Understanding Ecological-Momentary-Assessment Data: A Tutorial on Exploring Item Performance in Ecological-Momentary-Assessment Data

The use of ecological-momentary-assessment (EMA) data to study individuals in their everyday lives is popular in many areas of social and life sciences. At the same time, EMA data sets are complex, the psychometric properties of EMA items are often not investigated systematically, and scales are often neither standardized nor validated beyond their face validity. Here, we present different descriptive statistics and data-visualization techniques to increase the understanding of the performance of EMA items. We apply these techniques to a wide range of items used in a large EMA data set (599 participants, 360 time points) collected in the WARN-D study to investigate their distributions, contextual influences, change over time, sources of variability, and relationship with classical static measures of psychopathology. We discuss the theoretical and substantive implications of our findings and provide researchers with R code that they can adapt to their own EMA data, as well as literature recommendations for each topic. We hope to inspire more researchers to share in-depth descriptive summaries of their experience-sampling data such that the field can move forward in understanding the performance of EMA measures across contexts.