Evidence map›Paper›PMID 41162915›Full record

ArticleBMC psychiatry2025

Cross-sectional and longitudinal network analyses depict variations of symptom networks in depression patients across the lifespan: insight from a large-scale sample.

Ziyu Hao, Wei Qu, Zhiren Wang, Shuping Tan

Abstract read
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Article in BMC psychiatry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

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3 · Its place in the literature

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2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Ziyu HaoBeijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, 100096, China.
Wei QuBeijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, 100096, China.
Zhiren WangBeijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, 100096, China. zhiren75@163.com.
Shuping TanBeijing HuiLongGuan Hospital, Peking University HuiLongGuan Clinical Medical School, Beijing, 100096, China. shupingtan@126.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDepressive symptoms and their interrelations vary across developmental stages, yet the developmental dynamics of symptom networks remain insufficiently explored. Network analysis offers a framework to identify age-specific symptom structures and central nodes, which may inform more precise, developmentally tailored interventions. However, most prior studies are limited by small sample sizes and narrow age ranges. Leveraging a large-scale clinical sample encompassing a broad age spectrum, the present study aims to map both cross-sectional and longitudinal depressive symptom networks across the lifespan to clarify dynamic patterns of symptom connectivity and centrality.

methodsA total of 56,920 patients diagnosed with depression were classified into four age groups: adolescents (12-17 years, n = 9,191), young adults (18-40 years, n = 34,302), middle adults (41-65 years, n = 11,385), and older adults (> 65 years, n = 1,919). Depressive symptoms were measured using Self-rating Depression Scale. Cross-sectional symptom networks were constructed separately for each age group to examine group-specific network structures and centrality patterns. Longitudinal data from a subsample of 4,297 patients were analyzed using cross-lagged panel network models to investigate the directional associations among symptoms over time.

resultsIn the cross-sectional networks, "crying" emerged as the most central symptom in adolescents, "diminished capacity" in young and middle-aged adults, and "hopelessness" in older adults. Global strength increased from adolescence to middle adulthood and a subsequent decrease in older adulthood. In the longitudinal networks, "meaninglessness" exhibited the highest temporal influence in adolescents and older adults, while "hopelessness" and "diminished capacity" were most influential in young and middle-aged adults, respectively.

conclusionThis study emphasises the dynamic and developmentally specific structuring of depressive symptom networks across the lifespan. Distinct central symptoms and varying levels of symptom connectivity across age groups suggest stage-specific psychological vulnerabilities. These structural characteristics inform intervention strategies: tightly connected networks in earlier life stages may benefit from focused treatment targeting central symptoms, whereas the more diffuse networks observed in late life may require integrative, multimodal approaches. The findings support a developmental systems perspective on depression and emphasize the need for age-sensitive clinical assessment and intervention.

Indexed as

DepressionAdolescentAdultAgedAge FactorsChildCross-Sectional StudiesFemaleHumansLongitudinal StudiesMaleMiddle AgedPsychiatric Status Rating ScalesYoung AdultAcross lifespanDepressionLongitudinal networkNetwork analysis

Identifiers

PMID41162915
PMCPMC12574187

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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 OpenQuestion graph.