Pressure to not feel bad among (different-sex) romantic partners: prevalence, and correlates.

Western society generally highly values happiness. As a result, people sometimes experience pressure not to feel negative emotions. In this study, we comprehensively investigated this pressure, and how it manifests itself, in adult romantic relationships. Specifically, we first examined when, how often and how intensely people experience pressure not to feel bad from their romantic partners (94 different-sex couples). Additionally, we investigated (both between- and within-person) how this pressure is related to context (presence of, contact and or conflict with a partner), emotional processes (i.e. experienced sadness and anxiety, emotion suppression, and how their partner perceived their affect), and relationship well-being. Using experience sampling methodology data (6/14 reports per day over one week) we found that although participants generally did not experience strong pressure from their partner, they experienced some feelings of pressure about 50% of the time. Furthermore, within-person predictors associated with negative processes/emotions (i.e. negative emotions, conflict, emotion suppression) were related to the momentary frequency (odds) and/or intensity of perceived pressure not to feel bad. At the between-person level, individuals who experience more sadness, anxiety and reported suppressing their emotions more often tended to experience more and/or stronger pressure. Only weak associations with relationship well-being were found.

Neuroticism may not reflect emotional variability.

Neuroticism is one of the major traits describing human personality, and a predictor of mental and physical disorders with profound public health significance. Individual differences in emotional variability are thought to reflect the core of neuroticism. However, the empirical relation between emotional variability and neuroticism may be partially the result of a measurement artifact reflecting neuroticism's relation with higher mean levels-rather than greater variability-of negative emotion. When emotional intensity is measured using bounded scales, there is a dependency between variability and mean levels: at low (or high) intensity, it is impossible to demonstrate high variability. As neuroticism is positively associated with mean levels of negative emotion, this may account for the relation between neuroticism and emotional variability. In a metaanalysis of 11 studies (N = 1,205 participants; 83,411 observations), we tested whether the association between neuroticism and negative emotional variability was clouded by a dependency between variability and the mean. We found a medium-sized positive association between neuroticism and negative emotional variability, but, when using a relative variability index to correct for mean negative emotion, this association disappeared. This indicated that neuroticism was associated with experiencing more intense, but not more variable, negative emotions. Our findings call into question theory, measurement scales, and data suggesting that emotional variability is central to neuroticism. In doing so, they provide a revisionary perspective for understanding how this individual difference may predispose to mental and physical disorders.

Roles of recalled parenting experiences and effortful control in adult daily emotion regulation.

Research suggests that both childhood experiences with one's parents and individual differences in effortful control contribute to adult emotion regulation (ER). However, it is unclear how they associate with specific ER processes. In this adult study, we examined the roles of recalled parenting experiences and effortful control in daily ER selection and implementation. Using ecological momentary assessment (EMA), we focused on ER strategies of reappraisal, suppression, and rumination. We hypothesized recalled parental warmth, rejection, and overcontrol to predict adult ER selection and effectiveness of ER implementation and effortful control to mediate these effects. One hundred twenty-two adults answered self-reported questionnaires on their childhood experiences with their parents and effortful control. In EMA, they reported ER and emotions seven times daily for seven days. Recalled parental warmth predicted less suppression and rumination, whereas recalled overcontrol, especially in fathers, predicted greater suppression and reappraisal. However, recalled parenting experiences did not predict the effectiveness of ER implementation, and no support was found for the mediating role of effortful control between recalled parenting experiences and ER. Our findings suggest that recalled parenting experiences may guide adult ER selection rather than shape ER implementation, and these links may be largely independent of their effortful control.

Interpersonal Emotion Dynamics in Couples With Somatic Symptom Disorder: Dyadic Coherence in Facial Temperature During Emotional Interactions.

