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Predicting Long-Term Outcomes in First-Admission Psychosis: Does the Hierarchical Taxonomy of Psychopathology Aid DSM in Prognostication?
Author(s) -
Elizabeth A. Martin,
Katherine Jonas,
Wenxuan Lian,
Dan Foti,
Kayla R. Donaldson,
Evelyn J. Bromet,
Roman Kotov
Publication year - 2021
Publication title -
schizophrenia bulletin
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.823
H-Index - 190
eISSN - 1745-1707
pISSN - 0586-7614
DOI - 10.1093/schbul/sbab043
Subject(s) - psychopathology , schizoaffective disorder , psychosis , psychology , medical diagnosis , psychiatry , incremental validity , bipolar disorder , clinical psychology , global assessment of functioning , diagnosis of schizophrenia , dsm 5 , schizophrenia (object oriented programming) , cohort , mental health , cognition , medicine , psychometrics , construct validity , pathology
The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical, dimensional model of psychological symptoms and functioning. Its goals are to augment the use and address the limitations of traditional diagnoses, such as arbitrary thresholds of severity, within-disorder heterogeneity, and low reliability. HiTOP has made inroads to addressing these problems, but its prognostic validity is uncertain. The present study sought to test the prediction of long-term outcomes in psychotic disorders was improved when the HiTOP dimensional approach was considered along with traditional (ie, DSM) diagnoses. We analyzed data from the Suffolk County Mental Health Project (N = 316), an epidemiologic study of a first-admission psychosis cohort followed for 20 years. We compared 5 diagnostic groups (schizophrenia/schizoaffective, bipolar disorder with psychosis, major depressive disorder with psychosis, substance-induced psychosis, and other psychoses) and 5 dimensions derived from the HiTOP thought disorder spectrum (reality distortion, disorganization, inexpressivity, avolition, and functional impairment). Both nosologies predicted a significant amount of variance in most outcomes. However, except for cognitive functioning, HiTOP showed consistently greater predictive power across outcomes—it explained 1.7-fold more variance than diagnoses in psychiatric and physical health outcomes, 2.1-fold more variance in community functioning, and 3.4-fold more variance in neural responses. Even when controlling for diagnosis, HiTOP dimensions incrementally predicted almost all outcomes. These findings support a shift away from the exclusive use of categorical diagnoses and toward the incorporation of HiTOP dimensions for better prognostication and linkage with neurobiology.

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