网络温度作为衡量青春期抑郁症状稳定性的指标。

Nature mental health Pub Date : 2025-01-01 Epub Date: 2025-04-29 DOI:10.1038/s44220-025-00415-5
Poppy Z Grimes, Aja L Murray, Keith Smith, Andrea G Allegrini, Giulia G Piazza, Henrik Larsson, Sacha Epskamp, Heather C Whalley, Alex S F Kwong
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引用次数: 0

摘要

抑郁症的特点是不同的症状组合,可以表现为动态网络。虽然以前的研究侧重于有针对性干预的中心症状,但对整个网络特性的关注较少。在这里,我们展示了“网络温度”,一种衡量心理网络稳定性的新方法,可以捕捉到青春期的症状一致性——抑郁发作的关键时期。网络温度反映了系统的稳定性,较高的值表明较少的症状一致性和较大的可变性。在三个大型纵向青少年队列中(总N = 35,901),我们发现网络温度在整个青春期下降,在青春期早期下降最快,特别是在男性中。这表明抑郁症状网络在整个发育过程中通过增加症状一致性而稳定下来,这可能解释了为什么青春期是抑郁症发病的关键时期。这些发现强调了青春期早期是一个关键的干预窗口,并强调了性别特异性和个性化干预的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Network temperature as a metric of stability in depression symptoms across adolescence.

Depression is characterized by diverse symptom combinations that can be represented as dynamic networks. While previous research has focused on central symptoms for targeted interventions, less attention has been given to whole-network properties. Here we show that 'network temperature', a novel measure of psychological network stability, captures symptom alignment across adolescence-a critical period for depression onset. Network temperature reflects system stability, with higher values indicating less symptom alignment and greater variability. In three large longitudinal adolescent cohorts (total N = 35,901), we found that network temperature decreases across adolescence, with the steepest decline during early adolescence, particularly in males. This suggests that depression symptom networks stabilize throughout development via increased symptom alignment, potentially explaining why adolescence is a crucial period for depression onset. These findings highlight early adolescence as a key intervention window and underscore the importance of sex-specific and personalized interventions.

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