Cargando…
Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas
Contemporarily, depression has become a common psychiatric disorder that influences people’s life quality and mental state. This study presents a systematic review analysis of depression based on a hierarchical structure approach. This research provides a rich theoretical foundation for understandin...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160970/ https://www.ncbi.nlm.nih.gov/pubmed/35664156 http://dx.doi.org/10.3389/fpsyg.2022.920920 |
_version_ | 1784719384834473984 |
---|---|
author | Yu, Qingyue Wang, Zihao Li, Zeyu Liu, Xuejun Oteng Agyeman, Fredrick Wang, Xinxing |
author_facet | Yu, Qingyue Wang, Zihao Li, Zeyu Liu, Xuejun Oteng Agyeman, Fredrick Wang, Xinxing |
author_sort | Yu, Qingyue |
collection | PubMed |
description | Contemporarily, depression has become a common psychiatric disorder that influences people’s life quality and mental state. This study presents a systematic review analysis of depression based on a hierarchical structure approach. This research provides a rich theoretical foundation for understanding the hot spots, evolutionary trends, and future related research directions and offers further guidance for practice. This investigation contributes to knowledge by combining robust methodological software for analysis, including Citespace, Ucinet, and Pajek. This paper employed the bibliometric methodology to analyze 5,000 research articles concerning depression. This current research also employed the BibExcel software to bibliometrically measure the keywords of the selected articles and further conducted a co-word matrix analysis. Additionally, Pajek software was used to conduct a co-word network analysis to obtain a co-word network diagram of depression. Further, Ucinet software was utilized to calculate K-core values, degree centrality, and mediated centrality to better present the research hotspots, sort out the current status and reveal the research characteristics in the field of depression with valuable information and support for subsequent research. This research indicates that major depressive disorder, anxiety, and mental health had a high occurrence among adolescents and the aged. This present study provides policy recommendations for the government, non-governmental organizations and other philanthropic agencies to help furnish resources for treating and controlling depression orders. |
format | Online Article Text |
id | pubmed-9160970 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91609702022-06-03 Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas Yu, Qingyue Wang, Zihao Li, Zeyu Liu, Xuejun Oteng Agyeman, Fredrick Wang, Xinxing Front Psychol Psychology Contemporarily, depression has become a common psychiatric disorder that influences people’s life quality and mental state. This study presents a systematic review analysis of depression based on a hierarchical structure approach. This research provides a rich theoretical foundation for understanding the hot spots, evolutionary trends, and future related research directions and offers further guidance for practice. This investigation contributes to knowledge by combining robust methodological software for analysis, including Citespace, Ucinet, and Pajek. This paper employed the bibliometric methodology to analyze 5,000 research articles concerning depression. This current research also employed the BibExcel software to bibliometrically measure the keywords of the selected articles and further conducted a co-word matrix analysis. Additionally, Pajek software was used to conduct a co-word network analysis to obtain a co-word network diagram of depression. Further, Ucinet software was utilized to calculate K-core values, degree centrality, and mediated centrality to better present the research hotspots, sort out the current status and reveal the research characteristics in the field of depression with valuable information and support for subsequent research. This research indicates that major depressive disorder, anxiety, and mental health had a high occurrence among adolescents and the aged. This present study provides policy recommendations for the government, non-governmental organizations and other philanthropic agencies to help furnish resources for treating and controlling depression orders. Frontiers Media S.A. 2022-05-19 /pmc/articles/PMC9160970/ /pubmed/35664156 http://dx.doi.org/10.3389/fpsyg.2022.920920 Text en Copyright © 2022 Yu, Wang, Li, Liu, Oteng Agyeman and Wang. 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 | Psychology Yu, Qingyue Wang, Zihao Li, Zeyu Liu, Xuejun Oteng Agyeman, Fredrick Wang, Xinxing Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas |
title | Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas |
title_full | Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas |
title_fullStr | Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas |
title_full_unstemmed | Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas |
title_short | Hierarchical Structure of Depression Knowledge Network and Co-word Analysis of Focus Areas |
title_sort | hierarchical structure of depression knowledge network and co-word analysis of focus areas |
topic | Psychology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9160970/ https://www.ncbi.nlm.nih.gov/pubmed/35664156 http://dx.doi.org/10.3389/fpsyg.2022.920920 |
work_keys_str_mv | AT yuqingyue hierarchicalstructureofdepressionknowledgenetworkandcowordanalysisoffocusareas AT wangzihao hierarchicalstructureofdepressionknowledgenetworkandcowordanalysisoffocusareas AT lizeyu hierarchicalstructureofdepressionknowledgenetworkandcowordanalysisoffocusareas AT liuxuejun hierarchicalstructureofdepressionknowledgenetworkandcowordanalysisoffocusareas AT otengagyemanfredrick hierarchicalstructureofdepressionknowledgenetworkandcowordanalysisoffocusareas AT wangxinxing hierarchicalstructureofdepressionknowledgenetworkandcowordanalysisoffocusareas |