The Association Between Work-Related Rumination and Executive Function Using the Behavior Rating Inventory of Executive Function

Abstract

Work-related rumination has been associated with a number of health complaints, however, little is known about the underlying factors associated with rumination. Previous work using proxy measures of executive function showed work-related rumination to be negatively associated with executive function. In this paper, we report two studies that examined the association between work-related rumination and executive function utilizing an ecological valid measure of executive function: the Behavior Rating Inventory of Executive Function (BRIEF-A, Roth et al., 2005). In study 1 (N = 63), high, relative to low work-related ruminators, were found to demonstrate lower executive function skills, in eight of the nine subscales of the BRIEF. The aim of study 2 (N = 237) was to identify, the key executive function subscale/s associated with work-related rumination. Controlling for known factors associated with work-related rumination (fatigue and sleep), regression analysis identified the behavioral regulation subscale "shift" as the key predictor within the model. Shift relates to our ability to switch attention, to think about different solutions, and dealing with and accepting change. It was concluded that these findings lend support for future research to develop interventions for enhancing shift ability, as an aid to reduce work-related ruminative thinking.

Always on, never done? How the mind recovers after a stressful workday?

“…For instance, it was found that psychological detachment was related to better patient and worker safety (Buljac-Samardžić et al, 2018;Chen and Li, 2020), lower counterproductive work behavior (Chen et al, 2017), and better work-life balance (Barber et al, 2019). Considering the different types of work-related thoughts during nonwork time, studies have, for instance, investigated relationships to work-family-conflict and enrichment (Junker et al, 2020), executive functions (Cropley and Collis, 2020;Cropley et al, 2016), and thriving (Weigelt et al, 2019).…”

Yesterday’s Work–Home Conflict and Actigraphically Recorded Sleep-Onset Latency as Predictors of Today’s Cognitive Failure

“…Not surprisingly, we found an effect of work-related rumination on cognitive failures on the next day; these results indicate impaired behavioral regulation. Work-related rumination is known to impair executive function, especially for switching attention, thinking about different solutions, or dealing with and accepting change (Cropley & Collis, 2020). However, WHC and rumination contribute independently to the cognitive failures the next day.…”

Review of the Internal Structure, Psychometric Properties, and Measurement Invariance of the Work-Related Rumination Scale – Spanish Version

“…Interestingly, of the 25 studies revised, only seven studies used the complete WRRS and those included the original study in which the WRRS was developed ( Cropley et al, 2012 ; Querstret and Cropley, 2012 ; Vandevala et al, 2017 ; Dunn and Sensky, 2018 ; Sulak Akyüz and Sulak, 2019 ; Weigelt et al, 2019a ; Mullen et al, 2020 ), 11 used the affective and problem-solving pondering subscales ( Bisht, 2017 ; Kinnunen et al, 2017 , 2019 ; Querstret et al, 2017 ; Syrek et al, 2017 ; Vahle-Hinz et al, 2017 ; Firoozabadi et al, 2018a , b ; Junker et al, 2020 ; Zhang et al, 2020 ; Pauli and Lang, 2021 ), two studies used the problem-solving pondering and Detachment subscales ( Zoupanou et al, 2013 ; Mehmood and Hamstra, 2021 ), only one used the Detachment subscale ( Svetieva et al, 2017 ), and four studies used the affective rumination subscale ( Querstret et al, 2016 ; Van Laethem et al, 2019 ; Weigelt et al, 2019b ; Cropley and Collis, 2020 ; Smyth et al, 2020 ). Thus, the use of the subscales of the WRRS vary according to the researchers need and purpose.…”

“…Regarding of method of factorial designs, one used exploratory factor analysis (EFA; Cropley et al, 2012 ), seven studies used CFA ( Bisht, 2017 ; Syrek et al, 2017 ; Vahle-Hinz et al, 2017 ; Firoozabadi et al, 2018a ; Kinnunen et al, 2019 ; Sulak Akyüz and Sulak, 2019 ; Weigelt et al, 2019a , b ; and two of the studies did not report any of such methods, Querstret et al, 2016 ; Cropley and Collis, 2020 ). Those seven studies that relied on CFA, two studies used the maximum likelihood (ML) estimator, two used robust maximum likelihood (MLR), one used diagonally-weight least squares (DWLS), and two did not report it.…”