OBJECTIVE: Disturbances in emotional processes are commonly reported in patients with a somatic symptom disorder (SSD). Although emotions usually occur in social interactions, little is known about interpersonal emotion dynamics of SSD patients during their actual emotional encounters. This study examined physiological coherence (linkage) between SSD patients and their partners, and in healthy couples during their emotional interactions. Secondarily, we explored group-level relationships between participants' and their partners' subjective affect. METHODS: Twenty-nine romantic couples (16 healthy and 13 SSD patient-couples) underwent a dyadic conversation task with neutral and anger-eliciting topics followed by a guided relaxation. Partners' cutaneous facial temperature was recorded simultaneously by functional infrared thermal imaging. Immediately after each condition, participants reported on their pain intensity, self-affect, and perceived partner-affect. RESULTS: Emotional conditions and having a partner with an SSD significantly affected coherence amplitude on the forehead (F(2,54) = 4.95, p = .011) and nose tip temperature (F(2,54) = 3.75, p = .030). From baseline to anger condition, coherence amplitude significantly increased in the patient-couples, whereas it decreased in the healthy couples. Correlation changes between partners' subjective affect comparably accompanied the changes in physiological coherence in healthy and patient-couples. CONCLUSIONS: Inability to reduce emotional interdependence in sympathetic activity and subjective affect during a mutual conflict observed in SSD patient-couples seems to capture emotion co-dysregulation. Interventions should frame patients' emotional experiences as embodied and social. Functional infrared thermal imaging confirms to be an ecological and reliable method for examining autonomic changes in interpersonal contexts.Registration Page: https://osf.io/8eyjr.

Designing daily-life research combining experience sampling method with parallel data.

BACKGROUND: Ambulatory monitoring is gaining popularity in mental and somatic health care to capture an individual's wellbeing or treatment course in daily-life. Experience sampling method collects subjective time-series data of patients' experiences, behavior, and context. At the same time, digital devices allow for less intrusive collection of more objective time-series data with higher sampling frequencies and for prolonged sampling periods. We refer to these data as parallel data. Combining these two data types holds the promise to revolutionize health care. However, existing ambulatory monitoring guidelines are too specific to each data type, and lack overall directions on how to effectively combine them. METHODS: Literature and expert opinions were integrated to formulate relevant guiding principles. RESULTS: Experience sampling and parallel data must be approached as one holistic time series right from the start, at the study design stage. The fluctuation pattern and volatility of the different variables of interest must be well understood to ensure that these data are compatible. Data have to be collected and operationalized in a manner that the minimal common denominator is able to answer the research question with regard to temporal and disease severity resolution. Furthermore, recommendations are provided for device selection, data management, and analysis. Open science practices are also highlighted throughout. Finally, we provide a practical checklist with the delineated considerations and an open-source example demonstrating how to apply it. CONCLUSIONS: The provided considerations aim to structure and support researchers as they undertake the new challenges presented by this exciting multidisciplinary research field.

Tracking Subjective Sleep Quality and Mood With Mobile Sensing: Multiverse Study.

BACKGROUND: Sleep influences moods and mood disorders. Existing methods for tracking the quality of people's sleep are laborious and obtrusive. If a method were available that would allow effortless and unobtrusive tracking of sleep quality, it would mark a significant step toward obtaining sleep data for research and clinical applications. OBJECTIVE: Our goal was to evaluate the potential of mobile sensing data to obtain information about a person's sleep quality. For this purpose, we investigated to what extent various automatically gathered mobile sensing features are capable of predicting (1) subjective sleep quality (SSQ), (2) negative affect (NA), and (3) depression; these variables are associated with objective sleep quality. Through a multiverse analysis, we examined how the predictive quality varied as a function of the selected sensor, the extracted feature, various preprocessing options, and the statistical prediction model. METHODS: We used data from a 2-week trial where we collected mobile sensing and experience sampling data from an initial sample of 60 participants. After data cleaning and removing participants with poor compliance, we retained 50 participants. Mobile sensing data involved the accelerometer, charging status, light sensor, physical activity, screen activity, and Wi-Fi status. Instructions were given to participants to keep their smartphone charged and connected to Wi-Fi at night. We constructed 1 model for every combination of multiverse parameters to evaluate their effects on each of the outcome variables. We evaluated the statistical models by applying them to training, validation, and test sets to prevent overfitting. RESULTS: Most models (on either of the outcome variables) were not informative on the validation set (ie, predicted R2≤0). However, our best models achieved R2 values of 0.658, 0.779, and 0.074 for SSQ, NA, and depression, respectively on the training set and R2 values of 0.348, 0.103, and 0.025, respectively on the test set. CONCLUSIONS: The approach demonstrated in this paper has shown that different choices (eg, preprocessing choices, various statistical models, different features) lead to vastly different results that are bad and relatively good as well. Nevertheless, there were some promising results, particularly for SSQ, which warrant further research on this topic.

