Affective structure, measurement invariance, and reliability across different experience sampling protocols

Chasing consistency: On the measurement error in self-reported affect in experiments

How feelings change over time is a central topic in emotion research. To study these affective fluctuations, researchers often ask participants to repeatedly indicate how they feel on a self-report rating scale. Despite widespread recognition that this kind of data is subject to measurement error, the extent of this error remains an open question. Complementing many daily-life studies, this study aimed to investigate this question in an experimental setting. In such a setting, multiple trials follow each other at a fast pace, forcing experimenters to use a limited number of questions to measure affect during each trial. A total of 1398 participants completed a probabilistic reward task in which they were unknowingly presented with the same string of outcomes multiple times throughout the study. This allowed us to assess the test-retest consistency of their affective responses to the rating scales under investigation. We then compared these consistencies across different types of rating scales in hopes of finding out whether a given type of scale led to a greater consistency of affective measurements. Overall, we found moderate to good consistency of the affective measurements. Surprisingly, however, we found no differences in consistency across rating scales, which suggests that the specific rating scale that is used does not influence the measurement consistency.

When Future Leads to a Moral Present: Future Self-Relatedness Predicts Moral Judgments and Behavior in Everyday Life

Future self-perceptions seem to promote far-sighted decisions in intertemporal choices. Previous work suggested that future self-relatedness, the extent to which we feel similar and connected to our future self, is associated with moral concerns. We aimed to extend these findings to everyday moral judgments and behavior using experience sampling methods. In addition, we assessed how moral foundation concerns mediate the relationship between future self-relatedness and moral behavior. Participants (N = 151) reported their state-levels of future self-relatedness, individualizing, and binding moral foundations and answered whether they performed a moral action five times a day for seven days. Within- and between-participants future self-relatedness predicted daily fluctuations in individualizing and binding moral foundations concerns. On the behavioral level, only within-participants future self-relatedness predicted individualizing moral actions with individualizing moral foundations mediating this effect. Our findings suggest that within- and between-person changes in future self-relatedness might be used to predict everyday moral concerns and behavior.

A scoping review of intensive longitudinal methods in informal caregivers of people with dementia

BACKGROUND

The daily life of informal caregivers assisting individuals with dementia widely varies throughout the day and week. As an answer, an increasing number of researchers have used intensive longitudinal methods (ILMs) such as diary studies, experience sampling methods, or ecological momentary assessment.

OBJECTIVES AND METHODS

The present scoping review aims at synthesizing the use of ILMs in informal dementia caregivers to clarify what is currently done and how, as well as what remains unaddressed.

RESULTS

The screening process identified 48 studies from 22 different datasets. Synthesis of these studies showed the diversity of devices and uses of ILMs in informal care, including the exploration of associations between variables or accompanying an intervention. ILMs showed the important variability of caregiving phenomena, as well as the important association of momentary stress and well-being. Gaps were nevertheless identified, such as transparency in the construction of the tool or the absence of focus on emotions and dyads.

CONCLUSIONS

For now, this field of research remains in its infancy and does not seem to have reached its full potential as it has in other fields. Nevertheless, it appears that ILMs are promising tools for informal dementia caregivers as they contribute to understanding the complexity of their daily life, with changing resources and challenges. Future directions include focusing more on (emotion) regulation, temporal lags, and the use of ILMs in interventional designs.

TRIAL REGISTRATION

The present review was registered on OSF (osf.io/b2qr4).

Is daily-life stress reactivity a measure of stress recovery? An investigation of laboratory and daily-life stress

Typical measures of laboratory reactivity (i.e. difference between control and stress) and recovery (i.e. difference between stress and post-stress) were compared with a conventional measure of daily-life reactivity, best known as event-related stress. Fifty-three healthy individuals between 19 and 35 years of age took part in a laboratory session where stress was induced using the repeated Montreal Imaging Stress Task and 8 days of experience sampling method. Measures of negative affect, heart rate (HR), HR variability, and skin conductance level were collected. Findings show no strong associations between laboratory and daily life measures with the exception of laboratory affective recovery and daily life reactivity. Findings and their implications are discussed.

Applying multiverse analysis to experience sampling data: Investigating whether preprocessing choices affect robustness of conclusions

The experience sampling method (ESM) has revolutionized our ability to conduct psychological research in the natural environment. However, researchers have a large degree of freedom when preprocessing ESM data, which may hinder scientific progress. This study illustrates the use of multiverse analyses regarding preprocessing choices related to data exclusion (i.e., based on various levels of compliance and exclusion of the first assessment day) and the calculation of constructs (i.e., composite scores calculated as the mean, median, or mode) by reanalyzing established group differences in negative affect, stress reactivity, and emotional inertia between individuals with and without psychosis. Data came from five studies and included 233 individuals with psychosis and 223 healthy individuals (in total, 26,892 longitudinal assessments). Preprocessing choices related to data exclusion did not affect conclusions. For both stress reactivity and emotional inertia of negative affect, group differences were affected when negative affect was calculated as the mean compared to the median or mode. Further analyses revealed that this could be attributed to considerable differences in the within- and between-factor structure of negative affect. While these findings show that observed differences in affective processes between individuals with and without psychosis are robust to preprocessing choices related to data exclusion, we found disagreement in conclusions between different central tendency measures. Safeguarding the validity of future experience sampling research, scholars are advised to use multiverse analysis to evaluate the robustness of their conclusions across different preprocessing scenarios.

Psychopathological networks: Theory, methods and practice

In recent years, network approaches to psychopathology have sparked much debate and have had a significant impact on how mental disorders are perceived in the field of clinical psychology. However, there are many important challenges in moving from theory to empirical research and clinical practice and vice versa. Therefore, in this article, we bring together different points of view on psychological networks by methodologists and clinicians to give a critical overview on these challenges, and to present an agenda for addressing these challenges. In contrast to previous reviews, we especially focus on methodological issues related to temporal networks. This includes topics such as selecting and assessing the quality of the nodes in the network, distinguishing between- and within-person effects in networks, relating items that are measured at different time scales, and dealing with changes in network structures. These issues are not only important for researchers using network models on empirical data, but also for clinicians, who are increasingly likely to encounter (person-specific) networks in the consulting room.