How Past Work Stressors Influence Psychological Well-Being in the Face of Current Adversity: Affective Reactivity to Adversity as an Explanatory Mechanism

Schilbach, Miriam; Baethge, Anja; Rigotti, Thomas Article — Published Version How Past Work Stressors Influence Psychological Well-Being in the Face of Current Adversity: Affective Reactivity to Adversity as an Explanatory Mechanism Journal of Business and Psychology Provided in Cooperation with: Springer Nature Suggested Citation: Schilbach, Miriam; Baethge, Anja; Rigotti, Thomas (2023) : How Past Work Stressors Influence Psychological Well-Being in the Face of Current Adversity: Affective Reactivity to Adversity as an Explanatory Mechanism, Journal of Business and Psychology, ISSN 1573-353X, Springer US, New York, NY, Vol. 39, Iss. 4, pp. 1-18, https://doi.org/10.1007/s10869-023-09922-7 This Version is available at: https://hdl.handle.net/10419/309458 Standard-Nutzungsbedingungen: Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden. 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If the documents have been made available under an Open Content Licence (especially Creative Commons Licences), you may exercise further usage rights as specified in the indicated licence. https://creativecommons.org/licenses/by/4.0/ Vol.:(0123456789) 1 3 Journal of Business and Psychology (2024) 39:909–926 https://doi.org/10.1007/s10869-023-09922-7 ORIGINAL PAPER How Past Work Stressors Influence Psychological Well‑Being intheFace ofCurrent Adversity: Affective Reactivity toAdversity asanExplanatory Mechanism MiriamSchilbach1 · AnjaBaethge2 · ThomasRigotti1,3 Accepted: 13 October 2023 / Published online: 8 November 2023 © The Author(s) 2023 Abstract This study advances the understanding of the mechanisms that link past challenge and hindrance stressors to resilience outcomes, as indicated by emotional and psychosomatic strain in the face of current adversity. Building on the propositions of Conservation of Resources Theory and applying them to the challenge-hindrance framework, we argue that challenge and hindrance stressors experienced in the past relate to different patterns of affective reactivity to current adversity, which in turn predict resilience outcomes. To test these assumptions, we collected data from 134 employees who provided information on work stressors between April 2018 and November 2019 (T0). During the first COVID-19 lockdown (March/April 2020), the same individuals participated in a weekly study over the course of 6 weeks (T1–T6). To test our assumptions, we combined the pre- and peri-pandemic data. We first conducted multilevel random slope analyses and extracted individual slopes indicating affective reactivity to COVID-19 adversity in positive and negative affect. Next, results of path analyses showed that past challenge stressors were associated with lower affective reactivity to COVID-19 adversity in positive affect, and in turn with lower levels of emotional and psychosomatic strain. Past hindrance stressors were associated with greater affective reactivity to COVID-19 adversity in positive and negative affect, and in turn to higher strain. Taken together, our study outlines that past work stressors may differentially affect employees’ reactivity and resilient outcomes in the face of current nonwork adversity. These spillover effects highlight the central role of work stressors in shaping employee resilience across contexts and domains. Keywords Resilience· Affective reactivity· Conservation of Resources Theory· Challenge-hindrance framework Throughout their lives, most individuals experience adversity (e.g., Bonanno, 2005) which represents a major risk factor for the development of psychopathology (Green etal., 2010). Individual resilience prevents adversityrelated declines in psychological well-being and mental health (Fisher etal., 2019; King etal., 2016). Consequently, researchers strive to identify the antecedents of resilience and throughout this process outline the central role of past experiences (e.g., King etal., 2016; Seery etal., 2010; Ungar, 2011). In this study, we focus on the experience of past work stressors and examine how they influence employees’ demonstration of resilience outcomes, that is the maintenance of psychological well-being in the face of current adversity, specifically COVID-19-related adversity. Note that we refer to adversity as a stressful experience that lies outside the “business-as-usual” context (i.e., the COVID- 19 pandemic), whereas work stressors represent stressful experiences that employees encounter frequently within their work environment (see Britt etal., 2016; Kuntz etal., 2017). To date, a handful of studies have examined the relationship between work stressors and resilience, with resilience operationalized as a capacity, that is, a hypothetical but not demonstrated ability to maintain health and functioning in the face of adversity (Crane & Searle, 2016; Jannesari & Additional supplementary materials may be found here by searching on article title https:// osf. io/ colle ctions/ jbp/ disco ver * Miriam Schilbach [email protected] 1 Leibniz Institute forResilience Research, Wallstraße 7, 55122Mainz, Germany 2 Department ofHuman Sciences, Medical School Hamburg, Hamburg, Germany 3 Department ofPsychology, Johannes Gutenberg University, Mainz, Germany 910 Journal