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. 2020 Apr 16;6(3):153–164. doi: 10.1093/workar/waaa007

Disrespect at Work, Distress at Home: A Longitudinal Investigation of Incivility Spillover and Crossover Among Older Workers

Lisa A Marchiondo 1,✉, Gwenith G Fisher 2,3,4, Lilia M Cortina 5,6, Russell A Matthews 7
Editor: Donald Truxillo
PMCID: PMC7348587  PMID: 32685181

Abstract

The prevalence of workplace mistreatment toward older adults is well-documented, yet its effects are understudied. We applied the strength and vulnerability integration model (SAVI) to hypothesize that, despite its low intensity, workplace incivility has numerous deleterious outcomes for older employees over time. Specifically, we investigated whether and how incivility relates to well-being outside of work, among both targeted employees and their partners. We drew on affective events theory to examine how incivility “spills over” to older targets’ personal lives. We also tested whether incivility is potent enough to “crossover” to the well-being of older targets’ partners at home. Based on longitudinal data from a national study of older workers (N = 598; 299 couples), results demonstrate that workplace incivility related to decrements in targets’ affective well-being, which in turn, was associated with life dissatisfaction, interference with work, and lower overall health. Workplace incivility also predicted declines in partner well-being, although these crossover effects varied by gender: Men’s postincivility affective well-being predicted their female partners’ life satisfaction but not vice versa. However, women’s uncivil experiences directly related to the affective well-being of their male partners. These results suggest that for both older workers and their partners, the harms of incivility eventually extend beyond the organizations where they originate.

The older workforce is particularly vulnerable to interpersonal mistreatment (Barnes-Farrell, 2005; Palmore, 2015; Perron, 2018)—including being ignored, teased (e.g., “old age” jokes), and provided fewer job and promotion opportunities—but the effects of these experiences remain underexplored. Due to their distinct coping strategies, older adults are a unique group among which to study the effects of mistreatment. They tend to cope more effectively with and react less negatively to stressors, compared with younger adults (Charles & Piazza, 2009; Diehl, Coyle, & Labouvie-Vief, 1996). These advantages can be short-lived, however: According to the strength and vulnerability integration model (SAVI; Charles, 2010), older adults’ coping strengths help in the short-term but eventually erode as resources are taxed. Over time, mistreatment might yield a host of negative outcomes for older workers. This could be especially true for low-intensity forms of mistreatment, such as incivility (e.g., being devalued, overlooked, treated as less capable), which skirts below age discrimination laws and often continues unregulated (Marchiondo, Gonzales, & Ran, 2016). Thus, the overarching goal of the current study is to investigate long-term outcomes of workplace incivility for older employees.

Abundant research has demonstrated relationships between workplace incivility and targets’ professional outcomes (e.g., performance decline, job burnout, job turnover; Cortina, Kabat-Farr, Magley, & Nelson, 2017; Porath & Erez, 2007). We extend this literature by testing whether workplace incivility “spills over” into life domains outside of work, consistent with the spillover-crossover model (Bakker & Demerouti, 2013). Some cross-sectional research has not found a link between workplace incivility and non-work outcomes though (e.g., life satisfaction; Lim & Lee, 2011). It could be that incivility harms are isolated to the immediate context (work), given that it is a low-intensity, ambiguous stressor (Andersson & Pearson, 1999). Alternatively, nonwork outcomes of incivility might emerge only longer-term, particularly for older workers—a proposition we test using a longitudinal panel study.

Beyond incivility spillover, minimal research has investigated whether incivility outcomes “cross over” to affect targets’ partners at home—also in line with the spillover-crossover model (Bakker & Demerouti, 2013). In a notable exception, Ferguson (2012) found correlations between incivility and several partner-reported variables, including marital satisfaction and conflict. This was a relatively young sample, with an average age of 35–36 years. Many unanswered questions remain about incivility crossover, especially for older couples.

Our work makes several novel contributions to the aging and incivility literatures. First, we provide one of the few empirical tests of the SAVI model (Charles, 2010), examining the degree to which incivility negatively relates to older workers’ experiences over time, despite their coping advantages. We focus on personal, nonwork outcomes in order to address ambiguous results in previous research. Cross-sectional spillover studies might not have revealed personal outcomes of incivility because these effects could take time and repeated exposure to manifest (Matthews & Ritter, 2019). Second, we hypothesize that incivility will crossover to affect the well-being of older workers’ partners at home (Miner et al., 2018). Uncovering the contagious effects of incivility demonstrates how far-reaching this type of mistreatment can be, despite its low-intensity nature. Finally, we conduct exploratory tests of possible gender differences in incivility crossover. This not only brings fresh insights to the workplace incivility literature but also adds new data to an ongoing debate about gender in work–family interactions (e.g., Westman, Brough, & Kalliath, 2009). Many studies have documented crossover only from men to women (Westman et al., 2009), but findings are mixed, warranting more attention to this topic, particularly among an understudied but growing population such as older workers.

