Using Residual Dynamic Structural Equation Modeling to Explore the Relationships among Employees’ Self-Reported Health, Daily Positive Mood, and Daily Emotional Exhaustion

Kung, Ya-Tzu; Chi, Shyh-Ching; Chen, Yung-Chou; Chang, Chia‐Ming

doi:10.3390/healthcare9010093

Cited by 8 publications

(7 citation statements)

References 54 publications

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“…The most popular specification, which we will focus on in this manuscript, is the specification of an autoregressive (AR) equation for how the residuals behave over time (e.g. Takano et al, 2014;Myin-Germeys et al, 2001;Asparouhov and Muthén, 2021;Ravindran et al, 2020;Mak and Schneider, 2020;Dixon-Gordon and Laws, 2021;Johnson et al, 2020;Kung et al, 2021;Whelen and Strunk, 2021).…”

Section: Introductionmentioning

confidence: 99%

One Does Not Simply Correct for Serial Dependence

Ariens

Adolf

Ceulemans

2023

Structural Equation Modeling: A Multidisciplinary Journal

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Serial dependence is present in most time series data sets collected in psychological research. This paper investigates the implications of various approaches for handling such serial dependence, when one is interested in the linear effect of a time-varying covariate on the time-varying criterion. Specifically, the serial dependence is either neglected, corrected for by specifying autocorrelated residuals, or modeled by including a lagged version of the criterion as an additional predictor. Using both empirical and simulated data, we showcase that the obtained results depend considerably on which approach is selected.We discuss how these differences can be explained by understanding the restrictions imposed under the various approaches. Based on the insight that all three approaches are restricted versions of an autoregressive distributed lag model, we demonstrate that accessible statistical tools, such as information criteria and likelihood-ratio tests can be used to justify a chosen approach empirically.

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Section: Introductionmentioning

confidence: 99%

One Does Not Simply Correct for Serial Dependence

Ariens

Adolf

Ceulemans

2023

Structural Equation Modeling: A Multidisciplinary Journal

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“…While the literature is currently limited, DSEM has been used to explore the within‐ and between‐person differences in the short‐term dynamic relations of psychological processes, particularly between different affective states (Hamaker et al, 2018), negative affect and rumination (Blanke et al, 2021), emotional exhaustion (Kung et al, 2021), and nonsuicidal self‐injury engagement (Kiekens et al, 2020). However, to date, the role of between‐person differences in ADHD traits in within‐person fluctuations in perceived provocation and resultant aggression has yet to be explored using a DSEM methodology.…”

Section: Introductionmentioning

confidence: 99%

Exploring the effect of ADHD traits on the moment‐to‐moment interplay between provocation and aggression: Evidence from dynamic structural equation modeling

Brown

Speyer

Eisner

et al. 2023

Aggressive Behavior

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The relation between attention deficit hyperactivity disorder (ADHD) symptoms and aggression is well documented; however, the processes that account for higher levels of aggression associated with ADHD in the course of daily life are little understood. The current study used ecological momentary assessment to explore how ADHD traits relate to individual differences in perceiving provocation from others and the resultant aggressive behaviors; and the strengths of the links between provocation and aggression in the flow of daily life. A dynamic structural equation model was fit using data from a subpopulation of young adults involved in the longitudinal z-proso study (n = 259, median-age 20). Data on provocation and aggression was collected at four quasi-random time periods per day over a 14-day period. Individuals with higher ADHD trait levels reported higher instances of provocation and aggression, with ADHD traits significantly moderating aggression inertia such that those with higher levels of ADHD traits showed greater persistence of aggressive behavior over time. However, ADHD trait levels did not significantly moderate any of the observed cross-lagged effects. Our findings suggest that individuals with higher levels of ADHD traits are at greater risk of exposure to interpersonal interactions involving interpersonal provocation, show higher levels of aggressive behavior in daily life, and find it more difficult to reduce their aggression once triggered. These findings support the importance of targeting factors such as social skills and emotion regulation that may underpin the increased difficulties in interpersonal interactions often experienced by individuals with high levels of ADHD symptoms.

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“…While the literature is currently limited, DSEM has been used to explore the within-and between-person differences in the shortterm dynamic relations of psychological processes, particularly between different affective states (Hamaker et al, 2018), negative affect and rumination (Blanke et al, 2021), emotional exhaustion (Kung et al, 2021), and nonsuicidal self-injury engagement (Kiekens et al, 2020). However, to date, the role of between-person differences in ADHD traits in within-person fluctuations in perceived provocation and resultant aggression has yet to be explored using a DSEM methodology.…”

Section: Introductionmentioning

confidence: 99%

Exploring the effect of ADHD traits on the moment-to-moment interplay between provocation and aggression: evidence from dynamic structural equation modelling

Brown¹,

Speyer²,

Eisner³

et al. 2022

Preprint

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The relation between ADHD symptoms and aggression has been well documented; however, the processes that account for higher levels of aggression associated with ADHD ‘in the moment’ in the course of daily life interactions have been little researched. The current study used ecological momentary assessment (EMA) to explore how ADHD traits might relate to individual differences in provocations, aggression, and the strengths of the links between provocation and aggression in the flow of daily life. We used dynamic structural equation modelling (DSEM) fit to data from the D2M study (n=254 adults aged 20; 35% male from the longitudinal z-proso study) which collected provocation and aggression data at four quasi-random time periods per day over a 14-day period. We found that individuals with higher ADHD trait levels reported higher instances of provocation and aggression, with ADHD traits significantly moderating aggression inertia such that those with higher levels of ADHD traits showed greater persistence of aggressive behaviour across time points. However, ADHD trait levels did not significantly moderate any of the observed cross-lagged effects. Our findings suggest that individuals with higher levels of ADHD traits are at greater risk of exposure to interpersonal interactions involving provocation, show higher levels of aggressive behaviour in daily life, and find it more difficult to reduce their aggression once triggered. These findings support the importance of targeting factors such as social skills and emotion regulation that may underpin the increased difficulties in interpersonal interactions often experienced by individuals with high levels of ADHD symptoms.

show abstract

Using Residual Dynamic Structural Equation Modeling to Explore the Relationships among Employees’ Self-Reported Health, Daily Positive Mood, and Daily Emotional Exhaustion

Cited by 8 publications

References 54 publications

One Does Not Simply Correct for Serial Dependence

One Does Not Simply Correct for Serial Dependence

Exploring the effect of ADHD traits on the moment‐to‐moment interplay between provocation and aggression: Evidence from dynamic structural equation modeling

Exploring the effect of ADHD traits on the moment-to-moment interplay between provocation and aggression: evidence from dynamic structural equation modelling

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