Mapping Multimodal Risk Factors to Mental Health Outcomes.

IF 8.7
Robert J Jirsaraie, Deanna M Barch, Ryan Bogdan, Scott A Marek, Janine D Bijsterbosch, Aristeidis Sotiras, Nicole R Karcher
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Abstract

A key challenge in predicting a person's state of mind is that there are a wide range of contributing factors that each have a subtle, yet significant, influence on mental health. We applied data mining techniques to identify the most important risk factors for predicting current symptoms and longitudinal outcomes from the Adolescent Brain Cognitive Developmental study (n = 11,552). Our results consistently revealed that social conflicts were the strongest predictors of psychopathology, especially family fighting and reputational damage between peers. Sex-differences also emerged as a critical factor for predicting long-term mental health outcomes. Neuroimaging derived metrics were consistently the least informative. While these findings provide novel insight into the developmental origins of psychopathology, our best performing models could only explain up to 40% of the variation between individuals. Future research is needed to obtain a more complete understanding of all the factors that meaningfully contribute to mental health.

绘制心理健康结果的多模式风险因素。
预测一个人的心理状态的一个关键挑战是,有一系列的影响因素,每个因素对心理健康都有微妙但重要的影响。我们应用数据挖掘技术,从青少年大脑认知发展研究(n = 11552)中确定预测当前症状和纵向结果的最重要危险因素。我们的研究结果一致表明,社会冲突是精神病理的最强预测因素,尤其是家庭冲突和同龄人之间的名誉损害。性别差异也成为预测长期心理健康结果的关键因素。神经影像学衍生指标始终是最不具信息性的。虽然这些发现为精神病理学的发展起源提供了新的见解,但我们最好的模型只能解释高达40%的个体差异。未来的研究需要更全面地了解对心理健康有意义的所有因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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