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Graphic Methods for Interpreting Longitudinal Dyadic Patterns From Repeated-Measures Actor-Partner Interdependence Models
Abstract and Figures
Researchers commonly use repeated-measures actor-partner interdependence models (RM-APIM) to understand how romantic partners change in relation to one another over time. However, traditional interpretations of the results of these models do not fully or correctly capture the dyadic temporal patterns estimated in RM-APIM. Interpretation of results from these models largely focuses on the meaning of single-parameter estimates in isolation from all the others. However, considering individual coefficients separately impedes the understanding of how these associations combine to produce an interdependent pattern that emerges over time. Additionally, positive within-person, or actor, effects are commonly misinterpreted as indicating growth from one time point to the next when they actually represent decline. We suggest that change-as-outcome RM-APIMs and vector field diagrams (VFDs) can be used to improve the understanding and presentation of dyadic patterns of association described by standard RM-APIMs. The current article briefly reviews the conceptual foundations of RM-APIMs, demonstrates how change-as-outcome RM-APIMs and VFDs can aid interpretation of standard RM-APIMs, and provides a tutorial in making VFDs using multilevel modeling. (PsycINFO Database Record
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... measured at 38 years. This indicated that adult happiness and health each had a positive association with the regressed change in PFR from childhood to adulthood (McArdle, 2009;Perry et al., 2017). Furthermore, PFR indirectly related to happiness (children's β = .16, ...
... Additionally, the stability of positive family relationships from childhood to adulthood is related to increases in adult health and happiness. This shows that the longitudinal pattern from early to adult PFR may be a key pathway in predicting adult health and happiness (Perry et al., 2017). Taken together, our findings suggest that early positive family relationships set the stage for family relationships in adulthood: the more adult family relationships are perceived as supportive, the greater one's health and happiness. ...
In this prospective study, we examined the link between positive family relationships during childhood and adolescence and health and happiness three decades later in middle adulthood. We also investigated the stability of positive family relationships into adulthood as one possible pathway underlying this long-term association. Data were from the Fullerton Longitudinal Study (FLS) an ongoing investigation in the United States initiated in 1979 when children were aged 1 year with the most recent data collected in 2017. A cross-informant methodology was employed in which mothers and children independently completed the Positive Family Relationships (PFR) scale annually when children were of ages 9-17 years. When study children reached age 38, they reported on their current PFR, global health, and comprehensive happiness. Structural equation models revealed that children's perceptions of the family during childhood and adolescence predicted both their health and happiness at age 38. Mothers' perspectives of PFR predicted greater adult children's health, but did not predict their happiness. Associations were independent of family socioeconomic status, gender, intelligence, and extraversion. Moreover, while controlling for behavior problems (proxy for health) and happiness at age 17, both children's and mothers' early PFR related to PFR at 38 years, which in turn, predicted increased health and happiness at age 38, thus providing evidence for a pathway underlying this long-term connection. Our prospective findings revealed that families in which members get along well and support each other during the childhood and adolescent years furnish a foundation for positive family relationships in adulthood, which are associated with greater health and happiness. (PsycInfo Database Record (c) 2022 APA, all rights reserved).
... The second limitation of averaging scores within dyads is the power of the hypothesis tests (Krull & MacKinnon, 2001). To eliminate this concern, we ran a sensitivity analysis, which suggests that we have sufficient power to detect a small effect size. 4. The repeated-measures actor-partner interdependence model (RM-APIM; Cook & Kenny, 2005;Perry et al., 2017) is a good approach to examine how Player A's actions affect Player B's actions. However, one of the most important assumptions of the RM-APIM is that dyad members are distinguishable (Kenny et al., 2006;Perry et al., 2017). ...
... To eliminate this concern, we ran a sensitivity analysis, which suggests that we have sufficient power to detect a small effect size. 4. The repeated-measures actor-partner interdependence model (RM-APIM; Cook & Kenny, 2005;Perry et al., 2017) is a good approach to examine how Player A's actions affect Player B's actions. However, one of the most important assumptions of the RM-APIM is that dyad members are distinguishable (Kenny et al., 2006;Perry et al., 2017). Theoretically, Player A and Player B are indistinguishable as both players come from the same cultural setting and engage in the same type of game. ...
