Emotion dynamics

A new sample-size planning approach for person-specific VAR(1) studies: Predictive accuracy analysis

Researchers increasingly study short-term dynamic processes that evolve within single individuals using N = 1 studies. The processes of interest are typically captured by fitting a VAR(1) model to the resulting data. A crucial question is how to perform sample-size planning and thus decide on the number of measurement occasions that are needed. The most popular approach is to perform a power analysis, which focuses on detecting the effects of interest. We argue that performing sample-size planning based on out-of-sample predictive accuracy yields additional important information regarding potential overfitting of the model. Predictive accuracy quantifies how well the estimated VAR(1) model will allow predicting unseen data from the same individual. We propose a new simulation-based sample-size planning method called predictive accuracy analysis (PAA), and an associated Shiny app. This approach makes use of a novel predictive accuracy metric that accounts for the multivariate nature of the prediction problem. We showcase how the values of the different VAR(1) model parameters impact power and predictive accuracy-based sample-size recommendations using simulated data sets and real data applications. The range of recommended sample sizes is smaller for predictive accuracy analysis than for power analysis.

From lab to life: Evaluating the reliability and validity of psychophysiological data from wearable devices in laboratory and ambulatory settings

Despite the increasing popularity of ambulatory assessment, the reliability and validity of psychophysiological signals from wearable devices is unproven in daily life settings. We evaluated the reliability and validity of physiological signals (electrocardiogram, ECG; photoplethysmography, PPG; electrodermal activity, EDA) collected from two wearable devices (Movisens EcgMove4 and Empatica E4) in the lab (N = 67) and daily life (N = 20) among adults aged 18-64 with Mindware as the laboratory gold standard. Results revealed that both wearable devices' valid data rates in daily life were lower than in the laboratory (Movisens ECG 82.94 vs. 93.10%, Empatica PPG 8.79 vs. 26.14%, and Empatica EDA 41.16 vs. 42.67%, respectively). The poor valid data rates of Empatica PPG signals in the laboratory could be partially attributed to participants' hand movements (r = - .27, p = .03). In laboratory settings, heart rate (HR) derived from both wearable devices exhibited higher concurrent validity than heart rate variability (HRV) metrics (ICCs 0.98-1.00 vs. 0.75-0.97). The number of skin conductance responses (SCRs) derived from Empatica showed higher concurrent validity than skin conductance level (SCL, ICCs 0.38 vs. 0.09). Movisens EcgMove4 provided more reliable and valid HRV measurements than Empatica E4 in both laboratory (split-half reliability: 0.95-0.99 vs. 0.85-0.98; concurrent validity: 0.95-1.00 vs. 0.75-0.98; valid data rate: 93.10 vs. 26.14%) and ambulatory settings (split-half reliability: 0.99-1.00 vs. 0.89-0.98; valid data rate: 82.94 vs. 8.79%). Although the reliability and validity of wearable devices are improving, findings suggest researchers should select devices that yield consistently robust and valid data for their measures of interest.

Cognitive control processes and emotion regulation in adolescence: Examining the impact of affective inhibition and heart-rate-variability on emotion regulation dynamics in daily life

Cognitive control processes likely influence the extent to which adolescents can successfully regulate their emotions. This study examined whether individual differences in affective inhibition and heart rate variability (HRV), as a peripheral index of cognitive control, moderated the association between momentary emotion regulation and negative affect (NA). Ecological Momentary Assessments (EMA) over 14 days were obtained in 235 adolescents (Mage = 13.48 years; 106 females). At each assessment, participants reported their current NA and the extent to which they used cognitive reappraisal and rumination. Moreover, at three time points (approximately 1 year, 6 months, and just before the EMA), affective inhibition was assessed using an affective go/no-go task and HRV was recorded at rest. Results indicate that adolescents with lower affective inhibition reported lower average levels of daily rumination. However, affective inhibition did not moderate the association between either daily cognitive reappraisal or rumination and momentary NA. Consistent with hypotheses, the association between momentary rumination and NA was weaker in adolescents showing higher levels of resting HRV. Overall, findings may underscore the importance of interventions targeting HRV as a malleable factor for enhancing adolescents' affective well-being.

Neuroticism is Associated With Greater Affective Variability at High Levels of Momentary Affective Well-Being, but With Lower Affective Variability at Low Levels of Momentary Affective Well-Being

OBJECTIVE

Research challenged the notion that neuroticism correlates with affective variability, suggesting that it may result from statistical artifacts due to the non-normal distribution of negative affect. We aim to advance this line of research by (a) introducing affect balance as a normally distributed measure of affective well-being and (b) examining current affect balance as a moderator of the relationship between neuroticism and affect balance variability.

METHOD

We meta-analyzed the results of 14 ambulatory assessment datasets (N = 2389 participants, N = 174,423 observations).

RESULTS

We found that while the associations between the mean and affective variability were large for negative affect, they were much smaller for affect balance. Moreover, the association between neuroticism and variability in negative affect was very small, yet medium-sized for affect balance. Importantly, the latter association depended on current affect levels: Participants high relative to low in neuroticism showed stronger subsequent fluctuations in affect balance when currently feeling better than usual, but weaker subsequent fluctuations in (and thus more persistent) affect balance when currently feeling worse than usual.

CONCLUSION

Increased variability should not be seen as a bad sign but may be a sign that an affective system is changing, which may be adaptive or maladaptive for an individual, depending on the initial state of the system.

In the Mood: How Sexual Desire Predicts and is Predicted by Romantic Partners' Mood

The association between mood and sexual desire has been the object of significant scientific and public interest. How mood shapes and is shaped by sexual desire is typically studied within one and the same individual, yet sexual desire is often experienced in the context of a romantic relationship. To obtain a more complete picture of the relation between mood and sexual desire, we examined the temporal interplay between mood and sexual desire both within and between partners in a romantic relationship. Using data from an experience sampling study involving both partners of mixed-gender romantic couples (N = 188; Mage = 26.34, SDage = 5.33), we investigated how each partner's mood (in terms of positive and negative affect) predicted their own sexual desire as well as that of their partner and vice versa. Results of both concurrent and temporal analyses confirmed bidirectional associations between mood and sexual desire both within and between partners, such that (1) both a person's own and their partner's positive mood predicted an increase in sexual desire, and a person's own and their partner's negative mood predicted a decrease in sexual desire. In addition, (2) both a person's own and their partner's sexual desire predicted an increase in positive mood, and a person's own and their partner's sexual desire predicted a decrease in negative mood. Only a few gender differences were found. The results underscore how sexual desire can predict and be predicted by both romantic partners' mood, highlighting the need for interactional models of sexual desire.

Intraindividual variability in post-stroke cognition and its relationship with activities of daily living and social functioning: an ecological momentary assessment approach

INTRODUCTION

Ecological momentary assessment (EMA) is a methodological approach to studying intraindividual variation over time. This study aimed to use EMA to determine the variability of cognition in individuals with chronic stroke, identify the latent classes of cognitive variability, and examine any differences in daily activities, social functioning, and neuropsychological performance between these latent classes.

METHODS

Participants (N = 202) with mild-to-moderate stroke and over 3-month post-stroke completed a study protocol, including smartphone-based EMA and two lab visits. Participants responded to five EMA surveys daily for 14 days to assess cognition. They completed patient-reported measures and neuropsychological assessments during lab visits. Using latent class analysis, we derived four indicators to quantify cognitive variability and identified latent classes among participants. We used ANOVA and Chi-square to test differences between these latent classes in daily activities, social functioning, and neuropsychological performance.

