Considerable quantitative evidence has now been amassed suggesting that mental disorders are more accurately understood as continuously distributed dimensions of psychopathology rather than categorical constructs. The result has been an increasing shift towards a dimensional organization of psychopathology in contemporary psychiatry. Data-driven (i.e., factor model-based) modeling of numerous measures of mental disorders and psychopathology has provided robust empirical support for evidence of a transdiagnostic general factor model of psychopathology. The general psychopathology, or “p” factor, reflects both the common variation among all symptoms of psychopathology, as well as low to high psychopathology severity, thus cutting across diverse mental disorder categories and/or symptoms (i.e., those included as input for empirical modeling). This shared variation is consistent with the high rates of comorbidity commonly observed across most classic mental disorder categories. Current methodological work is now addressing important questions concerning the empirical definition of the “p” factor and plausible mechanisms that give rise to the observed interrelationships amongst mental illness (or symptom) indicators (see Watts et al., 2020). As we begin to integrate dimensional symptom measures in clinical practice, it is important to examine the significance of dimensionally-measured constructs, as well as their trajectories across development and across treatment. Such evidence will support an evidence-based approach to identifying children and youth at risk and will inform the timing and nature of prevention and intervention efforts.
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