Products of Variables in Structural Equation Models.

A general method is introduced in which variables that are products of other variables in the context of a structural equation model (SEM) can be decomposed into the sources of variance due to the multiplicands. The result is a new category of SEM which we call a Products of Variables Model (PoV). Some useful and practical features of PoV models include estimation of interactions between latent variables, latent variable moderators, manifest moderators with missing values, and manifest or latent squared terms. Expected means and covariances are analytically derived for a simple product of two variables and it is shown that the method reproduces previously published results for this special case. It is shown algebraically that using centered multiplicands results in an unidentified model, but if the multiplicands have non-zero means, the result is identified. The method has been implemented in OpenMx and Ωnyx and is applied in five extensive simulations.

Portion size affects food selection in an immersive virtual reality buffet and is related to measured intake in laboratory meals varying in portion size.

A crucial step for validating the utility of an immersive virtual reality (iVR) buffet to study eating behavior is to determine whether variations in food characteristics such as portion size (PS) are relevant predictors of food selection in an iVR buffet. We tested whether manipulating PS in an iVR buffet affects the weight of food selected, and whether this response to PS is similar to participants' measured intake when PS varies at laboratory meals. In a randomized crossover design, 91 adults (18-71 y; 64 females; BMI = 25.3 ± 5.7) used their iVR remote to select lunch and dinner portions from an iVR buffet before consuming a standardized lab meal at two visits separated by one week. The PS in the iVR buffet and lab meals varied between a standard PS and a large PS. This design enabled comparisons of PS effects between iVR and lab settings, despite the scale difference in food weight between the environments. Portion size significantly affected food selection and food intake (p < 0.001). Subjects selected an additional 350 g in iVR and consumed an additional 154 g of food in the lab meals when offered the large portion compared to the small portion. The effect of PS showed a similar percentage increase in iVR (36.5%) and lab meals (39.2%). There was no significant difference in the effect of PS between iVR and lab meals after accounting for scale differences in food weight between the environments. The response to PS was not influenced by subject characteristics such as body mass index, sex, or age. These results demonstrate the utility of iVR for replicating real-world eating behaviors and enhancing our understanding of the intricate dynamics of food-related behaviors in a variety of contexts.

Validation of computational models to characterize cumulative intake curves from video-coded meals.

Introduction: Observational coding of eating behaviors (e.g., bites, eating rate) captures behavioral characteristics but is limited in its ability to capture dynamic patterns (e.g., temporal changes) across a meal. While the Universal Eating Monitor captures dynamic patterns of eating through cumulative intake curves, it is not commonly used in children due to strict behavioral protocols. Therefore, the objective of this study was to test the ability of computational models to characterize cumulative intake curves from video-coded meals without the use of continuous meal weight measurement. Methods: Cumulative intake curves were estimated using Kisslieff's Quadratic model and Thomas's logistic ordinary differential equation (LODE) model. To test if cumulative intake curves could be characterized from video-coded meals, three different types of data were simulated: (1) Constant Bite: simplified cumulative intake data; (2) Variable Bite: continuously measured meal weight data; and (3) Bite Measurement Error: video-coded meals that require the use of average bite size rather than measured bite size. Results: Performance did not differ by condition, which was assessed by examining model parameter recovery, goodness of fit, and prediction error. Therefore, the additional error incurred by using average bite size as one would with video-coded meals did not impact the ability to accurately estimate cumulative intake curves. While the Quadratic and LODE models were comparable in their ability to characterize cumulative intake curves, the LODE model parameters were more distinct than the Quadradic model. Greater distinctness suggests the LODE model may be more sensitive to individual differences in cumulative intake curves. Discussion: Characterizing cumulative intake curves from video-coded meals expands our ability to capture dynamic patterns of eating behaviors in populations that are less amenable to strict protocols such as children and individuals with disordered eating. This will improve our ability to identify patterns of eating behavior associated with overconsumption and provide new opportunities for treatment.

The ILHBN: challenges, opportunities, and solutions from harmonizing data under heterogeneous study designs, target populations, and measurement protocols.

