Considering the very large number of studies that have applied ambulatory assessment (AA) in the last decade across diverse fields of research, knowledge about the effects that these design choices have on participants’ perceived burden, data quantity (i.e., compliance with the AA protocol), and data quality (e.g., within-person relationships between time-varying variables) is surprisingly restricted. The aim of the current research was to experimentally manipulate aspects of an AA study’s assessment intensity—sampling frequency (Study 1) and questionnaire length (Study 2)—and to investigate their impact on perceived burden, compliance, within-person variability, and within-person relationships between time-varying variables. In Study 1, students (n = 313) received either 3 or 9 questionnaires per day for the first 7 days of the study. In Study 2, students (n = 282) received either a 33- or 82-item questionnaire three times a day for 14 days. Within-person variability and within-person relationships were investigated with respect to momentary pleasant-unpleasant mood and state extraversion. The results of Study 1 showed that a higher sampling frequency increased perceived burden but did not affect the other aspects we investigated. In Study 2, longer questionnaire length did not affect perceived burden or compliance but yielded a smaller degree of within-person variability in momentary mood (but not in state extraversion) and a smaller within-person relationship between state extraversion and mood. Differences between Studies 1 and 2 with respect to the type of manipulation of assessment intensity are discussed.

As the number of studies using ambulatory assessment (AA) has been increasing across diverse fields of research, so has the necessity to identify potential threats to AA data quality such as careless responding. To date, careless responding has primarily been studied in cross-sectional surveys. The goal of the present research was to identify latent profiles of momentary careless responding on the occasion level and latent classes of individuals (who differ in the distribution of careless responding profiles across occasions) on the person level using multilevel latent class analysis (ML-LCA). We discuss which of the previously proposed indices seem promising for investigating careless responding in AA studies, and we show how ML-LCA can be applied to model careless responding in intensive longitudinal data. We used data from an AA study in which the sampling frequency (3 vs. 9 occasions per day, 7 days, n = 310 participants) was experimentally manipulated. We tested the effect of sampling frequency on careless responding using multigroup ML-LCA and investigated situational and respondent-level covariates. The results showed that four Level 1 profiles (“careful,” “slow,” and two types of “careless” responding) and four Level 2 classes (“careful,” “frequently careless,” and two types of “infrequently careless” respondents) could be identified. Sampling frequency did not have an effect on careless responding. On the person (but not the occasion) level, motivational variables were associated with careless responding. We hope that researchers might find the application of an ML-LCA approach useful to shed more light on factors influencing careless responding in AA studies.