Data from ‘Critical Slowing Down as a Personalized Early Warning Signal for Depression’

Authors

  • Jolanda J Kossakowski Department of Psychology, University of Amsterdam, Amsterdam, https://orcid.org/0000-0002-6946-1732
  • Peter C Groot User Research Center, Department of Psychiatry and Psychology, Maastricht University Medical Centre, Maastricht,
  • Jonas M B Haslbeck Department of Psychology, University of Amsterdam, Amsterdam,
  • Denny Borsboom Department of Psychology, University of Amsterdam, Amsterdam,
  • Marieke Wichers University of Groningen, University Medical Center Groningen, Department of Psychiatry, Interdisciplinary Center Psychopathy and Emotion Regulation, Groningen,

DOI:

https://doi.org/10.5334/jopd.29

Keywords:

ESM, time-series, depression, critical transition, psychopathology

Abstract

We present a dataset of a single (N = 1) participant diagnosed with major depressive disorder, who completed 1478 measurements over the course of 239 consecutive days in 2012 and 2013. The experiment included a double-blind phase in which the dosage of anti-depressant medication was gradually reduced. The entire study looked at momentary affective states in daily life before, during, and after the double-blind phase. The items, which were asked ten times a day, cover topics like mood, physical condition and social contacts. Also, depressive symptoms were measured on a weekly basis using the Symptom Checklist Revised (SCL-90-R). The data are suitable for various time-series analyses and studies in complex dynamical systems.

Author Biography

Jolanda J Kossakowski, Department of Psychology, University of Amsterdam, Amsterdam,

PhD-student at the University of Amsterdam

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Published

2017-02-09

Issue

Vol. 5 No. 1 (2017)

Section

Data Papers

License

Copyright (c) 2017 The Author(s)

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