of Business and Psychology (2024) 39:909–926 1 3 Sullivan, 2021; Kunzelmann & Rigotti, 2021; Zhou etal., 2021). These studies conjointly drew on the challengehindrance framework (Cavanaugh etal., 2000; O’Brien & Beehr, 2019) and showed that challenge stressors positively whereas hindrance stressors negatively relate to employees’ resilience capacity. However, research remains limited in two important ways. First, the mechanisms that mediate the relationship between past work stressors and resilience outcomes remain un(der)explored. That is, how do past work stressors influence the way that individuals react to current adversity, which in turn predicts health and functioning in the face of current adversity? Identifying such explanatory mechanisms is essential to advance our understanding of the role that everyday stressors play in predicting employee resilience, and further facilitates the development of more targeted programs that organizations can offer to prevent stress-related pathology (e.g., Kalisch etal., 2015). Second, resilience researchers showed that measuring resilience as a hypothetical capacity does not adequately predict actual, real-life adaptation to adversity (Bonanno, 2012; Britt etal., 2016; Waaktaar & Torgersen, 2010). As a result, research to date does not allow for the conclusion that work stressors are related to positive adaptation in the face of real-life adversity. Accordingly, in this study, we aim to advance the understanding of the mechanisms that link past work stressors to resilience outcomes in the face of current real-life adversity. To this end, we draw on the Conservation of Resources (COR) Theory (Hobfoll, 1989) as an overarching theoretical model and combine it with the challenge-hindrance framework (Cavanaugh etal., 2000) as well as the concepts of stress inoculation (Meichenbaum, 1977) and stress sensitization (Post, 1992). Specifically, we argue that past challenge stressors are associated with an inoculation process in which individuals experience a net resource gain that expands their coping capacities by overcoming the challenges. This prevents the experience of acute psychological distress in the form of heightened affective reactivity in the face of current adversity, that is decreasing positive and increasing negative affect (see e.g., Cohen etal., 2005; Houben etal., 2015). Lower affective reactivity, in turn, is expected to facilitate the demonstration of resilience outcomes, namely the maintenance of psychological well-being in the face of adversity (e.g., Fredrickson etal., 2003; Hobfoll, 2011; O’Neill etal., 2004). In contrast, hindrance stressors are expected to trigger a sensitization process characterized by resource losses, resulting in diminished coping capacities and thus increased affective reactivity to adversity and lower well-being (e.g., Hobfoll, 2011; Post, 1992). Thus, taken together, we propose that everyday work stressors experienced in the past influence individuals’ affective reactivity to current adversity, which in turn predicts emotional and psychosomatic well-being in the face of current adversity. Figure1 illustrates our conceptual research model. This study makes three main contributions. First, we go beyond previous research that focused on the direct impact of work stressors on hypothetical resilience (e.g., Crane & Searle, 2016; Jannesari & Sullivan, 2021). By integrating the propositions of COR theory with the challenge-hindrance framework, we offer an explanation for how work stressors experienced in the past may influence resilience outcomes in the face of current adversity, namely through shaping affective reactivity to current adversity. This approach not only enhances our understanding of the stressor-resilience Fig. 1 Conceptual model: challenge and hindrance stressors experienced in the past as antecedents of the resilience process to current adversity. Note. Direct paths from challenge and hindrance demands at T0 to outcome variables at T6 are omitted for clarity of presentation. Affective reactivity was operationalized as individual slopes extracted from multilevel analysis. Slopes indicated an individual’s average weekly relationship between COVID-19-related adversity and positive as well as negative affect 911Journal of Business and Psychology (2024) 39:909–926 1 3 relationship and broadens the nomological network of the challenge-hindrance framework but also holds important implications for stress research in general. Specifically, it advances our understanding of the long-term effects of stressors on strain. This is crucial given that studies that have examined the stressor-strain relationship while controlling for autoregressive effects found heterogeneous relationship patterns, with relationships being positive, nonsignificant, or even negative (Guthier etal., 2020). Stressor-induced changes in affective reactivity to future adversity may provide an explanation for this heterogeneity. Second, we acknowledge the assumption inherent in COR theory and the concepts of stress inoculation and sensitization that past experiences shape reactivity and positive adaptation to different forms of future adversity across contexts and domains (e.g., Belda etal., 2016; Dienstbier, 1989; Freedy & Hobfoll, 1994; Hobfoll, 2011). Building on this assumption, we investigate whether past work stressors