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Derailment of the affective system: Measurement, early detection, and underlying mechanisms
Throughout their life many individuals suffer from one or more episodes of a mood disorder (e.g., depression), which typically go with a derailment of the time dynamics of their affective system. This is often devastating for the individual and may come at a great cost for society. Accurate measurement of moment-to-moment affective dynamics, early detection of imminent derailments, and understanding the mechanisms and principles underlying them are thus of great scientific, clinical, and societal importance. This project proposes to achieve these aims in the following ways: First, we will upscale the quality of the measurement of affective dynamics in daily life by optimizing both what is being measured (via adaptive ambulatory self-reports as well as mobile sensing) and when this is done (by relying on principles of design of experiments). Second, within the powerful framework of statistical process control, we will build and validate novel methods for an online detection of early warning signs of affective derailment. Third, we will construct, test, and apply computational models that shed light on the mechanisms and principles governing the affective system and derailments of its dynamics.
Date:1 Oct 2019 → Today
Keywords:affective and mood disorders, ambulatory measurement, Experience Sampling Methods, affect, temporal dynamics, early warning signals, change point detection, computational affective models
Disciplines:Motivation and emotion, Behavioural sciences, Mathematical psychology, Psychometrics, Statistics and data analysis, Psychological assessment, Psychopathology