RESULTS

The latent class analysis converged on a three-class model. The moderate and high variability classes demonstrated significantly greater problems in daily activities and social functioning than the low class. They had significantly higher proportions of participants with problems in daily activities and social functioning than the low class. Neuropsychological performance was not statistically different between the three classes, although a trend approaching statistically significant difference was observed in working memory and executive function domains.

DISCUSSION

EMA could capture intraindividual cognitive variability in stroke survivors. It offers a new approach to understanding the impact and mechanism of post-stroke cognitive problems in daily life and identifying individuals benefiting from self-regulation interventions.

Understanding the Sociocultural Dynamics of Loneliness in Southern Spanish Youth

Loneliness among young people has been increasing in recent years and is considered a major public health problem. This article delves into the sociocultural dynamics that favour the experiences of loneliness. For this purpose, 40 students between 19 and 24 years of age were interviewed using the photo elicitation interview (PEI) strategy. The results show a gradual normalization of the experience of loneliness and an effort to become accustomed to it. Virtual relationships and isolation linked to the COVID-19 pandemic are considered the two factors that have most enabled a climate prone to loneliness. Young people identify a few elements that feed social loneliness, such as an understanding of instrumental relationships, a scarcity of intimate relationships, a demand for hyperconnectivity, a fantasy of independence and a culture of positivity that hinders the establishment of quality social ties. Faced with hostile relational conditions, youth are sent into a cycle of loneliness. The greater the distrust of the environment is, the greater the defensive reactions and social distancing, and the greater the search for nearby spaces of refuge, security and shelter. Social withdrawal makes in-person relationships difficult and strengthens the need to isolate and become accustomed to loneliness.

Network state dynamics underpin basal craving in a transdiagnostic population

Emerging fMRI methods quantifying brain dynamics present an opportunity to capture how fluctuations in brain responses give rise to individual variations in affective and motivation states. Although the experience and regulation of affective states affect psychopathology, their underlying time-varying brain responses remain unclear. Here, we present a novel framework to identify network states matched to an affective experience and examine how the dynamic engagement of these network states contributes to this experience. We apply this framework to investigate network state dynamics underlying basal craving, an affective experience with important clinical implications. In a transdiagnostic sample of healthy controls and individuals diagnosed with or at risk for craving-related disorders (total N = 252), we utilized connectome-based predictive modeling (CPM) to identify brain networks predictive of basal craving. An edge-centric timeseries approach was leveraged to quantify the moment-to-moment engagement of the craving-positive and craving-negative subnetworks during independent scan runs. We found that dynamic markers of network engagement, namely more persistence in a craving-positive network state and less dwelling in a craving-negative network state, characterized individuals with higher craving. We replicated the latter results in a separate dataset, incorporating distinct participants (N = 173) and experimental stimuli. The associations between basal craving and network state dynamics were consistently observed even when craving-predictive networks were defined in the replication dataset. These robust findings suggest that network state dynamics underpin individual differences in basal craving. Our framework additionally presents a new avenue to explore how the moment-to-moment engagement of behaviorally meaningful network states supports our affective experiences.

Threat sensitivity in emotion dynamics: Negativity effects and sex differences

Evolutionary theorizing has given rise to the idea that responding to any particular threat may be more mandatory than responding to any particular reward. The present three experiments (total N = 375) sought to provide support for this perspective in an emotion dynamics task in which participants continuously rated their affective state in response to appetitive (reward-related) versus aversive (threat-related) images. Even when equating images for arousal and extremity, several negativity effects (e.g., steeper reactivity slopes in response to aversive images) were found. These negativity effects can serve as an experimental model of threat sensitivity, which should predispose some individuals, more than others, to symptoms related to fear and anxiety. This point was made with respect to sex differences, given that women (relative to men) are diagnosed with anxiety disorders at higher rates. Sex differences were pronounced and extensions of this work, both basic and applied, are proposed.

Emotional state dynamics impacts temporal memory

Emotional fluctuations are ubiquitous in everyday life, but precisely how they sculpt the temporal organisation of memories remains unclear. Here, we designed a novel task - the Emotion Boundary Task - wherein participants viewed sequences of negative and neutral images surrounded by a colour border. We manipulated perceptual context (border colour), emotional-picture valence, as well as the direction of emotional-valence shifts (i.e., shifts from neutral-to-negative and negative-to-neutral events) to create events with a shared perceptual and/or emotional context. We measured memory for temporal order and temporal distances for images processed within and across events. Negative images processed within events were remembered as closer in time compared to neutral ones. In contrast, temporal distances were remembered as longer for images spanning neutral-to-negative shifts - suggesting temporal dilation in memory with the onset of a negative event following a previously-neutral state. The extent of negative-picture induced temporal dilation in memory correlated with dispositional negativity across individuals. Lastly, temporal order memory was enhanced for recently-presented negative (versus neutral) images. These findings suggest that emotional-state dynamics matters when considering emotion-temporal memory interactions: While persistent negative events may compress subjectively remembered time, dynamic shifts from neutral-to-negative events produce temporal dilation in memory, with implications for adaptive emotional functioning.

Trait Hedonism and the Distribution of Savoring and Positive Emotion States in Everyday Life

The present study aimed at (1) identifying the emotion regulation processes that can explain the trait hedonism positive emotions relationship, and (2) determining whether this relationship varies according to which part of the distribution of positive emotions is considered. To this end, the intensity of the positive emotions felt by 84 adult participants, and the intensity of their engagement in savoring, were assessed twice a day over a month period, using an Experience Sampling Method. Participants' distributions of these variables were then related to their level of trait hedonism, assessed with a common questionnaire. Results suggested that, as expected, the trait hedonism positive emotions relationship varied according to which part of the distribution of positive emotions was considered. In their worst times (i.e., first centiles of each individual's distribution), individuals with low versus high trait hedonism differed very little from each other. By contrast, in more favorable times (i.e., following centiles), individuals with high levels of trait hedonism experienced more intense positive emotions than individuals with low levels of trait hedonism. This phenomenon was mediated by individuals' engagement in savoring. These results are discussed in light of current theories on emotion dynamics.

Attuned to the Flux of Life: Relations Between Ability Emotional Intelligence and Emotional Reactivity

The field of ability-related emotional intelligence (ability EI) could benefit from new perspectives concerning dynamic operations. According to a recent perspective, variations in ability EI are likely to be linked to variations in skills related to evaluation. This perspective contends, perhaps counterintuitively, that higher levels of ability EI are likely to be linked to higher levels of emotional reactivity, defined in terms of stronger event-emotion relationships. Two studies (total N = 245) pursue such ideas in the context of multilevel models involving event valence and emotional experience. Variations in ability EI modulated event-emotion relationships in the context of laboratory inductions involving hypothetical events (Study 1), affective images varying in valence (Study 1), and with respect to naturally occurring variations in positive and negative daily events (Study 2), such that higher levels of ability EI were linked to stronger event-emotion relationships, regardless of whether events and emotions were positive or negative in valence. These results provide new evidence for recent theorizing concerning ability EI while speaking to functional versus dysfunctional perspectives on emotional reactivity.

Idiographic bidirectional associations of stressfulness of events and negative affect in daily life as indicators for mental health: An experience sampling study

Evidence suggests that complex micro-dynamics occurring in daily life underly the development of mental distress. We aimed to (1) study the cross-lagged association between stressful events and negative affect (NA), (2) show that there is substantial between-person variability in idiographic associations and (3) show that idiographic associations are indicative of mental health. Experience sampling study assessing perceived stressfulness of events (PSE) and NA four times per day for 2 weeks in a non-clinical convenience sample (N = 70, mean age = 22.9, 61% female, 69% German). Bivariate vector autoregressive model implemented in dynamic structural equation modelling to model the associations between stressful events and NA and obtain idiographic associations. Stressfulness of events and NA were significantly reciprocally associated. Autocorrelations and cross-lagged associations from PSE to NA showed substantial variability and were significantly related with trait measures of depression, anxiety, well-being, and perceived stress. Contrary to expectations, cross-lagged associations from NA to stressfulness of events were not related to trait mental health. The approach outlined in this article is useful for studying idiographic dynamics in daily life. The findings increase our understanding of micro-dynamics underlying mental health and individual differences in these processes.

