Advances in psychotherapy research and precision mental health
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BORIS DOI
Subtitle
answering the "what works for whom” question for patients with depression
Abstract
The present doctoral thesis focuses on two articles which are embedded in the field of precision mental health and treatment selection. Study 1 examined if model determined treatment allocation to cognitive behavioral therapy (CBT) or CBT with integrated exposure and emotion-focused elements (CBT-EE) results in better treatment outcomes while using important predictors found for each intervention. Study 2 investigated important predictors in routine care and blended internet- and face-to-face CBT in secondary care, as well as treatment outcomes for treatment allocation using this predictive information. Both studies use a Bayesian approach called Bayesian Model Averaging (BMA) and the Personalized Advantage Index (PAI) for their statistical analyses. After an introduction to the Generic Model of Psychotherapy, the development of process and outcome research and the thematic field of treatment selection and precision medicine, the individual articles will be described and critically reflected in more detail. Possibilities and limits of predicting the optimal treatment for an individual based on algorithms are discussed based on the results of the two studies. Taken together, the two studies provide an important contribution to psychotherapy research as the feasibility of treatment selection using BMA and PAI is shown. Last but not least, implications for future research are discussed and an example of how treatment selection can be transferred into clinical practice is presented.
Date of Publication
2020
Year of graduation
2020
Theses Type
dissertation
Subject(s)
Language(s)
en
Author(s)
Friedl, Nadine |
Faculty/Graduate School
Access(Rights)
open.access
Primary OA Publication
true