Byeon H. Developing a nomogram for predicting the depression of senior citizens living alone while focusing on perceived social support. World J Psychiatr 2021; 11(12): 1314-1327 [PMID: 35070780 DOI: 10.5498/wjp.v11.i12.1314]
Corresponding Author of This Article
Haewon Byeon, DSc, PhD, Associate Professor, Director, Department of Medical Big Data, Inje University, 197, Inje-ro, Gimhae, 50834, Gyeonsangnamdo, South Korea. bhwpuma@naver.com
Research Domain of This Article
Psychiatry
Article-Type of This Article
Case Control Study
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Byeon H. Developing a nomogram for predicting the depression of senior citizens living alone while focusing on perceived social support. World J Psychiatr 2021; 11(12): 1314-1327 [PMID: 35070780 DOI: 10.5498/wjp.v11.i12.1314]
World J Psychiatr. Dec 19, 2021; 11(12): 1314-1327 Published online Dec 19, 2021. doi: 10.5498/wjp.v11.i12.1314
Developing a nomogram for predicting the depression of senior citizens living alone while focusing on perceived social support
Haewon Byeon
Haewon Byeon, Department of Medical Big Data, Inje University, Gimhae, 50834, Gyeonsangnamdo, South Korea
Author contributions: Byeon H was designed the study, involved in data interpretation, preformed the statistical analysis, and assisted with writing the article.
Supported byBasic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (NRF-2018R1D1A1B07041091, NRF-2021S1A5A8062526).
Institutional review board statement: The study was approved by the Research Ethics Review Board of the National Biobank of Korea (No. KBN-2019-005) and the H University (No. 20180042).
Informed consent statement: All patients gave informed consent.
Conflict-of-interest statement: No benefits in any form have been received or will be received from a commercial party related directly or indirectly to the subject of this article.
Data sharing statement: Technical appendix, statistical code from the corresponding author at bhwpuma@naver.com.
STROBE statement: The authors have read the STROBE statement—checklist of items, and the manuscript was prepared and revised according to the STROBE statement—checklist of items.
Corresponding author: Haewon Byeon, DSc, PhD, Associate Professor, Director, Department of Medical Big Data, Inje University, 197, Inje-ro, Gimhae, 50834, Gyeonsangnamdo, South Korea. bhwpuma@naver.com
Received: May 23, 2021 Peer-review started: May 23, 2021 First decision: July 14, 2021 Revised: July 18, 2021 Accepted: November 3, 2021 Article in press: November 3, 2021 Published online: December 19, 2021 Processing time: 206 Days and 0.7 Hours
ARTICLE HIGHLIGHTS
Research background
Senile diseases are rapidly increasing globally due to the rapid aging of the population. Among these diseases, depression is an important and frequent psychiatric disorder in the senile stage, and it is predicted to be the second major factor in the global burden of disease.
Research motivation
Although the number of senior citizens living alone is increasing, only a few studies have identified factors related to the depression characteristics of senior citizens living alone by using epidemiological survey data that can represent a population group.
Research objectives
This study developed a nomogram that allows physicians to check the multiple risk factors of depression of senior citizens living alone using visual graphs and to calculate the prevalence probability of depression while considering the personal characteristics of a subject based on these results.
Research methods
This study analyzed 1558 senior citizens (695 males and 863 females) who were 60 years or older. Depression, an outcome variable, was measured using the short form of the Korean version CES-D (short form of CES-D). This study built a depression prediction model using logistic regression analysis to find out the effect of each variable on depression. The developed depression prediction model contained a nomogram to make it possible for clinicians to interpret the prediction results easily.
Research results
In this study, the significant predictors of depression of the senior citizens living alone were the experiences of suicidal urge over the past year, dissatisfaction with help (support) from neighbors, subjective loneliness, age, and low self-esteem.
Research conclusions
The results of this study implied that it is necessary to develop a support system customized for subjects to strengthen the relation network for preventing depression in senior citizens living alone so that they can receive actual support from acquaintances such as neighbors rather than the frequency of physical contact.
Research perspectives
It is needed to establish an improved mental health policy that identifies high depression risk groups among senior citizens living alone based on multiple risk factors and continuously manages them.
