Person-Related Selection Bias in Mobile Sensing Research: Robust Findings From Two Panel Studies.

In psychology, mobile sensing is increasingly used to record behavior in real-life situations. However, little is known about the selectivity of samples participating in these new data collection approaches and thus about potential risks to the validity of research findings. We therefore investigate...

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Publicado en:Journal of Personality & Social Psychology Vol. 130; no. 3; pp. 597 - 626
Autores principales: Schoedel, Ramona, Reiter, Thomas, Krämer, Michael D., Roos, Yannick, Bühner, Markus, Richter, David, Mehl, Matthias R., Wrzus, Cornelia
Formato: Artículo
Publicado: American Psychological Association Mar2026
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Mar2026
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      pub: American Psychological Association
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        atl: Person-Related Selection Bias in Mobile Sensing Research: Robust Findings From Two Panel Studies.
      aug:
        au:
          Schoedel, Ramona
          Reiter, Thomas
          Krämer, Michael D.
          Roos, Yannick
          Bühner, Markus
          Richter, David
          Mehl, Matthias R.
          Wrzus, Cornelia
        affil:
          Differential Psychology and Psychological Assessment, Charlotte Fresenius University
          Department of Psychology, Ludwig-Maximilians-Universität München
          Department of Psychology, University of Zurich
          Psychological Institute, Heidelberg University
          Department of Education and Psychology, Freie Universität Berlin
          SHARE BERLIN Institute GmbH, Berlin, Germany
          Department of Psychology, University of Arizona
          Network Aging Research, Heidelberg University
      su:
        Android (Operating system)
        Sociodemographic factors
        Personality
        Selection bias (Statistics)
        Nonresponse (Statistics)
        Panel analysis
        Mobile operating systems
        Wearable technology
        Acquisition of data
      sug:
        subj:
          Sociodemographic factors
          Personality
          Selection bias (Statistics)
          Nonresponse (Statistics)
          Panel analysis
          Mobile operating systems
          Wearable technology
          Acquisition of data
          Android (Operating system)
      keyword:
        adherence
        Big Five personality traits
        mobile sensing
        selection bias
        smartphone sensing
        adherence
        Big Five personality traits
        mobile sensing
        selection bias
        smartphone sensing
      ab: In psychology, mobile sensing is increasingly used to record behavior in real-life situations. However, little is known about the selectivity of samples participating in these new data collection approaches and thus about potential risks to the validity of research findings. We therefore investigated two potential sources of selection bias in smartphone-based data collections. Specifically, we examined whether smartphone system ownership (Android vs. iOS, i.e., platform-related differences) and willingness to participate (nonparticipation vs. intention to participate vs. actual participation, i.e., nonresponse error) are associated with sociodemographic, socioeconomic, and personality characteristics. Using two large-scale panel studies, we found replicable patterns for platform-related differences (N = 1,218 and N = 5,123) and nonresponse error (N = 1,673 and N = 2,337): The ownership of Android devices (in comparison to iOS devices) was associated with lower levels of education, income, and extraversion. The willingness to participate in mobile sensing studies was found to be higher among younger age groups, males, those with higher levels of openness to experience, and those with lower levels of neuroticism. Furthermore, different person characteristics played different roles at different stages of the recruitment process. Taken together, the results show that some selection bias in mobile sensing studies exists and that the effects were small to moderate in magnitude as well as comparable to selection bias for other, more common data collection approaches, such as online surveys.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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