Linking Affect Dynamics and Well-Being: A Novel Methodological Approach for Mental Health.

Emotions are dynamic processes; their variability relates to psychological well-being and psychopathology. Affective alterations have been linked to mental diseases like depression, although little is known about how similar patterns occur in healthy individuals. This study investigates the psychophysiological correlations of emotional processing in healthy subjects, specifically exploring the relationship between depressive traits, cognitive distortions, and facial electromyographic (f-EMG) responses during affective transitions. A cohort of 44 healthy participants underwent f-EMG recording while viewing emotional images from the International Affective Picture System (IAPS). Self-report measures included the Beck Depression Inventory (BDI) and the Cognitive Distortion Scale (CDS). Higher BDI scores were associated with increased EMG activity in the corrugator muscle during transitions between positive and negative emotional states. Cognitive distortions such as Catastrophizing, All-or-Nothing Thinking, and Minimization showed significant positive correlations with EMG activity, indicating that individuals with higher levels of these distortions experienced greater facial muscle activation during emotional transitions. This study's results indicate that there is a bidirectional correlation between depressed features and cognitive distortions and alterations in facial emotional processing, even in healthy subjects. Facial EMG in the context of dynamic affective transitions has the potential to be used as a non-invasive method for detecting abnormal emotional reactions at an early stage. This might help in identifying individuals who are at risk of developing depression and guide therapies to prevent its advancement.

Temporal Dynamics of Positive and Negative Affect in Adolescents: Associations with Depressive Disorders and Risk.

Alterations in dynamic affective processes are associated with dysregulated affect and depression. Although depression is often associated with heightened inertia (i.e., greater moment-to-moment correlation) and variability (i.e., larger departures from typical levels) of affect in adults, less is known about whether altered affect dynamics are present in youth at risk for depression. This study investigated the association of clinical depression and depression risk with the inertia and variability of positive and negative affect in a sample of youth at varying risk for depression. Our sample included 147 adolescents aged 14 to 17, categorized into three groups: never-depressed lower-risk, never-depressed higher-risk (based on maternal history of depression), and currently depressed adolescents. Adolescents completed ecological momentary assessments of positive and negative affect up to seven times per day for a week. Multilevel models and ANOVAs were used to examine associations of affective inertia and variability with adolescent depression and risk based on maternal history, controlling for average affect. Depressed adolescents showed more inert and diminished positive affect, and more variable and elevated negative affect compared to lower- and higher-risk youth, though associations attenuated after controlling for average affect. No differences were identified between never-depressed higher-risk and lower-risk youth. Additional longitudinal studies are needed to evaluate whether altered affect dynamics in daily life precede depression onset to understand their utility for developing preventive interventions.

Irritability: associations with real-time affect dynamics, social interactions, and daily substance use in older adolescents.

Irritability is a common and clinically significant symptom associated with a wide range of negative outcomes. Ecological Momentary Assessment (EMA) is a valuable tool for capturing experiences, such as emotions, social interactions, and substance use in real-time, and may be useful in understanding how irritability is related to everyday functioning. We investigated cross-sectional associations between a widely used self-report irritability rating scale and affect dynamics, social interactions, and substance use captured with EMA (5 surveys daily for 14 days) in 349 18-year-olds. We also examined the associations of self- and parent-reported irritability at ages 12 and 15 with the age 18 EMA variables to explore whether these relationships persist over time. Youth-reported irritability at age 18 was linked to greater intensity, variability, and inertia of irritability, sadness, and anxiety, less positive and more negative interpersonal experiences, and greater cigarette and drug use. Most effect sizes were in the medium-small range. Associations of youth- and parent-reported irritability at ages 12 and 15 with the age 18 EMA measures were generally similar, although smaller in magnitude. Findings contribute to understanding how irritability is manifested in real-time affect dynamics and interpersonal functioning, as well as daily substance use. Most effects were evident over the course of up to 6 years - that is, early adolescent irritability, reported by both youth and their parents, was associated with similar real-time affect dynamics and interpersonal experiences at age 18. This study contributes to the literature on the developmental psychopathology of irritability by extending findings to everyday functioning.

