Dynamic Structural Equation Research Articles

The relations among prosocial behavior, hedonic, and eudaimonic well-being in everyday life.

Existing research highlights the significance of prosocial behavior (voluntary, intentional behavior that results in benefits for another) to people's well-being. Yet, the extent to which this expected positive relation operates at the within-person level (e.g., is more prosocial behavior than usual related to a higher than usual level of well-being?) while taking into account stable interindividual differences, remains a research question that deserves further investigation. In this study, we aimed to explore the relations between prosocial behavior and hedonic (HWB; subjective assessment of life satisfaction and happiness) and eudaimonic (EWB; actualization of human potential in alignment with personal goals, including concepts like meaning in life and closeness to others) well-being in daily life. Using ecological momentary assessment for 4 weeks, data were collected from two British samples, comprising 82 adolescents and 166 adults. Dynamic Structural Equation Modeling revealed a positive relations between prosocial behavior and HWB/EWB at both between and within-person levels across the samples. In summary, these findings further support the positive link between prosocial behavior and well-being in everyday life. Notably, this association was consistent across different age groups (adolescent and adults) at both between and within-person levels.

From attentional fluctuations to intentional fluctuations? Monitoring behavior and intraindividual variability in time-based prospective memory.

In sharp contrast to event-based prospective memory (PM), dynamics of (re)allocation of attention between the ongoing and PM tasks have been much less investigated in time-based PM tasks. We propose an in-depth examination of attention allocation in a time-based PM task by jointly analyzing multiple indicators of time-monitoring behavior, net and time-structured intraindividual variability (IIV) in ongoing-task reaction times (OT RTs), and task performance. Results from dynamic structural equation modeling in a lifespan sample of 198 adults (19-86 years) revealed that larger fluctuations in OT RTs (net IIV) predicted poorer OT performance, but fostered a more efficient pattern of time-monitoring behavior (i.e., checking a clock more frequently and strategically, and slowing OT RTs during the PM response window) that, in turn, enhanced PM. Conversely, greater inertia in OT RTs (time-structured IIV) led to fewer clock-checks and poorer PM performance. Focusing attention on time monitoring to enhance PM performance did not detrimentally affect OT accuracy. Instead, participants showed a speed-accuracy tradeoff to optimize both OT and PM accuracies by slowing their OT RTs during the PM response window. This study therefore shows that two concomitant aspects of IIV (net and time-structured IIV) not only predicted time-monitoring behavior, but also OT and PM accuracies differentially, hence advocating for the necessity to consider both aspects of IIV and time monitoring together to better understand attention allocation policies in time-based PM tasks. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The inertia of anger and sadness among adolescents and adults: The role of self-efficacy in regulating negative emotions

Emotional inertia (i.e., the resistance to change of emotional states) is an index of regulatory deficit linked to psychological maladjustment. Using ecological momentary assessment, we explored the role of Self-efficacy in Regulating Negative Affect (SRN), as a baseline measure, to buffer sadness and anger inertia, measured three times a day over 28 days in two samples from the UK: (1) adults ( n = 166 adults; Mage = 35.71, SD = 12.96; 73% women) and (2) adolescents ( n = 82 adolescents; Mage 14.88, SD = 1.34; 72% girls). Dynamic Structural Equation Modeling showed that both sadness and anger had significant levels of inertia. Importantly, the inertia of sadness was weakened by high levels of SRN among both adults and adolescents ( β = −.211, 95% CI [−.303, −.112]; and β = −.485, 95% CI [−.707, −.162], respectively). No buffering effect of SRN was found for the inertia of anger. These findings suggest the importance of strengthening adults’ and adolescents’ SRN to manage their sadness in everyday life.

