The DYNAMIC Lab investigates emotional processes within and across individuals to understand the development, maintenance, and consequences of psychopathology using ecological momentary assessment, longitudinal tracking, and experimental methods. The lab also incorporates computational approaches, including natural language processing and deep learning applied to language and smartphone sensor data, to study emotional functioning and depression in real-world contexts. The lab aims to bridge affective science and clinical psychology by identifying everyday emotional processes that contribute to vulnerability and resilience in depression and inform prevention and intervention efforts. While much of their work focuses on adults, their collaborative portfolio spans the lifespan, including federally funded studies involving children, adolescents, and older adults.

• Lai, J., Eckland, N. S., & Thompson, R. J. (2026). When and why people do NOT regulate their emotion: Examining the reasons and contexts. Cognition and Emotion, 40(2), 301-315. https://doi.org/10.1080/02699931.2025.2504560
• Lai, J., Liu, D. Y., Eckland, N. S., Strube, M. J., & Thompson, R. J. (2026). A multilevel factor structure of emotion beliefs: Evidence for situational relevance and emotion structure beliefs. Emotion, 26(4), 949–961. https://doi.org/10.1037/emo0001620
• Liu, Y. D., Springstein, T., Tuck, A. B., English, T. & Thompson, R. J. (2023). Everyday emotion regulation goals, motives, and strategies in current and remitted major depressive disorder: An experience sampling study. Journal of Psychopathology and Clinical Science, 132(5), 594–609. https://doi.org/10.1037/abn0000831
• Liu, Y. D., Strube, M J, & Thompson, R. J. (2024). Do emotion regulation difficulties in depression extend to social context? Everyday interpersonal emotion regulation in current and remitted major depressive disorder. Journal of Psychopathology and Clinical Science, 133(1), 61-75. https://doi.org/10.1037/abn0000877
• Thompson, R.J., Bailen, N., & English, T. (2021). Everyday emotional experiences in Major Depressive Disorder in Remission: An experience sampling study. Clinical Psychological Science, 9(5), 866-878. https://doi.org/10.1177/2167702621992082
• Thompson, R.J., Liu, D. Y., Sudit, E., & Boden, M. T. (2021). Emotion differentiation in current and remitted Major Depressive Disorder. Frontiers in Psychology, 12, 685851 https://doi.org/10.3389/fpsyg.2021.685851
• Tuck, A. B., Tallion, G. A., & Thompson, R. J. (2026). Prohedonic emotion regulation goals in everyday life: How increasing positive affect and reducing negative affect relate to the emotion regulation process and depression. Affective Science.https://doi.org/10.1007/s42761-026-00375-8
• Tuck, A. B., & Thompson, R. J. (2024). The Social Media Use Scale: Development and validation. Assessment, 31(3), 617-636.https://doi.org/10.1177/10731911231173080
• Tuck, A. B., & Thompson, R. J. (2024). Types of social media use are differentially associated with trait and momentary affect. Emotion, 24(7), 1600–1611. https://doi.org/10.1037/emo0001379
• Tuck, A. B., Zhu, Y., & Thompson, R. J. (2026). Depressive symptoms are associated with linguistic features of negative but not positive autobiographical narratives. Affective Science. https://doi.org/10.1007/s42761-026-00395-4.
• Zhu, Y., Trent, K., Garcia, B., & Thompson, R. J. (2026). Language of perseverative thoughts predicts emotion regulation strategy choice. Affective Science, 7, 253-264. https://doi.org/10.1007/s42761-026-00357-w
• Zhu, Y., Yang, Y., & Thompson, R. J. (2026). Using transformer-based models to monitor and understand momentary affect intensity from smartphone sensors. [Manuscript in press]. JMIR mHealth and uHealth.