Mean Affect Moderates the Association between Affect Variability and Mental Health.

Increasing evidence suggests that within-person variation in affect is a dimension distinct from mean levels along which individuals can be characterized. This study investigated affect variability's association with concurrent and longitudinal mental health and how mean affect levels moderate these associations. The mental health outcomes of depression, panic disorder, self-rated mental health, and mental health professional visits from the second and third waves of the Midlife in the United States Study were used for cross-sectional (n = 1,676) and longitudinal outcomes (n = 1,271), respectively. These participants took part in the National Study of Daily Experiences (NSDE II), where they self-reported their affect once a day for 8 days, and this was used to compute affect mean and variability. Greater positive affect variability cross-sectionally predicted a higher likelihood of depression, panic disorder, mental health professional use, and poorer self-rated mental health. Greater negative affect variability predicted higher panic disorder probability. Longitudinally, elevated positive and negative affect variability predicted higher depression likelihood and worse self-rated mental health over time, while greater positive affect variability also predicted increased panic disorder probability. Additionally, mean affect moderated associations between variability and health such that variability-mental health associations primarily took place when mean positive affect was high (for concurrent mental health professional use and longitudinal depression) and when mean negative affect was low (for concurrent depression, panic disorder, self-rated mental health, and longitudinal self-rated mental health). Taken together, affect variability may have implications for both short- and long-term health and mean levels should be considered. Supplementary Information: The online version contains supplementary material available at 10.1007/s42761-024-00238-0.

Characterizing the momentary association between loneliness, depression, and social interactions: Insights from an ecological momentary assessment study.

Evidence suggests that loneliness causes people to feel more depressed. It is unknown, however, why this association occurs and whether momentary versus chronic experiences of loneliness are implicated. Theoretical accounts suggest that momentary feelings of loneliness produce two competing motivations: social reaffiliation and social withdrawal. Social affiliation is protective against depression; social withdrawal, in contrast, is a risk factor. Thus, engaging in frequent and high-quality interactions following experiences of loneliness may protect against subsequent depression. We tested this hypothesis using a random-interval experience sampling design (5x/day/day, 14 days; Nobs = 6568) with a racially/ethnically diverse sample of adults with elevated depression symptoms (N = 102). Momentary loneliness was associated with depressed mood at the same time point and âˆ¼2.5h and âˆ¼5h later. Frequency and quality of social interaction did not moderate these associations. Findings suggest that momentary feelings of loneliness may be an important target for clinical intervention.

Multilevel Latent Differential Structural Equation Model with Short Time Series and Time-Varying Covariates: A Comparison of Frequentist and Bayesian Estimators.

Continuous-time modeling using differential equations is a promising technique to model change processes with longitudinal data. Among ways to fit this model, the Latent Differential Structural Equation Modeling (LDSEM) approach defines latent derivative variables within a structural equation modeling (SEM) framework, thereby allowing researchers to leverage advantages of the SEM framework for model building, estimation, inference, and comparison purposes. Still, a few issues remain unresolved, including performance of multilevel variations of the LDSEM under short time lengths (e.g., 14 time points), particularly when coupled multivariate processes and time-varying covariates are involved. Additionally, the possibility of using Bayesian estimation to facilitate the estimation of multilevel LDSEM (M-LDSEM) models with complex and higher-dimensional random effect structures has not been investigated. We present a series of Monte Carlo simulations to evaluate three possible approaches to fitting M-LDSEM, including: frequentist single-level and two-level robust estimators and Bayesian two-level estimator. Our findings suggested that the Bayesian approach outperformed other frequentist approaches. The effects of time-varying covariates are well recovered, and coupling parameters are the least biased especially using higher-order derivative information with the Bayesian estimator. Finally, an empirical example is provided to show the applicability of the approach.