The ILHBN is funded by the National Institutes of Health to collaboratively study the interactive dynamics of behavior, health, and the environment using Intensive Longitudinal Data (ILD) to (a) understand and intervene on behavior and health and (b) develop new analytic methods to innovate behavioral theories and interventions. The heterogenous study designs, populations, and measurement protocols adopted by the seven studies within the ILHBN created practical challenges, but also unprecedented opportunities to capitalize on data harmonization to provide comparable views of data from different studies, enhance the quality and utility of expensive and hard-won ILD, and amplify scientific yield. The purpose of this article is to provide a brief report of the challenges, opportunities, and solutions from some of the ILHBN's cross-study data harmonization efforts. We review the process through which harmonization challenges and opportunities motivated the development of tools and collection of metadata within the ILHBN. A variety of strategies have been adopted within the ILHBN to facilitate harmonization of ecological momentary assessment, location, accelerometer, and participant engagement data while preserving theory-driven heterogeneity and data privacy considerations. Several tools have been developed by the ILHBN to resolve challenges in integrating ILD across multiple data streams and time scales both within and across studies. Harmonization of distinct longitudinal measures, measurement tools, and sampling rates across studies is challenging, but also opens up new opportunities to address cross-cutting scientific themes of interest.

Health behavior changes, such as prevention of suicidal thoughts and behaviors, smoking, drug use, and alcohol use; and the promotion of mental health, sleep, and physical activities, and decreases in sedentary behavior, are difficult to sustain. The ILHBN is a cooperative agreement network funded jointly by seven participating units within the National Institutes of Health to collaboratively study how factors that occur in individuals' everyday life and in their natural environment influence the success of positive health behavior changes. This article discusses how information collected using smartphones, wearables, and other devices can provide helpful active and passive reflections of the participants' extent of risk and resources at the moment for an extended period of time. However, successful engagement and retention of participants also require tailored adaptations of study designs, measurement tools, measurement intervals, study span, and device choices that create hurdles in integrating (harmonizing) data from multiple studies. We describe some of the challenges, opportunities, and solutions that emerged from harmonizing intensive longitudinal data under heterogeneous study and participant characteristics within the ILHBN, and share some tools and recommendations to facilitate future data harmonization efforts.

Triangulating on developmental models with a combination of experimental and nonexperimental estimates.

Plausible competing developmental models show similar or identical structural equation modeling model fit indices, despite making very different causal predictions. One way to help address this problem is incorporating outside information into selecting among models. This study attempted to select among developmental models of children's early mathematical skills by incorporating information about the extent to which models forecast the longitudinal pattern of causal impacts of early math interventions. We tested for the usefulness and validity of the approach by applying it to data from three randomized controlled trials of early math interventions with longitudinal follow-up assessments in the United States (Ns = 1,375, 591, 744; baseline age 4.3, 6.5, 4.4; 17%-69% Black). We found that, across data sets, (a) some models consistently outperformed other models at forecasting later experimental impacts, (b) traditional statistical fit indices were not strongly related to causal fit as indexed by models' accuracy at forecasting later experimental impacts, and (c) models showed consistent patterns of similarity and discrepancy between statistical fit and models' effectiveness at forecasting experimental impacts. We highlight the importance of triangulation and call for more comparisons of experimental and nonexperimental estimates for choosing among developmental models. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Prefrontal cortical response to natural rewards and self-reported anhedonia are associated with greater craving among recently withdrawn patients in residential treatment for opioid use disorder.

Both anhedonia and craving are common among patients with opioid use disorder (OUD), and are associated with vulnerability to relapse. Although these constructs are theoretically linked relatively few studies have examined them together. In the current study, recently withdrawn patients (N = 71) in residential treatment for prescription OUD underwent a cue reactivity paradigm while being monitored with functional near-infrared spectroscopy (fNIRS). Patients also self-reported symptoms of anhedonia via the Snaith-Hamilton Pleasure Scale (SHAPS), while smartphone-based ecological momentary assessments (EMA) were used to measure craving levels. On average, lower right prefrontal cortex (PFC) activity in response to positive social stimuli was associated with higher craving (ß = - 2.87; S.E. = 1.23; p = 0.02). Self-reported anhedonia moderated the association between PFC activity and craving (ß = - 1.02; S.E. = 0.48; p = 0.04), such that patients with two or more anhedonic symptoms had a significant and stronger negative association between PFC activation to hedonically positive images and craving, compared to patients with fewer than two anhedonic symptoms, among whom the association was not significant. This finding provides evidence that higher levels of anhedonia among patients in residential treatment for OUD are associated with a stronger link between lower PFC response to positive social experiences and higher levels of craving, potentially increasing overall vulnerability to relapse.

