Over the past several decades, the diagnosis of mental disorders has been characterized by classifying psychopathology into as many discrete diagnoses as can be reliability identified (e.g., APA, 2013). There is increasing evidence, however, that this approach to diagnosis may come at the expense of validity as trivial symptom-level differences are emphasized with little regard for common core mechanisms. Traditionally, cognitive-behavioral (CBT) approaches to treating psychopathology have followed a diagnosis-specific approach such that unique protocols have been developed for most disorders. Recent advances in CBT have suggested that targeting transdiagnostic mechanisms responsible for the development and maintenance of a wider range of psychopathology may be a more efficient approach to treatment than addressing disorder symptoms themselves. In order to create a more personalized treatment package, we propose establishing a profile for each patient that quantifies dysfunction in terms of empirically-supported underlying mechanisms; we further suggest that data from this profile be used to select CBT modules specific to the core mechanisms maintaining an individual patient's symptoms.
Keywords: Transdiagnostic; modular treatments; personalized treatments; treatment.
© 2014 Wiley Periodicals, Inc.