Reciprocity is a fundamental mechanism for sustained social relationships. Escalation-based theories suggest that reciprocity intensifies over time. In contrast, equity-based theories propose that people reciprocate behaviors in kind. We reconcile these conflicting perspectives by examining social exchanges across different cultural contexts. Using three complementary experiments, we investigate when, how, and why individuals in East Asian settings and those in North American settings differentially reciprocate positive versus negative behaviors over time. Study 1 demonstrated that in positively framed exchanges (i.e., giving) Americans escalated their reciprocity, but Singaporeans reciprocated in kind. However, in negatively framed exchanges (i.e., taking), Singaporeans escalated their reciprocity, but Americans reciprocated in kind. Study 2 replicated the results using Hong Kongers and showed that cultural differences in regulatory focus were associated with specific emotions (i.e., anxiety and happiness), which then escalated reciprocity. To establish causality, Study 3 manipulated regulatory focus within one culture and replicated the pattern of results.
... The outcome for these APIM models is a change score representing the difference between an individual's raw f 0 at a particular point in time and the individual's raw f 0 at the prior point in time, or t − (t − 1)(Perry et al., 2017). ...
Communication has long been associated with the well-being of a couple's relationship, and it is also important to explore associations with individual well-being. This study examined the associations between emotions communicated within couple interactions and each partner's psychopathology symptoms concurrently and up to 3 years later. Vocally-encoded emotional arousal (f₀) was measured during couples' (N = 56) conversations. Analyses examined each partner's trajectories of f₀ and how each partner influenced the other's f₀ across the conversation. The findings indicated that women experienced higher symptoms if they (a) decreased more steeply in f₀ overall and (b) returned to their baseline in f₀ more quickly. Moreover, women had higher symptoms if they had a steeper return to baseline because of men's elevated f₀. In contrast, men experienced higher symptoms when men (a) more slowly returned to baseline and (b) changed their f₀ trajectory because of women's elevated f₀. That is, women who expressed less emotional arousal, independently and as a result of the influence of their male partner, experienced more symptoms. In contrast, men's symptoms were differentially associated with their own independent experience of emotional arousal (in which he experienced fewer symptoms when changing arousal more quickly) from how they responded to women's arousal. Given how differently men's and women's psychopathology were associated with emotional expression, these findings raise questions about how partners can communicate to protect their own and their partner's mental health in the short- and long-term. (PsycInfo Database Record (c) 2021 APA, all rights reserved).
... For example, couples, strangers, team members, and patient-therapist dyads tend to synchronize their heart rates and skin conductance during interactions (see Palumbo et al., 2017 for review) and this occurs in multiple behavioral modalities too (e.g., Louwerse, Dale, Bard, & Jeuniaux, 2012). Increasingly, researchers have linked various forms of interpersonal coordination to important constructs and outcomes in several areas including team work (Chanel et al., 2013;Gorman, 2014;Gorman et al., 2016;Guastello & Peressini, 2017;Likens et al., 2014;Wiltshire et al., 2018Wiltshire et al., , 2019, relationship science (Butler, 2011;Gottman, 2014;Perry et al., 2017;Randall et al., 2013), conversational dynamics (Abney et al., 2015;Fusaroli & Tylén, 2016), and clinical psychology (Crowell et al., 2017;Ramseyer & Tschacher, 2016;Ramseyer & Tschacher, 2011Wiltshire, Philipsen, et al., 2020). ...
Social interactions are pervasive in human life with varying forms of interpersonal coordination emerging and spanning different modalities (e.g., behaviors, speech/language, and neurophysiology). However, during social interactions, as in any dynamical system, patterns of coordination form and dissipate at different scales. Historically, researchers have used aggregate measures to capture coordination over time. While those measures (e.g., mean relative phase, cross-correlation, coherence) have provided a wealth of information about coordination in social settings, some evidence suggests that multiscale coordination may change over the time course of a typical empirical observation. To address this gap, we demonstrate an underutilized method, windowed multiscale synchrony, that moves beyond quantifying aggregate measures of coordination by focusing on how the relative strength of coordination changes over time and the scales that comprise social interaction. This method involves using a wavelet transform to decompose time series into component frequencies (i.e., scales), preserving temporal information and then quantifying phase synchronization at each of these scales. We apply this method to both simulated and empirical interpersonal physiological and neuromechanical data. We anticipate that demonstrating this method will stimulate new insights on the mechanisms and functions of synchrony in interpersonal contexts using neurophysiological and behavioral measures.