predict the way individuals adapt to current adversity that arises from a context outside the work setting, such as the COVID-19 pandemic. The important implications of such spillover effects are evident, as they may serve as a foundation for facilitating positive adaptation not only to one type of adversity but to multiple or all forms of adversity (e.g., Kalisch etal., 2015) through work design. Third, we address the criticism from resilience researchers who have highlighted the limitations of operationalizing resilience as a hypothetical construct (Britt etal., 2016; Waaktaar & Torgersen, 2010), an approach commonly used in previous studies of the stressor-resilience relationship (e.g., Crane & Searle, 2016; Jannesari & Sullivan, 2021). To overcome this limitation, we specifically focus on observing affective reactivity to adversity and the subsequent maintenance of well-being, indicating the demonstration of resilience (Fisher etal., 2019). By adopting this perspective, we gain valuable insights into how work stressors contribute to shaping adaptive processes in the face of real-life adversity. Theoretical Background A Conservation ofResource Perspective onIndividual Resilience COR theory was developed by Hobfoll (1989) to explain human motivation and the sources of psychological distress (see also Halbesleben etal., 2014). The central tenet of COR theory is that humans seek to protect their current resources and acquire new ones, where resources are defined as objects, personal characteristics, conditions, or energies that are valued by an individual (Hobfoll, 1989) and that facilitate goal attainment (Halbesleben etal., 2014). According to the theory, psychological distress occurs when there is (a) a threat of a net loss of valued resources, (b) an actual net loss of valued resources, or (c) a failure to gain valued resources after significant effort (Hobfoll, 1989; Hobfoll etal., 2018). Hobfoll (1989) further outlines that achieving overall or net resource gains is an active process in which individuals must invest resources, such as energy, in order to gain new resources, such as self-efficacy. In addition, resource gains and losses are likely to affect individuals in the long run, as they can trigger gain and loss spirals, respectively. That is, individuals who have gained resources are more capable of additional resource gains (i.e., gain spirals), whereas an initial resource loss begets future losses (i.e., loss spirals, Hobfoll, 2001; Hobfoll etal., 2018). Importantly, according to COR theory, resource gains and losses influence an individual’s responses to future stress events or adversity and thus their resilience (Freedy & Hobfoll, 1994; Hobfoll, 2011). Specifically, resource gains relate to having a wider range of resources that expand an individual’s coping capacity, facilitating positive adaptation, preventing further resource losses due to adversity, and consequently preventing the experience of psychological distress and inhibited well-being. In contrast, resource losses relate to lower resource levels which are associated with insufficient coping capacities and increased vulnerability to future stress events, leading to additional resource losses and, consequently, increased psychological distress and lower well-being (Freedy & Hobfoll, 1994; Hobfoll, 1989). Taken together, COR theory posits that resource gains and losses will shape individual resilience to future adversity, with gains leading to increased resilience and losses leading to increased vulnerability. In what follows, we will apply a stressor lens to these propositions of COR theory, incorporating the challenge-hindrance framework and the concepts of stress inoculation and stress sensitization into the theoretical model. Challenge‑Hindrance Framework: Stressor‑Induced Net Resource Gains andLosses Building on transactional stress theory (Lazarus & Folkman, 1987), Cavanaugh etal. (2000) introduced the challengehindrance framework to the stress literature, arguing that there are two distinct types of work stressors: challenge and hindrance stressors (see also LePine, 2022). Overcoming either type of stressor requires individuals to invest energy resources and effort, and thus is likely to result in strain (Cavanaugh etal., 2000). In the case of challenge stressors, the investment of energy resources and effort is expected to lead to the acquisition of other valued resources (see also Hobfoll, 1989), including the experience of mastery, goal attainment, and personal development such as increases in self-efficacy (e.g., Webster etal., 2010), resulting in an overall net resource gain (see also Cavanaugh etal., 1998). 