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南京医科大学学报（社会科学版）京医科大学学报（社会科学版） 第5期 总第130期
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Journal of Nanjing Medical University（Social Sciences）of Nanjing Medical University（Social Sciences） 2025年10月
Journal

Network analysis of depressive symptoms in older adults

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HEI Xiaojing ，PENG Songhao ，ZHANG Tao ，TANG Yiwei ，ZHOU Min 1
1. School of Humanities and Social Sciences，
2. Student Affairs Office，Shanxi Medical University，Taiyuan 030001，China
Abstract：This study aimed to investigate the network structure and core features of depressive symptoms
among older adults in China，and to compare the networks of depressive symptoms among older adults across
different genders and severity levels of depression. Data from the 2020 China Health and Retirement
Longitudinal Study （CHARLS） were used for the survey，which included 8 445 valid samples. Network
analyses were conducted using R software. The results of the study showed that the core features of depressive
symptoms in older adults were low mood and feeling unable to go on with their lives. There was a marginally
significant difference in the network structure of depressive symptoms among older adults of different genders，
while no significant differences in the strength of network connections. The centrality value of feeling unable to
go on with their lives was significantly higher in men than in women. There were significant differences in
certain edge weights between depressive symptom networks across genders. There were significant differences in
the network structure and network strength of depressive symptoms among older adults with different severity
levels of depression. The centrality values of feeling depressed and feeling unable to go on with their lives were
higher in the group without depressive symptoms than in the group with depressive symptoms. These results
suggest that the network structure of depressive symptoms among Chinese older adults is complex. It is
recommended to prioritize core symptoms， such as feeling down， in the prevention and intervention of
depressive symptoms among older adults，while developing personalized intervention strategies for gender
differences to improve the mental health of older adults.
Key words：older adults；depressive；network analysis；CHARLS