Dynamics of attachment and emotion regulation in daily life: uni- and bidirectional associations.

Attachment theory proposes that the activation of the attachment system enacts emotion regulation (ER) to maintain security or cope with insecurity. However, the effects of ER on attachment states and their bidirectional influences remain poorly understood. In this ecological momentary assessment study, we examined the dynamics between attachment and ER. We hypothesised that attachment states and ER influence each other through time. Specifically, we hypothesised bidirectional short-term cycles between state attachment security and reappraisal, state attachment anxiety and rumination, and state attachment avoidance and suppression. We also tested how trait attachment is related to state attachment and ER. One hundred twenty-two participants (Mage = 26.4) completed the Experiences in Close Relationship-Revised and reported state attachment and ER seven times daily for seven days. The results were only partly consistent with our cycle hypotheses yet revealed a cycle between low state attachment security and rumination that was attenuated by reappraisal. Moreover, rumination and suppression predicted increased insecure states, and reappraisal predicted increased secure and insecure states. Finally, trait attachment showed associations with state attachment and ER. Our study suggests regulatory dynamics between attachment and ER and opens important questions about their functional relationship in maintaining attachment-related behavioural patterns and emotional well-being.

: An R Package for performing kernel change point detection on the running statistics of multivariate time series.

In many scientific disciplines, researchers are interested in discovering when complex systems such as stock markets, the weather or the human body display abrupt changes. Essentially, this often comes down to detecting whether a multivariate time series contains abrupt changes in one or more statistics, such as means, variances or pairwise correlations. To assist researchers in this endeavor, this paper presents the package for performing kernel change point (KCP) detection on user-selected running statistics of multivariate time series. The running statistics are extracted by sliding a window across the time series and computing the value of the statistic(s) of interest in each window. Next, the similarities of the running values are assessed using a Gaussian kernel, and change points that segment the time series into maximally homogeneous phases are located by minimizing a within-phase variance criterion. To decide on the number of change points, a combination of a permutation-based significance test and a grid search is provided. stands out among the variety of change point detection packages available in because it can be easily adapted to uncover changes in any user-selected statistic without imposing any distribution on the data. To exhibit the usefulness of the package, two empirical examples are provided pertaining to two types of physiological data.

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

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

The Affective Ising Model: A computational account of human affect dynamics.

The human affect system is responsible for producing the positive and negative feelings that color and guide our lives. At the same time, when disrupted, its workings lie at the basis of the occurrence of mood disorder. Understanding the functioning and dynamics of the affect system is therefore crucial to understand the feelings that people experience on a daily basis, their dynamics across time, and how they can become dysregulated in mood disorder. In this paper, a nonlinear stochastic model for the dynamics of positive and negative affect is proposed called the Affective Ising Model (AIM). It incorporates principles of statistical mechanics, is inspired by neurophysiological and behavioral evidence about auto-excitation and mutual inhibition of the positive and negative affect dimensions, and is intended to better explain empirical phenomena such as skewness, multimodality, and non-linear relations of positive and negative affect. The AIM is applied to two large experience sampling studies on the occurrence of positive and negative affect in daily life in both normality and mood disorder. It is examined to what extent the model is able to reproduce the aforementioned non-Gaussian features observed in the data, using two sightly different continuous-time vector autoregressive (VAR) models as benchmarks. The predictive performance of the models is also compared by means of leave-one-out cross-validation. The results indicate that the AIM is better at reproducing non-Gaussian features while their performance is comparable for strictly Gaussian features. The predictive performance of the AIM is also shown to be better for the majority of the affect time series. The potential and limitations of the AIM as a computational model approximating the workings of the human affect system are discussed.