HOW INCIVILITY AFFECTS OLDER WORKERS: APPLYING THE SAVI MODEL

The aging workforce is a population of critical interest to many organizations and policy-makers. Older adults comprise the largest segment of the U.S. workforce, due not only to the large Baby Boomer generation but also to increasing life expectancies and retirement ages (Fisher, Chaffee, & Sonnega, 2016). Older workers could be at greater risk of incivility due to pervasive and increasingly negative older age stereotypes (Levy, 2017). Even when stereotypes of older adults include both positive and negative elements, this mixed pattern of stereotyping breeds interpersonal disregard and exclusion (Cuddy, Norton, & Fiske, 2005). Ample research has documented overt forms of mistreatment toward older workers (e.g., Gordon & Arvey, 2004; Richardson, Webb, Webber, & Smith, 2013), although covert manifestations such as incivility appear to be even more common (Marchiondo, 2015; Marchiondo et al., 2016).

The effects of covert mistreatment on older workers are not well understood, particularly over time. (More generally, there is a dearth of mistreatment research that takes an over-time perspective, Cole, Shipp, & Taylor, 2016; exceptions are noted below.) Most research linking workplace incivility to target outcomes has centered on the experiences of young and middle-aged workers. Extending this work to capture its effects on older employees is important, given that experiences of and responses to stressors vary with age (Barnes-Farrell, 2005; Jex, Wang, & Zarubin, 2007). Older adults cope with stressors more effectively and better regulate their emotions than younger adults (Charles & Piazza, 2009; Diehl et al., 1996), perhaps providing a buffer against incivility. However, the SAVI model proposes that chronic stressors eventually erode older adults’ skills so that, over time, they experience strain similar to other age groups (Charles, 2010). Similar to “wear and tear” models of workplace incivility (Cortina, Magley, Williams, & Langhout, 2001), the SAVI model can be applied to hypothesize that repeated exposure to mistreatment will undermine older employees’ strengths in responding to stressful events (Charles, Piazza, Mogle, Sliwinski, & Almeida, 2013). In an example of this effect, continual social rejection (a form of incivility) has been shown to result in cognitive declines for older adults (Cheng & Grühn, 2015). Extending empirical support for the SAVI model, we investigate long-term outcomes of incivility for older employees as well as their partners.

WORKPLACE INCIVILITY SPILLOVER

Compared to the abundant literature on professional outcomes of incivility, less is known about incivility spillover to targets’ personal lives. Unlike other mistreatment constructs, incivility is low in intensity and ambiguous in intent to harm (Andersson & Pearson, 1999). This could limit the extent to which the harms of incivility reach beyond the context of the workplace. However, empirical research has begun to demonstrate otherwise, demonstrating links between incivility and targets’ work–family conflict (Lim & Lee, 2011), negative marital behavior (Lim, Ilies, Koopman, Christoforou, & Arvey, 2018), and marital dissatisfaction (Ferguson, 2012). Moreover, targets of incivility and supervisor undermining are more likely to report poorer sleep quality, and in turn, mistreat cohabitants at home (Barber, Taylor, Burton, & Bailey, 2017; Fritz, Park, & Shepherd, 2019).

To expand the nascent literature on incivility spillover, we theorize that many nonwork outcomes of incivility might require time to emerge due to the proposed wear and tear process of incivility (Cortina et al., 2001). Daily diary and experience sampling studies have addressed short-term effects of incivility. This work has established several day- and week-long consequences of incivility (e.g., lower situational well-being after work; Nicholson & Griffin, 2015), demonstrating that targets do not simply “shake off incivility” when they leave work. Taking a medium-term perspective, Lim and Tai (2014) demonstrated decrements in job performance 2 months after employees reported family incivility. Taylor, Bedeian, Cole, and Zhang (2017) found that workplace incivility predicts job burnout and subsequently turnover intentions, over a 6-week period. What remain understudied are nonwork outcomes of incivility over the long-term, particularly among older workers (many incivility studies have focused on workers in their 20s and 30s; e.g., MBA students).

To expand the workplace incivility literature and address notable gaps, we develop a longitudinal model of the spillover and crossover outcomes of workplace incivility among older adults (Figure 1). This model heeds recommendations to conduct work/family, mistreatment, and ageism research across multiple time points (e.g., Cole et al., 2016; Matthews, Wayne, & Ford, 2014) and to provide holistic attention to a wider variety of constructs (Posthuma, Wagstaff, & Campion, 2012; Voydanoff, 2007). Next, we discuss each pathway in the model.

Figure 1.

Figure 1.

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Proposed model of spillover effects (solid lines) and crossover effects (double lines) of workplace incivility. Workplace incivility was measured at T1. Affective well-being was measured at T2. Life satisfaction, overall health, and personal-life-to-work interference were measured at T3.