Daily Levels and Dynamic Metrics of Affective-Cognitive Constructs Associate With Suicidal Thoughts and Behaviours in Adults After Psychiatric Hospitalization.

The period after psychiatric hospitalization is an extraordinarily high-risk period for suicidal thoughts and behaviours (STBs). Affective-cognitive constructs (ACCs) are salient risk factors for STBs, and intensive longitudinal metrics of these constructs may improve personalized risk detection and intervention. However, limited research has examined how within-person daily levels and between-person dynamic metrics of ACCs relate to STBs after hospital discharge. Adult psychiatric inpatients (N = 95) completed a 65-day ecological momentary assessment protocol after discharge as part of a 6-month follow-up period. Using dynamic structural equation models, we examined both within-person daily levels and between-person dynamic metrics (intensity, variability and inertia) of positive and negative affect, rumination, distress intolerance and emotion dysregulation as risk factors for STBs. Within-person lower daily levels of positive affect and higher daily levels of negative affect, rumination, distress intolerance and emotion dysregulation were risk factors for next-day suicidal ideation (SI). Same-day within-person higher rumination and negative affect were also risk factors for same-day SI. At the between-person level, higher overall positive affect was protective against active SI and suicidal behaviour over the 6-month follow-up, while greater variability of rumination and distress intolerance increased risk for active SI, suicidal behaviour and suicide attempt. The present study provides the most comprehensive examination to date of intensive longitudinal metrics of ACCs as risk factors for STBs. Results support the continued use of intensive longitudinal methods to improve STB risk detection. Interventions focusing on rumination and distress intolerance may specifically help to prevent suicidal crises during critical transitions in care.

Intraindividual time-varying dynamic network of affects: linear autoregressive mixed-effects models for ecological momentary assessment.

An interesting recent development in emotion research and clinical psychology is the discovery that affective states can be modeled as a network of temporally interacting moods or emotions. Additionally, external factors like stressors or treatments can influence the mood network by amplifying or dampening the activation of specific moods. Researchers have turned to multilevel autoregressive models to fit these affective networks using intensive longitudinal data gathered through ecological momentary assessment. Nonetheless, a more comprehensive examination of the performance of such models is warranted. In our study, we focus on simple directed intraindividual networks consisting of two interconnected mood nodes that mutually enhance or dampen each other. We also introduce a node representing external factors that affect both mood nodes unidirectionally. Importantly, we disregard the potential effects of a current mood/emotion on the perception of external factors. We then formalize the mathematical representation of such networks by exogenous linear autoregressive mixed-effects models. In this representation, the autoregressive coefficients signify the interactions between moods, while external factors are incorporated as exogenous covariates. We let the autoregressive and exogenous coefficients in the model have fixed and random components. Depending on the analysis, this leads to networks with variable structures over reasonable time units, such as days or weeks, which are captured by the variability of random effects. Furthermore, the fixed-effects parameters encapsulate a subject-specific network structure. Leveraging the well-established theoretical and computational foundation of linear mixed-effects models, we transform the autoregressive formulation to a classical one and utilize the existing methods and tools. To validate our approach, we perform simulations assuming our model as the true data-generating process. By manipulating a predefined set of parameters, we investigate the reliability and feasibility of our approach across varying numbers of observations, levels of noise intensity, compliance rates, and scalability to higher dimensions. Our findings underscore the challenges associated with estimating individualized parameters in the context of common longitudinal designs, where the required number of observations may often be unattainable. Moreover, our study highlights the sensitivity of autoregressive mixed-effect models to noise levels and the difficulty of scaling due to the substantial number of parameters.

Associations between affect dynamics and eating regulation in daily life: a preliminary ecological momentary assessment study.