Testing a computational model of subjective well-being: a preregistered replication of Rutledge et al. (2014).

Subjective well-being changes over time. While the causes of these changes have been investigated extensively, few attempts have been made to capture these changes through computational modelling. One notable exception is the study by Rutledge et al. [Rutledge, R. B., Skandali, N., Dayan, P., & Dolan, R. J. (2014). A computational and neural model of momentary subjective well-being. Proceedings of the National Academy of Sciences, 111(33), 12252-12257. https://doi.org/10.1073/pnas.1407535111], in which a model that captures momentary changes in subjective well-being was proposed. The model incorporates how an individual processes rewards and punishments in a decision context. Using this model, the authors were able to successfully explain fluctuations in subjective well-being observed in a gambling paradigm. Although Rutledge et al. reported an in-paper replication, a successful independent replication would further increase the credibility of their results. In this paper, we report a preregistered close replication of the behavioural experiment and analyses by Rutledge et al. The results of Rutledge et al. were mostly confirmed, providing further evidence for the role of rewards and punishments in subjective well-being fluctuations. Additionally, the association between personality traits and the way people process rewards and punishments was examined. No evidence for such associations was found, leaving this an open question for future research.

Effects of a mindfulness-based intervention on cancer-related cognitive impairment: Results of a randomized controlled functional magnetic resonance imaging pilot study.

BACKGROUND: Many breast cancer survivors suffer from cognitive complaints after cancer treatment, affecting their quality of life. The objective of this pilot study was to investigate the effect of a blended-care mindfulness-based intervention (MBI) on chemotherapy-related cognitive impairment and functional brain changes. Furthermore, correlations between changes in cognitive functioning and self-reported behavioral factors were investigated. METHODS: Breast cancer survivors (n = 33) who reported cognitive impairment were randomly allocated to a mindfulness condition (n = 18) or a waitlist control condition (n = 15). Patients completed questionnaires on cognitive impairment, emotional distress, and fatigue; neuropsychological tests; and resting-state functional magnetic resonance imaging before the start of MBI (time 1 [T1]), immediately after the completion of an 8-week MBI program (T2), and 3 months postintervention (T3). Resting-state functional connectivity was estimated in the default mode network, the dorsal and salience attention networks, and the frontoparietal network. Mixed model repeated-measures analysis was performed to test the intervention effect. RESULTS: Patients in the mindfulness condition exhibited significantly higher connectivity between the dorsal and salience attention networks after the mindfulness intervention compared with those in the control condition. MBI participants also had reduced subjective cognitive impairment, emotional distress, and fatigue. No intervention effect was observed on neurocognitive tests. CONCLUSIONS: MBI may induce functional brain changes in networks related to attention and may have a positive effect on subjective measures of cognitive impairment in breast cancer survivors. Therefore, MBI could be a suitable intervention to improve quality of life in this population and deserves further study in this context.

Dimensions over categories: a meta-analysis of taxometric research.

Taxometric procedures have been used extensively to investigate whether individual differences in personality and psychopathology are latently dimensional or categorical ('taxonic'). We report the first meta-analysis of taxometric research, examining 317 findings drawn from 183 articles that employed an index of the comparative fit of observed data to dimensional and taxonic data simulations. Findings supporting dimensional models outnumbered those supporting taxonic models five to one. There were systematic differences among 17 construct domains in support for the two models, but psychopathology was no more likely to generate taxonic findings than normal variation (i.e. individual differences in personality, response styles, gender, and sexuality). No content domain showed aggregate support for the taxonic model. Six variables - alcohol use disorder, intermittent explosive disorder, problem gambling, autism, suicide risk, and pedophilia - emerged as the most plausible taxon candidates based on a preponderance of independently replicated findings. We also compared the 317 meta-analyzed findings to 185 additional taxometric findings from 96 articles that did not employ the comparative fit index. Studies that used the index were 4.88 times more likely to generate dimensional findings than those that did not after controlling for construct domain, implying that many taxonic findings obtained before the popularization of simulation-based techniques are spurious. The meta-analytic findings support the conclusion that the great majority of psychological differences between people are latently continuous, and that psychopathology is no exception.

