APS
2026 APS Annual Convention
Beyond the Static: Mapping Mental Health through Innovations In Dynamic Time-Series Approaches
Mental health disorders are inherently dynamic with temporally evolving symptoms. Traditional research methods struggle to capture these fluctuations, limiting their ability to inform real-time, personalized treatments. This symposium presents innovative research applying state-of-the-art time-series and machine learning methodologies to attain deeper insights into the temporal patterns underlying mental health disorders
Chairs & Discussants
- Joshua CurtissChair
Northeastern University
Presentations
- Predicting the Peaks and Valleys: Personalized Affective Forecasting In Emotional DisordersShane Pracar
- The Emotional Core of Grief: Leveraging Intensive Longitudinal Data to Investigate the Nature, Dynamics, and Cognitive and Behavioral Correlates of Yearning and Emotional PainDonald Robinaugh
- The Influence of State Dynamics and Personality In Predicting Thought and Affect States with Intensive Longitudinal DataEric Andrews
- Back to the Basics: Limitations of Idiographic Machine Learning Forecasting In Mental Health DataSophie Engels