Subjective and objective difficulty of emotional facial expression perception from dynamic stimuli.

This study aimed to discover predictors of subjective and objective difficulty in emotion perception from dynamic facial expressions. We used a multidimensional emotion perception framework, in which observers rated the perceived emotion along a number of dimensions instead of choosing from traditionally-used discrete categories of emotions. Data were collected online from 441 participants who rated facial expression stimuli in a novel paradigm designed to separately measure subjective (self-reported) and objective (deviation from the population consensus) difficulty. We targeted person-specific (sex and age of observers and actors) and stimulus-specific (valence and arousal values) predictors of those difficulty scores. Our findings suggest that increasing age of actors makes emotion perception more difficult for observers, and that perception difficulty is underestimated by men in comparison to women, and by younger and older adults in comparison to middle-aged adults. The results also yielded an increase in the objective difficulty measure for female observers and female actors. Stimulus-specific factors-valence and arousal-exhibited quadratic relationships with subjective and objective difficulties: Very positive and very negative stimuli were linked to reduced subjective and objective difficulty, whereas stimuli of very low and high arousal were linked to decreased subjective but increased objective difficulty. Exploratory analyses revealed low relevance of person-specific variables for the prediction of difficulty but highlighted the importance of valence in emotion perception, in line with functional accounts of emotions. Our findings highlight the need to complement traditional emotion recognition paradigms with novel designs, like the one presented here, to grasp the "big picture" of human emotion perception.

Do I look like I'm sure?: Partial metacognitive access to the low-level aspects of one's own facial expressions.

As humans we communicate important information through fine nuances in our facial expressions, but because conscious motor representations are noisy, we might not be able to report these fine movements. Here we measured the precision of the explicit metacognitive information that young adults have about their own facial expressions. Participants imitated pictures of themselves making facial expressions and triggered a camera to take a picture of them while doing so. They then rated how well they thought they imitated each expression. We defined metacognitive access to facial expressions as the relationship between objective performance (how well the two pictures matched) and subjective performance ratings. As a group, participants' metacognitive confidence ratings were only about four times less precise than their own similarity ratings. In turn, machine learning analyses revealed that participants' performance ratings were based on idiosyncratic subsets of features. We conclude that metacognitive access to one's own facial expressions is only partial.

Evaluating measurement of longitudinal education data using the Measurement Model of Derivatives.

The Measurement Model of Derivatives (MMOD; Estabrook, 2015) provides the opportunity to evaluate and refine measurement scales used in longitudinal studies to clarify their theoretical distinctions and relationship to academic achievement. We demonstrate this using three teacher-rated scales of child self-regulatory behavior obtained from the Early Childhood Longitudinal Study Kindergarten Class of 2010-11 (ECLS-K:2011; Tourangeau et al., 2019). Data-driven factor structures were generated using a training sample (N = 2821), then compared using the MMOD to the theoretical measurement structure on a holdout sample (N = 2822). Finally, to externally validate their utility, the best-fitting data-driven measurement structure was compared to the theoretical structure in their ability to predict academic achievement on a validation sample (N = 5643). We discuss theoretical implications for self-regulation, as well as the MMODs applicability to other educational data sets.

Associations Between Traumatic Stress, Brain Volumes and Post-traumatic Stress Disorder Symptoms in Children: Data from the ABCD Study.

