Modeling Nonstationary Emotion Dynamics in Dyads using a Time-Varying Vector-Autoregressive Model

Emotion dynamics are likely to arise in an interpersonal context. Standard methods to study emotions in interpersonal interaction are limited because stationarity is assumed. This means that the dynamics, for example, time-lagged relations, are invariant across time periods. However, this is generally an unrealistic assumption. Whether caused by an external (e.g., divorce) or an internal (e.g., rumination) event, emotion dynamics are prone to change. The semi-parametric time-varying vector-autoregressive (TV-VAR) model is based on well-studied generalized additive models, implemented in the software R. The TV-VAR can explicitly model changes in temporal dependency without pre-existing knowledge about the nature of change. A simulation study is presented, showing that the TV-VAR model is superior to the standard time-invariant VAR model when the dynamics change over time. The TV-VAR model is applied to empirical data on daily feelings of positive affect (PA) from a single couple. Our analyses indicate reliable changes in the male’s emotion dynamics over time, but not in the female’s—which were not predicted by her own affect or that of her partner. This application illustrates the usefulness of using a TV-VAR model to detect changes in the dynamics in a system.     

On Measuring and Modeling Physiological Synchrony in Dyads

Physiological synchrony within a dyad, or the degree of temporal correspondence between two individuals' physiological systems, has become a focal area of psychological research. Multiple methods have been used for measuring and modeling physiological synchrony. Each method extracts and analyzes different types of physiological synchrony, where ‘type’ refers to a specific manner through which two different physiological signals may correlate. Yet, to our knowledge, there is no documentation of the different methods, how each method corresponds to a specific type of synchrony, and the statistical assumptions embedded within each method. Hence, this article outlines several approaches for measuring and modeling physiological synchrony, connects each type of synchrony to a specific method, and identifies the assumptions that need to be satisfied for each method to appropriately extract each type of synchrony. Furthermore, this article demonstrates how to test for between-dyad differences of synchrony via inclusion of dyad-level (i.e., time-invariant) covariates. Finally, we complement each method with an empirical demonstration, as well as online supplemental material that contains Mplus code.     

Identification of a Semiparametric Item Response Model

We consider the identification of a semiparametric multidimensional fixed effects item response model. Item response models are typically estimated under parametric assumptions about the shape of the item characteristic curves (ICCs), and existing results suggest difficulties in recovering the distribution of individual characteristics under nonparametric assumptions. We show that if the shape of the ICCs are unrestricted, but the shape is common across individuals and items, the individual characteristics are identified. If the shape of the ICCs are allowed to differ over items, the individual characteristics are identified in the multidimensional linear compensatory case but only identified up to a monotonic transformation in the unidimensional case. Our results suggest the development of two new semiparametric estimators for the item response model.     

Dealing with Multiple Solutions in Structural Vector Autoregressive Models

Structural vector autoregressive models (VARs) hold great potential for psychological science, particularly for time series data analysis. They capture the magnitude, direction of influence, and temporal (lagged and contemporaneous) nature of relations among variables. Unified structural equation modeling (uSEM) is an optimal structural VAR instantiation, according to large-scale simulation studies, and it is implemented within an SEM framework. However, little is known about the uniqueness of uSEM results. Thus, the goal of this study was to investigate whether multiple solutions result from uSEM analysis and, if so, to demonstrate ways to select an optimal solution. This was accomplished with two simulated data sets, an empirical data set concerning children's dyadic play, and modifications to the group iterative multiple model estimation (GIMME) program, which implements uSEMs with group- and individual-level relations in a data-driven manner. Results revealed multiple solutions when there were large contemporaneous relations among variables. Results also verified several ways to select the correct solution when the complete solution set was generated, such as the use of cross-validation, maximum standardized residuals, and information criteria. This work has immediate and direct implications for the analysis of time series data and for the inferences drawn from those data concerning human behavior.     

Reciprocal Markov Modeling of Feedback Mechanisms Between Emotion and Dietary Choice Using Experience-Sampling Data

With intensively collected longitudinal data, recent advances in the experience-sampling method (ESM) benefit social science empirical research, but also pose important methodological challenges. As traditional statistical models are not generally well equipped to analyze a system of variables that contain feedback loops, this paper proposes the utility of an extended hidden Markov model to model reciprocal the relationship between momentary emotion and eating behavior. This paper revisited an ESM data set (Lu, Huet, &; Dube, 2011 Lu, J., Huet, C., &; Dubé, L. (2011). Emotional reinforcement as a protective factor for healthy eating in home settings. The American Journal of Clinical Nutrition, 94(1), 254–261. http://dx.doi.org/10.3945/ajcn.110.006361[Crossref], [PubMed], [Web of Science ®] , [Google Scholar]) that observed 160 participants' food consumption and momentary emotions 6 times per day in 10 days. Focusing on the analyses on feedback loop between mood and meal-healthiness decision, the proposed reciprocal Markov model (RMM) can accommodate both hidden (“general” emotional states: positive vs. negative state) and observed states (meal: healthier, same or less healthy than usual) without presuming independence between observations and smooth trajectories of mood or behavior changes. The results of RMM analyses illustrated the reciprocal chains of meal consumption and mood as well as the effect of contextual factors that moderate the interrelationship between eating and emotion. A simulation experiment that generated data consistent with the empirical study further demonstrated that the procedure is promising in terms of recovering the parameters.     

