Introduction

Though traditionally addressed as a disorder with emotional symptomatology at its core, depression can also be understood as an alteration of cognition, particularly executive functions (EFs) (^{Hammar & Årdal, 2009}; ^{Millan et al., 2012}; ^{Snyder, 2013}). This is so because: a) the very signs and symptoms of depression are akin to those of the dysexecutive syndrome (^{Godefroy et al., 2010}), e.g., abulia (a deficit of behavior initiation), inability to concentrate (often due to lack of inhibition of depressive thoughts), or cognitive inflexibility (observed in thought rumination) (^{Watkins & Brown, 2002}); b) anomalies in frontal lobe networks commonly found in cases of executive dysfunction have also been observed in cases of depression (^{Bracht, Linden, & Keedwell, 2015}; ^{Goodwin, 2016}); c) poor performance on a wide variety of EFs’ tasks have been steadily observed too (^{Hammar & Årdal, 2009}; ^{Snyder, 2013}).

One of the common critical features of both depression and dysexecutive functioning is that they often lead to significant impairment on areas of everyday life functioning (^{American Psychiatric Association, 2013}; ^{Millan et al., 2012}; ^{Villalobos-Gallegos et al., 2019}), such as work. In fact, as close as 50% of lost productive time may be explained by depression (^{Stewart, Ricci, Chee, Hahn, & Morganstein, 2003}), and work-related stressors are significant risk factors of this disorder (^{Bonde, 2008}). For its part, ADHD, a common EF-related disorder, has been associated with lost of productivity across diverse samples of workers (^{Kessler et al., 2005}), and ADHD-related EFs’ deficits have been found to be associated with a higher frequency of unemployment (^{Halleland, Sørensen, Posserud, Haavik, & Lundervold, 2015}).

As relevant as this evidence is, to our knowledge, there has not been an analysis of the moderating effect of executive function between depression and work performance. Given the close relation these constructs have, it seems plausible that such interaction may help to better explain the variation on indicators of work performance. A moderating effect of EFs has been observed, for example, between: behavioral intention and behavioral performance (^{Hall, Fong, Epp, & Elias, 2008}; ^{Hall, Zehr, Paulitzki, & Rhodes, 2014}), perceived stress and aggressive behavior (^{Sprague, Verona, Kalkhoff, & Kilmer, 2011}), and in interventions for promoting socio-emotional functioning (^{Riggs, Jahromi, Razza, Dillworth-Bart, & Mueller, 2006}).

The objective of this study was to analyze the interactive effect of EF and depression severity on variables of work performance (presenteeism and absenteeism). We hypothesize that the expected correlations between depression and work performance variables are boosted by the moderating effects of higher levels of dysexecutive functioning. Overall, our purpose is to add evidence to the understanding of depression as impairment of EFs, and its impact on a specific clinical outcome.

Method

Results

Five hundred and fourteen individuals were initially recruited, excluding: one (.2%) because of incomprehension of informed consent, one (.2%) for rejecting participation, six (1.2%) because of not meeting age criterion, 30 (5.8%) for not meeting the criterion of at least three months working, seven (1.3%) repeated cases (based on repetition of personal e-mail provided for devolution of results), and two (.4%) cases with extreme values in the indicators of absenteeism. A total of 462 cases were included in the analyses.

Characteristics of participants are shown in Table 1. The sample was mostly constituted by women (65.1%), with an overall range of age between 18-60 years-old, and virtually all the sample distributed within the highest degrees of education (92%). Concerning diagnostic results of the PHQ-9: 47.6% qualified as not being depressed, 34.6% for mild depression, and 17.8% for moderate to severe depression.

No significant difference was observed regarding main variables and gender, but one was observed for depression within education degree (F[2,471]=5.37, p < .05), particularly in relation to elementary-to-high school level vs college and postgraduate levels; however, since most of the sample was in the higher education degrees, this variable was not finally treated as a confounder. Age did significantly correlate with all the main variables (r ranging from -.12 to .20), so it was included as a covariate within the main analyses.

