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采用纵向网络结构对青少年抑郁症状进行亚组划分。

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

机构信息

Affiliated Mental Health Centre & Hangzhou Seventh People's Hospital, Zhejiang University School of Medicine, 305 Tianmushan Road, 310013, Hangzhou, China.

Hangzhou Institute of Educational Science, 310003, Hangzhou, China.

出版信息

BMC Psychol. 2024 Jan 24;12(1):46. doi: 10.1186/s40359-024-01537-8.

Abstract

BACKGROUND

Network 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.

METHODS

We 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.

RESULTS

The 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.

CONCLUSIONS

Our 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.

摘要

背景

网络建模已被提出作为一种有效的方法来研究前因、中介和症状之间的复杂关联。本研究旨在探讨抑郁症状的严重程度是否会影响症状和中介因素之间的多变量关系在 2 年的纵向随访中。

方法

我们在 2020 年 1 月至 2021 年 12 月的四个学期内招募了一个基于学校的 1480 名中小学生队列。在四个时间点(基线时年龄为 10-13 岁)评估参与者(n=1145)。基于每个时间点的 9 项患者健康问卷的 5 分作为截止分数,参与者被分为非抑郁症状(NDS)和抑郁症状(DS)组。我们进行网络分析以调查这两个组在随时间的症状间影响。

结果

在四个时间点,NDS 和 DS 组之间的全局网络度量没有统计学差异。然而,网络连接强度随症状严重程度而变化。学习焦虑和社交焦虑之间的边缘权重在 NDS 组中随着时间的推移而显著增加。NDS 和 DS 的中心因素分别是过度敏感和冲动(4 个时间点中的 3 个)。此外,两组的节点强度和接近度在随时间都很稳定。

结论

我们的研究表明,青少年中症状和促成因素之间的相互关系通常是稳定的,但抑郁症状的严重程度较高可能会导致这些关系的稳定性增加。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d873/10807250/a664ff3d7c07/40359_2024_1537_Fig1_HTML.jpg

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