An analysis of the effects of value cocreation and tech enjoyment on customer satisfaction in tourism virtual reality

PurposeThe main objective of our study is to shed light on how perceived enjoyment influences the intricate relationship between value cocreation and consumer satisfaction, with a specific focus on the realms of tourist services.Design/methodology/approachTo achieve the objective outlined in this research, an information survey was carried out on 400 consumers of tourist services who have participated in virtual cocreation processes through digital platforms. As a data analysis technique, the dynamic structural equation modeling (DSEM) analyzes the causal relationships between the elements under study.FindingsOur extensive analysis draws upon the data collected through a survey spanning from 2018 to 2023, encompassing 400 participants who actively engaged in value cocreation processes in both physical and virtual settings. Our investigation considers two competing models to elucidate the role of perceived enjoyment. Our findings, established through DSEM illuminates that perceived enjoyment predominantly functions as a mediator, exerting a more pronounced influence on the connection between value cocreation and consumer satisfaction. Contrary to a moderating role, perceived enjoyment emerges as a significant mediator in our study.Originality/valueThe most significant addition is recognizing virtual value cocreation behaviors in tourist sector activities over time, primarily because it indicates the likelihood of negative repercussions of its usage. Furthermore, it must be capable of designing surroundings according to the characteristics of customers in terms of immersion and technology usage, preventing a rise in stress situations that might result in more negative consequences than planned. Another important insight is that virtual value cocreation initiatives have detrimental long-term implications, particularly in tourism.

Daily associations between global self-esteem and self-concept clarity and their relationships with subjective well-being in a sample of adult workers.

The present pre-registered study examined the reciprocal day-to-day associations between global self-esteem and self-concept clarity and their incremental validity with respect to daily life satisfaction, positive affect, and negative affect. We used intensive longitudinal data from 153 adult workers (45.1% women), over a period of 31 days. Data were analyzed using dynamic structural equation modeling. Results attested higher global self-esteem and self-concept clarity mean levels for older vs. younger participants, and lower global self-esteem and self-concept clarity variability for older vs. younger participants. Furthermore, global self-esteem and self-concept clarity were correlated at a cross-sectional daily level, yet only self-concept clarity states positively predicted subsequent global self-esteem states, while global self-esteem states did not predict subsequent self-concept clarity states. Daily global self-esteem and daily self-concept clarity further predicted subsequent daily higher life satisfaction and positive affect, respectively. Overall, our findings shed light on the short-term relationships linking global self-esteem and self-concept clarity, pointing to their discriminant validity in predicting individuals' subjective well-being.

A Bayesian Structural Modal Updating Method Based on Sparse Grid and Ensemble Kalman Filter

This study presents a sparse grid interpolation and ensemble Kalman filter (EnKF)-based Markov Chain Monte Carlo (MCMC) method (SG-EnMCMC). Initiating with the formulation of a recursive equation for the state space vector, derived from the structural dynamic equation, this study adopts a dimensionality reduction strategy. This approach involves a separation of physical parameters and the state space vector. The acquisition of physical parameters is accomplished through sampling, utilizing sample moments to substitute population moments, thereby mitigating the need for computationally high-dimensional covariance matrix calculations. To further streamline the recursive equation of the state space vector, a sparse grid method is employed for interpolation. This step simplifies the process while ensuring superior accuracy compared to the Extended Kalman Filter (EKF) and Unscented Kalman Filter (UKF). Subsequent to this, acceptance rates and the final parameter posterior distribution within the MCMC framework are derived. The efficiency of the proposed method is assessed through validation in two shaking table experiments.

Within- and between-person associations between social interactions and loneliness: students’ experiences during the COVID-19 pandemic

ABSTRACT The COVID-19 pandemic introduced many restrictions to in-person interactions, and remote social interactions may be especially important for managing loneliness when such restrictions are in place. However, it is unclear how social interactions are related to loneliness when in-person interactions are limited. Data were collected between February 2021 and March 2022 from a sample of 581 university students. Participants reported their loneliness and participation in positive in-person or remote social interactions each day for 14 days. Results from dynamic structural equation models showed that participants felt less lonely than they usually felt on the days they engaged in positive remote interactions at the within-person level. Moreover, participants generally felt less lonely when engaging more frequently in remote interactions, but only when in-person interactions were restricted (between-person level). Some of these results varied by changing COVID-19 restrictions. Finally, for participants who felt lonelier in general, the effect of positive in-person and remote interactions on loneliness was less strong. These findings suggest that social interactions may buffer loneliness but are not as impactful for those who experience greater loneliness.

