Investigating self-reporting behavior in long-term studies

  • Authors:
  • Andreas Möller;Matthias Kranz;Barbara Schmid;Luis Roalter;Stefan Diewald

  • Affiliations:
  • Technische Universität München, Munich, Germany;Universität Passau, Passau, Germany;Technische Universität München, Munich, Germany;Technische Universität München, Munich, Germany;Technische Universität München, Munich, Germany

  • Venue:
  • Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
  • Year:
  • 2013

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Abstract

Self-reporting techniques, such as data logging or a diary, are frequently used in long-term studies, but prone to subjects' forgetfulness and other sources of inaccuracy. We conducted a six-week self-reporting study on smartphone usage in order to investigate the accuracy of self-reported information, and used logged data as ground truth to compare the subjects' reports against. Subjects never recorded more than 70% and, depending on the requested reporting interval, down to less than 40% of actual app usages. They significantly overestimated how long they used apps. While subjects forgot self-reports when no automatic reminders were sent, a high reporting frequency was perceived as uncomfortable and burdensome. Most significantly, self-reporting even changed the actual app usage of users and hence can lead to deceptive measures if a study relies on no other data sources. With this contribution, we provide empirical quantitative long-term data on the reliability of self-reported data collected with mobile devices. We aim to make researchers aware of the caveats of self-reporting and give recommendations for maximizing the reliability of results when conducting large-scale, long-term app usage studies.