Transitions and Resilience in Ecological Momentary Assessment: A Multiple Single-Case Study.

Area of Science:

• Psychology
• Complexity Science
• Statistical Modeling

Background:

• Ecological momentary assessment (EMA) collects real-time data on affect, cognition, and behavior.
• Traditional statistical methods often treat non-stationarity and outlying values as data nuisances.

Purpose of the Study:

• To compare statistical and dynamic pattern perspectives on EMA data phenomena.
• To investigate the meaning of non-stationarity and outlying values in EMA.

Main Methods:

• A triangulation study analyzing EMA data from the Track your Mood study.
• Participants reported emotions and daily events over 60 days.
• Comparison of statistical and dynamic pattern approaches to data interpretation.

Main Results:

• Non-stationarity in EMA data correlated with transitions between dynamic patterns (e.g., mood shifts).
• Outlying values in EMA data were linked to recovery from perturbations (e.g., stressful events).

Conclusions:

• A dynamic pattern perspective enhances person-oriented EMA research by identifying clinically relevant phenomena.
• Integrating contextual and qualitative data is crucial for a comprehensive understanding of EMA findings.