Disordered eating behaviors consistently associated with emotion regulation difficulties. However, most studies have focused on affect intensity without considering dynamic affective patterns. We examined these patterns in relation to daily overeating, loss of control eating (LOCE), dietary restraint, and food craving in young adults using ecological momentary assessment (EMA).Adults (N = 24) completed a 10-day EMA protocol during which they reported momentary affect and eating patterns. Generalized linear mixed-models examined each index in relation to eating variable.Higher PA instability (within-person) was associated with higher ratings of binge-eating symptoms (B = 0.15, SE = 0.06, p = 0.007). Lower NA differentiation (within-person) was associated with higher levels of food craving (B = -10.11, SE = 4.74, p = 0.033).Our results support previous findings suggesting that acute fluctuations in PA may increase risk of binge-eating symptoms. Further, inability to differentiate between momentary states of NA was associated with cravings. This study highlights the importance of examining multiple facets of NA and PA in relation to eating regulation.Trial registration: ClinicalTrials.gov identifier: NCT02945475.

Emotion differentiation among individuals in a randomized clinical trial for alcohol use disorder: Within- and between-person associations with affect, craving, and alcohol use in daily life.

Emotion differentiation refers to cognitively distinguishing among discrete, same-valenced emotions. Negative emotion differentiation (NED) is a transdiagnostic indicator of emotional functioning. The role of positive emotion differentiation (PED) in clinical disorders, including alcohol use disorder (AUD), is less understood. Further, despite consensus that emotions are highly variable, little is known about within-person fluctuations in NED/PED. The current study leveraged 84 consecutive daily smartphone surveys from participants (N = 181) in a clinical trial of cognitive behavioral therapy for AUD to investigate whether between-person differences in overall NED/PED, or within-person variability in daily NED/PED, were associated with affect intensity, craving, drinking, and heavy drinking in daily life. Subsequent analyses explored whether associations were moderated by baseline alexithymia. At the between-persons level, greater average PED, but not NED, was associated with lower heavy drinking odds. At the within-persons level, higher-than-usual PED was associated with lower negative affect and odds of any drinking. Individuals with baseline alexithymia had stronger negative within-person associations between daily NED and both any and heavy drinking. PED is a skill linked to less alcohol use between- and within-persons irrespective of baseline alexithymia, whereas greater daily NED appears especially important for reduced alcohol use among individuals with co-morbid AUD and alexithymia.

Outlining a novel psychometric model of mental flexibility and affect dynamics.

Theoretically, affective states have always been conceived as complex phenomena enabling individuals to respond flexibly and dynamically to environmental demands. Methodologically, the novel field of Affect Dynamics has started to analyze affective states as inherently dynamic and interdependent phenomena by focusing on how and why they fluctuate over time. Fluctuations of affective states can also be conceived as a function of individuals' ability to flexibly modulate their responses according to environmental demands. However, this ability has been sparsely investigated in different disciplines and domains, thus, engendering a plethora of terms and models. In this conceptual analysis, we first aimed to disentangle the puzzle of flexibility by outlining the distinctive cross-domain features of this concept, thus providing a novel comprehensive operationalization. We termed this novel unitary concept "mental flexibility," the general ability to variably adapt to environmental demands. Then, we outlined the interplay between individuals' mental flexibility and affect dynamics by proposing a novel psychometric model of affect dynamics, using Markovian chain.

Chasing consistency: On the measurement error in self-reported affect in experiments.

How feelings change over time is a central topic in emotion research. To study these affective fluctuations, researchers often ask participants to repeatedly indicate how they feel on a self-report rating scale. Despite widespread recognition that this kind of data is subject to measurement error, the extent of this error remains an open question. Complementing many daily-life studies, this study aimed to investigate this question in an experimental setting. In such a setting, multiple trials follow each other at a fast pace, forcing experimenters to use a limited number of questions to measure affect during each trial. A total of 1398 participants completed a probabilistic reward task in which they were unknowingly presented with the same string of outcomes multiple times throughout the study. This allowed us to assess the test-retest consistency of their affective responses to the rating scales under investigation. We then compared these consistencies across different types of rating scales in hopes of finding out whether a given type of scale led to a greater consistency of affective measurements. Overall, we found moderate to good consistency of the affective measurements. Surprisingly, however, we found no differences in consistency across rating scales, which suggests that the specific rating scale that is used does not influence the measurement consistency.