912 Journal of Business and Psychology (2024) 39:909–926 1 3 A net gain in resources following exposure to challenges is also the underlying principle of the concept of stress inoculation (Meichenbaum, 1977). The concept suggests that much like exposure to pathogens strengthens immunity to infectious disease; exposure to challenge stressors provides a training opportunity to acquire effective coping strategies and to develop regulatory capacities which strengthens individual resilience to future adversity (e.g., DiCorcia & Tronick, 2011; Meichenbaum, 1977). Similar processes are described by Bandura (1977), who outlines that performance accomplishments (i.e., mastery experiences) represent the primary source of self-efficacy which in turn facilitates positive adaptation to adversity (see also Bandura, 2001). Resources built through challenge-induced stress inoculation are further expected to positively affect adaptation to adversity across contexts (i.e., cross-inoculation) and thus likely enhance resilience to qualitatively distinct forms of adversity (see Ayash etal., 2020; Dienstbier, 1989; Freedy & Hobfoll, 1994; Schilbach etal., 2021). In contrast, in the case of hindrance stressors, the investment of energy resources and effort is not met by any resource gains in return (e.g., Webster etal., 2010). In fact, hindrance stressors represent barriers to goal attainment and are related to the experience of failure and frustration, and thus impede personal development (e.g., Cavanaugh etal., 2000; Kern etal., 2021; Shawney & Michel, 2022). Accordingly, hindrance stressors are associated with a net resource loss and the investment of energy and effort is not accompanied by a subsequent gain of valued resources (see e.g., Crane & Searle, 2016; Webster etal., 2010). According to COR theory, such losses are associated with psychological distress and increased vulnerability to future adversity (Hobfoll, 1989, 2011). The concept of stress sensitization which was developed to explain why stressors can lead to affective disorders (Post, 1992), makes similar assumptions. It argues that exposure to negative stressful experiences (e.g., hindrance stressors) triggers hyperreactivity to the same or different stressors in the future (Belda etal., 2015; Post, 1992; Stroud, 2020). Thus, similar to the concept of stress inoculation, stress sensitization posits a cross-context effect in which individuals experience heightened stress reactivity to a variety of different stressful events (i.e., cross-sensiti- zation). Such heightened reactivity inhibits positive adaptation and represents an important risk factor for individual resilience (e.g., Rutter, 2012). Researchers illustrated that (cross-)sensitization likely occurs via maladaptive cognitive and behavioral processes which lead to continuous resource losses. For example, Farb etal. (2015) proposed that sensitization occurs through dysphoric attention (i.e., fixation on the negative) and dysphoric elaboration (i.e., rumination), which are related to the formation of negative schemata, in which individuals develop a negative view of the self and the world. These processes likely lead to a loss of valued resources including efficacy beliefs, or social support (e.g., Lyubomirsky etal., 1999; Nolen-Hoeksema etal., 2008). Such losses render individuals increasingly vulnerable to subsequent stressful events and inhibit their resilience (Friedmann etal., 2016). The Link Between Past Work Stressors andAdaptation toCurrent Adversity Resilience is a process of positive adaptation to adversity. Fisher etal. (2019) outline that adversity, resilience mechanisms, and resilience outcomes represent the elements of the resilience process. Adversity indicates that an individual is facing negative and stressful life experiences (e.g., Kuntz etal., 2017; Obradović etal., 2012). It can be viewed on a continuum characterized by the intensity, the chronicity, the predictability, and the frequency of events (e.g., Britt etal., 2016; Estrada etal., 2016). Adversity further represents a precondition without which the resilience process cannot be observed (e.g., Britt etal., 2016; Fisher & Law, 2021). In this article, we refer to adversity as an event that occurs outside of the “business-as-usual” context (i.e., COVID-19 adversity), following the definition of Kuntz etal. (2017; see also Britt etal., 2016). However, we note that work stressors (e.g., overload) may also constitute adversity, especially if they are chronically present (see Fisher etal., 2019). When individuals face adversity, they will exhibit psychological and/or physiological reactions and engage in strategies to overcome adversity. Fisher etal. (2019) referred to these reactions and strategies as resilience mechanisms. Optimally, these mechanisms allow individuals to exhibit resilient outcomes that indicate health, functioning, wellbeing, or the absence of problems (e.g., burnout) despite adversity (Fisher etal., 2019; Hartmann etal., 2020). In the following sections, we will elaborate on the elements of the resilience process in more detail and derive their hypothesized relationships with past work stressors. Adversity In this study, we use the COVID-19 pandemic as an adverse event, specifically the first lockdown in Germany, which likely induced adversity in several ways. For example, concerns about one’s own health and the health of loved ones represent highly adverse experiences (Trougakos etal., 2020). Additionally, individuals were confronted with changes in daily life, such as social distancing, the inability to pursue hobbies, or the need to cope with increased private stressors (Rudolph etal., 2021). As such, the COVID-19 pandemic provides an appropriate context in which to study resilience (see e.g., Prime etal., 2020). However, not everyone was affected by the pandemic in the same way. While some lost a loved one, experienced 913Journal of Business and Psychology (2024) 39:909–926 1 3 financial worries, or had to cope with changing childcare arrangements, others were more