First, we propose that an important proximal outcome of incivility is affective well-being, which encompasses emotions, moods, and related psychological states (Vanhoutte & Nazroo, 2014). Psychological well-being, or mental health, is a notable component of affective well-being (Daniels, 2000), as Vanhoutte and Nazroo (2014) remark: “The affective aspect of well-being brings measurement very close to assessing mental health” (p. 3). Beyond symptoms of mood disorders such as anxiety and depression, affective well-being captures positive and negative emotions and generalized mood as well (Luhmann, Hawkley, Eid, & Cacioppo, 2012). It differs from cognitive well-being, which involves global satisfaction with specific domains of one’s life, such as life satisfaction (Luhmann et al., 2012; Vanhoutte & Nazroo, 2014).

Incivility targets have reported various decrements in affective well-being, including specific negative emotions (e.g., sadness), generalized negative affect, psychological distress (e.g., symptoms of depression, anxiety), and emotional exhaustion (Schilpzand, De Pater, & Erez, 2016). Workplace incivility has been modeled as eroding targets’ emotional resources and mental health, and eventually, global aspects of their well-being (Lim, Cortina, & Magley, 2008). Indeed, daily stressors relate to long-term affective distress (Charles et al., 2013). Supporting affective well-being as a bridge between work and home domains, research has shown that emotional exhaustion mediates the link between unethical customer behavior and service employees’ work–family conflict (Greenbaum, Quade, Mawritz, Kim, & Crosby, 2014).

Our proposition regarding the role of affective well-being is rooted in affective events theory (AET), which posits that work events trigger affective states that then shape employees’ attitudes and behaviors over time (Weiss & Cropanzano, 1996). According to AET, affect is central to explaining relationships between work events and distal outcomes. Although the bulk of this research has centered on affect as a mediator between work events and work-related outcomes, we extend application of AET to propose that affective well-being also serves as a conduit between incivility and targets’ nonwork outcomes.

Hypothesis 1: Workplace incivility negatively relates to targets’ affective well-being.

According to both AET and the SAVI model, negative affective experiences accumulate and eventually shape attitudes and behaviors (Charles, 2010; Weis & Cropanzano, 1996). We apply these theories to explain how workplace incivility relates to three distal outcomes: target life satisfaction, overall health, and personal-life-to-work interference.

With regard to the first distal variable, one could hypothesize that workplace incivility relates directly to life satisfaction. This possibility has received mixed support though, with some studies finding this relationship (Lim & Cortina, 2005; Miner, Settles, Pratt-Hyatt, & Brady, 2012) and others not (Cortina et al., 2001; Lim & Lee, 2011). These inconsistent findings could be due to the cross-sectional nature of the research: Life satisfaction is a broad, global construct, so it might take time for a low-intensity stressor such as workplace incivility to affect it. In addition, this effect might emerge only after affective well-being has declined, consistent with AET. Therefore, incivility is apt to influence facets of cognitive well-being such as life satisfaction through more proximal, affect-laden variables.

Hypothesis 2: Affective well-being positively relates to targets’ life satisfaction.

The second distal outcome of incivility in our model is overall physical health. Ample research demonstrates a link between mind and body (Brower, 2006). Declines in affective well-being can impair physical health, occurring directly through physiological changes (e.g., increases in cortisol) or indirectly through behavioral changes (e.g., unhealthy or risky behavior; Leventhal & Patrick-Miller, 2000). AET provides theoretical support for the latter pathway, positing that affective experiences influence not only attitudes but also behaviors (Weis & Cropanzano, 1996). Consistent with this, Lim and colleagues (2008) found that psychological distress (indicating lower affective well-being) mediated the relationship between workplace incivility and targets’ physical health. Yet, several studies found no relationship between incivility and physical health (Cortina et al., 2001; Lim & Lee, 2011; Miner et al., 2012). Similar to the null findings between incivility and life satisfaction, the incivility-to-health link is apt to take time to develop and to emerge by undercutting affective well-being, consistent with AET. Therefore, we hypothesize:

Hypothesis 3: Affective well-being positively relates to targets’ overall health.

The third distal outcome, again predicted by affective wellbeing, is personal-life-to-work interference. Work and personal domains are intertwined according to the spillover-crossover model, so struggles in employees’ personal lives eventually circle back to their work lives (Bakker & Demerouti, 2013). Supporting this interplay, Ferguson (2012) demonstrated a cross-sectional relationship between workplace incivility and family-to-work conflict among younger workers. Extending this research using longitudinal methods and an older sample, we test long-term “boomerang” effects between workplace incivility, spillover to nonwork outcomes (i.e., affective well-being), and spillover back to the work domain (i.e., personal-life-to-work interference):

Hypothesis 4: Affective well-being negatively relates to targets’ personal-life-to-work-interference.

WORKPLACE INCIVILITY CROSSOVER

Research on whether and how incivility crosses over to targeted employees’ spouses (herein referred to as partners) is limited but important for uncovering the reach of incivility (Miner et al., 2018). The concept of crossover suggests that incivility, despite its low-intensity features, should influence targets’ partners. According to the spillover-crossover model (Bakker & Demerouti, 2013), one’s stress and strain increase the stress and strain of others in the same environment (Westman & Etzion, 1995). An individual’s psychological state and well-being can quite easily influence those with whom s/he interacts (Bolger, DeLongis, Kessler, & Wethington, 1989). The crossover literature can be conceptualized using the systems theory framework, which treats family and work systems as interrelated and thus continually influencing one another (Bronfenbrenner, 1977). Accordingly, partners affect one another’s personal and work lives (Hammer, Cullen, Neal, Sinclair, & Shafiro, 2005).

