Quantifying Interpersonal Dynamics for Studying Socio-Emotional Processes and Adverse Health Behaviors

Sexual Synchrony During Partnered Sex

There is growing interest in understanding how sexual arousal unfolds between partners, and how this may change over the course of a relationship and in the face of sexual distress. To capture the variable, dynamic, and dyadic nature of sexual responding, this paper introduces the concept of sexual synchrony, defined as the temporal, reciprocal, and coordinated interchange between partners' subjective and genital sexual arousal. Sexual synchrony is a key mechanism for understanding how partners experience and adapt their sexual arousal responses as they evolve over time. Its relevance lies in examining the mechanisms that may disrupt and facilitate synchrony and exploring how it may contribute to sexual well-being by enabling partners to mutually regulate their sexual arousal within and across sexual interactions. The paper also discusses how sexual synchrony may evolve throughout relationship development and its potential role in sexual problems, offering valuable insights into improving sexual relationships. Suggestions are provided for future research, together with a discussion of the methodological and statistical issues involved when examining sexual dynamics. Understanding how partners jointly regulate their sexual responses allows the development of dyadic models of sexual arousal which will inform treatments for improving couples' (sexual) well-being. The study of sexual synchrony also exemplifies the importance of translational research that is relevant across disciplinary borders.

How to use machine learning and fuzzy cognitive maps to test hypothetical scenarios in health behavior change interventions: a case study on fruit intake

BACKGROUND

Intervention planners use logic models to design evidence-based health behavior interventions. Logic models that capture the complexity of health behavior necessitate additional computational techniques to inform decisions with respect to the design of interventions.

OBJECTIVE

Using empirical data from a real intervention, the present paper demonstrates how machine learning can be used together with fuzzy cognitive maps to assist in designing health behavior change interventions.

METHODS

A modified Real Coded Genetic algorithm was applied on longitudinal data from a real intervention study. The dataset contained information about 15 determinants of fruit intake among 257 adults in the Netherlands. Fuzzy cognitive maps were used to analyze the effect of two hypothetical intervention scenarios designed by domain experts.

RESULTS

Simulations showed that the specified hypothetical interventions would have small impact on fruit intake. The results are consistent with the empirical evidence used in this paper.

CONCLUSIONS

Machine learning together with fuzzy cognitive maps can assist in building health behavior interventions with complex logic models. The testing of hypothetical scenarios may help interventionists finetune the intervention components thus increasing their potential effectiveness.

(Mis)align: a simple dynamic framework for modeling interpersonal coordination

As people coordinate in daily interactions, they engage in different patterns of behavior to achieve successful outcomes. This includes both synchrony-the temporal coordination of the same behaviors at the same time-and complementarity-the coordination of the same or different behaviors that may occur at different relative times. Using computational methods, we develop a simple framework to describe the interpersonal dynamics of behavioral synchrony and complementarity over time, and explore their task-dependence. A key feature of this framework is the inclusion of a task context that mediates interactions, and consists of active, inactive, and inhibitory constraints on communication. Initial simulation results show that these task constraints can be a robust predictor of simulated agents' behaviors over time. We also show that the framework can reproduce some general patterns observed in human interaction data. We describe preliminary theoretical implications from these results, and relate them to broader proposals of synergistic self-organization in communication.

multiSyncPy: A Python package for assessing multivariate coordination dynamics

In order to support the burgeoning field of research into intra- and interpersonal synchrony, we present an open-source software package: multiSyncPy. Multivariate synchrony goes beyond the bivariate case and can be useful for quantifying how groups, teams, and families coordinate their behaviors, or estimating the degree to which multiple modalities from an individual become synchronized. Our package includes state-of-the-art multivariate methods including symbolic entropy, multidimensional recurrence quantification analysis, coherence (with an additional sum-normalized modification), the cluster-phase 'Rho' metric, and a statistical test based on the Kuramoto order parameter. We also include functions for two surrogation techniques to compare the observed coordination dynamics with chance levels and a windowing function to examine time-varying coordination for most of the measures. Taken together, our collation and presentation of these methods make the study of interpersonal synchronization and coordination dynamics applicable to larger, more complex and often more ecologically valid study designs. In this work, we summarize the relevant theoretical background and present illustrative practical examples, lessons learned, as well as guidance for the usage of our package - using synthetic as well as empirical data. Furthermore, we provide a discussion of our work and software and outline interesting further directions and perspectives. multiSyncPy is freely available under the LGPL license at: https://github.com/cslab-hub/multiSyncPy , and also available at the Python package index.

