Ecological validity of a quantitative classification system for mental illness in treatment-seeking adults.

Abstract

Quantitative models of mental illness, such as the Hierarchical Taxonomy of Psychopathology (HiTOP), aim to optimize clinical assessment, which conventionally follows categorical diagnostic rubrics. The evidence base for these models is robust, but also uniform; available data come mostly from structured diagnostic interviews in nationally representative samples. It remains to be seen whether HiTOP adequately reflects mental illness as evaluated in routine clinical care, where diagnosis is often unsystematic and incomplete, relative to controlled research conditions. To test the generalizability of a quantitative nosology to real-world assessment contexts, we fit the HiTOP model to diagnoses in a large sample (N = 25,002) of treatment-seeking university students who were seen by health professionals in everyday practice. We then examined the criterion validity of model components in relation to clinically relevant outcomes (i.e., suicide attempts, self-injury, and binge drinking). Three related structures fit the data well: a correlated-factor model with internalizing, externalizing, and eating pathology dimensions; a higher-order model that added a general factor of psychopathology that spanned these 3 first-order factors; and a bifactor model that partitioned diagnostic (co)variance across a general factor and 3 orthogonal group factors. The first-order factors had expected patterns of criterion validity, and the general factor was a strong predictor of suicidality and self-injury, paralleling past research. Bifactor model group factors had interpretative problems, however. Across models, categorical diagnoses consistently offered minimal incremental validity relative to the transdiagnostic factors. We conclude that HiTOP is ecologically valid—explaining comorbidity patterns among diagnoses assigned “in the field”—and is poised to enhance clinical assessment and decision-making in routine care.

The role of maladaptive personality domains across multiple levels of the HiTOP structure

“…Only the latter remained intact in a post hoc model that included the spectra level as well, suggesting more predictive specificity for negative affectivity at a lower level. Nevertheless, these findings indicating negative affectivity as possibly the most substantial vulnerability factor for general psychopathology is consistent with some emerging p factor research linking this domain to internalizing outcomes more so than other problems (e.g …”

Criterion Validity and Relationships between Alternative Hierarchical Dimensional Models of General and Specific Psychopathology

“…Such advantages of bifactor models for discovering the correlates of psychopathology at each level of the hierarchy are not in dispute (Bornovalova et al, 2020;Watts, Poore, & Waldman, 2019). What is in dispute, however, is whether the psychometric properties of all factors in bifactor models are sufficient to realize its logical advantages (Conway, Mansolf, & Reise, 2019;Watts et al, 2019).…”

Evaluating the Criterion Validity of Hierarchical Psychopathology Dimensions Across Models: Familial Aggregation and Associations with Research Domain Criteria (RDoC) (Sub)constructs

“…Due to concerns about factor reliability in the bifactor model based on prior studies (Conway, Mansolf, et al, 2019;Levin-Aspenson et al, 2020;Martel et al, 2017; 2019), we assessed factor reliability for the best-fitting models. Specifically, construct replicability of the latent factors in the best-fitting correlated factor model and bifactor model was measured by Hancock's H (Hancock & Mueller, 2001), which quantifies the extent to which a factor is well-defined by its indicators and replicable.…”

“…The bifactor model of psychopathology has also been critiqued for yielding factors that are unreliable and difficult to interpret due to weak and inconsistent factor loadings (Levin-Aspenson et al, 2020;Watts et al, 2019) and the orthogonality of the general and specific factors (Bonifay et al, 2017). These concerns, in conjunction with recent findings that the validity of HiTOP dimensions can differ substantially across models (Conway, Mansolf, et al, 2019;Hyland et al, 2020;Moore et al, 2020), have prompted recommendations that comparisons between bifactor models and alternative models consider external validity in addition to model fit (e.g., Bonifay et al, 2017;Bornovalova et al, 2020;Forbes et al, 2020;Watts et al, 2019).…”

“…Based on several studies that compared the validity of bifactor and correlated factor psychopathology models using other validators and in other populations (Conway, Mansolf, et al, 2019;Forbes et al, 2020;Watts et al, 2019), we hypothesized that the best-fitting bifactor model may have a less consistent and interpretable validity pattern than the correlated factor model.…”