Evidence map›Paper›PMID 38268052›Full record

ArticleBMC psychology2024

Using a longitudinal network structure to subgroup depressive symptoms among adolescents.

Sugai Liang, Zejun Huang, Yiquan Wang, Yue Wu, Zhiyu Chen, Yamin Zhang, Wanjun Guo, Zhenqing Zhao, Sabrina D Ford, Lena Palaniyappan and 1 more

Abstract read
In one paragraph

Article in BMC psychology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Review
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

11 authors.

Sugai Liang *Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China.
Zejun Huang *Hangzhou Institute of Educational Science, 310003, Hangzhou, China.
Yiquan WangAffiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China.
Yue WuAffiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China.
Zhiyu ChenAffiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China.
Yamin ZhangAffiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China.
Wanjun GuoAffiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China.
Zhenqing ZhaoHangzhou Vocational & Technical College, 310018, Hangzhou, China.
Sabrina D FordDouglas Mental Health University Institute, Department of Psychiatry, McGill University, H4H1R3, Montreal, Canada.
Lena PalaniyappanDouglas Mental Health University Institute, Department of Psychiatry, McGill University, H4H1R3, Montreal, Canada. lena.palaniyappan@mcgill.ca.
Tao LiAffiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China. litaozjusc@zju.edu.cn.

Funding

China Brain Project 2021ZD0200404Key R & D Program of Zhejiang 2022C03096National Natural Science Foundation of China 81920108018, 82230046
6 · The paper itself

Abstract

backgroundNetwork modeling has been proposed as an effective approach to examine complex associations among antecedents, mediators and symptoms. This study aimed to investigate whether the severity of depressive symptoms affects the multivariate relationships among symptoms and mediating factors over a 2-year longitudinal follow-up.

methodsWe recruited a school-based cohort of 1480 primary and secondary school students over four semesters from January 2020 to December 2021. The participants (n = 1145) were assessed at four time points (ages 10-13 years old at baseline). Based on a cut-off score of 5 on the 9-item Patient Health Questionnaire at each time point, the participants were categorized into the non-depressive symptom (NDS) and depressive symptom (DS) groups. We conducted network analysis to investigate the symptom-to-symptom influences in these two groups over time.

resultsThe global network metrics did not differ statistically between the NDS and DS groups at four time points. However, network connection strength varied with symptom severity. The edge weights between learning anxiety and social anxiety were prominently in the NDS group over time. The central factors for NDS and DS were oversensitivity and impulsivity (3 out of 4 time points), respectively. Moreover, both node strength and closeness were stable over time in both groups.

conclusionsOur study suggests that interrelationships among symptoms and contributing factors are generally stable in adolescents, but a higher severity of depressive symptoms may lead to increased stability in these relationships.

Indexed as

AnxietyDepressionAdolescentAnxiety DisordersChildHumansImpulsive BehaviorLearningAdolescentAnxietyDepressive symptomsNetwork analysis

Identifiers

PMID38268052
PMCPMC10807250

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Registered trials

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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.