Evidence map›Paper›PMID 39735859›Full record

ArticlePsychology research and behavior management2024

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

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

Abstract read
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Article in Psychology research and behavior management, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Linlin YeMental Health Education Center, Guangzhou Railway Polytechnic, Guangzhou, 511370, People's Republic of China.
Shujuan ChenDepartment of Psychology, School of Education, Ningxia University, Yinchuan, 750021, People's Republic of China.
Qing-Wei ChenLab 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.ORCID 0000-0002-5458-0210
Xue LuoDepartment of Psychiatry, Sleep Medical Center, Nanfang Hospital, Southern Medical University, Guangzhou, 510515, People's Republic of China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

anxietydepressionfamily functioninghigher vocational college studentsnetwork analysis

Identifiers

PMID39735859
PMCPMC11682667

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.