This paper is in the following e-collection/theme issue:

Electronic/Mobile Data Capture, Internet-based Survey & Research Methodology (832) mHealth for Data Collection and Research (955) Machine Learning (1465) Ecological Momentary Assessment (EMA) (311) Mobile Health (mhealth) (2941) Wearable Devices and Sensors (889)

Published on in Vol 24, No 4 (2022): April

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34015, first published .
Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment

Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment

Using Smartphone Sensor Paradata and Personalized Machine Learning Models to Infer Participants’ Well-being: Ecological Momentary Assessment

Authors of this article:

Alexander Hart1 Author Orcid Image ;   Dorota Reis1 Author Orcid Image ;   Elisabeth Prestele2 Author Orcid Image ;   Nicholas C Jacobson3 Author Orcid Image
Article Authors Cited by (9) Tweetations (4) Metrics

Alexander Hart   1 , MSc ;   Dorota Reis   1 , PhD ;   Elisabeth Prestele   2 , PhD ;   Nicholas C Jacobson   3 , PhD

1 Research Group Applied Statistical Modeling, Department of Psychology, Saarland University, Saarbrücken, Germany

2 Research Group Diagnostics, Differential and Personality Psychology, Methods and Evaluation, Department of Psychology, University of Koblenz-Landau, Landau, Germany

3 Center for Technology and Behavioral Health, Departments of Biomedical Data Science and Psychiatry, Geisel School of Medicine, Dartmouth College, Lebanon, NH, United States

Corresponding Author:

  • Alexander Hart, MSc
  • Research Group Applied Statistical Modeling
  • Department of Psychology
  • Saarland University
  • Campus A2 4
  • Saarbrücken, 66123
  • Germany
  • Phone: 49 6813023130
  • Email: hart.research@pm.me