Interpersonal risk and resilience factors are prominent in current conceptual models of suicide. A growing body of empirical evidence links suicidal thoughts and behaviors to a range of interpersonal phenomenon adding further support to the value of this line of inquiry. At present, research on interpersonal phenomenon focuses on assessing individuals' perceptions of interpersonal phenomenon, such as appraisals of burdensomeness, experienced loneliness, and thwarted belongingness. As this line of research continues to develop, we argue that it would be valuable to consider incorporating conceptual models of interpersonal phenomenon and corresponding methodological approaches from closely allied fields. After providing a brief overview of interpersonal models of suicide, we present an introduction to conceptual models of interpersonal phenomenon developed in relationship science, describe how these models can be applied to the study of interpersonal phenomenon in suicide research, and close with a guided tutorial on data collection and statistical analysis methods for testing hypotheses derived from these conceptual approaches. References for additional reading are provided, and the Appendix S1 provides simulated data sets and statistical code for the analyses in the tutorial section.
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).
Background
The aim of this study was to gain a better understanding of interpersonal coordination (i.e., covariation over time) in different modalities (e.g., physiology, language) during psychotherapy and their importance for understanding the dynamics of psychotherapeutic interaction and efficacy.Methods
We conducted a systematic review of all studies examining some form of interpersonal coordination in a psychotherapeutic context.ResultsWe first summarize details of the included studies such as gender composition, therapy types, and methods used. The collation of these studies provided evidence that, during psychotherapeutic contexts, interpersonal coordination occurs in physiology, movements, interpersonal displays, and language/vocalizations. Further, it also showed that movement coordination was most frequently associated with psychotherapy outcomes, physiological coordination was most frequently associated with empathy, and coordination in a variety of modalities including language/vocalizations were most frequently associated with therapeutic alliance.Conclusions
We discuss these results, shortcomings with the current literature, and highlight three crucial questions for future research. Research on interpersonal coordination in psychotherapy has potential to advance the both the research and practice of psychotherapy.
High patient emotional arousal during rationale development for in vivo exposure in CBT for panic disorder with agoraphobia might endanger comprehension of the exposure rationale. Since therapists are supposed to coregulate patients' emotions, this study investigated whether there was evidence of coregulation of vocally encoded emotional arousal, assessed by fundamental frequency (f0), during rationale development. Furthermore, the association of patient f0 stability and therapist coregulation with patients' perceived rationale plausibility was analyzed. N = 197 therapy videos-used to deduct f0-from a multicenter randomized controlled trial evaluating therapist-guided exposure on CBT outcome were analyzed post hoc. Plausibility of the exposure rationale was assessed by patients after its development. This trial-specific rating aggregates plausibility ratings for every manual component in the development of the exposure rationale and showed good internal consistency (Cronbach's alpha = .85). Stability in f0 and its coregulation were calculated using cross-lagged Actor-Partner Interdependence Models (APIMs), and APIM dyad estimates were associated with plausibility using linear regression analyses. Analyses indicated a relative stability in emotional arousal within both patients and therapists. Therapists' f0 had a significant effect on patients in that with therapist covariation, patients' f0 departed from their equilibrium level, while patients' f0 had no effect on therapists. Therapists' f0 covariation was positively associated with rationale plausibility. This study sheds light on interpersonal regulation mechanisms of patients' and therapists' emotional arousal during development of the exposure rationale. It suggests that coregulation of patients' emotional arousal supports patients' perceived rationale plausibility. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
Humans are a social species, wired for relationships. The presence or absence of another has salient effects on human responding. This chapter discusses important considerations for dyadic research, including key concepts and theories, common designs and measures, recent innovations, and unique challenges. Attachment theory is foundational for understanding a range of dyadic relationships, including child-caregiver, peer, and romantic couples. Social baseline theory provides further context regarding how humans utilize relationships to enhance survival potential. Numerous dyadic methods and measures exist, though fewer are designed for peer relationships. Recent innovations have focused on automated coding methods, vocal pitch analysis, and cutting-edge statistics. Common obstacles for dyadic research include participant scheduling, ethical concerns, complex research paradigms, and data set configuration.
