Beyond comorbidity: Toward a dimensional and hierarchical approach to understanding psychopathology across the life span

Abstract

In this review, we propose a novel developmentally informed framework to push research beyond a focus on comorbidity between discrete diagnostic categories, and to move towards research based on the well-validated dimensional and hierarchical structure of psychopathology. For example, a large body of research speaks to the validity and utility of the Internalizing and Externalizing (IE) spectra as organizing constructs for research on common forms of psychopathology. The IE spectra act as powerful explanatory variables that channel the psychopathological effects of genetic and environmental risk factors, predict adaptive functioning, and account for the likelihood of disorder-level manifestations of psychopathology. As such, our proposed theoretical framework uses the IE spectra as central constructs to guide future psychopathology research across the lifespan. The framework is particularly flexible, as any of the facets or factors from the dimensional and hierarchical structure of psychopathology can form the focus of research. We describe the utility and strengths of this framework for developmental psychopathology in particular, and explore avenues for future research.

Unique Associations between Childhood Temperament Characteristics and Subsequent Psychopathology Symptom Trajectories from Childhood to Early Adolescence

“…We consequently acknowledge that the results of the present study indicate temperament is one risk/protective factor that makes up part of a larger cumulative risk for psychopathology (cf. Busseri, Willoughby, & Chalmers, 2006; Forbes, Tackett, Markon, & Krueger, 2016). …”

“…Given each of the four domains of psychopathology we investigated are developmentally coherent into adulthood (see Forbes et al, 2016, for a review), our results have important implications for the early detection and prevention of childhood psychopathology, allowing us to interrupt maladaptive pathways before they develop into increasingly severe forms of psychopathology (cf. Beauchaine & McNulty, 2014).…”

Delineating the joint hierarchical structure of clinical and personality disorders in an outpatient psychiatric sample

“…We analyzed the systematic patterns of covariance among 24 indicators of clinical and personality disorders from the DSM to elucidate the spectra of psychopathology identified in the present sample [37]. The hierarchical structure of the spectra was delineated using two statistical methods: (1) Goldberg’s [38] bass-ackwards method, which sequentially extracts principal components from the top-down 1 .…”

Characterising the latent structure and organisation of self-reported thoughts, feelings and behaviours in adolescents and young adults

“…A broader approach appears to be warranted: Recent research indicates that increasing precision in behavioural phenotypes using modern psychometric methods can increase signal within molecular genetics [32] as well within analysis of personality and cognitive correlates of psychopathology [25]. Such findings demonstrate that mathematical modelling can aid in validity studies of mental illnesses (see Forbes and colleagues [33] for a theoretical argument as well). In summary, the structure of mental illness and well-being in the general population is likely to be a multi-dimensional complex structure.…”