Concerning the hierarchical linear regression models (Table 2), significant prediction of presenteeism was found for depression (model 1.1), and for depression + EF (model 1.2), with a significant change in R² value (predicting 25% of the variation of presenteeism vs. 23% of model 1.1), but no significant change was found when adding the interactive term depression severity × EF (model 1.3). Controlling for age confounder, a significant change in R² was found (predicting 26% of the variation of presenteeism). Regarding prediction of absenteeism, only depression resulted in a single significant association (model 2.1), and thus no change in R² was observed for the subsequent models.

Discussion

The objective of this study was to analyze the moderating effect of EF between depression severity and work performance. Based on the results, no significant interaction was found, but only additive effects of depression severity and EF on presenteeism, and no effect of these variables on absenteeism. This indicates that sadness, apathy, abulia, anhedonia, and other symptoms of depression (^{Kroenke et al., 2001}) deplete the capacity of the worker to concentrate and achieve goals at his/her workplace, and so do, independently, symptoms of impulsivity, cognitive inflexibility and disorganization, difficulties for behavior initiation, self-monitoring, and working memory deficits (^{Roth et al., 2013}). However, interaction in the form of sadness potentiated by cognitive inflexibility, or abulia potentiated by lack of behavior initiation, was not found.

Our main finding disagrees with those reported about the moderating effects of specific EFs between other psychological variables (^{Hall et al., 2008}; ²⁰¹⁴; ^{Sprague et al., 2011}), and is somewhat conflicted with the understanding of depression as a form of EF alteration (^{Millan et al., 2012}; ^{Snyder, 2013}). The use of the BRIEF-A, which evaluates EF impairment close to the diagnostic criteria for ADHD, may have contributed to this lack of interaction. In this sense, we hypothesize that EF alterations may have particular features for specific psychiatric disorders, in a similar fashion to the distinction of hot and cold EFs (^{Moreno-López et al., 2012}) for specific neuropsychological tasks and daily-life activities. For example, hot EFs, which encompass emotional regulation and decision-making, may have a more crucial involvement in depression than cold EFs, which relates to the use of mental regulation for the execution of cognitive tasks. Development of self-report scales with items aiming to explore dysexecutive functions in close relation to depression symptomatology may be useful in this regard (e.g., for cognitive inflexibility: “I have difficulties thinking in something else besides sad thoughts”).

The univariate effects of depression severity and EF on presenteeism are in accordance with previous findings (^{Kessler et al., 2005}; ^{Stewart et al., 2003}). The lack of meaningful associations with absenteeism may be explained by the fact that most of the sample qualified for mild depression, which may suppose enough functionality for attending to the workplace; additionally, in individuals with mild-to-moderate depression, the perspective of job dismissal may function as a more potent stimulus for the conditioning of behavior than the inner stimuli of the depression. These suppositions may be further strengthened by the fact that presenteeism did associate with our predictors, meaning that, despite attending work, performance is still compromised by depressive and dysexecutive symptoms.

There are limitations to consider. First, the generalisability is minimized by the sampling method, which restricted the education of the participants to the highest degrees, and most likely restricted the socioeconomical status to middle- and high-income individuals too. Moderating effects of cognitive reserve may have played a role because of this demographic bias, particularly in the expression of EFs; we tried to temper this limitation with the snowball recruitment and social networks, however, further studies evaluating a more diverse demographic samples are needed in order to corroborate the findings. Second, web-based surveys come with inherent limitations, like a higher probability of misunderstanding of items or multiple responses from the same participant (^{Regmi et al., 2016}). We tried to minimize this by using brief and easy-to-understand scales, by providing the instruction not to response twice, and by eliminating possible duplicated cases from the final database. Third, though we used widely-employed psychometrically valid measures, self-reports leave aside important behavioral information provided by EF tasks and naturalistic indicators of work performance; future studies should test our findings by solving this limitation.