What works for whom?
The challenge in treating mental health disorders is not that there are no effective treatments available, but that many patients often do not receive the treatment that will work best for them.
The overarching aims of research in our lab include:
- Estimate the effectiveness of treatments for common mental disorders, especially major depressive disorder
- Re-examine assumptions about the effects of treatments using data and innovative methodologies
- Develop and implement tools to identify mechanisms and promote the “personalization” of treatments
Our lab has worked on developing predictive models to answer the question: what works for whom? Efforts to examine the individual differences affecting patient outcome and response to treatment include the Personalized Advantage Index (PAI) (DeRubeis, Cohen, et al., 2014), as well as prognostic models (Lorenzo-Luaces, DeRubeis et al., 2017). Through machine learning, statistical models, and other innovative techniques, we aim to further enhance the accuracy of predicting – and selecting – the best treatment for a given patient.