Reduced volumes in brain regions of interest (ROIs), primarily from adult samples, are associated with posttraumatic stress disorder (PTSD). We extended this work to children using data from the Adolescent Brain Cognitive Development (ABCD) Study® (N = 11,848; Mage = 9.92). Structural equation modeling and an elastic-net (EN) machine-learning approach were used to identify potential effects of traumatic events (TEs) on PTSD symptoms (PTSDsx) directly, and indirectly via the volumes 300 subcortical and cortical ROIs. We then estimated the genetic and environmental variation in the phenotypes. TEs were directly associated with PTSDsx (r = 0.92) in children, but their indirect effects (r < 0.0004)-via the volumes of EN-identified subcortical and cortical ROIs-were negligible at this age. Additive genetic factors explained a modest proportion of the variance in TEs (23.4%) and PTSDsx (21.3%), and accounted for most of the variance of EN-identified volumes of four of the five subcortical (52.4-61.8%) three of the nine cortical ROIs (46.4-53.3%) and cerebral white matter in the left hemisphere (57.4%). Environmental factors explained most of the variance in TEs (C = 61.6%, E = 15.1%), PTSDsx (residual-C = 18.4%, residual-E = 21.8%), right lateral ventricle (C = 15.2%, E = 43.1%) and six of the nine EN-identified cortical ROIs (C = 4.0-13.6%, E = 56.7-74.8%). There is negligible evidence that the volumes of brain ROIs are associated with the indirect effects of TEs on PTSDsx at this age. Overall, environmental factors accounted for more of the variation in TEs and PTSDsx. Whereas additive genetic factors accounted for most of the variability in the volumes of a minority of cortical and in most of subcortical ROIs.

Using factorial mediation analysis to better understand the effects of interventions.

To improve understanding of how interventions work or why they do not work, there is need for methods of testing hypotheses about the causal mechanisms underlying the individual and combined effects of the components that make up interventions. Factorial mediation analysis, i.e., mediation analysis applied to data from a factorial optimization trial, enables testing such hypotheses. In this commentary, we demonstrate how factorial mediation analysis can contribute detailed information about an intervention's causal mechanisms. We briefly review the multiphase optimization strategy (MOST) and the factorial experiment. We use an empirical example from a 25 factorial optimization trial to demonstrate how factorial mediation analysis opens possibilities for better understanding the individual and combined effects of intervention components. Factorial mediation analysis has important potential to advance theory about interventions and to inform intervention improvements.

Effectiveness and Utility of Mobile Device Assessment of Subjective Craving during Residential Opioid Dependence Treatment.

Background: Craving is a dynamic state that is both theoretically and empirically linked to relapse in addiction. Static measures cannot adequately capture the dynamic nature of craving, and research has shown that these measures are limited in their capacity to link craving to treatment outcomes. Methods: The current study reports on assessments of craving collected 4x-day across 12 days from 73 patients in residential treatment for opioid dependence. Analyses investigated whether the within-person assessments yielded expected across- and within-day variability, whether levels of craving changed across and within days, and, finally, whether individual differences in craving variability predicted post-residential treatment relapse. Results: Preliminary analyses found acceptable levels of data entry compliance and reliability. Consistent with expectations, craving varied both between (46%) and within persons, with most within-person variance (over 40%) existing within days. Other patterns that emerged indicated that, on average, craving declined across the 12-days of assessment, and was generally strongest at mid-day. Analyses also found that patients' person-level craving variability predicted post-treatment relapse, above and beyond their mean levels of craving. Conclusion: Analyses support the reliability, sensitivity, and potential utility of the 4x-day, 12-day assessment protocol for measuring craving during residential treatment.

Using association rules mining to characterize loss of control eating in childhood.

Childhood loss of control (LOC)-eating, the perceived inability to stop or control eating, is associated with increased risk for binge-eating disorder and obesity. However, the correlates of LOC-eating in childhood remain unclear. A secondary analysis of 177, 7-12-year-old children from five laboratory feeding studies was performed to investigate potential family (e.g., frequency of meals together, feeding practices), parental (e.g., education, weight status), and child (e.g., weight status, appetite traits) correlates of LOC-eating. Association rules mining (ARM1), a data-driven approach, was used to examine all characteristics that were common across studies to identify which were associated with LOC-eating. Results showed LOC-eating was characterized by a combination of child appetitive behaviors and parental feeding practices. In particular, LOC-eating was associated with low parental pressure to eat in combination with a high propensity to want to eat all the time and frequent refusal or dislike of novel foods. This pattern of both food approach (i.e., wanting to eat all the time) and avoidant behaviors (i.e., food fussiness) highlights the need for more research to characterize the complex patterns of appetitive traits associated with LOC-eating. In contrast, the absence of LOC-eating was associated with a low propensity to want to eat all the time, greater family income, and infrequent emotional overeating. Therefore, propensity to want to eat all the time, a single question from the Children's Eating Behavior Questionnaire, characterized both the presence and absence of LOC-eating, highlighting the need for more research to determine if this question captures clinically relevant individual differences. Future studies addressing these questions will advance our understanding of pediatric LOC-eating and may lead to interventions to reduce risk for more severe eating disorder symptomology.