Temporal dynamics of positive emotion regulation: insights from facial electromyography

Introduction

Emotion regulation (ER) is a complex process that manifests gradually over time. This study investigated the temporal dynamics of ER in modifying positive emotions in terms of both negative affect (NA) and positive affect (PA) dimensions.

Methods

After participants had been exposed to pleasant pictures for 8,000 ms, they received instructions to either continue viewing the picture (no regulation) or reappraise it with a neutral meaning (neutralize goal) or negative meaning (transform goal) for another 8,000 ms. We obtained corrugator supercilii and zygomaticus major electromyography (EMG) as objective measures of NA and PA.

Results

For the no-regulation condition, upon instruction onset, we observed maintained low levels of corrugator and high levels of zygomaticus EMG reactivity, indicating sustained PA activation. Compared to the no-regulation condition, for the neutralize goal, we observed no change in corrugator reactivity, which remained at a low level, while zygomaticus reduction started at 1,000 ms after instruction onset, indicating decreased PA and generation of a neutral emotional state. For the transform goal, we observed corrugator increase and zygomaticus decrease both starting at 1,500 ms after instruction onset and co-existing throughout the regulation period. These results indicate increased NA and decreased PA, relating to generation of a negative emotional state. The transform goal differed from the neutralize goal in terms of corrugator increase starting at 2,500 ms after instruction onset. Albeit simultaneous onset of changes on corrugator and zygomaticus reactivity under the transform goal, model-fitting analyses indicated that the best-fitting trajectory was one that first emphasized PA reduction until, at 3,000 ms, it turned into primary NA increase.

Discussion

These distinct temporal patterns highlight the possibility of effecting one-dimensional PA change with the neutralize goal and sequential two-dimensional change (first decreasing PA, then increasing NA) with the transform goal. This research sheds light on the time course of emotional change brought about by different regulatory goals.

A Comparison of Affective-Cognitive States in Daily Life Between Emerging Adults With and Without Past-Year Nonsuicidal Self-Injury

Although the literature suggests trait-like differences in affective and cognitive vulnerabilities between individuals with and without a history of nonsuicidal self-injury (NSSI), little is known about how these dispositional differences are experienced in the natural environment. The present study compares the intensity, inertia, interaction, and variability of affective (negative and positive affect) and cognitive states (rumination, self-criticism) in the everyday lives of individuals who do and do not engage in NSSI. Using experience sampling methodology (ESM), 60 emerging adults (ages = 18-22 years) with and without past-year NSSI (equally distributed) completed eight questionnaires per day for 12 days (in total, 96 questionnaires per participant), resulting in 4,587 assessments (median compliance = 83.3%; IQR = 71.9-91.7). In a dynamic structural equation modeling framework, dynamic parameters (i.e., mean intensity, carryover effects, spillover effects, and within-person variability) were evaluated using multilevel vector autoregressive models. Emerging adults who engage in NSSI experience higher intensity and greater variability of negative affect, rumination, and self-criticism, whereas those who do not engage in NSSI experience higher intensity and lower variability of positive affect. In addition, past-year NSSI predicted stronger affective-cognitive interactions over time, with stronger spillover effects of negative and positive affect on subsequent rumination and self-criticism in individuals who engage in NSSI. Depressive symptoms and trait levels of emotion dysregulation and self-criticism partially negated these differences. Our findings provide evidence that emerging adults who self-injure experience more negative affective-cognitive states in daily life and point to the potential relevance of boosting positive emotions to buffer negative cognitions.

Daily life affective dynamics as transdiagnostic predictors of mental health symptoms: An ecological momentary assessment study

BACKGROUND

Affective dynamics have been identified as a correlate of a broad span of mental health issues, making them key candidate transdiagnostic factors. However, there remains a lack of knowledge about which aspects of affective dynamics - especially as they manifest in the course of daily life - relate to a general risk for mental health issues versus specific symptoms.

METHODS

We leverage an ecological momentary assessment (EMA) study design with four measures per day over a two-week period to explore how negative affect levels, inertia, lability, and reactivity to provocation and stress in the course of daily life relate to mental health symptoms in young adults (n = 256) in the domains of anxiety, depression, psychosis-like symptoms, behaviour problems, suicidality, and substance use.

RESULTS

Dynamic structural equation modelling (DSEM) suggested that negative affect levels in daily life were associated with depression, anxiety, indirect and proactive aggression, psychosis, anxiety, and self-injury; negative affective lability was associated with depression, physical aggression, reactive aggression, suicidal ideation, and ADHD symptoms; negative affective inertia was associated with depression, anxiety, physical aggression, and cannabis use; and emotional reactivity to provocation was related to physical aggression.

LIMITATIONS

The cross-sectional design, the limited span of mental health issues included, and the convenience nature and small size of the sample are limitations.

CONCLUSIONS

Findings suggest that a subset of mental health symptoms have shared negative affective dynamics patterns. Longitudinal research is needed to rigorously examine the directionality of the effects underlying the association between affective dynamics and mental health issues.

Attachment insecurities, emotion dynamics and stress in intimate relationships during the transition to parenthood

BACKGROUND

In intimate relationships, which are characterized by emotional interdependence, partners act as attachment figures which serve emotion regulation functions. The experience of emotions as well as the strategies that partners use to regulate them and to respond to relational experiences, especially during stressful periods, differ greatly according to their attachment orientation. An important aspect in emotion dynamics is emotional inertia, which reflects the degree to which a person's current affective state is resistant to change on a moment-to-moment basis. Inertia has been related to maladaptive emotion regulation strategies, like suppression and rumination, preferentially used by highly anxious and avoidant individuals. The aim of this study is to examine associations between attachment orientations and reports on the experience of positive and negative affect, and their dynamics in daily life across the transition to parenthood.

METHODS

Longitudinal data from a sample of 152 mixed-gender couples collected across the transition to parenthood was analyzed. We predicted that individuals with a more insecure attachment would report more negative and less positive affect, and that their emotional experience would be more resistant to change over time. We explored effects when participants reported feeling stressed.

RESULTS

The data suggested that attachment anxiety was associated with less positive and more negative affect and that attachment avoidance was associated with more positive affect. Anxious individuals showed lower emotional inertia and not higher as we expected. Reported stress for anxious and avoidant individuals was significantly associated with more negative but not less positive affect.

CONCLUSIONS

Results are discussed in the light of their impact on couples during stressful periods. Differences between anxiety and avoidance are found, emphasizing the importance of attachment insecurities on the experience of emotion. Furthermore, our findings on momentary fluctuating affect offer complementary insight into the emotional functioning of individuals with different attachment orientations.

Daily associations between global self-esteem and self-concept clarity and their relationships with subjective well-being in a sample of adult workers

OBJECTIVES

The present pre-registered study examined the reciprocal day-to-day associations between global self-esteem and self-concept clarity and their incremental validity with respect to daily life satisfaction, positive affect, and negative affect.

METHODS

We used intensive longitudinal data from 153 adult workers (45.1% women), over a period of 31 days. Data were analyzed using dynamic structural equation modeling.

