Evidence map›Paper›PMID 41091322›Full record

ArticleThe Psychiatric quarterly2025

The Relationship between Loneliness and Depression Symptoms in Adolescents: Network Analysis and Cross-lag Panel Model.

Weiwei Lan, Xinyuan Duan, Siping Lin, Yueting Huang, Zhicheng Zhong, Xinling Liang, Jianglu Zhao, Yunfei Cai, Hong Cai, Li Su

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

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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

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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

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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

10 authors.

Weiwei Lan *Department of Epidemiology and Health Statistics, School of Public Health of Guangxi Medical University, Nanning, 530021, China.
Xinyuan Duan *School of Public Health of Guangxi Medical University, Nanning, 530021, China.
Siping LinSchool of Public Health of Guangxi Medical University, Nanning, 530021, China.
Yueting HuangDepartment of Epidemiology and Health Statistics, School of Public Health of Guangxi Medical University, Nanning, 530021, China.
Zhicheng ZhongDepartment of Epidemiology and Health Statistics, School of Public Health of Guangxi Medical University, Nanning, 530021, China.
Xinling LiangSchool of Public Health of Guangxi Medical University, Nanning, 530021, China.
Jianglu ZhaoSchool of Public Health of Guangxi Medical University, Nanning, 530021, China.
Yunfei CaiSchool of Public Health of Guangxi Medical University, Nanning, 530021, China.
Hong CaiSchool of Public Health of Guangxi Medical University, Nanning, 530021, China. caiong722@outlook.com.
Li SuDepartment of Epidemiology and Health Statistics, School of Public Health of Guangxi Medical University, Nanning, 530021, China. suli2018@hotmail.com.

Funding

the China Undergraduate Innovation Training Program under Grant X202410598275X
6 · The paper itself

Abstract

The increased prevalence of loneliness and depression among adolescent and young adults is attributed to social media use, academic pressures, and future worries. This study aimed to model the relationship between loneliness and depressive symptoms in adolescents and investigate their dynamic interplay using cross-lagged panel analysis. A total of 649 secondary school students participated in our study. This study evaluated loneliness and depressive symptoms using an online questionnaire. This study constructed a network model to identify the core and bridge symptoms of loneliness using network analysis and employed a cross-lagged panel network model to investigate the dynamic relationship between loneliness and depressive symptoms. At both survey time points, the bridge symptom was U11 (T1: Strength = 1.68; T2: Strength = 1.46). The symptom with the highest influence on others was U20 (OEI = 1.04), while the symptom most influenced by others was U14 (IEI = 0.73). Timely interventions for adolescent loneliness can prevent depression and mitigate its severity in affected individuals.

Indexed as

CLPNDepressive symptomsLonelinessNetwork analysis

Identifiers

PMID41091322

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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.