fortunate. Additionally, given the dynamic nature of the pandemic and the frequent changes in regulations and restrictions as well as potentially varying levels of personal (e.g., energy) and structural resources (e.g., social support), there are likely to be inter- and intrapersonal differences in the adversity experienced. For example, during one week, parents may have been able to send their children to school, while the following week, schools may have had to close due to infections. To account for these inter- and intraindividual differences, we asked employees weekly about the extent to which they experienced COVID-19 adversity, so that we obtained an individual adversity indicator for each person and each week. In addition to experiencing different levels of adversity, individuals will also differ in their affective responses to changing adversity. For example, while person A may remain calm and serene despite increasing adversity, person B may become increasingly nervous and anxious. In what follows, we will discuss the relevance of such affective reactivity and elaborate on how it may explain the relationship between past work stressors and resilience outcomes in the face of current adversity. Affective Reactivity asaResilience Mechanism We focus on affective reactivity, which is the tendency to experience negative changes in affective states in response to specific events, in this study COVID-19 adversity (Sliwinski etal., 2009; Spear, 2009), as a resilience mechanism (i.e., how individuals react to adversity, Fisher etal., 2019). Fisher etal. (2019) emphasize that greater reactivity to adversity results in “increasingly large deviations from normal or optimal functioning, which is indicative of lower resilience” (p. 605). In simpler terms, as reactivity to adversity increases, the likelihood of maintaining good health, functioning, and ultimately demonstrating resilience decreases. Note that affective reactivity is only one of several potential resilience mechanisms. Fisher etal. (2019) provide an overview of other relevant mechanisms, such as cognitive appraisal, suppression of competing activities, or seeking social support. We chose to focus on affective reactivity as a resilience mechanism because it is an indicator of acute psychological distress and vulnerability to stressors and adversity (e.g., Charles etal., 2013; O’Neill etal., 2004; Piazza etal., 2013). In addition, it can be seen as a reflection of the adequate resources that individuals have to cope with an adverse situation: According to COR theory, when resources are adequate, individuals can protect themselves from adversity-induced resource losses by employing appropriate coping strategies and making effective use of existing resources. When resource losses are not experienced or anticipated, personal harm can be prevented, and thus, individuals will not respond to adversity with psychological distress (e.g., Hobfoll etal., 2018), that is, affective reactivity. In contrast, when resources are insufficient, individuals will be unable to protect themselves from additional adversity-induced resource losses. These actual or anticipated resource losses, in turn, lead to vulnerability to future adversity and thus to greater affective reactivity (e.g., Hobfoll, 2011; Hobfoll etal., 2018). To date, affective reactivity has mainly been studied in the context of the negative valence of affect (i.e., aversive mood states such as anger, contempt, fear, and nervousness; Watson etal., 1988). The positive valence (i.e., the extent to which a person feels enthusiastic, active, and alert; Watson etal., 1988) of affect is only rarely included in the study of affective reactivity (Ong etal., 2006). However, we argue that the negative and positive valence need to be considered because they serve different functions within the resilience process (e.g., Ong etal., 2006; Posner etal., 2005). Notably, research based on the broaden-and-build theory (Fredrickson, 2001) has demonstrated that negative and positive affect play different roles in positive adaptation. For instance, Fredrickson etal. (2003) found that negative affect following adversity had a positive whereas positive affect had a negative correlation with the development of depression. In addition, Tugade and Fredrickson (2004) showed that positive affect was linked to reduced cardiovascular reactivity and faster cardiovascular recovery during acute stress. These findings are further supported by Folkman and Moskowitz’s review (2000), suggesting that a lesser decrease in positive affect in response to stress signals the potential for mastery or gain and holds significant adaptive value. Accordingly, we included reactivity to COVID-19 adversity in positive and negative affect as a resilience mechanism. Previously, we argued that past challenge stressors may act as inoculation stressors by promoting the experience of mastery and personal growth, resulting in a net gain of resources (see e.g.,Cavanaugh etal., 2000 ; Crane & Searle, 2016 ; Webster etal., 2010). For example, individuals who have faced and successfully overcome challenge stressors in the past may believe that they can adequately cope with difficult and stressful situations, that is, they developed efficacy beliefs (e.g., Dienstbier, 1989; Webster etal., 2010). Such efficacy beliefs add to the coping