The Structure of Psychopathology in a Sample of Clinically Referred, Emotionally Dysregulated Early Adolescents
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The Structure of Psychopathology in a Sample of Clinically Referred, Emotionally Dysregulated Early Adolescents Vera Vine 1
&
Amy L. Byrd 1 & Harmony Mohr 1 & Lori N. Scott 1 & Joseph E. Beeney 1 & Stephanie D. Stepp 1,2
# Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract This investigation answers and amplifies calls to model the transdiagnostic structure of psychopathology in clinical samples of early adolescents and using stringent psychometric criteria. In 162 clinically referred, clinically evaluated 11–13-year-olds, we compared a correlated two-factor model, containing latent internalizing and externalizing factors, to a bifactor model, which added a transdiagnostic general factor. We also evaluated the bifactor model psychometrically, including criterion validity with broad indicators of psychosocial functioning. In doing so, we compared alternative approaches to defining and interpreting criterion validity: a recently proposed incremental definition based on amounts of variance in criterion factors explained, and the more typical definition based on the presence of conceptually meaningful relationships. While traditional fit statistics favored the bifactor model as expected, psychometric analyses added important nuance. Despite moderate reliability, the general factor was not fully transdiagnostic (i.e., was not informed by several externalizing scores), and was partially redundant with internalizing scores. Approaches to criterion validity yielded opposing results. Compared to the correlated two-factor model, the bifactor model redistributed, without incrementally increasing, the total variance explained in criterion indicators of psychosocial functioning. Yet, the bifactor model did improve the precision of clinically important relationships to psychosocial functioning, raising questions about meaningful tests of bifactor psychopathology models. Keywords Structure of psychopathology . Bifactor model . P-factor . Internalizing . Externalizing
Understanding the structure of psychopathology, including features that are shared across disorders versus those that are unique to specific pathologies, bears directly on treatment and prevention. Data-driven approaches play a critical role by revealing common sources of variance shared by clusters of pathologies. Initially, quantitative studies on the structure of psychopathology focused on adult samples. Extensions into youth samples have made strides toward identifying common underlying pathogenic processes at play during high-risk periods preceding adult psychopathology (e.g., Haltigan et al. 2018). However, as we
discuss below, adolescent structural studies have made methodological trade-offs limiting their relevance to higher levels of clinical dysfunction. We addressed the remaining need for structural studies in clinically referred, clinically evaluated samples with enough psychiatric acui t y to a ll o w m o d e l i n g o f c l i n i c a l ly s i g n i f ic a n t , transdiagnostic dysfunction in youth. This study also applied
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