Thought habits and processing modes among Japanese university students do not influence dynamic associations between rumination and negative affect

The integrated model of rumination argues that two trait factors—negative thinking habits and processing modes—get people stuck in maladaptive rumination. There is little evidence showing whether these factors influence the daily dynamic associations between rumination and negative moods. To address this, in this study, we conducted an experience-sampling method on Japanese university students. We recruited 92 Japanese university students and assessed their daily rumination and negative affect (NA) eight times a day for seven days. We examined the effects of habits and processing modes on the dynamic associations between rumination and negative moods using dynamic structural equation modeling. We found that individuals were more likely to ruminate when they experienced NA. However, contrary to previous findings, this study’s participants did not experience NA after engaging in rumination. Moreover, we did not detect any significant trait factor effect on these dynamic associations. Our findings imply that individuals are more likely to engage in rumination after experiencing NA, but the reverse association, particularly the autoregression of rumination, may not be maintained in natural daily life. Furthermore, negative thinking habits and processing modes may not influence the daily dynamic associations between rumination and NA among Japanese university students.

Dynamic bidirectional relation between state mindfulness and suicidal ideation among female college students: The moderating effect of trait mindfulness

Research has indicated that mindfulness is a protective factor against suicidal ideation. However, the dynamic reciprocal relation between them has been understudied. In this study, 110 female college students with suicidal ideation completed a measure of trait mindfulness and a 28-day diary of suicidal ideation and three-dimensional state mindfulness, including acting with awareness, present-moment attention, and nonjudgmental acceptance. Dynamic structural equation modeling was used to examine the dynamic and bidirectional effects between dimensions of state mindfulness and suicidal ideation and the moderating effect of trait mindfulness. Results showed that suicidal ideation predicted lower levels of present-moment attention the next day. More importantly, there was a dynamic and bidirectional relation between nonjudgmental acceptance and suicidal ideation for people with trait mindfulness higher than the average level (i.e., M + 0.15SD). Our findings suggested that studies and interventions on suicide should pay more attention to specific dimensions of state mindfulness and trait mindfulness.

Assessing Between- and Within-Person Reliabilities of Items and Scale for Daily Procrastination: A Multilevel and Dynamic Approach.

Intensive longitudinal data (ILD) has been collected to capture the dynamic fluctuations of procrastination; however, researchers have typically measured daily procrastination by modifying trait measures (e.g., adding a time reference "today") without adequately testing their reliabilities. The main purpose of this study was to use an advanced approach, dynamic structural equation modeling, to assess the between- and within-person reliabilities of a widely used six-item measure of daily procrastination. A total of 252 participants completed retrospective measures of various types of trait procrastination and daily measures of procrastination over 34 consecutive days. The results showed that the entire scale for daily procrastination and five of its six items had high between- and within-person reliabilities, but one item had much lower reliabilities, suggesting that this item may be inappropriate in everyday contexts. Furthermore, we found moderate to strong associations between the latent trait factor of procrastination and trait measures of procrastination. In addition, we identified substantial between-person variation in person-specific reliabilities and explored its relevant factors. Overall, this study assessed the reliabilities of a daily measure of procrastination, which facilitated future studies to obtain more reliable and consistent results and to better estimate the reliability of ILD.

How a general vulnerability for psychopathology during adolescence manifests in young adults' daily lives.

