Abstract

Background

Psychological well-being plays a vital role in nursing students’ mental health and affects their decisions to stay in the nursing profession, particularly during the COVID-19 outbreak. Close relationships are undeniably linked to psychological well-being, but it is unknown how the specific pathways through which close relationships are related to each other and which are most strongly linked to nursing students’ psychological well-being.

Aims

To explore the network structure, central and bridge factors among well-being characteristics, and predictors based on a model of thriving through relationships.

Methods

A cross-sectional research design was used with a sample of undergraduate nursing students (531 participants from the Southwest part of China). We used a network model to analyze the network structure of perceived social support, mindfulness, self-integrity, self-compassion, professional self-concept, savoring, intentional self-regulation, non-relational self-expansion, relational self-expansion, attachment insecurity, and psychological well-being.

Results

A highly interconnected network of psychological well-being featured predictors and traits were formed. Node 8 (self-kindness), node 9 (self-judgment), and node 23 (non-relational self-expansion) were the predictors with the highest centrality in the network. Perceived social support and professional self-concept were most central in linking predictors to psychological well-being traits. Attachment insecurity was a non-supportive factor for predicting psychological well-being among female nursing students.

Conclusions

Interventions based on these supportive/non-supportive predictors, which operate on different psychological levels, hold promise to achieve positive effects on psychological well-being among nursing students.

Details

Title
Predicting nursing students’ psychological well-being: network analysis based on a model of thriving through relationships
Author
Zhou, Lu  VIAFID ORCID Logo  ; Sukpasjaroen, Khunanan; Wu, YuMing; Wang, Lei; Chankoson, Thitinan; Cai, EnLi
Pages
1-11
Section
Research
Publication year
2022
Publication date
2022
Publisher
BioMed Central
e-ISSN
14726920
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2678206508
Copyright
© 2022. This work is licensed under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.