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.