Experience Sampling Methods (ESM) refers to methods used to repeatedly
gather self-report data from participants in the context of their daily
life. With advances in mobile technologies, this method has gained
increasing adoption within the field of social and health sciences.
However, the unique opportunities that ESM brings to the field do not go
without challenges. One such challenge, and a known source of invalidity in
self-report data, is careless responding or insufficient effort
responding. Although
there is a growing literature on techniques that detect this type of
responding in classic survey data (Curran, 2016; Meade & Craig, 2012), the
phenomenon is, to the best of our knowledge, not yet studied in the context
of ESM. Yet, availability of such methods could be highly instrumental in
increasing the data quality in this type of research. To fill this gap, we
both adapted known techniques for CR detection in survey data to the ESM
context, and developed novel techniques specifically for the ESM context,
based on response time and response content parameters. Next, in two
studies we evaluated the mutual interrelations between these techniques,
how they are predictive of actual (self-rated or instructed) careless
responding itself, and how accurate combining them can be for identifying
careless responses in the context of ESM research.
References
Curran, P. G. (2016). Methods for the Detection of Carelessly Invalid
Responses in Survey
Data. *Journal of Experimental Social Psychology*, *66*, 4-19.
Meade, A. W., & Craig, S. B. (2012). Identifying Careless Responses in
Survey Data.
*Psychological Methods*, *17*(3), 437.