Emotion differentiation refers to the tendency to label emotions in a granular way. While differentiation is an important individual difference in the context of psychological well-being, it is unknown how it fluctuates within individuals. Such a within-person measure is important, since it would allow the study of how changes in differentiation predict subsequent levels of other variables of interest. Here, we present a framework to study emotion differentiation at the within-person level by introducing a momentary emotion differentiation index. This index is directly derived from the classical emotion differentiation index, the intraclass correlation. We first give a theoretical derivation of this index. Next, using data from two experience sampling studies, we show how this new momentary index is related to other momentary indicators of well-being, and take the first steps in building its nomological network. A better understanding of within-person fluctuations in emotion differentiation will allow us to identify the causes and consequences of these fluctuations, and search for ways to teach individuals to increase their level of emotion differentiation.

This article reviews the Space-Time Budget method developed by Wikström and colleagues and particularly discusses its relevance for criminological research. The Space-Time Budget method is a data collection instrument aimed at recording, retrospectively, on an hour-by-hour basis, the whereabouts and activities of respondents during four days in the week before the interview. The method includes items about criminologically relevant events, such as offending and victimization. We demonstrate that the method can be very useful in criminology, because it enables the study of situational causes of crime and victimization, because it enables detailed measurement of theoretical concepts such as individual lifestyles and individual routine activities, and because it enables the study of adolescents' whereabouts, which extends the traditional focus on residential neighborhoods. The present article provides the historical background of the method, explains how the method can be applied, presents validation results based on data from 843 secondary school students in the Netherlands and describes the methods' strengths and weaknesses. Two case studies are summarized to illustrate the usefulness of the method in criminological research. The article concludes with some anticipated future developments and recommendations on further readings. To enable cross-national comparison of time use, Szalai and colleagues developed methods for sampling, interviewing, coding and data processing that were implemented in all twelve participating countries. These methods and instruments shaped most of the subsequent time use studies (Harvey and Pentland 1999: 6; Michelson 2005: 12).Time use studies have now appeared on a variety of topics and in a variety of fields. Recent overviews mention time use studies within economics, business administration, gerontology, urban planning, political science and occupational therapy, nursing and medicine, recreation and physical and health education, sociology, anthropology and psychology. Just to give a few examples: in economics, time use data is applied for investigating poverty (e.g., whether individuals have too many obligations to enjoy leisure) or the time spent on paid work relative to 'nonmarket-productive' time such as time spent on domestic activity, education or child care. Health studies and studies in gerontology apply time use data to investigate active and sedentary behavior and time use by older

To sample situations that are psychologically arousing in daily life, we implemented an experience sampling strategy in which 82 Dutch young adults (Mage = 20.73) were triggered based on random time intervals and based on physiological skin conductance scores across a period of 5 days. When triggered, participants had to fill in short surveys on affect, situational characteristics and event characteristics on their smartphone. We found theoretically expected relationships between the skin conductance signal on the one hand and self‐reported arousal and positive energy (e.g. energetic and enthusiastic) on the other hand, although effect sizes were small. Unexpectedly, none of the negative affective scales (i.e. irritation, anxiety, and negative valence) were predicted by skin conductance levels. Despite the (partial) validity of the signal, a simple algorithm that triggered the survey based on relative increases of skin conductance levels produced counterintuitive results due to a dependence between level and slope. Additional exploratory analyses highlighted other skin conductance signal characteristics (i.e. autocorrelation, number of peaks, and change points) that might be worth examining when designing future algorithms to sample arousing moments. Overall, our experiences highlight not only the promise but also the complexity of real‐time measurement of physiological processes in daily life. © 2020 The Authors. European Journal of Personality published by John Wiley & Sons Ltd on behalf of European Association of Personality Psychology

Emotion differentiation refers to the tendency to label emotions in a granular way. While differentiation is an important individual difference in the context of psychological well-being (Kashdan et al., 2015), it is unknown how it fluctuates within individuals. Such a within-person measure is important, since it would allow the study of how changes in differentiation predict subsequent levels of other variables of interest. Here, we present a framework to study emotion differentiation at the within-person level by introducing a momentary emotion differentiation index. This index is directly derived from the classical emotion differentiation index, the intra-class correlation. We first give a theoretical derivation of this index. Next, using data from two experience sampling studies, we show how this new momentary index is related to other momentary indicators of well-being, and take the first steps in building its nomological network. A better understanding of within-person fluctuations in emotion differentiation will allow us to identify the causes and consequences of these fluctuations, and search for ways to teach individuals to increase their level of emotion differentiation.

In the first week after the first COVID-19 patient was reported in the Netherlands, we conducted a pre-registered momentary assessment study (7 surveys per day, 50 participants, 7 days) to study the dynamic relationship between individuals’ occupation with and worries about COVID-19 in daily life, and the moderating role of neuroticism in this relationship. At the group level, higher scores on occupation and worry co-occurred, and occupation predicted worry one hour later, but not vice versa. There were substantial individual differences in the magnitudes and directions of the effects. For instance, occupation with COVID-19 was related to increases in worry for some but decreases in worry for others. Neuroticism did not predict any of these individual differences in the links between worry and occupation. This study suggests that it is important to go beyond group-level analyses and to account for individual differences in responses to COVID-19.