We focus on three crossover relationships. They include facets of partner well-being that are not explicitly tied to the dyad, thereby testing whether incivility crosses over to partners’ individual outcomes (as opposed to only relationship-centered outcomes, such as marital satisfaction). According to Westman (2001), individuals experience empathic and emotional reactions to their partners’ stressful work events. Empirical support for this direct crossover mechanism exists. For instance, work-to-family conflict crosses over to influence partners’ depressive symptoms (Hammer et al., 2005). Emotional contagion and affiliation between individuals increase when one feels threatened, as does behavioral mimicry (Gump & Kulik, 1997). Thus, partners of incivility targets should experience decrements to their affective well-being when targets “bring incivility home.” Based on this reasoning, we propose that:

Hypothesis 5: Partner A’s incivility experience negatively crosses over to Partner B’s affective well-being.

More distally, does incivility cross over to shape other facets of partners’ well-being? Again drawing on Westman’s (2001) crossover mechanism, employees’ affective experiences influence their partners via empathetic and emotional contagion processes. Thus, the affective strain that results from incivility will cross over to undermine the distal outcomes of targets’ partners, similar to the relationship between affective well-being and targets’ own distal outcomes. Our model addresses crossover to two such distal outcomes for partners: personal-life-to-work interference and life satisfaction.

Preliminary support exists for the relationship between incivility and a partner’s family-to-work conflict. When partners of incivility targets sense stress transmission into the family domain, they are more likely to carry this burden into their own workplaces (Ferguson, 2012). Building on this foundation, we test a similar link longitudinally among older workers, incorporating affective well-being as a key predictor of interference with work (aligned with AET).

Incivility targets’ affective well-being might also shape their partners’ life satisfaction. Cross-sectional research has documented crossover in life satisfaction between spouses (e.g., Bookwala & Schulz, 1996; Park & Fritz, 2015). Work-to-family conflict also affects spousal life satisfaction (Zhang, Foley, & Yang, 2013). Applying AET and a longitudinal lens to this work, we propose that through emotional contagion, decrements to incivility targets’ affective well-being undermine their partners’ life satisfaction. Life satisfaction is apt to decline as partners “catch” one another’s negative affect (Bookwala & Schulz, 1996). In addition, workplace mistreatment targets have been shown to engage in angry and withdrawn marital behavior and undermining at home (Barber et al., 2017; Lim et al., 2018)—all likely to contribute to their partners’ life dissatisfaction.

Hypothesis 6: Partner A’s affective well-being crosses over to Partner B, (a) increasing his/her personal-life-to-work interference and (b) decreasing his/her life satisfaction.

GENDER DIFFERENCES IN INCIVILITY CROSSOVER

Discussion of the work–family interface inevitably invites inquiry about gender. We were especially interested in possible gender differences in crossover, in light of equivocal findings in prior research. While many effects cross over only from men to women, the opposite occurs for other crossover relationships, and the relationships can even be bidirectional (Westman et al., 2009; Westman & Etzion, 2005). In terms of male-to-female crossover, women might be more negatively affected than men by their partners’ uncivil work experiences. Women, more than men, are socialized to be empathic to others’ emotions and stressful experiences (Bekker & van Assen, 2008; Eagly & Wood, 1991). Women also tend to be more involved in family affairs (Cinamon & Rich, 2002). As a result, women could be more attuned to and affected by their husbands’ postwork affect than vice versa (Westman et al., 2009). Consistent with this idea, wives report being more affected by their husbands’ workloads (van Steenergen, Kluwer, & Karney, 2011). However, crossover studies have also found unilateral effects from women to men, null effects, and complicated patterns of effects, warranting caution in assuming male-to-female effects (e.g., Bakker & Demerouti, 2013). For instance, job-related support from wives can amplify husbands’ work–family conflict following job stress (Westman & Etzion, 2005). Given that the literature is inconclusive regarding gender differences in crossover effects (Westman et al., 2009), we pose the following exploratory research question with respect to the effects in Hypotheses 5 and 6: Do gender differences exist in incivility crossover?

METHOD

Participants and Procedure

Data were obtained from the 2006, 2008, and 2010 waves (T1–T3, respectively) of the Health and Retirement Study (HRS), a U.S. panel study conducted by the Institute for Social Research at the University of Michigan and funded by the National Institute on Aging (U01 AG009740). HRS participants were sampled at the household level, including individuals aged 51 or older and their spouses/partners regardless of age. In 2006, the HRS began administering a psychosocial questionnaire to the same respondents every 4 years. Thus, T1 and T3 data were gathered from the psychosocial questionnaire, whereas T2 data were gathered from the 2008 core (main) HRS interview. The response rate, accounting for participation in both the core and psychosocial HRS surveys, was 74% (Smith, Ryan, Fisher, Sonnega, & Weir, 2017).

