Time to get personal? The impact of researchers choices on the selection of treatment targets using the experience sampling methodology: The impact of researchers choices on the selection of treatment targets using the experience sampling methodology

Jojanneke A. Bastiaansen, Yoram K. Kunkels, Frank J. Blaauw, Steven M. Boker, Eva Ceulemans, Meng Chen, Sy-Miin Chow, Peter de Jonge, Ando C. Emerencia, Sacha Epskamp, Aaron J Fisher, Ellen L Hamaker, Peter Kuppens, Wolfgang Lutz, M Joseph Meyer, Robert Moulder, Zita Oravecz, Harriëtte Riese, Julian Rubel, Oisín RyanMichelle N. Servaas, Gustav Sjobeck, Evelien Snippe, Timothy J Trull, Wolfgang Tschacher, Date C. van der Veen, Marieke Wichers, Phillip K Wood, William C Woods, Aidan G C Wright, Casper J. Albers, Laura F. Bringmann*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

11 Citations (Scopus)
27 Downloads (Pure)

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.

Original languageEnglish
Article number110211
Number of pages14
JournalJournal of Psychosomatic Research
Volume137
Early online date5-Aug-2020
DOIs
Publication statusPublished - Oct-2020

Keywords

  • Time-series analysis
  • Electronic diary
  • Personalized medicine
  • Mental disorders
  • Psychological networks
  • Crowdsourcing science
  • MENTAL-HEALTH RESEARCH
  • DEPRESSION
  • INTERVENTIONS
  • PSYCHOTHERAPY
  • DYNAMICS
  • ANXIETY
  • LIFE

Cite this