Using Network Analysis for Examining Interpersonal Emotion Dynamics

A Network Study of Family Affect Systems in Daily Life

Adolescence is a time period characterized by extremes in affect and increasing prevalence of mental health problems. Prior studies have illustrated how affect states of adolescents are related to interactions with parents. However, it remains unclear how affect states among family triads, that is adolescents and their parents, are related in daily life. This study investigated affect state dynamics (happy, sad, relaxed, and irritated) of 60 family triads, including 60 adolescents (Mage = 15.92, 63.3% females), fathers and mothers (Mage = 49.16). The families participated in the RE-PAIR study, where they reported their affect states in four ecological momentary assessments per day for 14 days. First, we used multilevel vector-autoregressive network models to estimate affect dynamics across all families, and for each family individually. Resulting models elucidated how family affect states were related at the same moment, and over time. We identified relations from parents to adolescents and vice versa, while considering family variation in these relations. Second, we evaluated the statistical performance of the network model via a simulation study, varying the percentage missing data, the number of families, and the number of time points. We conclude with substantive and statistical recommendations for future research on family affect dynamics.

Detecting Prolonged Stress in Real Life Using Wearable Biosensors and Ecological Momentary Assessments: Naturalistic Experimental Study

BACKGROUND

Increasing efforts toward the prevention of stress-related mental disorders have created a need for unobtrusive real-life monitoring of stress-related symptoms. Wearable devices have emerged as a possible solution to aid in this process, but their use in real-life stress detection has not been systematically investigated.

OBJECTIVE

We aimed to determine the utility of ecological momentary assessments (EMA) and physiological arousal measured through wearable devices in detecting ecologically relevant stress states.

METHODS

Using EMA combined with wearable biosensors for ecological physiological assessments (EPA), we investigated the impact of an ecological stressor (ie, a high-stakes examination week) on physiological arousal and affect compared to a control week without examinations in first-year medical and biomedical science students (51/83, 61.4% female). We first used generalized linear mixed-effects models with maximal fitting approaches to investigate the impact of examination periods on subjective stress exposure, mood, and physiological arousal. We then used machine learning models to investigate whether we could use EMA, wearable biosensors, or the combination of both to classify momentary data (ie, beeps) as belonging to examination or control weeks. We tested both individualized models using a leave-one-beep-out approach and group-based models using a leave-one-subject-out approach.

RESULTS

During stressful high-stakes examination (versus control) weeks, participants reported increased negative affect and decreased positive affect. Intriguingly, physiological arousal decreased on average during the examination week. Time-resolved analyses revealed peaks in physiological arousal associated with both momentary self-reported stress exposure and self-reported positive affect. Mediation models revealed that the decreased physiological arousal in the examination week was mediated by lower positive affect during the same period. We then used machine learning to show that while individualized EMA outperformed EPA in its ability to classify beeps as originating from examinations or from control weeks (1603/4793, 33.45% and 1648/4565, 36.11% error rates, respectively), a combination of EMA and EPA yields optimal classification (1363/4565, 29.87% error rate). Finally, when comparing individualized models to group-based models, we found that the individualized models significantly outperformed the group-based models across all 3 inputs (EMA, EPA, and the combination).

CONCLUSIONS

This study underscores the potential of wearable biosensors for stress-related mental health monitoring. However, it emphasizes the necessity of psychological context in interpreting physiological arousal captured by these devices, as arousal can be related to both positive and negative contexts. Moreover, our findings support a personalized approach in which momentary stress is optimally detected when referenced against an individual's own data.

Taking Stock and Moving Forward: A Personalized Perspective on Mixed Emotions

Research on mixed emotions is flourishing but fractured. Several psychological subfields are working in parallel and separately from other disciplines also studying mixed emotions, which has led to a disorganized literature. In this article, we provide an overview of the literature on mixed emotions and discuss factors contributing to the lack of integration within and between fields. We present an organizing framework for the literature of mixed emotions on the basis of two distinct goals: solving the bipolar-bivariate debate and understanding the subjective experience of mixed emotions. We also present a personalized perspective that can be used when studying the subjective experience of mixed emotions. We emphasize the importance of assessing both state and trait emotions (e.g., momentary emotions, general levels of affect) alongside state and trait context (e.g., physical location, culture). We discuss three methodological approaches that we believe will be valuable in building a new mixed-emotions literature-inductive research methods, idiographic models of emotional experiences, and empirical assessment of emotion-eliciting contexts. We include recommendations throughout on applying these methods to research on mixed emotions, and we conclude with avenues for future interdisciplinary research. We hope that this perspective will foster research that results in the organized accumulation of knowledge about mixed emotions.