We selected couples in which both individuals were employed and remained working with the same employers and jobs across waves. We retained couples who remained partnered across all three waves. We restricted our sample to different-gender couples for two reasons: (a) the HRS contains few same-gender couples, so results from this subsample would not validly reflect the experiences of this population, and (b) one goal of the study is to test gender differences in crossover effects, necessitating different-gender couples. Participants missing data for two or more constructs were excluded from analyses, resulting in N = 598 workers (or 299 couples). Mean age at T1 was 54.67 years (SD = 6.23 years) for women and 57.85 years (SD = 6.14 years) for men. Most women (90.3%) and men (91%) were White, 6.4% of women and 6.4% of men were Black/African American, and 3.3% of women and 2.7% of men were of another race (unspecified). In addition, 6.7% of both women and men identified as Latino/a.

Measurement

The study contained multiple features consistent with Podsakoff and colleagues’ (2012) recommendations for minimizing common method bias. For example, the measures were collected at three time points, creating temporal separation between the criterion and predictor variables. In addition, data came from multiple sources (dyads). To promote honest responding, participants were assured confidentiality. Further, scale endpoints and formats varied between predictor and criterion variables. Outcome measures were rooted in established literature supporting their construct validity, and finally, correlations between variables were not unreasonably high.

Workplace incivility (T1)

Incivility was assessed at T1 using a measure by Williams, Yu, Jackson, and Anderson (1997), which contains similar items to the most commonly used incivility measure, the Workplace Incivility Scale (Cortina et al., 2001). Participants rated the frequency with which they experienced six situations at work during the last 12 months (e.g., “How often have you been unfairly humiliated in front of others at work?”, “How often do you feel that you are ignored or not taken seriously by your boss?”) from 1 (never) to 6 (almost every day). Internal consistency reliability was acceptable for both men (α = .78) and women (α = .74).

Affective well-being (T2)

Affective well-being includes emotions, moods, and related psychological states such as depression (Vanhoutte & Nazroo, 2014). To capture this construct, we followed precedent set by Wang (2007) by using the Center for Epidemiologic Studies Depression (CES-D) scale, administered in the T2 core survey. The CES-D is one of the most common and well-validated assessments of affective well-being, including among older adults (Vanhoutte & Nazroo, 2014). Eight items assessed facets such as emotions (e.g., “you felt happy”; reverse-coded), emotional exhaustion (e.g., “you could not get going”), and symptoms of psychological distress or mood disturbance (e.g., “your sleep was restless”). Participants indicated (yes or no) if each item was true much of the time, and a summation of “yes” responses yielded scores from 0 to 8. The inverse of the sum was used so that higher scores indicated higher well-being. With a history of strong psychometric properties (Steffick, 2000), this measure had acceptable reliability for men and women (α = .73 each).

Personal-life-to-work interference (T3)

At T3, the HRS administered MacDermid and colleagues’ (2000) measure of work-life tension, including three items assessing personal-life-to-work interference (e.g., “I am preoccupied with personal responsibilities while I am at work”). Participants rated each item from 1 (rarely) to 4 (most of the time). This measure is an improvement over traditional work–family conflict measures that capture only the extent to which immediate family interferes with work; “personal life” accounts for a broader spectrum of the nonwork domain, including roles unrelated to family (e.g., volunteer, friend; Fisher, Bulger, & Smith, 2009). Reliability was acceptable for men (α = .69) and women (α = .75).

Life satisfaction (T3)

The Satisfaction with Life Scale (Diener, Emmons, Larsen, & Griffin, 1985) contained five items (e.g., “I am satisfied with my life”), rated on a 7-point scale (strongly disagree to strongly agree). This measure’s reliability and construct validity are well established (e.g., Diener, Suh, Lucas, & Smith, 1999). Reliability was high for men and women (both α = .90).

Overall health (T3)

Participants rated their health, answering “Would you say your health is excellent, very good, good, fair, or poor?” Higher numbers indicated better health. Despite containing one item, this measure is common in epidemiological research and has been repeatedly shown to validly capture overall health and to predict mortality (e.g., Benyamini & Idler, 1999; DeSalvo, Bloser, Reynolds, He, & Muntner, 2006).

Neuroticism (T1 covariate)

Neuroticism at T1 was included as a covariate to account for the influence of negative dispositions, or stable personality traits, on the pathways in the model (i.e., each participant’s neuroticism predicted all of his/her outcomes). Empirical and theoretical work supports the idea that neuroticism predicts exposure to stressors, coping mechanisms, and ultimately, subjective well-being, including negative affect and life satisfaction (Bolger & Zuckerman, 1995; DeNeve & Cooper, 1998). Neuroticism was assessed with four items (α = .75 for men; α = .68 for women) from the International Personality Item Pool (Lachman & Weaver, 1997), rated on a 4-point scale from not at all to a lot.

