Linlin Ye,1 Shujuan Chen,2 Qing-Wei Chen,3– 5 Xue Luo6 

1Mental Health Education Center, Guangzhou Railway Polytechnic, Guangzhou, 511370, People’s Republic of China; 2Department of Psychology, School of Education, Ningxia University, Yinchuan, 750021, People’s Republic of China; 3Lab of Light and Physio-Psychological Health, National Center for International Research on Green Optoelectronics, South China Normal University, Guangzhou, 510006, People’s Republic of China; 4School of Psychology, South China Normal University, Guangzhou, 510631, People’s Republic of China; 5Guangdong Provincial Key Laboratory of Optical Information Materials and Technology & Institute of Electronic Paper Displays, South China Academy of Advanced Optoelectronics, South China Normal University, Guangzhou, 510006, People’s Republic of China; 6Department of Psychiatry, Sleep Medical Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, People’s Republic of China

Correspondence: Qing-Wei Chen, National Center for International Research on Green Optoelectronics, South China Normal University, No. 55 West Zhongshan Road, Guangzhou, Guangdong, People’s Republic of China, Email qingwei.chen@m.scnu.edu.cn Xue Luo, Department of Psychiatry, Nanfang Hospital Southern Medical University, No. 1838 North Guangzhou Avenue, Guangzhou, Guangdong, People’s Republic of China, Email nfyy8866@i.smu.edu.cn

Purpose: Network analysis is a statistical method that explores the complex interrelationships among variables by representing them as nodes and edges in a network structure. This study aimed to examine the interconnections between family functioning, anxiety, and depression among vocational school students through network analysis approach.
Participants and Methods: A sample of 2728 higher vocational school students participated in a survey utilizing the Family APGAR Index Questionnaire (APGAR), Generalized Anxiety Disorder Scale (GAD-7), and Patient Health Questionnaire (PHQ-9). Meanwhile, a network analysis was conducted to investigate the interrelationships between family functioning, anxiety, and depression symptoms among the higher vocational school students.
Results: The network analysis revealed that node APGAR2 (“Partnership”) exhibited the highest strength, followed by node GAD5 (“Restlessness”); node GAD7 (“Negative future anticipation”), PHQ9 (“Suicidal ideation”), and PHQ6 (“Guilty”) were bridge nodes linking family functioning, anxiety and depressive symptoms in the sample. The results of the Network comparisons test between male and female indicated that the edge weights and global strength did not exhibit a statistically significant difference.
Conclusion: These results emphasized that certain anxiety symptoms and family functioning nodes are more central than others, and thus play a more critical role in the family functioning-anxiety-depression network, which highlight potential targeting symptoms to be considered in future interventions.

Keywords: network analysis, family functioning, anxiety, depression, higher vocational college students