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Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory
OBJECTIVE: This study aimed to identify the central symptoms of late-life depression using network analysis and the item response theory. METHODS: A total of 3,472 older adults were enrolled and the Geriatric Depression Scale-15 (GDS-15) was used to evaluate the depressive symptoms. To identify the...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Korean Neuropsychiatric Association
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600216/ https://www.ncbi.nlm.nih.gov/pubmed/34710960 http://dx.doi.org/10.30773/pi.2021.0453 |
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author | Kim, Kyoung Min Kim, Dohyun Chung, Un Sun Lee, Jung Jae |
author_facet | Kim, Kyoung Min Kim, Dohyun Chung, Un Sun Lee, Jung Jae |
author_sort | Kim, Kyoung Min |
collection | PubMed |
description | OBJECTIVE: This study aimed to identify the central symptoms of late-life depression using network analysis and the item response theory. METHODS: A total of 3,472 older adults were enrolled and the Geriatric Depression Scale-15 (GDS-15) was used to evaluate the depressive symptoms. To identify the central symptoms and the network structures among the individual symptoms, the analyses of symptom network structures and item response theory were performed. RESULTS: Among items on the GDS-15, “Happy,” “Hopeless,” “Empty,” “Bored,” “Worthless,” and “Good spirits” showed significantly higher strength centrality than the other symptoms. Among all the edges, the edge between “Empty” and “Bored” was the strongest; however, these two symptoms were not connected strongly to other symptoms. In the analysis of item response theory, “Empty,” “Bored,” “Hopeless,” “Worthless,” “Happy,” “Helpless,” and “Satisfied” presented a very high value on the discrimination parameter. CONCLUSION: Our study identified the central symptoms and the network structures among symptoms listed on the GDS-15. Most of central symptoms identified by network analysis and item response theory coincided. Our results suggest that these central symptoms need to be prioritized as highly comorbid symptoms and can contribute to the development of a brief screening tool for the elderly. |
format | Online Article Text |
id | pubmed-8600216 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Korean Neuropsychiatric Association |
record_format | MEDLINE/PubMed |
spelling | pubmed-86002162021-11-18 Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory Kim, Kyoung Min Kim, Dohyun Chung, Un Sun Lee, Jung Jae Psychiatry Investig Original Article OBJECTIVE: This study aimed to identify the central symptoms of late-life depression using network analysis and the item response theory. METHODS: A total of 3,472 older adults were enrolled and the Geriatric Depression Scale-15 (GDS-15) was used to evaluate the depressive symptoms. To identify the central symptoms and the network structures among the individual symptoms, the analyses of symptom network structures and item response theory were performed. RESULTS: Among items on the GDS-15, “Happy,” “Hopeless,” “Empty,” “Bored,” “Worthless,” and “Good spirits” showed significantly higher strength centrality than the other symptoms. Among all the edges, the edge between “Empty” and “Bored” was the strongest; however, these two symptoms were not connected strongly to other symptoms. In the analysis of item response theory, “Empty,” “Bored,” “Hopeless,” “Worthless,” “Happy,” “Helpless,” and “Satisfied” presented a very high value on the discrimination parameter. CONCLUSION: Our study identified the central symptoms and the network structures among symptoms listed on the GDS-15. Most of central symptoms identified by network analysis and item response theory coincided. Our results suggest that these central symptoms need to be prioritized as highly comorbid symptoms and can contribute to the development of a brief screening tool for the elderly. Korean Neuropsychiatric Association 2021-11 2021-10-29 /pmc/articles/PMC8600216/ /pubmed/34710960 http://dx.doi.org/10.30773/pi.2021.0453 Text en Copyright © 2021 Korean Neuropsychiatric Association https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/ (https://creativecommons.org/licenses/by-nc/4.0/) ) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Original Article Kim, Kyoung Min Kim, Dohyun Chung, Un Sun Lee, Jung Jae Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory |
title | Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory |
title_full | Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory |
title_fullStr | Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory |
title_full_unstemmed | Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory |
title_short | Identification of Central Symptoms in Depression of Older Adults With the Geriatric Depression Scale Using Network Analysis and Item Response Theory |
title_sort | identification of central symptoms in depression of older adults with the geriatric depression scale using network analysis and item response theory |
topic | Original Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8600216/ https://www.ncbi.nlm.nih.gov/pubmed/34710960 http://dx.doi.org/10.30773/pi.2021.0453 |
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