RESULTS

Results attested higher global self-esteem and self-concept clarity mean levels for older vs. younger participants, and lower global self-esteem and self-concept clarity variability for older vs. younger participants. Furthermore, global self-esteem and self-concept clarity were correlated at a cross-sectional daily level, yet only self-concept clarity states positively predicted subsequent global self-esteem states, while global self-esteem states did not predict subsequent self-concept clarity states. Daily global self-esteem and daily self-concept clarity further predicted subsequent daily higher life satisfaction and positive affect, respectively.

CONCLUSION

Overall, our findings shed light on the short-term relationships linking global self-esteem and self-concept clarity, pointing to their discriminant validity in predicting individuals' subjective well-being.

Automating the analysis of facial emotion expression dynamics: A computational framework and application in psychotic disorders

Facial emotion expressions play a central role in interpersonal interactions; these displays are used to predict and influence the behavior of others. Despite their importance, quantifying and analyzing the dynamics of brief facial emotion expressions remains an understudied methodological challenge. Here, we present a method that leverages machine learning and network modeling to assess the dynamics of facial expressions. Using video recordings of clinical interviews, we demonstrate the utility of this approach in a sample of 96 people diagnosed with psychotic disorders and 116 never-psychotic adults. Participants diagnosed with schizophrenia tended to move from neutral expressions to uncommon expressions (e.g., fear, surprise), whereas participants diagnosed with other psychoses (e.g., mood disorders with psychosis) moved toward expressions of sadness. This method has broad applications to the study of normal and altered expressions of emotion and can be integrated with telemedicine to improve psychiatric assessment and treatment.

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.

Emotional state dynamics impacts temporal memory

Emotional fluctuations are ubiquitous in everyday life, but precisely how they sculpt the temporal organization of memories remains unclear. Here, we designed a novel task-the Emotion Boundary Task-wherein participants viewed sequences of negative and neutral images surrounded by a color border. We manipulated perceptual context (border color), emotional valence, as well as the direction of emotional-valence shifts (i.e., shifts from neutral-to-negative and negative-to-neutral events) to create encoding events comprised of image sequences with a shared perceptual and/or emotional context. We measured memory for temporal order and subjectively remembered temporal distances for images processed within and across events. Negative images processed within events were remembered as closer in time compared to neutral ones. In contrast, temporal distance was remembered as longer for images spanning neutral-to-negative shifts-suggesting temporal dilation in memory with the onset of a negative event following a previously-neutral state. The extent of this negative-picture induced temporal dilation in memory correlated with dispositional negativity across individuals. Lastly, temporal order memory was enhanced for recently presented negative (compared to neutral) images. These findings suggest that emotional-state dynamics matters when considering emotion-temporal memory interactions: While persistent negative events may compress subjectively remembered time, dynamic shifts from neutral to negative events produce temporal dilation in memory, which may be relevant for adaptive emotional functioning.

When eco-anger (but not eco-anxiety nor eco-sadness) makes you change! A temporal network approach to the emotional experience of climate change

Research on the emotional experience of climate change has become a hot topic. Yet uncertainties remain regarding the interplay between climate change-related emotions (i.e., eco-anxiety, eco-anger, eco-sadness), general emotions (i.e., regardless of climate change), and pro-environmental behaviors. Most previous research has focused on cross-sectional studies, and eco-emotions in everyday life have seldom been considered. In this preregistered study, 102 participants from the general population rated their eco-emotions (i.e., eco-anxiety, eco-anger, eco-sadness), general emotions (i.e., anxiety, anger, sadness), and pro-environmental intentions and behaviors daily over a 60-day period. Using a multilevel vector autoregressive approach, we computed three network models representing temporal (i.e., from one time-point to the next), contemporaneous (i.e., during the same time-frame), and between-subject (i.e., similar to cross-sectional approach) associations between variables. Results show that eco-anger was the only predictor of pro-environmental intentions and behaviors over time. At the contemporaneous level, the momentary experience of each eco-emotion was associated with the momentary emotional experience of the corresponding general emotion, indicating the distinctiveness of each eco-emotion and the correspondence between its experience and that of its general, non-climate-related emotion. Overall, our findings 1) emphasize the driving role of eco-anger in prompting pro-environmental behaviors over time, 2) suggest a functional and experiential distinction between eco-emotions, and 3) provide data-driven clues for the field's larger quest to establish the scientific foundations of eco-emotions.

Individual-Specific Animated Profiles of Mental Health

How important is the timing of the pretreatment evaluation? If we consider mental health to be a relatively fixed condition, the specific timing (e.g., day, hour) of the evaluation is immaterial and often determined on the basis of technical considerations. Indeed, the fundamental assumption underlying the vast majority of psychotherapy research and practice is that mental health is a state that can be captured in a one-dimensional snapshot. If this fundamental assumption, underlying 80 years of empirical research and practice, is incorrect, it may help explain why for decades psychotherapy failed to rise above the 50% efficacy rate in the treatment of mental-health disorders, especially depression, a heterogeneous disorder and the leading cause of disability worldwide. Based on recent studies suggesting within-individual dynamics, this article proposes that mental health and its underlying therapeutic mechanisms have underlying intrinsic dynamics that manifest across dimensions. Computational psychotherapy is needed to develop individual-specific pretreatment animated profiles of mental health. Such individual-specific animated profiles are expected to improve the ability to select the optimal treatment for each patient, devise adequate treatment plans, and adjust them on the basis of ongoing evaluations of mental-health dynamics, creating a new understanding of therapeutic change as a transition toward a more adaptive animated profile.

Childhood abuse and neglect and profiles of adult emotion dynamics

Childhood maltreatment (CM) is experienced by ∼40% of all children at major personal and societal costs. The divergent associations between emotional, physical, and sexual abuse or neglect in childhood and differences in adult emotional functioning and regulation were examined in terms of daily emotion intensity, variability, instability, inertia, and diversity, reported over 30 days by 290 Dutch aged 19-73. Participants described their abuse/neglect experiences retrospectively using the Childhood Trauma Questionnaire (CTQ). Dissecting CM effects on adult emotion dynamics may inform theories on the ontogenesis and functioning of emotions, on effects of abuse and neglect, to better understand (dys)functional emotional development, and to prevent their adverse sequelae. Structural equation models (SEM) showed that most types of CM were associated with specific patterns of emotion dynamics, and only emotional abuse had no unique effects on the emotional dynamic indices. Emotional neglect was associated with most measures of emotion dynamics (i.e., less intense, variable, unstable, and diverse emotions). Sexual abuse associated with increases and physical neglect decreases in negative affect variability and instability. Physical abuse was associated with inertia but with a small effect size. Social contact frequency did not mediate much of the relationship between CM types and emotion dynamics.

Physiological Dysregulation in Children With and Without Externalizing Difficulties: Novel Insights From Intensive Longitudinal Data

Extant research on physiological dysregulation in children has focused on point-in-time measures and absolute mean levels of physiology. However, these methods do not capture dynamic fluctuations in physiology that characterize dysregulation. In the present work, we aimed to assess whether physiological dysregulation as captured by fluctuations rather than mean levels would differentiate between children with and without clinically elevated levels of externalizing behavior. As an exploratory approach, we examined fluctuations in children's physiological responses (i.e., root mean square of successive differences [RMSSD] in beat-to-beat heart rate intervals) to social transgression scenarios across 15 short-term measurement occasions (5-second bins). Controlling for mean RMSSD, as well as emotional and cognitive correlates of externalizing behavior (i.e., sympathy and inhibitory control), children with externalizing difficulties exhibited greater within-person fluctuations in RMSSD (i.e., physiological dysregulation) compared to children without externalizing difficulties. The present findings provide preliminary support for using intensive longitudinal data comprised of short-term physiological measurements and point to the centrality of within-child physiological variability as a marker of dysregulation, particularly amongst children with externalizing disorders for whom self-regulation is a core challenge.

