Research
The Idiographic Dynamics Lab at UC Berkeley engages in research at the individual level. Our group is currently interested in issues of Precision, Personalization, and Prediction in psychopathology and substance use.
Specifically, we are interested in extending the Precision Medicine paradigm to psychological and psychiatric domains—a Precision Behavioral Health model that complements biomedical approaches by leveraging behavioral data to customize and fine-tune behavioral interventions. We are interested in identifying actionable units of information at the behavioral level of analysis that will allow us to match patients, problems, and optimal interventions.
Additionally, we believe that the concept of personalization extends beyond treatment delivery and should encompass study design, data collection, and statistical analysis. Recent research in our lab has revealed marked heterogeneity in the temporal patterns, correlational structures, and predictive relationships in psychopathology and substance use.
Finally, given the heterogeneity in the timing and predictors of individual problems and behaviors, our group is currently working on methods for predicting individual behavior moment to moment, in order to identify when problems might occur. Building accurate prediction systems may allow researchers and clinicians to provide interventions when they are most needed (i.e. "just in time").
Prospective students interested in joining our lab should have a concentrated interest in idiographic science, personalization, prediction, and related issues.
Selected Publications:
2022
Song, J., Howe, E., Oltmanns, J. R., & Fisher, A. J. (2022). Examining the concurrent and predictive validity of single items in ecological momentary assessments. Assessment, 10731911221113563.
Howe, E. S., & Fisher, A. J. (2022). Identifying and predicting posttraumatic stress symptom states in adults with posttraumatic stress disorder. Journal of Traumatic Stress, 35(5), 1508-1520.
Fisher, A. J., Howe, E., & Zong, Z. Y. (2022). Unsupervised clustering of autonomic temporal networks in clinically distressed and psychologically healthy individuals. Behaviour Research and Therapy, 154, 104105.
Soyster, P. D., Ashlock, L., & Fisher, A. J. (2022). Pooled and person-specific machine learning models for predicting future alcohol consumption, craving, and wanting to drink: A demonstration of parallel utility. Psychology of Addictive Behaviors, 36(3), 296.
2021
Lazarus, G., & Fisher, A. J. (2021). Negative emotion differentiation predicts psychotherapy outcome: Preliminary findings. Frontiers in Psychology, 12, 689407.
Fisher, A. J., Song, J., & Soyster, P. D. (2021). Toward a systems‐based approach to understanding the role of the sympathetic nervous system in depression. World Psychiatry, 20(2), 295.
Lazarus, G., Song, J., Crawford, C. M., & Fisher, A. J. (2021). A close look at the role of time in affect dynamics research. Affect Dynamics, 95-116.
2020
Altman, A. D., Shapiro, L. A., & Fisher, A. J. (2020). Why does therapy work? An idiographic approach to explore mechanisms of change over the course of psychotherapy using digital assessments. Frontiers in Psychology, 782.
Fisher, A. J., & Bosley, H. G. (2020). Identifying the presence and timing of discrete mood states prior to therapy. Behaviour Research and Therapy, 128, 103596.
Reeves, J. W., & Fisher, A. J. (2020). An examination of idiographic networks of posttraumatic stress disorder symptoms. Journal of traumatic stress, 33(1), 84-95.
Howe, E., Bosley, H. G., & Fisher, A. J. (2020). Idiographic network analysis of discrete mood states prior to treatment. Counselling and Psychotherapy Research, 20(3), 470-478.
2019
Fisher, A.J., Bosley, H.G., Fernandez, K.C., Reeves, JW., Diamond, A.E., Soyster, P.D., & Barkin, J. (2019). Open trial of a personalized modular treatment for mood and anxiety. Behaviour Research and Therapy, 116, 69-79.
2018
Fisher, A.J.,Medaglia, J.D., & Jeronimus, B.F. (2018). Lack of Group-to-Individual Generalizability is a Threat to Human Subjects Research. Proceedings of the National Academy of Sciences.
2017
Fisher, A.J., Reeves, J.W., Lawyer, G., Medaglia, J.D., & Rubel, J.A. (2017). Exploring the Idiographic Dynamics of Mood and Anxiety with Network Analysis. Journal of Abnormal Psychology.
Fernandez, K.C., Fisher, A. J., & Chi, C. (2017). Development and Initial Implementation of the Dynamic Assessment Treatment Algorithm (DATA). PLoS ONE, 12(6): e0178806.
2016
Fisher, A.J., Reeves, J.W., & Chi, C. (2016). Dynamic RSA: Examining parasympathetic regulatory dynamics via vector-autoregressive modeling of time-varying RSA and heart period. Psychophysiology, 53, 1093-1099.
Fisher, A.J. & Boswell, J.F. (2016). Enhancing the Personalization of Psychotherapy with Dynamic Assessment and Modeling. Assessment, 23, 496-506.
2015
Fisher, A.J. (2015). Toward a dynamic model of psychological assessment: Implications for personalized care. Journal of Consulting and Clinical Psychology, 83, 825-836