There is widespread interest in the general factor of psychopathology or 'p factor', which has been proposed to reflect vulnerability to psychopathology. We examined to what extent this 'vulnerability' is associated with dysregulations in affect and behavior that occur in daily life. As such we hoped to provide an account of how this vulnerability may be maintained. We used data from the Tracking Adolescents' Individual Lives Survey (TRAILS; N = 2,772) collected at ages 11, 14, 16, 19, and 22 years to fit a bifactor model with a general psychopathology factor, alongside internalizing, externalizing (EXT), attention-deficit/hyperactivity, and autism spectrum problem domains. Following the fifth TRAILS assessment, a subsample of participants (n = 133, age = 22.6, 43% women) with heightened risk for psychopathology completed a 6-month daily diary protocol with one assessment each day. Using a dynamic structural equation approach, we examined to what extent mean intensity, variability, inertia, and within-day co-occurrence of EXT, anxious-tense, and depressed-withdrawn affects and behaviors were associated with general factor scores. Unexpectedly, higher general factor scores were not associated with higher mean intensity of any of the three types of daily negative affects and behaviors, but were associated with higher variability and less carryover (inertia) EXT affects and behaviors. We showed that individual differences in general factor scores do not manifest as differences in average levels of daily affects and behaviors, but instead were related to a type of EXT reactivity to the environment. Future research is necessary to investigate whether reactive irritable moods may be involved in or signal vulnerability sustained psychopathology.

Identifying Dynamic Shifts to Careless and Insufficient Effort Behavior in Questionnaire Responses; a Novel Approach and Experimental Validation

Careless and insufficient effort responding (C/IER) is a situation where participants respond to survey instruments without considering the item content. This phenomena adds noise to data leading to erroneous inference. There are multiple approaches to identifying and accounting for C/IER in survey settings, of these approaches the best performing are model based classification techniques. Classic approaches to accounting for C/IER treat it as a person level phenomena. They first use some method to identify participants who exhibit C/IER, then use list-wise deletion to remove them prior to analysis. We argue that C/IER is actually a state that participants may exhibit for a portion of a survey instrument. In other words, participants start a survey with the intention to follow instructions, but at some point transition to a C/IER state and no longer respond in line with item contents. Accounting for C/IER at the item level, as opposed to the person level preserves data resulting in increased power. In this article we present a Bayesian Dynamic Latent Class Structural Equation Modeling (DLCSEM) approach for simultaneously accounting for C/IER at the item level and estimating a model of interest. We use a simulation study to establish the approaches performance under empirically relevant conditions and to compare it to other methods. We then conducted an experimental validation in which we induce C/IER like responses from human subjects and investigate the approaches ability to identify the point in which participants transition to a C/IER state. We also compare the model to existing approaches. In both the simulation and experimental validation the DLCSEM outperforms the alternative approaches. We conclude that the approach should be used by applied researchers for the pragmatic benefits of the method. Conclusions, limitations, and future directions are discussed.

Spillover Between Daily Marital Interactions and Parenting Practices: Sensory Processing Sensitivity as Moderators

The present study aimed to examine whether the spillover effects existed between daily marital interactions and daily parenting practices after disentangling the between- and within-family effects and whether parents’ sensory processing sensitivity (SPS) would moderate such associations. The current study included 127 parents (83.3% female and 16.7% male; M age = 34.18, SD = 4.15) who reported their marital interactions and parenting practices over 14 consecutive days. The results of two separate dynamic structural equation models showed that the spillover effects of marital interactions to parenting occurred in a transient and mood-congruent pattern, and SPS traits moderated the relations between marital conflict and negative parenting practices.

