.1%), and highest (9.5%) subgroups. Academic degree and psychological resilience were significant indicators of mental health profiles. Psychological resilience was negatively and nonlinearly correlated with mental health when the CD-RISC 10 score was >17.

Conclusion: There exists heterogeneity in NGNSs' mental health. The negative and nonlinear association between psychological resilience and mental health can only be confirmed in NGNSs with moderate and high resilience levels.

Keywords: generalized additive model analysis; latent profile analysis; mental health; newly graduated nursing students; psychological resilience.

Grants and funding

This research was funded by grants from the National Natural Science Foundation of China (71904033), Humanity and Social Science Youth Foundation of Ministry of Education of China (19YJCZH227), Humanity and Social Science Foundation of Department of Education of Guangdong Province (2020WTSCX009), Humanity and Social Science Foundation of Guangzhou (2021GZGJ57), and Humanity and Social Science Foundation of Guangzhou University of Chinese Medicine (2020SKXK01, 2021SKYB07).