Investigating dynamics in attentive and inattentive responding together with their contextual correlates using a novel mixture IRT model for intensive longitudinal data.

In ecological momentary assessment (EMA), respondents answer brief questionnaires about their current behaviours or experiences several times per day across multiple days. The frequent measurement enables a thorough grasp of the dynamics inherent in psychological constructs, but it also increases respondent burden. To lower this burden, respondents may engage in careless and insufficient effort responding (C/IER), leaving data contaminated with responses that do not reflect what researchers want to measure. We introduce a novel approach to investigating C/IER in EMA data. Our approach combines a confirmatory mixture item response theory model separating C/IER from attentive behaviour with latent Markov factor analysis. This enables gauging the occurrence of C/IER and studying transitions among states of different response behaviours including their contextual correlates. The approach can be implemented using R packages. An empirical application showcases the approach's efficacy in pinpointing C/IER instances and gaining insights into their underlying causes. We showcase that the approach identifies various C/IER response patterns but requires heterogeneous and negatively worded items to detect straightlining. In a simulation investigating robustness against unaccounted for changes in measurement models underlying attentive responses, the approach proved robust against heterogeneity in loading patterns but not against heterogeneity in factor structures. Extensions to accommodate the latter are discussed.