Publication Date:
Author(s): Jojanneke A. Bastiaansen, Yoram K. Kunkels, Frank J. Blaauw, Steven M. Boker, Eva Ceulemans, Meng Chen, Meng Cheng, Sy-Miin Chow, Peter de Jonge, de Jonge, Peter, Peter de Jonge, Ando C. Emerencia, Sacha Epskamp, Aaron J. Fisher, Ellen L. Hamaker, Peter Kuppens, Wolfgang Lutz, M. Meyer, Robert Moulder, Zita Oravecz, Harriette Riese, Julian Rubel, Oisin Ryan, Michelle N. Servaas, Gustav Sjobeck, Evelien Snippe, Timothy Trull, Wolfgang Tschacher, van der Veen, Date C., Date C. van der Veen, Marieke Wichers, Phillip Wood, William Woods, Wright, Aidan G. C., Aidan G.C. Wright, Casper Albers, Laura Bringmann
Publisher: Elsevier Inc.
Publication Type: Academic Journal Article
Journal Title: Journal of Psychosomatic Research
Volume: 137
Page Range: 110211
Abstract:

Objective: One of the promises of the experience sampling methodology (ESM) is that a statistical analysis of an individual's emotions, cognitions and behaviors in everyday-life could be used to identify relevant treatment targets. A requisite for clinical implementation is that outcomes of such person-specific time-series analyses are not wholly contingent on the researcher performing them. Methods: To evaluate this, we crowdsourced the analysis of one individual patient's ESM data to 12 prominent research teams, asking them what symptom(s) they would advise the treating clinician to target in subsequent treatment. Results: Variation was evident at different stages of the analysis, from preprocessing steps (e.g., variable selection, clustering, handling of missing data) to the type of statistics and rationale for selecting targets. Most teams did include a type of vector autoregressive model, examining relations between symptoms over time. Although most teams were confident their selected targets would provide useful information to the clinician, not one recommendation was similar: both the number (0–16) and nature of selected targets varied widely. Conclusion: This study makes transparent that the selection of treatment targets based on personalized models using ESM data is currently highly conditional on subjective analytical choices and highlights key conceptual and methodological issues that need to be addressed in moving towards clinical implementation.