Background

Youth mental health disorders are strong predictors of adult mental health disorders. Early identification of mental health disorders in youth is important as it could aid early intervention and prevention. In a disorder agnostic manner, we aimed to identify influential psychopathology symptoms that could impact mental health in youth.

Methods

This study sampled 6063 participants from the Philadelphia Neurodevelopmental Cohort and comprised of youth of ages 12–21 years. A mixed graphical model was used to estimate the network structure of 115 symptoms corresponding to 16 psychopathology domains. Importance of individual symptoms in the network were assessed using node influence measures such as strength centrality and predictability.

Results

The generated network had stronger associations between symptoms within a psychopathological domain; overall had no negative associations. A conduct disorder symptom eliciting threatening others and a depression symptom - persistent sadness or depressed mood - had the greatest strength centralities (β = 2.85). Fear of traveling in a car and compulsively going in and out a door had the largest predictability (classification accuracy = 0.99). Conduct disorder, depression, and obsessive compulsive disorder symptoms generally had the largest strength centralities. Suicidal thoughts had the largest bridge strength centrality (β = 2.85). Subgroup networks revealed that network structure differed by socioeconomic status (low versus high, p = 0.04) and network connectivity patterns differed by sex (p = 0.01), but not for age or race.

Conclusions

Psychopathology symptom networks offer insights that could be leveraged for early identification, intervention, and possibly prevention of mental health disorders.

中文翻译：

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青少年精神病理学症状的障碍不可知网络结构

背景

青少年心理健康障碍是成人心理健康障碍的有力预测因素。早期识别青年精神健康障碍很重要，因为它可以帮助早期干预和预防。以一种与疾病无关的方式，我们旨在确定可能影响青年心理健康的有影响力的精神病理学症状。

方法

这项研究从费城神经发育队列中抽取了 6063 名参与者，其中包括 12-21 岁的年轻人。使用混合图形模型来估计对应于 16 个精神病理学领域的 115 个症状的网络结构。使用节点影响度量（例如强度中心性和可预测性）评估网络中单个症状的重要性。

结果

生成的网络在精神病理学领域内的症状之间具有更强的关联；总体没有负面关联。引起威胁他人的品行障碍症状和抑郁症状——持续的悲伤或情绪低落——具有最大的强度中心（β = 2.85）。对乘车旅行和强迫进出门的恐惧具有最大的可预测性（分类准确度 = 0.99）。品行障碍、抑郁症和强迫症症状通常具有最大的强度中心性。自杀念头具有最大的桥强度中心性（β= 2.85）。亚组网络显示，网络结构因社会经济地位而异（低与高，p = 0.04）和网络连接模式因性别而异（p = 0.01），但与年龄或种族无关。

结论

精神病理学症状网络提供了可用于早期识别、干预和可能预防精神健康障碍的见解。