RESULTS

Descriptive statistics and t-tests comparing men’s and women’s means appear in Table 1. Men and women had similar means for each construct. Approximately 67% of men and 66% of women reported experiencing at least some incivility in the past year. Bivariate correlations between study variables for men and women are displayed in Table 2.

Table 1.

Descriptive Statistics and Alpha Coefficients for Study Variables by Participant Sex

Variable Men Women t-Test Comparing Means
M SD α M SD α
1. Workplace incivility 1.70 0.83 .78 1.61 0.73 .74 1.42
3. Affective well-being 7.32 1.36 .73 7.11 1.57 .73 1.40
4. Personal-life-to-work interference 1.13 0.29 .69 1.16 0.30 .75 1.44
5. Life satisfaction 4.98 1.46 .90 5.21 1.40 .90 0.32
6. Overall health 3.66 0.90 n/a 3.73 0.88 n/a −0.97
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Note. N = 244. We developed overall index scores by calculating the means of all items in each scale. Higher scores indicate higher levels of the underlying constructs. None of the t-tests were statistically significant (p < .05).

Table 2.

Intercorrelations Among Study Variables by Participant Sex

Variable 1 2 3 4 5
1. Workplace incivility −.25** .18** −.04 −.06
2. Affective well-being −.26** −.15** .27** .20**
3. Personal-life-to-work interference .05 −.22** −.26** −.05**
4. Life satisfaction −.21** .32** −.15* .28**
5. Overall health −.14* .29* −.14* −.13*
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Note. N = 244–299. Correlations for men are below the diagonal. Correlations for women appear above the diagonal.

*p < .05 (two-tailed); **p < .01 (two-tailed).

Conceptual Model Testing

We tested a path analytic model using AMOS 21 (Figure 1). Consistent with prior studies of crossover, we used the Actor-Partner Interdependence Model (APIM) to account for interdependence of the data in dyads (Campbell & Kashy, 2002; Kashy & Kenny, 2000). The APIM is both a conceptual model and a statistical technique, accounting for the notion that an individual’s experience of a predictor variable affects his/her own outcomes as well as his/her partner’s outcomes. The effect on the individual is known as the “actor effect,” and the effect on the partner is labeled the “partner effect” (Campbell & Kashy, 2002). Following APIM procedures, men (Partner A) and women (Partner B) were yoked per couple, and effects for men and women were modeled simultaneously (Kashy & Kenny, 2000).

The initial conceptual model demonstrated good fit, χ 2(36) = 47.24, p = .10, CFI = .95, TLI = .92, RMSEA = .036. Unstandardized and standardized path coefficients (direct effects) appear in Figure 2. Table 3 presents direct and indirect effects. We tested an alternative model of reverse-causality with crossover effects (i.e., health and personal-life-to-work interference predicting affective well-being, which predicted incivility). The alternative model did not fit the data as well as our original model, χ 2(36) = 88.9, p = .000, CFI = .778, TLI = .619, RMSEA = .077.

Figure 2.

Figure 2.

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Unstandardized / standardized path estimates (direct effects) for the empirical model. Dashed lines indicate nonsignificant paths. Not shown are the paths from neuroticism (T1 control variable) to the variables measured for each individual. PLWI = personal-life-to-work interference. *p < .05; **p < .01.

Table 3.

Direct and Indirect Effects of Predictor Variables on Outcome Variables

Predictor Variables Affective Wellbeing Life Satisfaction Overall Health Personal-Life-to-Work Interference Life Satisfaction Overall Health Personal-Life-to-Work Interference
Men Women Men Men Men Women Women Women
Direct effects
 Workplace incivility for men −.24** .05
 Workplace incivility for women −.11* −.17**
 Affective well-being for men .26** .24** −.13* .23** — .01
 Affective well-being for women .07 — −.01 .24** .14* −.15*
Indirect effects via affective well-being
 Workplace incivility for men −.06* −.06* .04* −.04* .01 .01
 Workplace incivility for women −.02 −.01 .00 −.05* −.02 .03
Total R2 .17 .07 .12 .08 .04 .13 .04 .04
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Note. N = 299. Standardized estimates are presented for direct and indirect effects, both of which were included in the model (i.e., each effect controls for all other effects). The results also control for neuroticism at T1.

*p < .05; **p < .01.

Spillover Effects

As predicted in Hypothesis 1, workplace incivility negatively related to affective well-being for men (β = −.24, p < .01) and women (β = −.17, p < .01). Affective well-being positively related to life satisfaction and overall health for both men (β = .26, p < .01 and β = .24, p < .01, respectively) and women (β = .24, p < .01 and β = .14, p < .05, respectively). Affective well-being negatively related to personal-life-to-work interference for men (β = −.13, p < .05) and women (β = −.15, p < .05). Thus, Hypotheses 2–4 were supported for men and women.

In the same analysis, maximum likelihood bootstrapping with 5,000 samples was used to estimate standard errors and confidence intervals (95%) for the indirect effects between incivility and distal outcomes via affective well-being. For women, incivility had a standardized indirect effect on their life satisfaction, −.05, [−.126, −.007], SE = .03, p < .05. For men, incivility indirectly related to their personal-life-to-work interference, .04, [.007, .080], SE = .018, p < .05, life satisfaction, −.06, [−.137, −.019], SE = .03, p < .05, and health, −.06, [−.121, −.016], SE = .026, p < .05.