A Cross-Sectional Association Between Screen-Based Sedentary Behavior and Anxiety in Academic College Students: Mediating Role of Negative Emotions and Moderating Role of Emotion Regulation

Purpose

The study aims to explore the relationship and potential mechanisms between screen time and anxiety and have a clear understanding of the role of negative emotions and emotion regulation, thus providing guidance for Chinese college students to improve mental health.

Methods

We conducted a questionnaire survey by selecting 1721 academic college students from 6 colleges and universities in 5 provinces in China, and the data were analyzed through the Process program of SPSS for mediating effect and moderating effect.

Results

There is a significant positive relationship between screen time and anxiety, negative emotions play a mediating role between the two (indirect effect = 0.32, p < 0.001), mediating effect accounts for 59.88% of the total effect, and emotion regulation regulates the direct relationship between screen time and anxiety (interaction effect = 0.027, p < 0.001).

Conclusion

This study sheds light on the potential mechanisms by which screen time affects anxiety in academic college students, providing a fresh perspective on anxiety reduction. Screen time positively affects anxiety levels, where negative emotions have a mediating role and emotion regulation has a moderating role. In the future, we can control screen ++time, increase physical activities, reduce negative emotions, and improve the emotional regulation ability to relieve anxiety, so as to improve the mental health of academic college students, and expect to have a positive impact on future learning, life, and planning.

Network state dynamics underpin craving in a transdiagnostic population

Emerging fMRI brain dynamic methods present a unique opportunity to capture how brain region interactions across time give rise to evolving affective and motivational states. As the unfolding experience and regulation of affective states affect psychopathology and well-being, it is important to elucidate their underlying time-varying brain responses. Here, we developed a novel framework to identify network states specific to an affective state of interest and examine how their instantaneous engagement contributed to its experience. This framework investigated network state dynamics underlying craving, a clinically meaningful and changeable state. In a transdiagnostic sample of healthy controls and individuals diagnosed with or at risk for craving-related disorders (N=252), we utilized connectome-based predictive modeling (CPM) to identify craving-predictive edges. An edge-centric timeseries approach was leveraged to quantify the instantaneous engagement of the craving-positive and craving-negative networks during independent scan runs. Individuals with higher craving persisted longer in a craving-positive network state while dwelling less in a craving-negative network state. We replicated the latter results externally in an independent group of healthy controls and individuals with alcohol use disorder exposed to different stimuli during the scan (N=173). The associations between craving and network state dynamics can still be consistently observed even when craving-predictive edges were instead identified in the replication dataset. These robust findings suggest that variations in craving-specific network state recruitment underpin individual differences in craving. Our framework additionally presents a new avenue to explore how the moment-to-moment engagement of behaviorally meaningful network states supports our changing affective experiences.

Combining experience sampling with temporal network analysis to understand inertia of negative emotion in dysphoria

BACKGROUND

Emotional inertia refers to the resistance to update or change an emotional state and is a hallmark of maladaptive emotional dynamics in psychopathology. Little is known, however, about the role of emotion regulation in negative emotional inertia in dysphoria. The current study aimed to explore the association between inertia of discrete negative emotions, and emotion-specific emotion regulation strategy selection use and efficacy in dysphoria.

METHODS

The Center for Epidemiologic Studies Depression Scale (CESD) was used to divide university students into a dysphoria (N = 65) and non-dysphoria control (N = 62) group. Using an experience sampling approach delivered via a smartphone app, participants were queried semi-randomly regarding negative emotions and emotion regulation strategies 10 times a day for 7 consecutive days. Temporal network analysis was employed to estimate autoregressive connections for each discrete negative emotion (inertia of negative emotion) and the bridge connections between negative emotion and emotion regulation clusters.

RESULTS

Participants with dysphoria showed stronger inertia for anger and sadness in the context of the use of emotion-specific regulation strategies. Specifically, individuals with dysphoria displaying greater inertia of anger were more likely to ruminate about the past to cope with anger, and to ruminate on the past and future when experiencing sadness.

LIMITATIONS

Lack of a clinical depression patient group for comparison.

CONCLUSIONS

Our findings suggest an inflexibility to adaptively shift attention from discrete negative emotions in dysphoria and provide important insights for development of interventions to support wellbeing in this population.

Unveiling the dynamics of emotions in society through an analysis of online social network conversations

Social networks can provide insights into the emotions expressed by a society. However, the dynamic nature of emotions presents a significant challenge for policymakers, politicians, and communication professionals who seek to understand and respond to changes in emotions over time. To address this challenge, this paper investigates the frequency, duration, and transition of 24 distinct emotions over a 2-year period, analyzing more than 5 million tweets. The study shows that emotions with lower valence but higher dominance and/or arousal are more prevalent in online social networks. Emotions with higher valence and arousal tend to last longer, while dominant emotions tend to have shorter durations. Emotions occupying the conversations predominantly inhibit others with similar valence and dominance, and higher arousal. Over a month, emotions with similar valences tend to prevail in online social network conversations.

Experimental evidence that browsing for activewear lowers explicit body image attitudes and implicit self-esteem in women

Online apparel shopping is popular amongst women and offers salient visual information for making body image and self-worth judgements. Apparel segments which emphasize the value of women's bodies are particularly effective for eliciting low body image and self-worth. Across two studies, we investigated the association between self-reported and experimental online activewear exposure on women's self-worth, body image, appearance attitudes, mood and gaze behavior. In Study 1, participants (N = 399) completed a survey collecting their online apparel shopping habits, body appreciation, self-esteem, appearance comparison tendencies and self-objectification attitudes. Activewear was the second-most popular apparel segment amongst women (after casualwear) and weekly activewear browse time was positively correlated with appearance comparison tendencies, desires to be muscular/athletic and body shame. In Study 2, participants (N = 126) were randomly allocated to browse an activewear, casualwear or homewares website and completed pre and post measures of mood, body image, implicit self-esteem and body gaze behavior. In the activewear condition, there was a significant reduction in positive body image and implicit self-esteem scores. There were no experimental effects for body gaze behavior. These findings illustrate that apparel choices have value for understanding the aetiology of maladaptive body image attitudes and low self-esteem in women.

Emotion dynamics and somatic symptoms in everyday life: Ecological momentary assessment in somatic symptom disorder and healthy controls

OBJECTIVE

Negative affectivity (NA) is associated with the emergence and persistence of physical symptoms with unclear organic pathology. This study investigated the temporal dynamics of NA and somatic symptom burden using ecological momentary assessment (EMA) in adults with somatic symptom disorder (SSD) and healthy control participants (HC).

METHODS

Participants underwent a seven-day, smartphone-based EMA, with 6 randomly-stratified time points per day. NA was assessed using a five-item short form of the Positive and Negative Affectivity Scale (PANAS) and somatic symptom burden with two self-constructed items. 22 persons with SSD and 20 HCs were included in multilevel analyses.

RESULTS

Within-person analyses showed a significantly stronger (positive) association of concurrent NA with somatic symptom burden in participants with SSD than in HCs, β = 0.15, SE = 0.04, p = .001. Time-lagged analyses demonstrated that, across groups, NA at a previous time point t-1 significantly predicted somatic symptom burden at the subsequent timepoint t, β = 0.09, SE = 0.03, p = .005, but not in the other direction (somatic symptom burdent-1→ NAt, β = 0.01, SE = 0.04, p = .79). Between-person analyses showed that both inertia (i.e., persistence of negative affective states), d = 0.74, and instability (i.e., magnitude of moment-to-moment fluctuations), d = 0.76 of NA were significantly higher in participants with SSD than in HCs.

