Evidence map›Paper›PMID 40917242›Full record

ArticleFrontiers in psychiatry2025

Network analysis on depressive symptoms and big five personality traits of community elderly over 60 years old: a cross-sectional study.

Mo Zhu, Yanqun Zheng, Yuan Fang, Qi Qiu, Xia Li

Abstract read
In one paragraph

Article in Frontiers in psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mo Zhu *Department of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Yanqun Zheng *Department of Psychiatry and Psychology, Huashan Hospital, Fudan University, Shanghai, China.
Yuan FangDepartment of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Qi QiuDepartment of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Xia LiDepartment of Geriatric Psychiatry, Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The global population is undergoing significant aging, with the elderly facing prominent physical and mental health challenges. Geriatric depression is becoming increasingly prevalent, imposing a heavy burden on healthcare and caregiving. This study employs network analysis to explore the relationship between geriatric depressive symptoms and the Big Five personality traits, aiming to provide a theoretical basis for preventing and intervening in geriatric depression. Methods: A total of 585 residents aged 60 and above, with an average age of 67.14 ± 5.26 years, were included in this study. The Geriatric Depression Scale-15 was used to assess depressive symptoms, and the 60-item version of the Big Five Personality Inventory was used to assess personality traits. The network model was constructed in R using the qgraph, bootnet, and networktools packages, applying LASSO regularization with EBIC for model selection. Network centrality was evaluated using Strength and Bridge Strength as indicators. Meanwhile, network comparison analyses were conducted for different genders. Results: The model included 45 edges, 29 of which had non-zero estimates, with an average edge weight of 0.038. Openness had negative connections with withdrawal apathy-vigor (WAV) and hopelessness; Conscientiousness had a negative connection with dysphoric mood; Extraversion had a negative connection with WAV; Agreeableness had a negative connection with anxiety; and Neuroticism had positive connections with dysphoric mood, WAV, anxiety, memory complaints, and hopelessness. According to the strength centrality ranking, the top four nodes were Neuroticism, Conscientiousness, dysphoric mood, and hopelessness. The nodes with higher bridge strength were Neuroticism, dysphoric mood, and WAV. The analysis stratified by gender revealed that Neuroticism consistently exhibited the highest strength and bridge strength. In terms of the strength of depressive symptoms, dysphoric mood was most prominent in males, while hopelessness was most significant in females. Regarding bridge strength, anxiety symptoms had the highest bridge strength in males, whereas dysphoric mood had the highest bridge strength in females. Conclusion: Different personality traits show varied associations with geriatric depressive symptoms. Neuroticism is crucial in the Personality-Depressive Symptoms network, and gender differences exist in this relationship. These findings may offer guidance for the prevention and treatment of depressive symptoms in older adults.

Indexed as

big five personality traitscross-sectional studydepressive symptomselderlynetwork analysis

Identifiers

PMID40917242
PMCPMC12408598

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.