An Exploratory Study of Physiological Linkage Among Strangers

The present study explores physiological linkage (i.e., any form of statistical interdependence between the physiological signals of interacting partners; PL) using data from 65 same-sex, same ethnicity stranger dyads. Participants completed a knot-tying task with either a cooperative or competitive framing while either talking or remaining silent. Autonomic nervous system activity was measured continuously by electrocardiograph for both individuals during the interaction. Using a recently developed R statistical package (i.e., rties), we modeled different oscillatory patterns of coordination between partner's interbeat interval (i.e., the time between consecutive heart beats) over the course of the task. Three patterns of PL emerged, characterized by differences in frequency of oscillation, phase, and damping or amplification. To address gaps in the literature, we explored (a) PL patterns as predictors of affiliation and (b) the interaction between individual differences and experimental condition as predictors of PL patterns. In contrast to prior analyses using this dataset for PL operationalized as covariation, the present analyses showed that oscillatory PL patterns did not predict affiliation, but the interaction of individual differences and condition differentially predicted PL patterns. This study represents a next step toward understanding the roles of individual differences, context, and PL among strangers.

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.

Good Theories in Need of Better Data: Combining Clinical and Social Psychological Approaches to Study the Mechanisms Linking Relationships and Health

The study of intimate relationships and health is a fast-growing discipline with numerous well-developed theories, many of which outline specific interpersonal behaviors and psychological pathways that may give rise to good or poor health. In this article, we argue that the study of relationships and health can move toward interrogating these mechanisms with greater precision and detail, but doing so will require a shift in the nature of commonly used research methods in this area. Accordingly, we draw heavily on the science of behavior change and discuss six key methodologies that may galvanize the mechanistic study of relationships and health: dismantling studies, factorial studies, experimental therapeutics, experimental mediation research, multiple assessments, and recursive modeling. We provide empirical examples for each strategy and outline new ways in which a given approach may be used to study the mechanisms linking intimate relationships and health. We conclude by discussing the key challenges and limitations for using these research strategies as well as novel ideas about how to integrate this work into existing paradigms within the field.

Couples' co-regulation dynamics as a function of perceived partner dyadic coping

BACKGROUND AND OBJECTIVES

Perceptions of partners' dyadic coping (DC) behaviors are associated with lower stress and higher relationship well-being. Albeit well-documented, these associations have predominately relied on cross-sectional data, overlooking temporal associations during conversations of mutual stress. Based on the systemic transactional model of DC [Bodenmann, G. (2005). Dyadic coping and its significance for marital functioning. In T. Revenson, K. Kayser, & G. Bodenmann (Eds.), Couples coping with stress: Emerging perspectives on dyadic coping (pp. 33-50). American Psychological Association.], we hypothesized that co-regulatory dynamics would be displayed for couples who generally perceive high positive DC, whereas co-dysregulatory dynamics would be displayed for couples who generally perceive high negative DC.

DESIGN AND METHODS

Using video-prompted second-by-second recall of stress experience from 42 different-gender romantic couples, this study examined whether couples' co-regulation dynamics were moderated by perceived partner DC behaviors, measured at baseline.

RESULTS

On average, partners' stress ratings were coupled; females tended to coregulate males' stress and both partners' stress dampened over time. Perceived negative DC moderated the coregulation of stress, suggesting that females unidirectionally coregulated males' stress when (1) negative DC was low in both partners and (2) when females reported lower negative DC than males. However, coregulation did not occur when (1) negative DC was high in both partners and (2) females reported higher negative DC than males.

CONCLUSIONS

Implications for utilizing methods sensitive to temporal interpersonal emotion dynamics are presented.