CONCLUSIONS

Our findings sustain the idea of (negative) affect-driven modulation in somatic signal processing and suggest that interoceptive and emotional differentiation training can advance the psychotherapeutic treatment of SSD.

Towards PPG-based anger detection for emotion regulation

BACKGROUND

Anger dyscontrol is a common issue after traumatic brain injury (TBI). With the growth of wearable physiological sensors, there is new potential to facilitate the rehabilitation of such anger in the context of daily life. This potential, however, depends on how well physiological markers can distinguish changing emotional states and for such markers to generalize to real-world settings. Our study explores how wearable photoplethysmography (PPG), one of the most widely available physiological sensors, could be used detect anger within a heterogeneous population.

METHODS

This study collected the TRIEP (Toronto Rehabilitation Institute Emotion-Physiology) dataset, which comprised of 32 individuals (10 TBI), exposed to a variety of elicitation material (film, pictures, self-statements, personal recall), over two day sessions. This complex dataset allowed for exploration into how the emotion-PPG relationship varied over changes in individuals, endogenous/exogenous drivers of emotion, and day-to-day differences. A multi-stage analysis was conducted looking at: (1) times-series visual clustering, (2) discriminative time-interval features of anger, and (3) out-of-sample anger classification.

RESULTS

Characteristics of PPG are largely dominated by inter-subject (between individuals) differences first, then intra-subject (day-to-day) changes, before differentiation into emotion. Both TBI and non-TBI individuals showed evidence of linear separable features that could differentiate anger from non-anger classes within time-interval analysis. However, what is more challenging is that these separable features for anger have various degrees of stability across individuals and days.

CONCLUSION

This work highlights how there are contextual, non-stationary challenges to the emotion-physiology relationship that must be accounted for before emotion regulation technology can perform in real-world scenarios. It also affirms the need for a larger breadth of emotional sampling when building classification models.

The Exponentially Weighted Moving Average Procedure for Detecting Changes in Intensive Longitudinal Data in Psychological Research in Real-Time: A Tutorial Showcasing Potential Applications

Affect, behavior, and severity of psychopathological symptoms do not remain static throughout the life of an individual, but rather they change over time. Since the rise of the smartphone, longitudinal data can be obtained at higher frequencies than ever before, providing new opportunities for investigating these person-specific changes in real-time. Since 2019, researchers have started using the exponentially weighted moving average (EWMA) procedure, as a statistically sound method to reach this goal. Real-time, person-specific change detection could allow (a) researchers to adapt assessment intensity and strategy when a change occurs to obtain the most useful data at the most useful time and (b) clinicians to provide care to patients during periods in which this is most needed. The current paper provides a tutorial on how to use the EWMA procedure in psychology, as well as demonstrates its added value in a range of potential applications.

Inferential Emotion Tracking reveals impaired context-based emotion processing in individuals with high Autism Quotient scores

Emotion perception is essential for successful social interactions and maintaining long-term relationships with friends and family. Individuals with autism spectrum disorder (ASD) experience social communication deficits and have reported difficulties in facial expression recognition. However, emotion recognition depends on more than just processing face expression; context is critically important to correctly infer the emotions of others. Whether context-based emotion processing is impacted in those with Autism remains unclear. Here, we used a recently developed context-based emotion perception task, called Inferential Emotion Tracking (IET), and investigated whether individuals who scored high on the Autism Spectrum Quotient (AQ) had deficits in context-based emotion perception. Using 34 videos (including Hollywood movies, home videos, and documentaries), we tested 102 participants as they continuously tracked the affect (valence and arousal) of a blurred-out, invisible character. We found that individual differences in Autism Quotient scores were more strongly correlated with IET task accuracy than they are with traditional face emotion perception tasks. This correlation remained significant even when controlling for potential covarying factors, general intelligence, and performance on traditional face perception tasks. These findings suggest that individuals with ASD may have impaired perception of contextual information, it reveals the importance of developing ecologically relevant emotion perception tasks in order to better assess and treat ASD, and it provides a new direction for further research on context-based emotion perception deficits in ASD.

Increased affective reactivity among depressed individuals can be explained by floor effects: An experience sampling study

Experience sampling studies into daily-life affective reactivity indicate that depressed individuals react more strongly to both positive and negative stimuli than non-depressed individuals, particularly on negative affect (NA). Given the different mean levels of both positive affect (PA) and NA between patients and controls, such findings may be influenced by floor/ceiling effects, leading to violations of the normality and homoscedasticity assumptions underlying the used statistical models. Affect distributions in prior studies suggest that this may have particularly influenced NA-reactivity findings. Here, we investigated the influence of floor/ceiling effects on the observed PA- and NA-reactivity to both positive and negative events. Data came from 346 depressed, non-depressed, and remitted participants from the Netherlands Study of Depression and Anxiety (NESDA). In PA-reactivity analyses, no floor/ceiling effects and assumption violations were observed, and PA-reactivity to positive events, but not negative events, was significantly increased in the depressed and remitted groups versus the non-depressed group. However, NA-scores exhibited a floor effect in the non-depressed group and naively estimated models violated model assumptions. When these violations were accounted for in subsequent analyses, group differences in NA-reactivity that had been present in the naive models were no longer observed. In conclusion, we found increased PA-reactivity to positive events but no evidence of increased NA-reactivity in depressed individuals when accounting for violations of assumptions. The results indicate that affective-reactivity results are very sensitive to modeling choices and that previously observed increased NA-reactivity in depressed individuals may (partially) reflect unaddressed assumption violations resulting from floor effects in NA.

Capturing the Dynamics of the Social Environment Through Experience Sampling Methods, Passive Sensing, and Egocentric Networks: Scoping Review

BACKGROUND

Social interactions are important for well-being, and therefore, researchers are increasingly attempting to capture people's social environment. Many different disciplines have developed tools to measure the social environment, which can be highly variable over time. The experience sampling method (ESM) is often used in psychology to study the dynamics within a person and the social environment. In addition, passive sensing is often used to capture social behavior via sensors from smartphones or other wearable devices. Furthermore, sociologists use egocentric networks to track how social relationships are changing. Each of these methods is likely to tap into different but important parts of people's social environment. Thus far, the development and implementation of these methods have occurred mostly separately from each other.

OBJECTIVE

Our aim was to synthesize the literature on how these methods are currently used to capture the changing social environment in relation to well-being and assess how to best combine these methods to study well-being.

METHODS

We conducted a scoping review according to the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines.

RESULTS

We included 275 studies. In total, 3 important points follow from our review. First, each method captures a different but important part of the social environment at a different temporal resolution. Second, measures are rarely validated (>70% of ESM studies and 50% of passive sensing studies were not validated), which undermines the robustness of the conclusions drawn. Third, a combination of methods is currently lacking (only 15/275, 5.5% of the studies combined ESM and passive sensing, and no studies combined all 3 methods) but is essential in understanding well-being.

CONCLUSIONS

We highlight that the practice of using poorly validated measures hampers progress in understanding the relationship between the changing social environment and well-being. We conclude that different methods should be combined more often to reduce the participants' burden and form a holistic perspective on the social environment.

Changes in children's anger, sadness, and persistence across blocked goals: Implications for self-regulation

The current study took a person-centered approach to examine the heterogeneity of changes in children's emotions and persistence during a goal-blocking task and examined how different profiles of emotions and persistence related to children's self-regulation. Children's anger, sadness, and persistence were rated in a goal-blocking task in toddlerhood (T1; N = 140, 72 boys, M_age  = 2.67 years, 90.7% White) and preschool (T2). Children's self-regulation, specifically sustained attention and engagement, was assessed at T1, T2, and early school-age (T3) from 2005 to 2012. Growth mixture modeling revealed two classes of children at T1 and three classes at T2 with different patterns of anger, sadness, and persistence. Children's classification at T2, but not T1, significantly predicted their sustained attention and engagement both concurrently and longitudinally.