This article illustrates new statistical methods for the study of psychological change in married couples. The design involves time-series data on each partner. The analysis combines longitudinal methods for studies of individual change with cross-sectional methods for the study of matched pairs. Each person is viewed as changing over time as a function of an individual growth curve or change function. As in previous studies of individual change, a person's trajectory depends on time-invariant personal background characteristics and time-varying changes in the environment. However, unlike typical studies of individual change, a person's changing psychological profile depends, in part, on the influence of that person's partner. These methods apply directly to other types of longitudinal studies on families (e.g., studies that use teacher and parent reports of a child's social behavior). The methodology is flexible in allowing randomly missing data, varying spacing of time points, unbalanced designs, and time-varying and time-invariant covariates.
Statistical and methodological innovations in the study of change are advancing rapidly, and visual tools have become an important component in model building and testing. Graphical representations such as path diagrams are necessary, but may be insufficient in the case of complex theories and models. Topology is a visual tool that connects theory and testable equations believed to capture the theorized patterns of change. Although some prior work has made use of topologies, these representations have often been generated as a result of the tested models. This article argues that utilizing topology a priori, when developing a theory, and applying analogous statistical models is a prudent method to conduct research. This article reviews topology by demonstrating how to build a topological representation of a theory and recover the implied equations, ultimately facilitating the transition from complex theory to testable model. Finally, topologies can guide researchers as they adjust or expand their theories in light of recent model testing. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
For the study of growth in dyads, methods have been developed to analyze growth at the level of the dyad members. In this article, we present a novel approach that we call the Common Fate Growth Model (CFGM). This model permits an analysis of growth at the level of the dyads when members are either distinguishable (e.g., heterosexual couples) or indistinguishable (e.g., lesbian couples). To estimate the model, we describe the use of structural equation modeling (SEM) for both distinguishable and indistinguishable members. For indistinguishable members and small groups, such as families, we provide details for the use of multilevel SEM (MSEM). For both SEM and MSEM, we address the issue of measurement invariance (MI) and the estimation of group-level means. The models are illustrated with data from couples collected at seven measurement occasions. To aid the estimation of the models, Mplus code and Amos setups are provided. (PsycINFO Database Record (c) 2014 APA, all rights reserved).
Potential moderators of effects in the actor–partner interdependence model (APIM) include variables that vary within dyads, between dyads, or both between and within dyads (i.e., mixed moderators). Another factor in the moderation of the APIM is whether dyads are indistinguishable (e.g., same-sex friendship pairs) or distinguishable (e.g., heterosexual couples). For each possibility, what are the potential moderator effects (up to 8), how they might be estimated and tested, and how they can be interpreted are discussed. Submodels are also presented, based on patterns of moderation of the actor and partner effects, which are statistically simpler, more conceptually meaningful, and more powerful in testing moderator effects. Example analyses illustrate the recommended steps involved in an APIM moderation analysis.
Several authors have proposed the use of multilevel models to analyze data from single-case designs. This article extends that work in 2 ways. First, examples are given of how to estimate these models when the single-case designs have features that have not been considered by past authors. These include the use of polynomial coefficients to model nonlinear change, the modeling of counts (Poisson distributed) or proportions (binomially distributed) as outcomes, the use of 2 different ways of modeling treatment effects in ABAB designs, and applications of these models to alternating treatment and changing criterion designs. Second, issues that arise when multilevel models are used for the analysis of single-case designs are discussed; such issues can form part of an agenda for future research on this topic. These include statistical power and assumptions, applications to more complex single-case designs, the role of exploratory data analyses, extensions to other kinds of outcome variables and sampling distributions, and other statistical programs that can be used to do such analyses. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
Examines procedures previously recommended by various authors for the estimation of "change" scores, "residual," or "basefree" measures of change, and other kinds of difference scores. A procedure proposed by F. M. Lord is extended to obtain more precise estimates, and an alternative to the L. R. Tucker, F. Damarin, and S. A. Messick (see 41:3) procedure is offered. A consideration of the purposes for which change measures have been sought in the past leads to a series of recommended procedures which solve research and personnel-decision problems without estimation of change scores for individuals. (22 ref.) (PsycINFO Database Record (c) 2012 APA, all rights reserved)