When “Gold Standard” Fails the Patient: Understanding How to Better Meet Our Patients’ Needs in Treatment
4 - (Sym 81) Behaviors Associated with Latent Mood States: Potential Clinical Utility of Person-specific Mood State Classification
Saturday, November 19, 2022
2:00 PM – 3:30 PM EST
Location: Broadhurst/Belasco, 5th Floor
Keywords: Psychotherapy Outcome, Change Process / Mechanisms, Recovery Recommended Readings: Demyttenaere, K., & Van Duppen, Z. (2019). The Impact of (the Concept of) Treatment-Resistant Depression: An Opinion Review. The International Journal of Neuropsychopharmacology, 22(2), 85–92. Fisher, A. J., & Boswell, J. F. (2016). Enhancing the personalization of psychotherapy with dynamic assessment and modeling. Assessment, 23(4), 496-506. Burchi, E., Hollander, E., & Pallanti, S. (2018). From treatment response to recovery: a realistic goal in OCD. International Journal of Neuropsychopharmacology, 21(11), 1007-1013.
Associate Professor, Department of Psychology University of California, Berkeley Berkeley, California
Fisher & Bosley (2020) recently published a novel approach to the identification of person-specific latent mood states by applying Gaussian finite mixture modelling (GFMM) idiographically to multivariate emotion time series. This approach classifies an individual’s experience into discrete mood states based on the unique combinations of emotions and individual experiences. However, whether these latent mood states are associated with observable differences in behavior remains an empirical question. We applied Fisher & Bosley’s idiographic GFMM to ecological momentary assessment (EMA) data collected from ten individuals with mood and anxiety disorder diagnoses who received treatment at a community clinic, and ran a series of regression models person-by-person to test whether the presence of each idiographic mood state was associated with five behavioral outcomes of relevance to mood and anxiety symptomatology (interpersonal conflict, procrastination, rumination, avoidance of people and activities). Across all ten participants, we found significant and class-specific associations between these behaviors and mood states identified by GFMM. The nature of each individual’s mood states, and the associations between mood states and behavior, were idiosyncratic. Findings from this case series bolster the potential clinical utility of Fisher & Bosley’s LPA approach by linking idiographic mood states to specific, differentiable behavioral outcomes. Implications for personalization of clinical practice are discussed, with an eye towards maximizing positive outcomes across a diverse range of clients.