Daily meaningfulness among patients with opioid use disorder: Examining the role of social experiences during residential treatment and links with post-treatment relapse.

BACKGROUND: A sense of meaningfulness is an important initial indicator of the successful treatment of addiction, and supports the larger recovery process. Most studies address meaningfulness as a static trait, and do not assess the extent to which meaningfulness might vary within an individual, or how it may vary in response to daily life events such as social experiences. METHODS: Ecological momentary assessment (EMA) was used to: 1) examine the amount of within-person variability in meaningfulness among patients in residential treatment for prescription opioid use disorder; 2) determine whether that variability was related to positive or negative social experiences on a daily basis; and 3) assess whether those day-to-day relationships were related to relapse at four months post-treatment. Participants (N = 73, 77% male, Mage = 30.10, Range = 19-61) completed smartphone-based assessments four times per day for 12 days. Associations among social experiences, meaningfulness, and relapse were examined using multilevel modeling. RESULTS: Between-person variability accounted for 52% (95% CI = 0.35, 0.67) of variance in end-of-day meaningfulness. End-of-day meaningfulness was higher on days when participants reported more positive social experiences (ß = 1.17, SE = 0.33, p < .05, ΔR2 = 0.041). On average, participants who relapsed within four months post-residential treatment exhibited greater within-day reactivity to negative social experiences (ß = -1.89, SE = 0.88, p < .05, ΔR2 = 0.024) during treatment than participants who remained abstinent. CONCLUSION: Individual differences in maintaining meaningfulness day by day when faced with negative social experiences may contribute to the risk of relapse in the early months following residential treatment.

How Much of Me Do I See in Other Minds? Modulating Egocentricity in Emotion Judgments by tDCS.

When inferring the mental states of others, individuals' judgments are influenced by their own state of mind, an effect often referred to as egocentricity. Self-other differentiation is key for an accurate interpretation of other's mental states, especially when these differ from one's own states. It has been suggested that the right supramarginal gyrus (rSMG) is causally involved in overcoming egocentricity in the affective domain. In a double-blind randomized study, 47 healthy adults received anodal (1 mA, 20 min) or sham transcranial direct current stimulation (tDCS) to the rSMG prior to performing a newly developed paradigm, the self-other facial emotion judgment (SOFE) task. In this task, participants made judgments of facial emotional expressions while having been previously confronted with congruent or incongruent emotion-inducing situations. To differentiate between emotional and cognitive egocentricity, participants additionally completed an established visual perspective-taking task. Our results confirmed the occurrence of emotional egocentric biases during the SOFE task. No conclusive evidence of a general role of the rSMG in emotional egocentricity was found. However, active as compared to sham tDCS induced descriptively lower egocentric biases when judging incongruent fearful faces, and stronger biases when judging incongruent happy faces, suggesting emotion-specific tDCS effects on egocentric biases. Further, we found significant tDCS effects on cognitive egocentricity. Results of the present study expanded our understanding of emotional egocentricity and point towards emotion-specific patterns of the underlying functionality.

Capturing emotion coherence in daily life: Using ambulatory physiology measures and ecological momentary assessments to examine within-person associations and individual differences.

While emotion coherence has long been theorized to be a core feature of emotion, to date, studies examining response coherence have been conducted in laboratory settings. The present study used a combined approach of ambulatory physiology measures and ecological momentary assessment conducted over a 4-week period to examine the extent to which emotional experience and physiology show coherence in daily life within-persons; and whether individual differences in response coherence are associated with between-person differences in well-being, negative emotionality, and gender. Results revealed that, on average, individuals exhibited coherence between subjective experience and physiology of emotion, but that there was substantial between-person variation in coherence in daily life. Exploratory analyses revealed no credible link between levels of response coherence and well-being, negative emotionality, or gender. Findings contribute to the literature by demonstrating a novel methodological approach to measuring coherence in daily life and supporting the generalizability of coherence to ecologically valid contexts.

The Effects of Selective Survival on Black Adults' Cognitive Development.

