Joshua Curtiss, Northeastern University

Joshua Curtiss

PhD

Assistant Professor

Applied Psychology


Overview

I am currently an Assistant Professor at Northeastern University in the Applied Psychology Department, with an appointment in the Center for Cognitive and Brain Health and an affiliation in the Psychology Department. I am also a Research Associate in the Psychiatry Department of Massachusetts General Hospital with the Depression Clinical and Research Program.

I completed my postdoctoral fellowship and predoctoral internship in the Psychiatry Department at Harvard Medical School/Massachusetts General Hospital and received my PhD in Clinical Psychology from Boston University. Prior to pursuing my doctoral degree, I was a statistician and researcher in the clinical Psychology Department at Yale University for several years.

My overall research program pertains to the general domain of computational clinical psychology, which involves leveraging state-of-the-art statistical approaches to address questions relating to the nosology and treatment of emotional disorders (i.e., anxiety and depression disorders). Specifically, my research embraces statistical procedures that foster idiographic and precision medicine approaches to clinical psychology, such as intensive time-series research designs and machine learning approaches. My approach emphasizes computational strategies that capture the dynamic complexity of emotional disorders (e.g., network science, dynamical systems, etc.) to promote more personalized and tailored interventions. In additional to the computational focus of my work, I also maintain active lines of research in affective science (i.e., delineating maladaptive emotion regulation components underlying anxiety and depression), mindfulness approaches to mental health, and elucidating mechanisms of empirically-supported treatments (e.g., CBT, mindfulness, etc.). These activities are complemented by my interests in philosophy of science. 

Research Interests

Dynamic Time-Series Approaches to Emotional Psychopathology using Network Science and Dynamical Systems Theory

Precision Medicine and Predictive Modelling for Emotional Disorders

Emotion Regulation and Mindfulness

Statistics and Computational Modeling of Psychopathology

Philosophy of Science and Psychopathology

Idiographic/Individual-Level Predictions

Selected Publications

Curtiss, J. E., Mischoulon, D., Fisher, L. B., Cusin, C., Fedor, S., Picard, R. W., & Pedrelli, P. (2023). Rising early warning signals in affect associated with future changes in depression: A dynamical systems approach. Psychological medicine53(7), 3124-3132.

Curtiss, J. E., Pinaire, M., Fulford, D., McNally, R. J., & Hofmann, S. G. (2022). Temporal and contemporaneous network structures of affect and physical activity in emotional disorders. Journal of Affective Disorders315, 139-147.

Curtiss, J. E., Bernstein, E. E., Wilhelm, S., & Phillips, K. A. (2023). Predictors of pharmacotherapy outcomes for body dysmorphic disorder: a machine learning approach. Psychological Medicine53(8), 3366-3376.

Google Scholar

https://scholar.google.com/citations?hl=en&user=qJdUF5EAAAAJ&view_op=list_works&gmla=AJ1KiT2n3Ocg-CdYGpZ3cN8vLSwMS-2zh3iZf2esjJsizuSvdSUxs7iye-S6yRWHOvFcz25D3ix9Yp2GtYast4Xd

Website

https://joshua-curtiss.github.io/