Exploring Physiological Linkage in Same-Sex Male Couples

We explore physiological linkage (i.e., covariation of physiological channels between interacting partners; PL) among 34 same-sex male couples. Interbeat interval, an indicator of cardiovascular arousal, was collected across four conversational contexts in the lab: (1) a baseline period that did not involve conversation, (2) a conversation about body image, (3) a conversation about health goals, and (4) a recovery period that allowed for unstructured conversation. We used a newly developed R statistical package (i.e., rties; Butler and Barnard, 2019) that simplifies the use of dynamic models for investigating interpersonal emotional processes. We identified two different PL patterns: (1) a simple one that was characterized by stable synchronization and low frequency of oscillation; and (2) a complex one that was characterized by drifting synchronization, high frequency of oscillation, and eventual damping. Guided by social baseline theory and the reactive flexibility perspective, we explored the interactions between couple relationship functioning (i.e., love, conflict, commitment, sexual satisfaction, and relationship length) and conversational context as predictors of the PL patterns. The results suggest that partners in well-functioning relationships and emotionally challenging situations may be especially likely to show complex PL patterns that may reflect (or support) coregulatory processes.

Incorporating physiology into the study of psychotherapy process

Increasing evidence indicates that psychological factors important to therapy effectiveness are associated with physiological activity. Knowledge of the physiological correlates of therapy process variables has the potential to provide unique insights into how and why therapy works, but little is currently known about the physiological underpinnings of specific therapy processes that facilitate client growth and change. The goal of this article is to introduce therapy process researchers to the use of physiological methods for studying therapy process variables. We do this by (a) presenting a conceptual framework for the study of therapy process variables, (b) providing an introductory overview of physiological systems with particular promise for the study of therapy process variables, (c) introducing the primary methods and methodological decisions involved in physiological research, and (d) demonstrating these principles and methods in a case of therapeutic presence during couple therapy. We close with a discussion of the promise and challenges in the study of physiological correlates of therapy process variables and consideration of future challenges and open questions in this line of research. Online supplemental materials include additional resources for therapy process researchers interested in getting started with physiological research. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Emotions in Social Relationships and Their Implications for Health and Disease: Introduction to the Special Issue of Psychosomatic Medicine

Social relationships and emotions are important to health and disease, but research in this area has largely progressed along parallel and distinct historical paths. These areas are critically linked because relationships are among the most powerful elicitors of health-relevant emotions and emotions can in turn influence relationships for better or worse. Conceptually, relationships and emotions can have mediational, reciprocal, and interactive influences on health outcomes, associations that seem dependent on the broader sociocultural context. The articles in this issue of Psychosomatic Medicine are based on a joint meeting of the American Psychosomatic Society and the Society for Affective Science titled "Emotions in social relationships: implications for health and disease." Recent research and conceptual models that fall at the interface of relationships, emotions, and health are highlighted in this special issue. Future work that capitalizes on these links will be critical if this area is to fulfill its potential in terms of new scientific insights and intervention opportunities.

The occurrence and correlates of emotional interdependence in romantic relationships

Interdependence, including emotional interdependence, is widely considered to be a cornerstone of close relationships. Through frequent interactions, romantic partners are thought to continuously exchange, influence, and respond to one another's emotions, leading their feelings to become closely aligned over time. Although prior research has shown that such emotional interdependence can arise in couples, no research to date has comprehensively investigated its occurrence, degree, consistency and correlates. Across 3 different studies, we examined whether and to what extent couples indeed show interpersonal emotional connections (compared to pseudocouples). Additionally, we investigated its consistency and moderating factors, by examining emotional interdependence across different types of emotions (negative vs. positive vs. emotional extremity), timescales (second-to-second vs. daily life), and situational contexts (supportive vs. conflictual), and by inspecting associations with indicators of relationship closeness (relationship longevity, cohabitation status, commitment, and closeness in terms of including the other in the self). The findings show limited evidence for emotional interdependence. The overall mean level of interdependence was significantly larger than that of randomly composed couples, but only a minority of the couples demonstrated emotional interdependence to a greater extent than these pseudocouples. Moreover, the degree to which couples exhibited emotional interdependence showed little consistency across timescales and contexts, and was not clearly associated with relationship closeness. We discuss potential implications for the field of interpersonal emotion dynamics. (PsycInfo Database Record (c) 2020 APA, all rights reserved).