What can be learned from couple research: Examining emotional co-regulation processes in face-to-face interactions.

A crucial component of successful counseling and psychotherapy is the dyadic emotion co-regulation process between patient and therapist that unfolds moment to moment during therapy sessions. The major reason for the disappointing progress in understanding this process is the lack of appropriate methods to assess subjectively experienced emotions continuously during therapy sessions without disturbing the natural flow of the interaction. The resulting inability has forced the field to focus on patients' overall emotion ratings at the end of each session with limited predictive value of the dyadic interplay between patient and therapist's emotional states within each session. The current tutorial demonstrates how couple research-confronted with a comparable problem-has overcome this issue by (i) developing a video-based retrospective self-report assessment method for individuals' continuous state emotions without undermining the dyadic interaction and (ii) using a validated statistical tool to analyze the dynamical process during a dyadic interaction. We show how to assess emotion data continuously, and how to unravel self-regulation and co-regulation processes using a Latent Differential Equation Modeling approach. Finally, we discuss how this approach can be applied in counseling psychology and psychotherapy to test basic theoretical assumptions about the co-creation of emotions despite the conceptual differences between couple dyads and therapist-patient dyads. The present method aims to inspire future research activities examining systematic real-time processes between patients and therapists. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

mobileQ: A free user-friendly application for collecting experience sampling data.

In this article we introduce mobileQ, which is a free, open-source platform that our lab has developed to use in experience sampling studies. Experience sampling has several strengths and is becoming more widely conducted, but there are few free software options. To address this gap, mobileQ has freely available servers, a web interface, and an Android app. To reduce the barrier to entry, it requires no high-level programming and uses an easy, point-and-click interface. It is designed to be used on dedicated research phones, allowing for experimenter control and eliminating selection bias. In this article, we introduce setting up a study in mobileQ, outline the set of help resources available for new users, and highlight the success with which mobileQ has been used in our lab.

Explaining illness with evil: pathogen prevalence fosters moral vitalism.

Pathogens represent a significant threat to human health leading to the emergence of strategies designed to help manage their negative impact. We examined how spiritual beliefs developed to explain and predict the devastating effects of pathogens and spread of infectious disease. Analysis of existing data in studies 1 and 2 suggests that moral vitalism (beliefs about spiritual forces of evil) is higher in geographical regions characterized by historical higher levels of pathogens. Furthermore, drawing on a sample of 3140 participants from 28 countries in study 3, we found that historical higher levels of pathogens were associated with stronger endorsement of moral vitalistic beliefs. Furthermore, endorsement of moral vitalistic beliefs statistically mediated the previously reported relationship between pathogen prevalence and conservative ideologies, suggesting these beliefs reinforce behavioural strategies which function to prevent infection. We conclude that moral vitalism may be adaptive: by emphasizing concerns over contagion, it provided an explanatory model that enabled human groups to reduce rates of contagious disease.

Differentiate to Regulate: Low Negative Emotion Differentiation Is Associated With Ineffective Use but Not Selection of Emotion-Regulation Strategies.

Emotion differentiation, which involves experiencing and labeling emotions in a granular way, has been linked with well-being. It has been theorized that differentiating between emotions facilitates effective emotion regulation, but this link has yet to be comprehensively tested. In two experience-sampling studies, we examined how negative emotion differentiation was related to (a) the selection of emotion-regulation strategies and (b) the effectiveness of these strategies in downregulating negative emotion (Ns = 200 and 101 participants and 34,660 and 6,282 measurements, respectively). Unexpectedly, we found few relationships between differentiation and the selection of putatively adaptive or maladaptive strategies. Instead, we found interactions between differentiation and strategies in predicting negative emotion. Among low differentiators, all strategies (Study 1) and four of six strategies (Study 2) were more strongly associated with increased negative emotion than they were among high differentiators. This suggests that low differentiation may hinder successful emotion regulation, which in turn supports the idea that effective regulation may underlie differentiation benefits.

