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Combining ESM With Parallel Data

In the project Combining ESM data with parallel data with different sample frequencies, considerations for designing a study and preparing analysis we examine how to combine ESM data with parallel data sampled at a much higher sampling frequency, and what considerations ought to be taken into account while designing such a study. ESM studies are often complemented with parallel datasets like actigraphy or heart rate data to study the effect of mood variables on physiological variables and vice versa. We explore the questions these studies attempt to answer and examine the designs that would help answer each of these specific questions, including the design of the ESM study and parallel data collection. We also explore previous studies that utilized different types of parallel data in combination with ESM, and explore the specific research questions they addressed and the designs used to achieve these. Since it is not straightforward to combine data with multiple different sample frequencies, authors have to think ahead of their study design for which this paper supplies a generic step-by-step tool by providing suggestions and considerations.

Included authors (in alphabetical order):

  • Joana De Calheiros Velozo (KU Leuven)
  • Philippe A.E.G. Delespaul (Maastricht University)
  • Sandip V. George (UMC Groningen)
  • Jeroen G.V. Habets (Maastricht University)
  • Noëmi Hagemann (KU Leuven)
  • Sjoerd van Halem (Tilburg University)
  • Fleur G.L. Helmink (Erasmus Universiteit)
  • Christian E. Herff (Maastricht University)
  • Peter Kuppens (KU Leuven)
  • Olga Minaeva (UMC Groningen)
  • Koen J. Niemeijer (KU Leuven)
  • Harriëtte Riese (UMCG)
  • Aki Rintala (KU Leuven)