repertoire of individuals, allowing them to cope more effectively with future adversity (Bandura, 2001). Adequate resources, in turn, prevent (anticipated) resource loss and thus the experience of psychological distress (e.g.,Hobfoll, 1989 ; Hobfoll etal., 2018). Initial empirical support for this line of argument comes from Dienstbier and PytlikZillig (2016), who outlined that certain activities (e.g., mental challenges) are associated with psychological toughness including emotional stability. Furthermore, Schilbach etal. (2021) illustrated that moderate challenge stressors related to lower levels and greater 914 Journal of Business and Psychology (2024) 39:909–926 1 3 stability of psychological distress during an acute laboratory stress event. Therefore, we hypothesize: H1: Past challenge stressors are associated with lower affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect. Furthermore, given their tendency to be detrimental and harmful to personal resources (Cavanaugh etal., 2000; Crane & Searle, 2016; Webster etal., 2010), we argued that hindrance stressors likely act as sensitizing stressors, resulting in net resource losses. For example, repeated exposure to hindrance stressors may relate to repeated experiences of failure (Cavanaugh etal., 2000). Failure despite the investment of effort, in turn, is associated with feelings of helplessness (Ursin & Eriksen, 2007), where individuals stop actively coping with stressful situations and lose their efficacy beliefs about overcoming future stress and adversity (e.g., Webster etal., 2010). Given these resource losses, individuals sensitized by hindrance stressors are at greater risk of experiencing additional resource losses in the face of novel adversity such as COVID-19 adversity, and thus are likely to experience greater psychological distress (e.g., Hobfoll, 1989) in the form of affective reactivity (see also Belda etal., 2015, 2016; Stroud, 2020). Accordingly, we hypothesize: H2: Past hindrance stressors are associated with greater affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect. Affective Reactivity andits Relationship toResilience Outcomes In this study, we chose emotional and psychosomatic strain during the COVID-19 pandemic as resilience outcomes. We did so for two main reasons. First, Hartmann etal. (2020) state that resilience outcomes can be modeled by examining the absence of problems—such as emotional strain—despite adversity. Second, Fisher etal. (2019) outline the need to consider the time frame in which resilience processes occur. We surveyed working employees over a 6-week period. We did not expect individuals in this sample to develop clinical psychopathology within such a relatively short time frame and therefore used emotional and psychosomatic strain as short- to medium-term indicators of resilience outcomes that may influence the risk of psychopathology over time (e.g., Santa Maria etal., 2017). COR theory posits that psychological distress, such as affective reactivity to adversity, arises from actual or anticipated resource losses, which can lead to a cycle of further losses (Hobfoll, 1989; Hobfoll etal., 2018). These loss cycles have a detrimental impact on individuals’ psychological and physical well-being. For instance, when adversity induces a decrease in positive affect (i.e., affective reactivity to adversity in positive affect), individuals may experience impaired attentional functioning, reduced social contacts, and diminished motivation for activities that would otherwise provide positive reinforcements (Fredrickson & Branigan, 2005). The absence of positive reinforcements may lead to a continuous decline in psychological well-being (e.g., De Wild-Hartmann etal., 2013). Similarly, when adversity triggers an increase in negative affect (i.e., affective reactivity to adversity in negative affect), it may initiate resource loss cycles through excessive negative rumination (e.g., Moberly & Watkins, 2008) or deterioration of relationship quality (e.g., Lépine & Briley, 2011). These factors can result in additional resource losses, such as declining levels of self-efficacy, optimism (e.g., Lyubomirsky etal., 1999), or social support (Nolen- Hoeksema etal., 2008), further inhibiting psychological wellbeing (see also Charles etal., 2013; Houben etal., 2015; O’Neill etal., 2004). Accordingly, we hypothesize: H3: Affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect is positively related to emotional exhaustion during the COVID-19 pandemic. With regard to psychosomatic symptoms, researchers outlined that affective reactivity in negative affect is associated with physiological loss cycles, as it triggers physiological stress responses that tax the body over time (McEwen, 2000) and increase the likelihood of health complaints (Charles etal., 2013; Piazza etal., 2013). Meta-analytic evidence supports this assumption showing that greater stress reactivity indicates a greater risk for the development of cardiovascular symptoms (Chida & Steptoe, 2010). Furthermore, several field studies suggest that stress-induced affective reactivity in negative affect positively relates to unhealthy habits (e.g., smoking and alcohol consumption; Schlauch etal., 2013), which may further promote the development of physical symptoms such as recurring back pain, migraines, or stomach problems (e.g., Piazza etal., 2013). In addition, a greater adversity-induced decrease in positive affect may also contribute to increased psychosomatic symptoms over time. Tugade and Fredrickson (2004) demonstrated that individuals who experienced lower positive affect during an acute stress event have prolonged cardiovascular reactivity (see also, Fredrickson & Levenson, 1998). Such prolonged stress reactivity may trigger similar loss processes to those described above and thus likewise contribute to psychosomatic symptoms (e.g., McEwen, 2000). Accordingly, we hypothesize: H4: Affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect is positively related to psychosomatic symptoms during the COVID-19 pandemic. 