Reciprocal effects between negative affect and emotion regulation in daily life

The extended process model of emotion regulation provides a framework for understanding how emotional experiences and emotion regulation (ER) mutually influence each other over time. To investigate this reciprocal relationship, 202 adults completed a ten-day experience-sampling survey capturing levels of negative affect (NA) experience and use of ten ER strategies in daily life. Residual dynamic structural equation models (DSEMs) were used to examine within-person cross-lagged and autoregressive effects of NA and ER (strategy use and between-strategy variability). Results showed that NA predicted lower between-strategy variability, lower subsequent use of acceptance and problem-solving, but higher subsequent use of rumination and worry. Moreover, reappraisal and between-strategy variability predicted lower subsequent NA levels, while expressive suppression and worry predicted higher subsequent NA levels. Stable autoregressive effects were found for NA and for maladaptive ER strategies (e.g., rumination and worry). Exploratory correlation analyses revealed positive associations between NA inertia and maladaptive ER strategies. Together, these findings provide evidence of a dynamic interplay between NA and ER. This work deepens how we understand the challenges of applying ER strategies in daily life. Future clinical and translational research should consider these dynamic perspectives on ER and affect.

Group member attachment style interacts with actor and partner helping alliance to predict decreasing binge eating episodes

Objective An individual’s attachment style may impact how they interact with their therapy group. This study examined the moderating role of a group member’s attachment on the dynamic relationships between that group member’s (actor) and other group members’ (partner) therapeutic alliances and symptom outcomes. Method: This is a secondary analysis of data from a trial testing the outcome of emotionally-focused group therapy for binge-eating disorder. The sample consisted of 2,360 sessions nested within 118 group members who attended a 20-session treatment. Patients recorded binge eating episodes (BEE), their body weight and an alliance measure session-by-session. Results Dynamic structural equation modelling showed decreases in BEE and weight over the therapy. When attachment style was not included in the model, higher-than-average partner’s alliance scores in the previous session were related to decreases in BEE in the current session. Attachment style moderated these actor and partner effects. For patients with preoccupied attachments, higher-than-average actor alliance in the previous session was related to subsequent decreases in BEE. For patients with dismissing or disorganized attachments, higher partner alliance in the previous session was related to subsequent decreases in BEE. Conclusion Group members’ attachment characteristics can play a role in the development of alliance-outcome patterns in group therapy.

Testing relational turbulence theory in daily life using dynamic structural equation modeling

Abstract Using dynamic structural equation modeling (DSEM; Asparouhov et al., 2018), this study tests how partner disruptions of daily routines create a chaotic relational state through intensified emotions directed at partners, as posited by relational turbulence theory (RTT; Solomon et al., 2016). To test this affective process, individuals in dating relationships (N = 130) completed daily surveys for 30 days (T = 30; 3,478 total observations), measuring that day’s interference from their partner, anger experienced while interacting with their partner, and their relational turbulence. DSEM accounted for the intensive longitudinal aspects of the data while modeling three types of person-specific random effects: random intercepts to account for subject-specific averages; random slopes to account for subject-specific effects; and random variances to account for subject-specific volatility. RTT processes were supported, as greater than typical interference of routines in daily life predicted more relational turbulence that day via increased daily anger (controlling for the previous day’s levels). The use of DSEM allowed us to further test RTT by modeling person-specific inertia and volatility (for levels of interference, anger, and relational turbulence throughout a month). The use of a multilevel “location-scale” DSEM with random intercepts and random variances revealed that attachment avoidance and anxiety predicted a variety of person-specific features of the studied longitudinal processes: averages, inertia, and volatility over time. We provide our data and a supplemental primer to illustrate how to test communication theory with DSEM and model the intensive dynamics of daily life.

A virtuous cycle between meaning in daily life and state mindfulness as well as the unique role of depression among young adults: A diary study.