Lonely Today, Lonely Tomorrow: Temporal Dynamics of Loneliness in Everyday Life and its Associations With Psychopathological Symptoms

Although theory emphasizes that loneliness fluctuates in everyday life, most previous studies focused on the general and stable tendency of feeling lonely. In the present study, we used daily diary data collected over two 4-week periods ( N1 = 3,309; N2 = 907) to examine different indicators of temporal dynamics of loneliness in everyday life and compare them with temporal dynamics of positive and negative affect. Moreover, we examined associations between temporal dynamics of loneliness and psychopathological symptoms (i.e., stress, anxiety, depression). We found large similarities in the variability, instability, and inertia of loneliness and affect. Moreover, all indicators of temporal dynamics of loneliness were related to psychopathological symptoms. However, these indicators had little added value above the average state and trait level of loneliness in predicting psychopathology. We discuss the potential of assessing the short-term dynamics of loneliness for the early detection of mental health issues.

Charting everyday activities in later life: Study protocol of the mobility, activity, and social interactions study (MOASIS)

Prominent theories of aging emphasize the importance of resource allocation processes as a means to maintain functional ability, well-being and quality of life. Little is known about which activities and what activity patterns actually characterize the daily lives of healthy older adults in key domains of functioning, including the spatial, physical, social, and cognitive domains. This study aims to gain a comprehensive understanding of daily activities of community-dwelling older adults over an extended period of time and across a diverse range of activity domains, and to examine associations between daily activities, health and well-being at the within- and between-person levels. It also aims to examine contextual correlates of the relations between daily activities, health, and well-being. At its core, this ambulatory assessment (AA) study with a sample of 150 community-dwelling older adults aged 65 to 91 years measured spatial, physical, social, and cognitive activities across 30 days using a custom-built mobile sensor ("uTrail"), including GPS, accelerometer, and audio recording. In addition, during the first 15 days, self-reports of daily activities, psychological correlates, contexts, and cognitive performance in an ambulatory working memory task were assessed 7 times per day using smartphones. Surrounding the ambulatory assessment period, participants completed an initial baseline assessment including a telephone survey, web-based questionnaires, and a laboratory-based cognitive and physical testing session. They also participated in an intermediate laboratory session in the laboratory at half-time of the 30-day ambulatory assessment period, and finally returned to the laboratory for a posttest assessment. In sum, this is the first study which combines multi-domain activity sensing and self-report ambulatory assessment methods to observe daily life activities as indicators of functional ability in healthy older adults unfolding over an extended period (i.e., 1 month). It offers a unique opportunity to describe and understand the diverse individual real-life functional ability profiles characterizing later life.

Tracking perceived stress, anxiety, and depression in daily life: a double-downward spiral process

Introduction

Previous studies using retrospective questionnaires have suggested a complex relationship between perceived stress and related negative emotions and emphasized their importance in mental health. However, how daily perceived stress, anxiety, and depression interact dynamically in a natural context remains largely unexplored.

Methods

This study conducted a longitudinal survey that applied experience sampling methodology to data from 141 Chinese college students (58% women, mean age = 20.1 ± 1.63 years).

Results

The hierarchical linear models confirmed that daily perceived stress and negative emotions (i.e., perceived depression and anxiety) could reciprocally reinforce one another with the characteristic dynamics of a cognitive-emotional downward spiral. Additionally, anxiety and depression could further circularly aggravate each other imminently. These two intertwined downward-spiral processes constitute a double-downward-spiral model.

Discussion

The findings contribute to a better understanding of the interactive mechanisms underlying perceived stress and its related negative emotions in everyday life and highlight the significance of early emotion regulation and stress relief in healthy people.

Measuring affect dynamics: An empirical framework

A fast-growing body of evidence from experience sampling studies suggests that affect dynamics are associated with well-being and health. But heterogeneity in experience sampling approaches impedes reproducibility and scientific progress. Leveraging a large dataset of 7016 individuals, each providing over 50 affect reports, we introduce an empirically derived framework to help researchers design well-powered and efficient experience sampling studies. Our research reveals three general principles. First, a sample of 200 participants and 20 observations per person yields sufficient power to detect medium-sized associations for most affect dynamic measures. Second, for trait- and time-independent variability measures of affect (e.g., SD), distant sampling study designs (i.e., a few daily measurements spread out over several weeks) lead to more accurate estimates than close sampling study designs (i.e., many daily measurements concentrated over a few days), although differences in accuracy across sampling methods were inconsistent and of little practical significance for temporally dependent affect dynamic measures (i.e., RMSSD, autocorrelation coefficient, TKEO, and PAC). Third, across all affect dynamics measures, sampling exclusively on specific days or time windows leads to little to no improvement over sampling at random times. Because the ideal sampling approach varies for each affect dynamics measure, we provide a companion R package, an online calculator ( https://sergiopirla.shinyapps.io/powerADapp ), and a series of benchmark effect sizes to help researchers address three fundamental hows of experience sampling: How many participants to recruit? How often to solicit them? And for how long?

The link between cognitive and affective empathy and interpersonal emotion regulation direction and strategies

Interpersonal emotion regulation (ER) refers to the different processes aimed at changing the emotional states of others. Some authors have speculated about the pivotal role of empathy for interpersonal ER to happen. However, the very limited empirical evidence suggests that only cognitive empathy as opposed to affective empathy may be a necessary antecedent. As previous research only considered interpersonal affect improvement and showed mixed evidence for the regulation strategies, we aimed to address this gap in the current research. To that aim, 374 adults (M = 30.3 years, 249 female) reported their tendency to engage in cognitive (perspective-taking) and affective empathy (empathic concern and personal distress) as well as their tendency to improve and worsen others' mood, and to use different regulation strategies (situation modification, attention deployment, cognitive change, and modulation of the emotional response) to change others' feelings. Results of the regression analyses showed that while affect improvement was not significantly predicted by any of the empathy variables, affect worsening was positively predicted by personal distress. Concerning the regulation strategies, while cognitive change and situation modification were positively predicted by personal distress, attention deployment was positively predicted by perspective-taking. Overall, the obtained results highlight the need to further investigate the link between empathy and ER and to carefully consider the methods selected for that purpose.

Dynamics of daily positive and negative affect and relations to anxiety and depression symptoms in a transdiagnostic clinical sample

BACKGROUND

Despite interest in transdiagnostic dimensional approaches to psychopathology, little is known about the dynamic interplay of affecting and internalizing symptoms that cut across diverse mental health disorders. We examined within-person reciprocal effects of negative and positive affect (NA, PA) and symptoms (depression and anxiety), and their between-person associations with affective dynamics (i.e., affect inertia).

METHODS

Individuals currently receiving treatment for psychological disorders (N = 776) completed daily assessments of affect and symptoms across 14 treatment days (average). We used dynamic structural equation modeling to examine daily affect-symptom dynamics.

RESULTS

Within-person results indicated NA-symptom reciprocal effects; PA only predicted subsequent depression symptoms. After accounting for changes in mean symptoms and affect over time, NA-anxiety and PA-depression relations remained particularly robust. Between-person correlations indicated NA inertia was positively associated with NA-symptom effects; PA inertia was negatively associated with PA-symptoms effects.

CONCLUSIONS

Results suggest that transdiagnostic affective treatment approaches may be more useful for reducing internalizing symptoms by decreasing NA compared to increasing PA. Individual differences in resistance to shifting out of affective states (i.e., high NA vs. PA inertia) may be a useful marker for developing tailored interventions.