OBJECTIVES: The theory of selective survival suggests that possibly around 70-75 years of age, Blacks may display substantive changes in their pattern of cognitive decline. This study examined the age-graded pattern of cognitive decline within older Blacks by describing a trend that characterizes differences in the change of cognitive decline from ages 51.5 to 95.5, and hypothesized that this age-graded pattern is nonlinear. METHOD: Utilizing 2 waves of longitudinal data from the Baltimore Study of Black Aging, this study used multilevel modeling to test whether the interaction between age and the 3-year study period (time between waves) had a positive effect on changes in inductive reasoning, declarative memory, working memory, and perceptual speed. RESULTS: A significant positive interaction between age and wave was found for inductive reasoning, demonstrating an age-grade pattern of change/decline in cognitive pattern for Blacks aged 51.5-95.4. Simple slope probing via the Johnson-Neyman Technique suggested that Black adults ~64 years and younger experienced significant decline in inductive reasoning across study time, whereas for those older than 63.71, the decline was nonsignificant. No significant age-wave interactions were found for declarative memory, working memory, or perceptual speed. DISCUSSION: Findings suggest a selective survival effect for inductive reasoning ability among Blacks. With decline evident so early, common cognitive intervention programs targeting adults 65+ may come too late for Blacks, signifying the importance and urgency for early health interventions and public policy designed to promote cognitive reserve.

Daily associations among craving, affect, and social interactions in the lives of patients during residential opioid use disorder treatment.

OBJECTIVE: This study captured the interrelationships among craving, negative affect, and positive and negative social exchanges in the daily lives of patients in residential treatment for opioid use disorders (OUDs). METHOD: Participants were 73 patients (77% male), age 19 to 61 (Mage = 30.10, SDage = 10.13) in residential treatment for OUD. Participants completed a smartphone-based survey 4 times per day for 12 consecutive days that measured positive and negative social exchanges (Test of Negative Social Exchange), negative affect (PA-NA scales), and craving (frequency and intensity). Within-person, day-level associations among daily positive and negative social exchanges, negative affect, and craving were examined using multilevel modeling. RESULTS: Daily negative social exchanges (M = 1.44, SD = 2.27) were much less frequent than positive social exchanges (M = 6.59, SD = 4.00) during residential treatment. Whereas negative social exchanges had a direct association with same-day craving (ß = 0.08; 95% CI = 0.01, 0.16, ΔR2 = 0.01), positive social exchanges related to craving indirectly via moderation of the within-person negative affect-craving link (ß = -0.01; 95% CI = -0.01, -0.001, ΔR2 = 0.002). Positive social exchanges decoupled the same-day linkage between negative affect and craving on days when individuals had at least four more positive social exchanges than usual. CONCLUSIONS: These results indicate that both negative affect and negative social exchanges are uniquely related to craving on a daily basis, and that extra positive social interactions can reduce the intraindividual coupling of negative affect and craving during residential treatment for OUD. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Distance to the Neutral Face Predicts Arousal Ratings of Dynamic Facial Expressions in Individuals With and Without Autism Spectrum Disorder.

Arousal is one of the dimensions of core affect and frequently used to describe experienced or observed emotional states. While arousal ratings of facial expressions are collected in many studies it is not well understood how arousal is displayed in or interpreted from facial expressions. In the context of socioemotional disorders such as Autism Spectrum Disorder, this poses the question of a differential use of facial information for arousal perception. In this study, we demonstrate how automated face-tracking tools can be used to extract predictors of arousal judgments. We find moderate to strong correlations among all measures of static information on one hand and all measures of dynamic information on the other. Based on these results, we tested two measures, average distance to the neutral face and average facial movement speed, within and between neurotypical individuals (N = 401) and individuals with autism (N = 19). Distance to the neutral face was predictive of arousal in both groups. Lower mean arousal ratings were found for the autistic group, but no difference in correlation of the measures and arousal ratings could be found between groups. Results were replicated in an high autistic traits group. The findings suggest a qualitatively similar perception of arousal for individuals with and without autism. No correlations between valence ratings and any of the measures could be found, emphasizing the specificity of our tested measures. Distance and speed predictors share variability and thus speed should not be discarded as a predictor of arousal ratings.

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).