915Journal of Business and Psychology (2024) 39:909–926 1 3 Finally, combining hypotheses H1 to H4, we derive the following mediation hypotheses: H5: Past challenge stressors are negatively related to emotional exhaustion during the COVID-19 pandemic via lower affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect. H6: Past challenge stressors are negatively related to psychosomatic symptoms during the COVID-19 pandemic via lower affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect. H7: Past hindrance stressors are positively related to emotional exhaustion during the COVID-19 pandemic via higher affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect. H8: Past hindrance stressors are positively related to psychosomatic symptoms during the COVID-19 pandemic via higher affective reactivity to COVID-19 adversity in (a) positive and (b) negative affect. Method Participants andProcedures In 2018, we invited 182 German organizations to participate in our study. To incentivize participation, we offered organizations parts of a psychological risk assessment, which is a mandatory procedure in Germany. Thirteen organizations agreed to take part. All organizations allowed employees to complete the surveys at work, and some offered additional incentives for participation, such as a drawing of wellness vouchers. To be eligible to participate, employees had to work at least 20 h per week. Participants were recruited through information sessions or intranet postings. A total of 572 employees enrolled in the study and completed the initial survey. Participants then provided information on their work stressors in a weekly diary over the course of 3 weeks and further completed two additional surveys six and 12 months after the last weekly survey. Thus, we obtained information on employees’ stressors on up to five measurement occasions over the course of 13 months between April 2018 and November 2019 (T0)1. We chose to use the repeated measures of work stressors over an extended period of time to gain a robust insight into the general working conditions of participants that may be related to inoculation (i.e., resource gains) or sensitization processes (i.e., resource losses), to control for seasonal effects that may be associated with high or low work stressors, and to further reduce the impact of common method variance (Podsakoff etal., 2003). Subsequently, in March 2020, we used the first COVID- 19-induced lockdown in Germany as an opportunity to examine the resilience process and re-contacted the same participants. Participants were invited to complete a baseline survey, followed by six weekly surveys (T1–T6). In the weekly surveys (T1–T5), participants provided information on COVID-19 adversity and their positive/negative affect. In addition, emotional exhaustion and psychosomatic symptoms were measured at week one (T1) and week six (T6). We used a 6-week weekly study mainly for two reasons: first, given the dynamics of the pandemic and associated the changing (government) regulations, we expected that levels of adversity would vary not only between individuals, but also within individuals. To account for these within-person variations in COVID-19 adversity, and given that regulations changed weekly rather than daily, we decided to administer weekly surveys. Second, our goal was to examine how shortterm reactivity (i.e., affective reactivity to COVID-19 adversity) accumulates to shape mid- to long-term psychological well-being as an indicator of resilience outcomes. Because stress-induced psychosomatic symptoms take several weeks to develop (e.g., Keller etal., 2020), we chose to administer our survey over the course of 6 weeks. We incentivized participation in the 6-week weekly study in the following ways: We sent out a summary of key findings including specific suggestions on how to maintain or strengthen individual resilience after the data collection was completed. In addition, we raffled 25 vouchers (20€ each) obtained from a social catering company. Ethical approval was obtained prior to data collection. The baseline survey of the 2020 weekly study was completed by 199 employees, resulting in a response rate of 34.8%. Individuals who participated in the 2020 weekly study did not differ in age, gender, or education from those who only participated in the 2018/2019 panel study. Given that we were interested in weekly affective reactivity to COVID-19 adversity, we excluded 17 individuals who did not respond to at least one of the weekly surveys. Of the resulting 182 participants, 134 individuals completed at least one of the 2018 weekly diary study follow-up surveys (i.e., at six- or 12-month follow-up) and also completed T1 and T6 during the COVID-19-induced lockdown. We based our analyses on these 134 individuals who provided a robust insight into their general work conditions (i.e., by providing information on their work stressors for at least 7 months), and whose participation in T1 and T6 allowed us to test whether mediator variables would predict outcomes at T6 over and above outcomes at T1. In the final sample, the mean age was 46.2 years (SD = 10.84), 70.5% of participants were female and 51.9% of the participants held an (applied) university degree. Additionally, 82.9% were in a 1 Note that this data collection was part of a larger project. A data transparency table is included in the online supplement on page 8. 