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DOI 10.2147/prbm.s490712

Медицинская библиотека · Psychology research and behavior management · 2024

Family Functioning, Anxiety and Depression in Chinese Higher Vocational School Students: A Network Analysis.

Ye Linlin, Chen Shujuan, Chen Qing-Wei, Luo Xue

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Аннотация

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.

Для цитирования: Ye Linlin, Chen Shujuan, Chen Qing-Wei, Luo Xue. Family Functioning, Anxiety and Depression in Chinese Higher Vocational School Students: A Network Analysis.. Psychology research and behavior management. 2024. DOI: 10.2147/prbm.s490712.
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