Affect Across the Wake-Sleep Cycle.

Affective scientists traditionally have focused on periods of active wakefulness when people are responding to external stimuli or engaging in specific tasks. However, we live much of our lives immersed in experiences not related to the current environment or tasks at hand-mind-wandering (or daydreaming) during wakefulness and dreaming during sleep. Despite being disconnected from the immediate environment, our brains still generate affect during such periods. Yet, research on stimulus-independent affect has remained largely separate from affective science. Here, we suggest that one key future direction for affective science will be to expand our field of view by integrating the wealth of findings from research on mind-wandering, sleep, and dreaming to provide a more comprehensive account of affect across the wake-sleep cycle. In developing our argument, we address two key issues: affect variation across the wake-sleep cycle, and the benefits of expanding the study of affect across the full wake-sleep cycle. In considering these issues, we highlight the methodological and clinical implications for affective science.

Do markers of daily affect mediate associations between interpretation bias and depressive symptoms? A longitudinal study of early adolescents.

INTRODUCTION: Early adolescence represents a time of heightened vulnerability for depression. Negative interpretation biases have been associated with increases in depressive symptoms during this developmental period; however, the mechanisms underlying the association between interpretation biases and depression remain poorly understood. Cognitive theories posit that interpretation biases give rise to depression by modulating daily affect, particularly in the context of stress. However, this has not yet been directly examined. The present study tested affect intensity and instability as mechanisms linking negative interpretation biases with change in adolescent depressive symptoms. METHODS: Ninety-four adolescents (aged 11-13 years; 51% boys) from Vancouver, Canada, were recruited for this longitudinal study. At baseline (Time 1), participants self-reported depressive symptoms and completed the Scrambled Sentences Task to assess negative interpretation biases. Next, participants completed daily diaries to assess positive affect (PA) and negative affect (NA) during a naturalistic stressor-the first 2 weeks of high school (Time 2). Finally, participants self-reported depressive symptoms 3 months later (Time 3). Path models were conducted to test whether PA and NA intensity and instability mediated prospective associations between negative interpretation biases and depressive symptom changes. RESULTS: Although NA intensity, NA instability, and PA instability predicted increases in depressive symptoms, only NA intensity mediated associations between interpretation biases and symptom changes. Neither PA intensity nor instability mediated these associations. CONCLUSIONS: Elevated daily NA represents a specific mechanism through which stronger negative interpretation biases predict increases in depressive symptoms in adolescence.

Exploring Biomarkers of Mental Flexibility in Healthy Aging: A Computational Psychometric Study.

Mental flexibility (MF) has long been defined as cognitive flexibility. Specifically, it has been mainly studied within the executive functions domain. However, there has recently been increased attention towards its affective and physiological aspects. As a result, MF has been described as an ecological and cross-subject skill consisting of responding variably and flexibly to environmental cognitive-affective demands. Cross-sectional studies have mainly focused on samples composed of healthy individual and of patients with chronic conditions such as Mild Cognitive Impairment and Parkinson's, emphasizing their behavioral rigidity. Our study is the first to consider a sample of healthy older subjects and to outline physiological and psychological markers typical of mental flexibility, to identify functional biomarkers associated with successful aging. Our results reveal that biomarkers (respiratory and heart rate variability assessments) distinguished between individuals high vs. low in mental flexibility more reliably than traditional neuropsychological tests. This unveiled the multifaceted nature of mental flexibility composed of both cognitive and affective aspects, which emerged only if non-linear multi-variate analytic approaches, such as Supervised Machine Learning, were used.

Affect variability and physical health: The moderating role of mean affect.