Crossover Effects

Additionally, several crossover effects emerged. Women’s uncivil experiences negatively crossed over to men’s affective well-being (β = −.11, p < .05), although the reverse was not significant. Thus, Hypothesis 5 was supported for crossover from women to men. Affective well-being did not significantly cross over to personal-life-to-work interference for either gender (Hypothesis 6a was not supported). However, men’s affective well-being positively crossed over to women’s life satisfaction (β = .23, p < .01); the opposite was not significant. Thus, Hypothesis 6b was supported for crossover from men to women.

DISCUSSION

Covert mistreatment toward older employees is pervasive (Marchiondo et al., 2016; Palmore, 2015), but its long-term effects remain understudied. In this study, we provide empirical support for the SAVI model (Charles, 2010), demonstrating that despite older adults’ advantageous coping strategies, workplace incivility undermines their well-being outside of work over time. Specifically, incivility negatively related to older employees’ affective well-being, which longer-term, took a toll on their life satisfaction, health, and work (i.e., a feedback loop). Our model advances incivility spillover research by establishing that it not only takes time for some nonwork outcomes to develop but that, consistent with AET, affective well-being mediates many of these outcomes. These advances might explain why a number of nonwork outcomes of incivility have not emerged in prior research. Establishing these relationships using a national sample of older workers across three waves widens the methods used to study incivility as well as older adults’ outcomes of workplace mistreatment.

Our study contributes to the literatures on aging and incivility by testing several novel propositions. With regard to aging, research has highlighted older adults’ strengths in coping with negative events, including reappraisal, avoidance, and emotion regulation (Charles, 2010; Diehl et al., 1996). As a result, many studies have documented older adults’ higher life satisfaction and affective well-being, compared with younger adults (Charles & Piazza, 2009; Mroczek & Spiro, 2005). Yet, the SAVI model is instrumental in positing that chronic stressors attenuate these benefits (Charles, 2010). Drawing on this model, we direct attention to a common stressor after which older adults do not fare as well—workplace incivility—thereby identifying a ubiquitous experience that diminishes older workers’ coping strengths over time.

Our results support an important proposition in the workplace incivility literature as well, namely that incivility has a wear and tear effect on targets (Cortina et al., 2001). Although notable work has documented the short-term effects (e.g., days) of workplace incivility, little is known about whether it continues to “wear down” target well-being long-term (i.e., a year or more). Our model demonstrates that, indeed, it does. This long-term approach is valuable for capturing targets’ nonwork outcomes, in particular, because incivility is an insidious stressor that could tax employees’ personal lives more gradually than their professional lives. Moreover, a long-term perspective is especially pertinent to capturing older workers’ well-being, given the wear and tear emphasis of the SAVI model.

A strength of this study is that it included couples who remained employed and partnered across waves. This allowed us to investigate gender differences in bidirectional crossover, thereby uncovering the extent to which incivility relates to the well-being of targets’ working partners. The results support the notion that gender differences in crossover are nuanced. Men’s dampened affective well-being following incivility crossed over to women’s life dissatisfaction, consistent with literature on unidirectional male-to-female crossover (Westman et al., 2009). However, women’s uncivil experiences unidirectionally related to their male partners’ affective well-being. Thus, the strains of workplace incivility cross over between both men and women, but these relationships vary based on the outcome of interest.

Several explanations for these results are plausible. Compared with men, women might be more empathetic to and ultimately affected longer-term by their partners’ affective well-being, thereby explaining their drop in life satisfaction (Bekker & van Assen, 2008; Eagly & Wood, 1991). Rather than feeling upset directly after hearing about their partners’ uncivil treatment, women appear to become dissatisfied once their partners display affective distress (i.e., contagion occurs). If men are able to “brush off” incivility and avoid affective decline, their female partners are less likely to be negatively influenced. In contrast, men have direct affective reactions to hearing about their female partners’ uncivil experiences. This may be due to a sense of protectiveness embedded in the traditional male gender role (i.e., ambivalent sexism; Glick & Fiske, 1996). Regardless of their female partners’ affective reactions to incivility, men might dislike the idea of someone mistreating their partners, triggering affective distress. Together, these results contribute to discussions in the work–family literature about the nuanced role of gender. Future research should test moderators (e.g., attentiveness, emotional contagion, resilience) that influence these crossover relationships.

Several sample features should be noted when interpreting these crossover relationships. First, both partners were employed, so discrepancy in breadwinner status, or household financial contributions, is likely lower than if the sample included partners not in the labor force. As Westman and colleagues (2009) stated, “gender may be confounded with a breadwinner role in the family and/or with a traditional gender and power relationship” (p. 591). Women in this sample might have had more power in their partnerships, given their financial contributions, thereby altering the extent to which they affected—and were affected by—their male partners (e.g., having less time to attend to partners’ grievances, having less energy to empathize with partners). Second, crossover could vary with age. Several studies have documented crossover and emotional contagion between older spouses (e.g., Bookwala & Schulz, 1996), but in general, work–family conflict decreases in later life (Higgins, Duxbury, & Lee, 1994), which might attenuate detrimental crossover relationships.