The dynamical signature of anhedonia in major depressive disorder: positive emotion dynamics, reactivity, and recovery.

BACKGROUND: Major Depressive Disorder (MDD) is the leading cause of disability worldwide. The cardinal features of MDD are depressed mood and anhedonia. Anhedonia is defined as a "markedly diminished interest or pleasure in all, or almost all, activities of the day", and has generally been investigated on group-level using retrospective data (e.g. via questionnaire/interview). However, inferences based on group-level findings not necessarily generalize to daily life experiences within individuals. METHODS: We repeatedly sampled pleasurable experiences within individuals' daily lives by means of Experience Sampling Methods, and compared how positive affect unfolded in the daily life of healthy controls versus patients diagnosed with MDD and anhedonia. We sampled Positive Affect (PA) and reward experiences on 10 semi-random time points a day, for seven days in the daily lives of 47 MDD patients with anhedonia, and 40 controls. RESULTS: Multilevel models showed that anhedonia was associated with low PA, but not to differences in PA dynamics, nor reward frequency in daily life. In reaction to rewards, MDD patients with anhedonia showed no difference in their increase in PA (i.e., PA reactivity), and showed no signs of a faster return to baseline thereafter (i.e., PA recovery). CONCLUSIONS: Our results suggest that the dynamical signature of anhedonia in MDD can be described best as a lower average level of PA, and "normal" in terms of PA dynamics, daily reward reactivity and reward recovery. Preregistration: https://osf.io/gmfsc/register/565fb3678c5e4a66b5582f67 . Preprint: https://osf.io/cfkts.

"I will fast tomorrow": Intentions to restrict eating and actual restriction in daily life and their person-level predictors.

OBJECTIVE: Dietary restraint is a common, yet controversial practice to tackle overweight. Yet, despite good intentions to reduce food intake, most restraint-based diets fail to produce long term weight loss. A better understanding of the naturalistic course of daily dieting intentions and their effectiveness in guiding subsequent eating behavior are therefore needed. METHOD: In two studies, participants (n = 49 and n = 59) reported both their state intention to restrict eating on the next day, as well as their actual restriction on that day via smartphone-based evening reports of 12 and 10 days, respectively. Intention-behavior gap scores were calculated as differences between intention at t1 (e.g. evening intention Monday for restriction Tuesday) and restriction at t2 (evening report of actual restraint on Tuesday). Restriction-related trait questionnaires served as predictors of general intention or restriction level, whereas several trait-level disinhibiting eating style questionnaires served as predictors for intention-behavior gaps (difference scores). RESULTS: Daily intentions to restrict were rated higher than the daily actual restrictive behavior. Participants with higher scores on restriction-related questionnaires (restrained eating, dieting, lower intuitive eating) showed higher levels of daily state intention and restriction. Larger state intention-behavior gaps, by contrast, were seen in participants scoring high on trait-level disinhibiting eating styles (emotional eating, stress eating and food craving). DISCUSSION: The results point to potential risk factors of diet failure in everyday life: emotional, stress eating, and food craving are disinhibiting traits that seem to increase intention-behavior gaps. These findings can inform individualized weight-loss interventions: individuals with disinhibiting traits might need additional guidance to avoid potentially frustrating diet failures.

Improving theory, measurement, and reality to advance the future of emotion research.

In this short contribution, I reflect on three domains I think are important to advance emotion research. The first concerns theoretical progress, which I hope will occur in the form of theoretical unification that will allow for a consensual definition and understanding of its main object of study. The second concerns measurement where in parallel to technological advances to measure behaviour and biology, particularly the measurement of experience deserves more attention. The third concerns reality, where I advocate the need to study real-world phenomena.