Walker Johanna C, Parker Alyssa J, Patel Krupali R, Dougherty Lea R, Wiggins Jillian Lee
Joint Doctoral Program in Clinical Psychology, San Diego State University/University of California, San Diego, CA, USA.
Department of Psychology, University of Maryland, College Park, MD, USA.
J Affect Disord. 2025 Aug 1;382:282-289. doi: 10.1016/j.jad.2025.04.082. Epub 2025 Apr 22.
Traditional categorical systems for diagnosing psychopathological symptoms, such as the DSM-5, face limitations including high comorbidity rates and insufficient support for transdiagnostic treatment protocols. Dimensional, person-centered approaches can address these limitations by focusing on cross-cutting psychiatric symptoms.
This study leverages data from the Adolescent Brain Cognitive Development℠ Study (ABCD Study®) to develop dimensional models of preadolescent psychopathology, focusing on a large, diverse sample of youths aged 9-10. We used latent profile analysis (LPA) on Child Behavior Checklist (CBCL) syndrome scales collected from an elevated symptomatology subsample to delineate subgroups for targeted interventions.
Four distinct profiles emerged: "Mildly Elevated" and "Highly Elevated" (on both internalizing and externalizing), "Moderately Elevated - Rule-Breaking," and "Moderately Elevated - Internalizing & Thought Problems." These profiles differed significantly across sociodemographic, neurocognitive, and life experience characteristics. The "Highly Elevated" group showed the highest levels of risk, including greater trauma exposure and higher rates of parental psychopathology. In contrast, the "Mildly Elevated" group demonstrated lower levels of risk factors and higher fluid intelligence compared to the other groups. The two Moderately Elevated profiles were largely similar across most risk indicators, though the Internalizing & Thought Problems group had a slightly higher proportion of parents with a college education.
These profiles offer the beginnings of a foundation for classifying symptom co-occurrence and highlight the need for developmentally specific nosologies to improve risk detection and intervention strategies. Future research should further validate these profiles and explore their stability across developmental stages to inform targeted interventions.
用于诊断精神病理症状的传统分类系统,如《精神疾病诊断与统计手册》第5版(DSM - 5),存在局限性,包括高共病率以及对跨诊断治疗方案的支持不足。维度化、以人为主的方法可以通过关注交叉性精神症状来解决这些局限性。
本研究利用青少年大脑认知发展(ABCD)研究的数据,以9至10岁的大量、多样化青少年样本为重点,建立青春期前精神病理学的维度模型。我们对从症状加重亚样本中收集的儿童行为清单(CBCL)综合征量表进行潜在剖面分析(LPA),以划定亚组进行有针对性的干预。
出现了四种不同的剖面:“轻度加重”和“高度加重”(在内化和外化方面均如此)、“中度加重 - 违规行为”以及“中度加重 - 内化及思维问题”。这些剖面在社会人口统计学、神经认知和生活经历特征方面存在显著差异。“高度加重”组显示出最高的风险水平,包括更多的创伤暴露和更高的父母精神病理学发生率。相比之下,“轻度加重”组与其他组相比,风险因素水平较低,流体智力较高。两个中度加重剖面在大多数风险指标上基本相似,不过内化及思维问题组中父母拥有大学学历的比例略高。
这些剖面为症状共现的分类提供了基础,并强调了需要有针对不同发育阶段的疾病分类学来改善风险检测和干预策略。未来的研究应进一步验证这些剖面,并探索它们在不同发育阶段的稳定性,以为有针对性的干预提供信息。