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The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis
BACKGROUND: Anxiety and depression are among the greatest contributors to the global burden of diseases. The close associations of personality traits with anxiety and depression have been widely described. However, the common practice of sum scores in previous studies limits the understanding of the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434527/ https://www.ncbi.nlm.nih.gov/pubmed/37601217 http://dx.doi.org/10.3389/fpubh.2023.1204285 |
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author | Yang, Tianqi Guo, Zhihua Zhu, Xia Liu, Xufeng Guo, Yaning |
author_facet | Yang, Tianqi Guo, Zhihua Zhu, Xia Liu, Xufeng Guo, Yaning |
author_sort | Yang, Tianqi |
collection | PubMed |
description | BACKGROUND: Anxiety and depression are among the greatest contributors to the global burden of diseases. The close associations of personality traits with anxiety and depression have been widely described. However, the common practice of sum scores in previous studies limits the understanding of the fine-grained connections between different personality traits and anxiety and depression symptoms and cannot explore and compare the risk or protective effects of personality traits on anxiety and depression symptoms. OBJECTIVE: We aimed to determine the fine-grained connections between different personality traits and anxiety and depression symptoms and identify the detrimental or protective effects of different personality traits on anxiety and depression symptoms. METHODS: A total of 536 college students from China were recruited online, and the average age was 19.98 ± 1.11. The Chinese version of the Ten-Item Personality Inventory, Generalized Anxiety Disorder-7, and Patient Health Questionnaire-9 was used to investigate the personality traits and symptoms of anxiety and depression of participants after they understood the purpose and filling method of the survey and signed the informed consent. The demographic characteristics were summarized, and the scale scores were calculated. The network model of personality traits and symptoms of anxiety and depression was constructed, and bridge expected influence (BEI) was measured to evaluate the effect of personality traits on anxiety and depression. The edge accuracy and BEI stability were estimated, and the BEI difference and the edge weight difference were tested. RESULTS: In the network, 29 edges (indicating partial correlations between variables) bridged the personality community and the anxiety and depression community, among which the strongest correlations were extraversion-fatigue, agreeableness-suicidal ideation, conscientiousness-uncontrollable worry, neuroticism-excessive worry, neuroticism-irritability, and openness-feelings of worthlessness. Neuroticism had the highest positive BEI value (0.32), agreeableness had the highest negative BEI value (−0.27), and the BEI values of neuroticism and agreeableness were significantly different from those of most other nodes (p < 0.05). CONCLUSION: There are intricate correlations between personality traits and the symptoms of anxiety and depression in college students. Neuroticism was identified as the most crucial risk trait for depression and anxiety symptoms, while agreeableness was the most central protective trait. |
format | Online Article Text |
id | pubmed-10434527 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-104345272023-08-18 The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis Yang, Tianqi Guo, Zhihua Zhu, Xia Liu, Xufeng Guo, Yaning Front Public Health Public Health BACKGROUND: Anxiety and depression are among the greatest contributors to the global burden of diseases. The close associations of personality traits with anxiety and depression have been widely described. However, the common practice of sum scores in previous studies limits the understanding of the fine-grained connections between different personality traits and anxiety and depression symptoms and cannot explore and compare the risk or protective effects of personality traits on anxiety and depression symptoms. OBJECTIVE: We aimed to determine the fine-grained connections between different personality traits and anxiety and depression symptoms and identify the detrimental or protective effects of different personality traits on anxiety and depression symptoms. METHODS: A total of 536 college students from China were recruited online, and the average age was 19.98 ± 1.11. The Chinese version of the Ten-Item Personality Inventory, Generalized Anxiety Disorder-7, and Patient Health Questionnaire-9 was used to investigate the personality traits and symptoms of anxiety and depression of participants after they understood the purpose and filling method of the survey and signed the informed consent. The demographic characteristics were summarized, and the scale scores were calculated. The network model of personality traits and symptoms of anxiety and depression was constructed, and bridge expected influence (BEI) was measured to evaluate the effect of personality traits on anxiety and depression. The edge accuracy and BEI stability were estimated, and the BEI difference and the edge weight difference were tested. RESULTS: In the network, 29 edges (indicating partial correlations between variables) bridged the personality community and the anxiety and depression community, among which the strongest correlations were extraversion-fatigue, agreeableness-suicidal ideation, conscientiousness-uncontrollable worry, neuroticism-excessive worry, neuroticism-irritability, and openness-feelings of worthlessness. Neuroticism had the highest positive BEI value (0.32), agreeableness had the highest negative BEI value (−0.27), and the BEI values of neuroticism and agreeableness were significantly different from those of most other nodes (p < 0.05). CONCLUSION: There are intricate correlations between personality traits and the symptoms of anxiety and depression in college students. Neuroticism was identified as the most crucial risk trait for depression and anxiety symptoms, while agreeableness was the most central protective trait. Frontiers Media S.A. 2023-08-03 /pmc/articles/PMC10434527/ /pubmed/37601217 http://dx.doi.org/10.3389/fpubh.2023.1204285 Text en Copyright © 2023 Yang, Guo, Zhu, Liu and Guo. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Public Health Yang, Tianqi Guo, Zhihua Zhu, Xia Liu, Xufeng Guo, Yaning The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis |
title | The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis |
title_full | The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis |
title_fullStr | The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis |
title_full_unstemmed | The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis |
title_short | The interplay of personality traits, anxiety, and depression in Chinese college students: a network analysis |
title_sort | interplay of personality traits, anxiety, and depression in chinese college students: a network analysis |
topic | Public Health |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10434527/ https://www.ncbi.nlm.nih.gov/pubmed/37601217 http://dx.doi.org/10.3389/fpubh.2023.1204285 |
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