Emotion Reporting Using Electronic Diaries Reduces Anxiety Symptoms in Girls With Emotion Dysregulation

Theory and empirical research suggest that electronic diaries, which require children to report on their emotional experiences, might encourage emotional processing and facilitate a reduction in symptoms of anxiety, particularly for children exhibiting emotion-related deficits. Electronic diaries were given to 52 children (aged 7–12) to track their emotions and associated intensity for 7?days; anxiety was assessed prior to and after the use of the electronic diary by both parent- and child-report. It was hypothesized that the use of an electronic diary to track emotional experiences would lead to a reduction in anxiety symptoms for those children high in poor awareness, high in expressive reluctance, and low in emotion coping. The use of electronic diaries was effective at reducing child self-reported anxiety symptoms in girls who reported low emotion coping and reducing parent-reported anxiety for girls who reported a high reluctance to express emotions. Current findings suggest that having children identify their emotions using electronic diaries may be particularly beneficial for girls who are reluctant to express emotions and who report poor coping abilities.     

时变效应模型及在密集追踪数据分析中的应用

密集追踪数据通常蕴含了心理过程的详细变化信息,反映了某些心理的复杂变化过程。时变效应模型用函数替代恒定的系数,可描述密集追踪数据中随时间推移心理的动态变化过程和时变效应,是分析复杂心理过程的有效方法。在介绍时变效应模型的原理后,通过模拟研究考察模型的表现,结果显示:(1)样本量增加可降低函数估计的误差;(2)惩罚样条法的节点数选择与函数的复杂度有关,函数越复杂,所需节点越多;(3)样本量与节点数对函数估计误差的交互效应不显著。进一步应探讨测量次数、数据分布形态、数据缺失等如何影响模型的表现。     

The 5C’s Model of Successful Partnerships in Elite Beach Volleyball Dyads

An athlete–athlete partnership is a form of athletic dyad in which both members equally share power and responsibility. Although research on the coach–athlete relationship is prevalent, research on the unique interpersonal dynamics of athlete–athlete partnerships in elite sport is sparse, particularly in beach volleyball. The purpose of the present study was to explore the interpersonal components of successful, elite athlete–athlete beach volleyball partnerships through the lens of interdependence theory and Jowett and colleagues’ 3?+?1C’s theory of coach–athlete relationships. Interpretative Phenomenological Analysis was applied to semistructured interviews with four Olympic-level beach volleyball players (3 male, 1 female). Results revealed 5 higher order themes: (a) compatibility, (b) commitment, (c) complementarity, (d) coorientation, and (e) closeness, which became the key constructs in the proposed 5C’s model of the successful athlete–athlete partnership. Interpersonal awareness, interpersonal maturation, and context were identified as 3 overarching meta-themes, whereas interdependence connected all interpersonal components. For example, in consultation, increasing athlete individual and interpersonal awareness (e.g., in the areas of personal and dyadic philosophy, personal and shared values, and individual and dyadic coping) requires careful contextualization and thoughtful implementation. Future studies need to examine diverse samples of athlete–athlete dyads to advance interpersonal theory in sport and add to emerging theories of performance behavior and expertise in sport.

Lay Summary: Successful beach volleyball partnerships share a philosophy and commitment to their sport. Desired partners are supportive and adaptive, are compatible, depend on one another, and continually appraise and reflect on their relationship to grow as individuals and as teammates.     

Emotion Regulation with Mindful Arts Activities Using a Personalized Self-Soothing Kit

Contrary to the occupational therapy tradition, there is little current research on harmonizing expressive doing with contemporary occupational therapy practice. This phenomenological multiple case study explored an integrated application of mindfulness, creative activity, and sensory modulation for adult mental health services users by making and using personalized self-soothing kits. The results showed significant improvements in arousal regulation, positive changes in emotion regulation and mixed results for mood regulation. Progress in participation in present roles and an increased focus on future productivity goals were also among the outcomes reported. The theoretical and clinical implications of the findings are discussed.     

Modeling Temporal Interaction Dynamics in Organizational Settings

Most workplace phenomena take place in dynamic social settings and emerge over time, and scholars have repeatedly called for more research into the temporal dynamics of organizational behavior. One reason for this persistent research gap could be that organizational scholars are not aware of the methodological advances that are available today for modeling temporal interactions and detecting behavioral patterns that emerge over time. To facilitate such awareness, this Methods Corner contribution provides a hands-on tutorial for capturing and quantifying temporal behavioral patterns and for leveraging rich interaction data in organizational settings. We provide an overview of different approaches and methodologies for examining temporal interaction patterns, along with detailed information about the type of data that needs to be gathered in order to apply each method as well as the analytical steps (and available software options) involved in each method. Specifically, we discuss and illustrate lag sequential analysis, pattern analysis, statistical discourse analysis, and visualization methods for identifying temporal patterns in interaction data. We also provide key takeaways for integrating these methods more firmly in the field of organizational research and for moving interaction analytical research forward.     