Research has only begun to explore how affect variability relates to physical health and has typically not assessed long-term associations nor considered the moderating role of mean affect. Therefore, we used data from the Midlife in the United States Study waves 2 (N = 1512) and 3 (N = 1499) to test how affect variability predicted concurrent and long-term physical health while also testing the moderating role of mean affect. Results indicated that greater negative affect variability was associated concurrently with a greater number of chronic conditions (p = .03) and longitudinally with worse self-rated physical health (p < .01). Greater positive affect variability was associated concurrently with more chronic conditions (p < .01) and medications (p < .01) and longitudinally with worse self-rated physical health (p = .04). Further, mean negative affect played a moderating role such that at lower levels of mean negative affect, as affect variability increased, so did the number of concurrent chronic conditions (p < .01) and medications (p = .03) and the likelihood of reporting worse long-term self-rated physical health (p < .01). Thus, the role of mean affect should be considered when testing short- and long-term associations between affect variability and physical health.

The emotional component of insomnia disorder: A focus on emotion regulation and affect dynamics in relation to sleep quality and insomnia.

Theoretical models of insomnia disorder recognise an emotional component in the maintenance of the disorder. Nonetheless, the field of emotions is vast and different processes are involved in psychological well-being. The present narrative review focusses on emotion regulation and affect dynamics, synthesising some of the most recent and relevant evidence on emotions in relation to the quality of sleep and to insomnia disorder. The literature underlines the close association between impaired sleep quality and difficulties in regulating emotions. Impaired sleep quality is also associated with reduced positive affect and increased negative affect, but little evidence supports a bi-directional association between affective states and sleep. Affect variability in relation to sleep has been less investigated. Initial evidence suggests that high variability in positive affect has a negative impact on sleep. Neurobiological and behavioural evidence indicates that insomnia disorder is associated with emotion dysregulation, negative affect, and a distinct daily profile of affective states. More research is needed on the affective experience of patients with insomnia disorder, adopting multiple sampling of affect across the day and the week. Understanding how the unfolding of emotions over time interact with sleep alterations may help to improve the tailoring and monitoring of treatments addressing disturbed emotional processes in insomnia disorder.

Sleep Quality Moderates the Relationship Between Daily Mean Levels and Variability of Positive Affect.

Despite the well-established bidirectional association between sleep and daytime affect, most studies examining this relationship have focused on mean levels of affect. However, research solely focusing on mean levels of affect inherently neglects variability in affect, which has been shown to predict both psychological and physical well-being beyond mean levels. The present study assessed sleep quality and daytime affect using ecological momentary assessment in a combined sample of individuals (N = 80; 8,881 observations) with and without anxiety and mood disorders. Results from the present study partially replicated extant work on the negative association between negative affect (NA) variability and subsequent sleep quality. Furthermore, less satisfying sleep amplified the positive relationship between daily mean levels and variability of positive affect (PA). The results did not differ by clinical status. The present study offers novel evidence suggesting that previous night's sleep quality influences the stability of varying daily levels of PA. Uncovering the dynamics of sleep and affect beyond mean levels will help further elucidate mechanisms linking sleep and subsequent affective experiences.

Overnight emotional inertia in relation to depressive symptomatology and subjective sleep quality.

Emotions show a certain degree of continuity during the day, a quality referred to as emotional inertia, and that is typically elevated in depression. Little is known however about the extent to which our emotional experiences may or may not also persist overnight. Do our feelings continue from evening to morning or not? And how is this related to depressive symptoms and sleep quality? In an experience sampling studies in healthy subjects (ns = 123) we investigated (1) to what extent people's mood, in terms of positive and negative affect, in the morning, after a night of sleep, can be predicted from their mood of the evening before, and whether this is moderated by (2) depressive symptom severity or (3) subjective sleep quality. Results showed that morning negative affect could be strongly predicted based on previous evening negative affect, whilst this carry-over effect was not observed for positive affect, indicating that negative affect shows a general tendency to persist overnight, while positive affect did not show such continuity. The overnight prediction of both negative and positive affect was not moderated by level of depressive symptoms, nor by subjective sleep quality.