The Relation of Mood and Sexual Desire: An Experience Sampling Perspective on the Dual Control Model

We investigated the effect of fluctuations in negative and positive affect on momentary sexual motivation in a sample of women and men in a steady relationship (n = 133). Sexual motivation was regarded as the aggregate of sexual desire, subjective sexual arousal and openness to sexual contact. Experience sampling methodology was used to collect up to 70 measurements per participant over a period of seven consecutive days of sexual motivation, and negative and positive affect. Using multilevel analysis, we investigated cross-level interactions between affect and trait measures as specified in the dual control model (DCM). This model postulates sexually excitatory and inhibitory mechanisms as relatively independent systems that together can explain individual differences in sexual motivation and behavior. Results implicated that any intensification of feelings, positive or negative, was associated with a momentary increase in sexual motivation for participants more prone to sexual excitation. In the lagged analysis, higher preceding negative affect, measured 1-2 h earlier, forecasted an increase in current sexual motivation for participants more prone to sexual excitation. The lagged analysis included the autoregressive effect or inertia of sexual motivation. Inertia reflects the extent to which sexual motivation lingers and persists at similar levels. Our findings showed that sexual motivation levels persisted less in individuals with higher sexual inhibition proneness due to threat of performance failure. This study demonstrated how experience sampling methodology can be used to extend research on associations between mood and sexual motivation and implicates that DCM factors moderate these associations.

Controllability of Structural Brain Networks and the Waxing and Waning of Negative Affect in Daily Life

Background

The waxing and waning of negative affect in daily life is normative, reflecting an adaptive capacity to respond flexibly to changing circumstances. However, understanding of the brain structure correlates of affective variability in naturalistic settings has been limited. Using network control theory, we examine facets of brain structure that may enable negative affect variability in daily life.

Methods

We used diffusion-weighted imaging data from 95 young adults (age [in years]: mean = 20.19, SD = 1.80; 56 women) to construct structural connectivity networks that map white matter fiber connections between 200 cortical and 14 subcortical regions. We applied network control theory to these structural networks to estimate the degree to which each brain region's pattern of structural connectivity facilitates the spread of activity to other brain systems. We examined how the average controllability of functional brain systems relates to negative affect variability, computed by taking the standard deviation of negative affect self-reports collected via smartphone-based experience sampling twice per day over 28 days as participants went about their daily lives.

Results

We found that high average controllability of the cingulo-insular system is associated with increased negative affect variability. We also found that greater negative affect variability is related to the presence of more depressive symptoms, yet average controllability of the cingulo-insular system was not associated with depressive symptoms.

Conclusions

Our results highlight the role that brain structure plays in affective dynamics as observed in the context of daily life, suggesting that average controllability of the cingulo-insular system promotes normative negative affect variability.

Pinpointing affective disturbances in psychosis: A comparison of temporal affect dynamics in individuals with psychotic disorders, individuals with attenuated psychotic symptoms, and clinical and healthy controls

Affective disturbances in psychosis are well-documented but our understanding of their phenotypic nature in everyday life remains limited. Filling this gap could advance mechanistic models of the affective pathway to psychosis and pave the ground for new research avenues. Therefore, this study focused on temporal affect dynamics in psychosis, i.e., the patterns with which affect fluctuates over time. We applied experience-sampling with nine assessments per day over one week in participants with psychotic disorders (PSY), participants with attenuated psychotic symptoms (AS), clinical controls with obsessive compulsive disorders (OCD) and healthy controls (HC; total N = 139) to assess whether in PSY and AS, dynamics in affective valence and arousal are characterized by higher instability (i.e., extreme and frequent moment-to-moment fluctuations of affect intensities), higher affective variability (i.e., larger range of affect intensities), or lower inertia (i.e., higher frequency of affective changes), compared to the clinical and healthy control samples. Mixed-model ANOVAs revealed higher instability in both PSY and OCD compared to HC, but no significant differences for variability and inertia. AS had an intermediate position and did not differ significantly from any other group. We found evidence for small to medium effect sizes for the influence of mean affect levels on the dynamic indicators. Our findings indicate that individuals with psychotic disorders have increased affective instability and that this could be a transdiagnostic phenomenon. Zooming in on the variability and inertia components did not confer additional benefits. Emotion-focused interventions for psychosis should focus on reducing frequent and extreme affective fluctuations.

Stimulus-Driven Affective Change: Evaluating Computational Models of Affect Dynamics in Conjunction with Input

The way in which emotional experiences change over time can be studied through the use of computational models. An important question with regard to such models is which characteristics of the data a model should account for in order to adequately describe these data. Recently, attention has been drawn on the potential importance of nonlinearity as a characteristic of affect dynamics. However, this conclusion was reached through the use of experience sampling data in which no information was available about the context in which affect was measured. However, affective stimuli may induce some or all of the observed nonlinearity. This raises the question of whether computational models of affect dynamics should account for nonlinearity, or whether they just need to account for the affective stimuli a person encounters. To investigate this question, we used a probabilistic reward task in which participants either won or lost money at each trial. A number of plausible ways in which the experimental stimuli played a role were considered and applied to the nonlinear Affective Ising Model (AIM) and the linear Bounded Ornstein-Uhlenbeck (BOU) model. In order to reach a conclusion, the relative and absolute performance of these models were assessed. Results suggest that some of the observed nonlinearity could indeed be attributed to the experimental stimuli. However, not all nonlinearity was accounted for by these stimuli, suggesting that nonlinearity may present an inherent feature of affect dynamics. As such, nonlinearity should ideally be accounted for in the computational models of affect dynamics.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42761-022-00118-5.

How Stable, Really? Traditional and Nonlinear Dynamics Approaches to Studying Temporal Fluctuations in Personality and Affect

A pair of quantitative case studies is presented to demonstrate how different approaches to quantifying temporal variability in ratings of traits and affect can provide rich information for personality researchers. Data are presented and analyzed from two college students who completed an Ecological Momentary Assessment protocol sampling ratings of affect and traits up to 24 times daily for one week. Both classical and nonlinear data analytic techniques were applied to the data to summarize and examine the temporal dynamics of both traits and affect. For the purposes of exposition, one Big Five trait rating, extraversion, and the PANAS positive and negative affects, are discussed. The results support previous research demonstrating a high degree of variability in ratings of both traits and affect over time. Analyses using nonlinear and complexity expand on these findings and suggest temporal patterning as well as disorder; implications of phase portraits for understanding variability are discussed. The findings are discussed in light of a processing dynamics approach to resolving the role of variability in understanding personality.

Emotional Activity Is Negatively Associated With Cognitive Load in Multimedia Learning: A Case Study With EEG Signals

We aimed to investigate the relationship between emotional activity and cognitive load during multimedia learning from an emotion dynamics perspective using electroencephalography (EEG) signals. Using a between-subjects design, 42 university students were randomly assigned to two video lecture conditions (color-coded vs. grayscale). While the participants watched the assigned video, their EEG signals were recorded. After processing the EEG signals, we employed the correlation-based feature selector (CFS) method to identify emotion-related subject-independent features. We then put these features into the Isomap model to obtain a one-dimensional trajectory of emotional changes. Next, we used the zero-crossing rate (ZCR) as the quantitative characterization of emotional changes ZCR EC . Meanwhile, we extracted cognitive load-related features to analyze the degree of cognitive load (CLI). We employed a linear regression fitting method to study the relationship between ZCR EC and CLI. We conducted this study from two perspectives. One is the frequency domain method (wavelet feature), and the other is the non-linear dynamic method (entropy features). The results indicate that emotional activity is negatively associated with cognitive load. These findings have practical implications for designing video lectures for multimedia learning. Learning material should reduce learners' cognitive load to keep their emotional experience at optimal levels to enhance learning.