Modeling Growth in Latent Variables Using a Piecewise Function

Latent growth curve models with piecewise functions for continuous repeated measures data have become increasingly popular and versatile tools for investigating individual behavior that exhibits distinct phases of development in observed variables. As an extension of this framework, this research study considers a piecewise function for describing segmented change of a latent construct over time where the latent construct is itself measured by multiple indicators gathered at each measurement occasion. The time of transition from one phase to another is not known a priori and thus is a parameter to be estimated. Utility of the model is highlighted in 2 ways. First, a small Monte Carlo simulation is executed to show the ability of the model to recover true (known) growth parameters, including the location of the point of transition (or knot), under different manipulated conditions. Second, an empirical example using longitudinal reading data is fitted via maximum likelihood and results discussed. Mplus (Version 6.1) code is provided in Appendix C to aid in making this class of models accessible to practitioners.     

Anticipating the Self: Toward a Personal Construct Model of Emotion

Previous accounts of the role of emotion in construct theory place insufficient emphasis on the constructive role of emotion as a “feeling toward.” Emotion is regarded either as an epiphenomenon of acts of construal or as an outcome of prior cognitive processes. It is argued in this paper that emotion performs an anticipatory role in pursuit of the current concerns of the self, a view that follows from a closer analysis of the function of anticipation. A revision of the control systems theory of Carver and Scheier (1981) is proposed, in which emotional anticipation at the level of the self is distinguished from schema-based anticipation at the level of behavior. Given the framework of personal construct theory as a method of analysis, this revised view of emotion enables a range of self-concept processes to be better understood.     

Modeling Associations Among Multivariate Longitudinal Categorical Variables in Survey Data: A Semiparametric Bayesian Approach

This paper proposes a semiparametric Bayesian framework for the analysis of associations among multivariate longitudinal categorical variables in high-dimensional data settings. This type of data is frequent, especially in the social and behavioral sciences. A semiparametric hierarchical factor analysis model is developed in which the distributions of the factors are modeled nonparametrically through a dynamic hierarchical Dirichlet process prior. A Markov chain Monte Carlo algorithm is developed for fitting the model, and the methodology is exemplified through a study of the dynamics of public attitudes toward science and technology in the United States over the period 1992?C2001.     

协变量相关对时变效应模型参数估计的影响

时变效应模型被广泛应用于密集追踪研究中,研究者往往会同时纳入2个或以上协变量。然而,协变量相关对其参数估计的影响较少被研究者关注。本研究在不同类型协变量的情境下,采用蒙特卡洛模拟,探讨协变量相关对时变效应模型参数估计的影响,结果表明：（1）在两种协变量类型的情境下,协变量相关都会影响时变效应模型斜率函数β_1和斜率函数β_2参数估计的准确性;（2）两种协变量类型的情境下,协变量相关和样本量的交互作用都会影响时变效应模型斜率函数β_1和斜率函数β_2参数估计的准确性;（3）两种协变量类型的情境下,样本量、观测数据缺失率主要通过主效应影响时变效应模型参数估计的准确性。     

Modeling Family Dynamics in Children with Fragile X Syndrome

Few studies have examined the impact of children with genetic disorders and their unaffected siblings on family functioning. In this study, the reciprocal causal links between problem behaviors and maternal distress were investigated in 150 families containing a child with fragile X syndrome (FXS) and an unaffected sibling. Both children's behavior problems appeared to have strong, direct effects on maternal distress, but maternal distress did not appear to have any reciprocal causal effects on either child's behavior problems. Surprisingly, there were no significant differences in the effects of the two children's behavior problems on maternal distress. These data suggest that the problem behaviors of children with FXS, as well as their unaffected siblings, can have a substantial and additive impact on maternal depression and anxiety. Future research efforts should employ longitudinal research designs to confirm these findings.     

Realism in Confidence Judgments as a Function of Working in Dyads or Alone

This study compares the realism of confidence judgments made by individuals and pairs of their answers to general knowledge questions, using a within-subjects design. In the initial Control condition, subjects first answered 30 questions and then confidence rated the chosen answer. For the next 30 questions (Condition 2), they wrote down an argument for the chosen answer and then confidence-rated their answer. In the third condition, the 40 subjects were divided into 20 pairs who then answered and confidence-rated the same 30 questions as in Condition 2. Pair members were asked to collaborate on all parts of the task. The results showed that overconfidence decreased in the Pair condition compared with the Single conditions. Analysis of the interaction in the Pair condition showed a higher overconfidence in those instances where one pair member dominated the interaction totally. Other analyses of the interaction in the Pair condition also supported the importance of argumentation between the pair members for realistic confidence judgments. A comparison with previous research suggests that the fact that the subjects first attempted the questions individually may have increased the proportion correct answers and limited the increase in confidence in the Pair condition. A control study, checking for the effect of subjects answering the same questions twice, found no effect of repetition for any of the three calibration measures used.