Exploring High vs. Low Burnout amongst Public Sector Educators: COVID-19 Antecedents and Profiles

The COVID-19 pandemic has had a prolonged impact on many people working in different sectors. This paper focuses on the psychological stress consequences of professionals working in the educational sector in Andalucía (Spain). Using a sample of 340 educators, this empirical paper identifies the antecedents and profiles of those that ended up with burnout vs. those that were able to develop resilience. Results from OLS regressions show that regardless of the origins of stress, the principal determinant of burnout is clearly a lack of support and a perception of an inability to control a situation. Furthermore, results also show that working sources have a higher impact on the configuration of high burnout, while family sources harm those who are more resilient (low burnout).

Emotional Linkage as a Moderator of Emotional Reactivity Effect on Partners' Depressive Symptoms

Introduction: Romantic partners’ emotions show a degree of interdependence, a process that is often described as emotional linkage. The current study sought to test the effects of emotional linkage in emotionally reactive individuals (i.e., those who easily become emotionally aroused and find it hard to regulate their emotions) and their partners. Specifically, we examined the interplay between emotional linkage and reactivity in predicting partners’ depressive symptoms over time. Method: To assess emotional linkage and reactivity, we collected daily diary data from two samples of cohabiting couples (Ncouples=76 and 84 in samples 1 and 2, respectively). Partners’ depressive symptoms were assessed before and after the diary. Results: In dyads with low emotional linkage men's emotional reactivity predicted their greater depressive symptoms in Sample 1, and women's greater depressive symptoms in Sample 2. Discussion: The study's results suggest that dyads’ emotional linkage can moderate the negative effects of men's emotional reactivity on their and their partners’ psychological distress.

Emotion network density in burnout

Background

Health care workers are often affected by burnout, resulting in reduced personal well-being and professional functioning. Although emotional exhaustion is considered a core component of burnout, little is known about the dynamics of emotions and their relation to burnout. We used network analysis to investigate the correlation between the density of a negative emotion network, a marker for emotional rigidity in person-specific networks, and burnout severity.

Methods

Using an ecological momentary assessment design, the intensity of negative emotions of forty-three health care workers and medical students was assessed five times per day (between 6 am and 8 pm) for 17 days. Burnout symptoms were assessed at the end of the study period with the Maslach Burnout Inventory. Multilevel vector autoregressive models were computed to calculate network density of subject-specific temporal networks. The one-sided correlation between network density and burnout severity was assessed. The study protocol and analytic plan were registered prior to the data collection.

Results

We found a medium-sized correlation between the negative emotion network density and burnout severity at the end of the study period r(45) = .32, 95% CI = .09–1.0, p = .014).

Conclusions

The strength of the temporal interplay of negative emotions is associated with burnout, highlighting the importance of emotions and emotional exhaustion in reaction to occupational-related distress in health care workers. Moreover, our findings align with previous investigations of emotion network density and impaired psychological functioning, demonstrating the utility of conceptualizing the dynamics of emotions as a network.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40359-021-00670-y.

Respiratory sinus arrhythmia as a dyadic protective factor in the transition to parenthood

Considerable heterogeneity has been observed in couples' adjustment to the transition to parenthood (TTP). One potential yet understudied predictor of emotional adjustment to the TTP is the new parents' capacity for regulation. A widely accepted biological marker of this capacity is respiratory sinus arrhythmia (RSA), which is closely tied to parasympathetic activation. In the present work, we sought to examine the role of tonic RSA and RSA reactivity as possible protective dyadic factors in the TTP. As part of a larger study, we recruited a sample (N = 100) of TTP couples. At 15 weeks postpartum, the couples took part in a lab session during which their RSA was assessed both at rest (tonic RSA) and during four affiliative dyadic interactions (RSA reactivity). Following this session, couples completed daily diaries over a period of 3 weeks, reporting their daily levels of negative affect and stress. A Multivariate Actor Partner Interdependence Model was used to examine the extent to which each partner's RSA predicted their own and their partner's negative affect (NA) level, as well as NA stress-reactivity (i.e., the strength of the within-person stress-affect association). New mothers' tonic RSA predicted their own lower NA level and NA stress-reactivity; both their tonic RSA and RSA reactivity predicted their (male) partners' lower NA level; and finally, new fathers' tonic RSA and RSA reactivity predicted their (female) partners' lower NA stress-reactivity. These results suggest that RSA may serve as a personal and dyadic protective factor.