Overall, workplace incivility is a notably pernicious stressor for older adults, given its features as a covert, ubiquitous, and therefore, often unavoidable form of mistreatment. Although incivility is low in intensity, our results demonstrate its far-reaching effects, such that it can spill outside the work context in which it originates, detracting from the well-being of older employees and their partners (who are employees in other organizations). These findings highlight incivility as a form of ageism and amplify the need to prevent it proactively.

LIMITATIONS AND FUTURE DIRECTIONS

Despite the study’s strengths, we acknowledge limitations and opportunities for future work. The HRS conducts the core interview every 2 years and the psychosocial survey every 4 years, so we could not manipulate the time lags in our model. However, a multiyear lag allowed the protracted effects of incivility to manifest per the SAVI model and the wear and tear model of incivility (Cortina et al., 2001). Moreover, linking incivility to target outcomes years later speaks to the significance of these relationships, as a multiyear lag provides a more conservative test of these effects. Future research should build on this work by adopting other time lags to pinpoint how long it takes incivility to undermine nonwork variables.

Additionally, not all variables in our study were available at every wave, precluding our ability to test an autoregressive model in which the outcome variables were predicted by the same constructs in the previous wave. Future research should investigate additional alternative models, including an autoregressive model, to determine whether other relationships exist among the variables that we were not able to test due to this methodological limitation.

This limitation also explains our use of slightly older waves of the HRS. While we do not believe our model would differ in recent years due to consistency in the underlying theories and mechanisms, an interesting future direction would be to test the model in locations where momentous changes affect a broad swath of employees (e.g., where workplace mistreatment laws are passed). Ideally, scholars would test the model both before and after workplace transformations to examine its generalizability as workforces evolve.

Finally, readers may wonder about the extent to which the results are generalizable to younger workers. We expect that the results might be amplified among younger workers, because (a) younger adults have greater affective expression and lower impulse control (Diehl et al., 1996; Gross et al., 1997), which could relate to higher levels of spillover and crossover, and (b) younger couples report heightened work–family interference (Grzywacz & Marks, 2000). We recommend comparative tests of our model using young and middle-aged worker samples.

Practical Implications

The importance of addressing workplace incivility is underscored by its long-term spillover to targets’ personal lives and crossover to their partners. Organizational leaders should be especially concerned with detriments to employee health, which cost companies billions of dollars annually (Stewart, Ricci, Chee, Morganstein, & Lipton, 2003). Healthy workers are more effective, more productive, and less costly (e.g., less sick leave; Roskes, Donders, & van der Gulden, 2005). They also tend to retire later (McGarry, 2004), thereby reducing costs associated with recruitment and training as well as burdens on social benefit programs. In the interest of promoting older worker health, it behooves organizations to foster civil work environments.

In particular, it is vital that informal cultures of civility and work–family support be promoted. Informal practices appear to influence employee well-being and relationships outside work more strongly than formal policies aimed at work–life enrichment (Thompson & Prottas, 2006; Wayne, Randel, & Stevens, 2006). Informal supportive work cultures might be particularly important for retaining older workers, who are more motivated by internally- rather than externally-rewarding job features (Inceoglu, Segers, & Bartram, 2012).

To create organizational cultures that are civil and supportive of work–family balance, strong social norms for these values are needed (Walsh et al., 2012). Organizations must signal that civil conduct is both prevalent (i.e., a descriptive norm) and socially approved (i.e., an injunctive norm) to foster cultures of respect that deter mistreatment (Jacobson, Marchiondo, Jacobson, & Hood, 2020). Employees should model respectful treatment, provide social support, and remedy violations of civility norms (Thompson & Prottas, 2006; Walsh et al., 2012). Leaders play particularly important roles in creating and upholding these norms, as passive leadership contributes to incivility perpetration (Harold & Holtz, 2015).

Civility norms can also be shaped through training programs, such as the Civility, Respect, and Engagement at Work (CREW) intervention (Leiter, Laschinger, Day, & Oore, 2011), in which employees reflect on, collectively discuss, and drive new social customs. Even a 3-day expressive writing intervention can reduce incivility and promote self-efficacy, emotional intelligence, and positive affect (Kirk, Schutte, & Hine, 2011). Thus, cognitively processing work experiences is an effective method for preventing incivility and promoting well-being.

ACKNOWLEDGMENTS

This research was supported by the National Institute on Aging [U01 AG009740] and the Mountain and Plains Education and Research Center [T42OH009229], funded by the National Institute for Occupational Safety and Health, Centers for Disease Control and Prevention. The content is the sole responsibility of the authors and does not necessarily represent the official views of the National Institute on Aging, the Centers for Disease Control and Prevention or the Department of Health and Human Services.

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