The positive association between meaning in life (MIL) and mindfulness has been supported; however, previous research has been limited to the trait level. To explore the dynamics of mindfulness and MIL in the state level, the present study used the experience sampling method (ESM) and conducted a dynamic structural equation model (DSEM). In addition, we examined the moderation of baseline depression in this dynamic relationship and the protective role of the dynamics on depression. We recruited 184 college students (Mage = 21.58, 33.15% male), who reported three times a day for 14 consecutive days, and analyzed the 7726 collected responses. Firstly, a virtuous cycle between mindfulness and MIL was proven. Besides, the baseline depressive symptoms moderated the predictive of mindfulness on MIL, suggesting state mindfulness gave people with more depressive symptoms more meaningful in daily life. Lastly, the result also demonstrated the positive prediction of mindfulness on MIL and alleviated the worsening of depressive symptoms within 2 weeks. The findings extended the relationship between MIL and mindfulness from trait level to state level, enriching the self-determination theory, and examined the unique effect of depressive symptoms in the dynamics.

Hybrid methods for solving structural geometric nonlinear dynamic equations: Implementation of fifth-order iterative procedures within composite time integration methods

This paper studies a class of hybrid methods that implement multi-point iterative procedures as the nonlinear solver within optimized composite implicit methods. These multi-point methods are employed to enhance convergence order and accuracy without requiring higher-order derivatives for solving structural geometric nonlinear dynamic equations. The promising approach provides an opportunity to delve deeper into its implications and explore the potential applications of multi-point techniques and composite methods across the analysis of dynamical systems. This study involves the utilization of two-point and five-point iterative methods with fifth-order convergence within three-step and four-step optimized composite implicit time integration methods. Moreover, a comprehensive hybrid scheme is introduced by integrating a family of optimized composite implicit methods with single-point and multi-point iterative methods. Then, the performance of the hybrid scheme is analyzed through structural examples, considering factors such as time step size, tolerance threshold, and the degrees of freedom of structures. The findings and numerical results illustrate that multi-point methods outperform the single-point method in terms of the number of iterations. Simultaneously, the four-step time integration method exhibits superior performance compared to the three-step time integration method, albeit with a marginal difference. It is observed that the hybrid method, consisting of the four-step time integration method and the five-point iterative method, performs better than other methods in terms of the number of iterations and errors for solving geometric nonlinear dynamic equations, especially in large structures. Thus, it stands out as a favorable choice for practical analyses and a possible candidate for generalization to other types of nonlinear problems in computational mechanics.

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.

Compassion Dynamics in Medical Students: An Ecological Momentary Assessment Study.

Effective interventions to support compassionate patient- and self-care requires an understanding of how to best assess compassion. Micro-ecological momentary assessment (micro-EMA), a method in which participants provide brief responses in real-time within their own environments, can capture changes in compassion across time and contexts. This study examined a micro-EMA approach for measuring the temporal dynamics of compassion in medical students during the COVID-19 pandemic. Medical students (N = 47) completed demographic information and self-report questionnaires assessing empathy and compassion for self and others. Participants then completed six bursts of micro-EMA smartphone-delivered surveys. Each burst was 14days, with 28days between bursts. During each burst, participants received four daily micro-EMA surveys assessing compassion, stress, positive affect, and negative affect. Dynamic structural equation modeling was used to examine micro-EMA responses. The overall micro-EMA response rate was 83.75%. On average, daily compassion did not significantly change across the academic year. However, there was significant within-person variability in medical students' compassion trajectories over the training year (b = 0.027, p < .01). At concurrent timepoints, micro-EMA assessed compassion was associated with greater happiness (b = 0.142, p < .001) and lower stress (b = -0.052, p < .05) but was not associated with sadness. In lagged analyses, higher micro-EMA assessed compassion predicted higher next day happiness (b = 0.116, p < .01) and vice versa (b = 0.185, p < .01). Results suggest it is feasible to use micro-EMA to assess daily levels of compassion among medical students. Additionally, there is wide variability in day-to-day fluctuations in compassion levels among medical students, with some students showing substantial increases in daily compassion across the training year and others showing decreases. Positive affect as opposed to negative affect may have particularly strong associations with compassion. Further examination of antecedents and consequences of fluctuations in daily compassion could inform potent intervention targets.