916 Journal of Business and Psychology (2024) 39:909–926 1 3 relationship and 52.2% reported having at least one child. On average, participants worked for 36.2 h per week (SD = 9.91). Our sample consisted of office/knowledge workers, mainly employed in the (public) service and the financial sectors. Measures We measured all study variables in German. Table1 presents descriptive statistics, intercorrelations, and reliability indices. Challenge andHindrance Stressors We assessed work stressors at T0 (i.e., at up to five measurement occasions between April 2018 and November 2019) using the challenge-hindrance scale developed by Rodell and Judge (2009). Participants indicated their responses on a scale from 1 (strongly disagree) to 5 (strongly agree), referring to either their workweek (for the first three measurement occasions) or the past 6 months (for the last two measurement occasions). The challenge stressor scale consists of eight items assessing time pressure, workload, complexity, and responsibility with two items each. In this study, we focused on responsibility and complexity as challenge stressors. Unlike time pressure and workload, for which the empirical evidence regarding their challenging potential is mixed (e.g., Schilbach, Haun, etal.,2023; Schmitt etal., 2015), these stressors show a clear challenging tendency: Kim and Beehr (2020), for example, showed that responsibility and learning demands (i.e., a construct closely related to complexity) were positively related to challenge and negatively related to hindrance appraisal. Similarly, Schilbach, Arnold, etal., (2023) showed that complexity was appraised as challenging regardless of co-occurring stressors but was appraised as hindering only when co-occurring stressors were high. Thus, we excluded the four items assessing workload and time pressure and tested our hypotheses based on the four items assessing complexity and responsibility (e.g., “My job has required me to use a number of complex or high-level skills,” “or “I’ve felt the weight of the amount of responsibility I have at work”). Hindrance stressors were measured using all eight items developed of the Rodell and Judge (2009) scale, which assesses levels of role conflict, role ambiguity, red tape, and daily hassles. Sample items were “I had to go through a lot of red tape to get my job done” or “I had many hassles to go through to get my projects/assignments done.” Given that the hypotheses were tested at the betweenperson level, we conducted a partially saturated multilevel confirmatory factor analysis (MCFA) to obtain betweenperson model fits (Ryu & West, 2009). In conducting the MCFAs, we also included workload and time pressure items (Rodell & Judge, 2009) to assess the appropriateness of excluding these items from the challenge stressor scale. Consistent with our assumptions, a three-factor model with complexity and responsibility items comprising one factor, time pressure and workload items comprising a second factor, and hindrance stressor items comprising a third factor (χ2(101) = 386.51, p<.001; CFI = .91, TLI = .79, AIC = 24857.53, RMSEA = 0.07) fit the data significantly better than a model in which the time pressure, workload, complexity, and responsibility items were modeled as one factor and the hindrance stressor items were modeled as a second factor (χ2(103) = 542.07, p<.001; CFI = .86, TLI = .68, AIC = 24959.63, RMSEA = 0.08), or a single-factor model (χ2(104) = 662.00, p<.001; CFI = .82, TLI = .59, AIC = 25056.14, RMSEA = 0.09). Table 1 Means, standard deviations, Cronbach’s alpha, and correlation of study variables N=134. In parentheses on the diagonal, we have depicted Cronbach’s alpha where applicable. All correlations andalphas are at the betweenperson level *p <.05; **p<.01 M (SD) 1 2 3 4 5 6 7 8 1. Challenge stressors (T0) 3.39 (0.66) (.92) 2. Hindrance stressors (T0) 2.62 (0.67) .58** (.86) 3. Affective reactivity to COVID-19 adversity in positive affect (T1–T5) −0.11 (0.06) .17* −.07 4. Affective reactivity to COVID- 19 adversity in negative affect (T1–T5) 0.61 (0.02) .16 .29** .12 5. Emotional exhaustion (T1) 2.29 (1.18) .15 .30** −.09 .08 (.89) 6. Psychosomatic symptoms (T1) 2.22 (0.79) .09 .19* .12 .22* .49** (.70) 7. Emotional exhaustion (T6) 2.31 (1.17) .17 .41** −.30** .02 .67** .30** (.88) 8. Psychosomatic symptoms (T6) 2.20 (0.85) .03 .22* −.24** .25** .34** .51** .58** (.72) 923Journal of Business and Psychology (2024) 39:909–926 1 3 Beckie, T. M. (2012). A systematic review of allostatic load, health, and health disparities. 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