“Dirty” Workplace Politics and Well-Being

Abstract

We build and empirically test an integrative model of gender, workplace politics, and stress by integrating social role theory and prescriptive gender stereotypes with the transactional theory of stress. To examine the effect of gender on the relation between exposure to non-sanctioned political influence tactics (NPITs; e.g., self-serving and socially undesirable behaviors such as manipulation and intimidation) and stress outcomes, we employed a daily diary design with 64 employed adults over the course of 12 working days. In support of our hypotheses, exposure to NPITs––that is, “dirty politics”––elicited a threat appraisal that, in turn, related to the activation of negative emotions. Moreover, unlike men, women who reported higher levels of NPITs experienced heightened levels of threat appraisal and ultimately negative emotions. We demonstrate that pairing social role theory with the transactional theory of stress is a useful approach for researchers interested in better understanding gender differences in the occupational stress process. Anyone interested in reducing stress in the workplace is encouraged not only to reduce the occurrence of NPITs, but also to consider ways to reduce the threat associated with them, especially for women.

Keywords

women and work workplace politics employee well-being stress

Organizational politics are a pervasive reality of organizational life (Ferris & Treadway, 2012; Mintzberg, 1983; Pfeffer, 1981) and are recognized as a vehicle for attaining work-related goals (Kurchner-Hawkins & Miller, 2006; Liu, Liu, & Wu, 2010). For both men and women, achieving one’s work-related goals is not just a rational, merit-based process but also a political process wherein people use power and social influence tactics (Judge & Bretz, 1994; Liu et al., 2010; Mintzberg, 1983; Ng, Eby, Sorensen, & Feldman, 2005). Researchers have shown that although women perform at least as well as men on factors related to merit (e.g., job performance), they might not fare as well as men in the political component of organizational life (Eagly, Gartzia, & Carli, 2014; Lyness & Thompson, 2000). This political disadvantage is reflected in a number of outcomes experienced by women. Studies have found that women need to outperform their male colleagues in order to be considered for the same promotion opportunities (Joshi, Son & Roh, 2015; Lyness & Heilman, 2006); are less likely to be offered challenging or developmental assignments (Gorman & Kmec, 2009; Silva, Carter, & Beninger, 2012); have less access to jobs with authority and responsibility (Elliott & Smith, 2004); and have fewer opportunities to develop relationships with powerful mentors, sponsors, and peers (McDonald & Westphal, 2013; Timberlake, 2005).

The occupational stress literature finds that some of the same political factors that disadvantage women in the workplace (e.g., fewer opportunities, lack of support) are also implicated in the occupational stress process that results in poor employee health and well-being (Sojo, Wood & Genat, 2016). Although the workplace politics → occupational stress process in general has been studied extensively (Chang, Rosen, & Levy, 2009; Cropanzano & Li, 2006; Perrewé, Rosen, & Maslach, 2012), the role of gender, and where potential gender differences might exist, has not. Furthermore, occupational stress researchers have focused almost exclusively on the relation between organizational politics and long-term outcomes rather than the process underlying that relation. The theoretical mechanisms through which person-related individual differences (i.e., gender) are theorized to initially exert their influence in the process that links workplace politics to those outcomes have not been tested (Cropanzano & Li, 2006 Perrewé et al., 2012). This underlying process may have critical implications for understanding the differential effects of workplace politics on men’s and women’s health and well-being and gender’s role in the workplace politics → occupational stress process.

Recognizing this important, yet missing, element in the literature, we tested a model to examine the potential differential effects of “dirty” workplace politics on women’s and men’s health and well-being and gender’s role in the workplace politics → occupational stress process. As elaborated below, we focused on a subset of organizational politics referred to as non-sanctioned political influence tactics (NPITs). NPITs are political influence tactics that are considered self-serving, socially undesirable, and illegitimate by the organization (Thiel, Hill, Griffith, & Connelly, 2014; Zanzi, Arthur, & Shamir, 1991; Zanzi & O’Neill, 2001). They include behaviors such as manipulation, intimidation, and blaming (Zanzi et al., 1991). They are considered political because the underlying motive of people engaging in these tactics is to accomplish their own goals or the goals of the organization, which may not be in line with the goals of the person exposed to them. Based on theory and research in the stress literature (Lazarus & Folkman, 1984), we proposed that exposure to such tactics has negative effects on others’ initial stress response, which in turn activates acute negative emotions (Lazarus, 1991). This negative affect activation is characterized by feelings of distress, fear, and anger (Sonnentag, Binnewies, & Mojza, 2008) and has been shown to lead to physical health and psychological symptoms (Folkman, Lazarus, Gruen, & DeLongis, 1986) including depression (Wichers et al., 2010) and burnout (Ilies, Dimotakis, & De Pater, 2010). It is also predictive of outcomes such as decreased job performance (Hoobler & Hu, 2013), organizational commitment (Panaccio & Vandenberghe, 2012), job satisfaction (Dimotakis, Scott, & Koopman, 2011), and increased employee deviance and turnover (Lee & Allen, 2002; Maertz & Griffeth, 2004). Because stress theory does not adequately specify a role for gender in the stress process, we integrated propositions derived from stress theory with theory and research on gendered social roles (Eagly, 1987; Heilman, 2001; Prentice & Carranza, 2002). We proposed that women and men respond differently to NPITs and, as a result, experience different levels of negative affect activation. In doing so, we began to address important yet unanswered questions about organizational politics and their differential effects on the health and well-being of men and women.

A Model of NPITs, Gender, and Stress

The transactional theory of stress (Lazarus, 1991; Lazarus & Folkman, 1984) provides an overarching framework for explaining the process that occurs when individuals are exposed to stressors. According to Lazarus and colleagues, stress is a process wherein an external event or stimulus (i.e., stressor) is appraised as taxing or exceeding one’s ability to cope and thus elicits a negative response. A major component of the transactional theory of stress is that responses to stressors (in the present study, active negative feelings) are determined by an intermediate appraisal process whereby the person determines the extent to which the stressor poses a potential risk or threat to her or his well-being (Lazarus & Folkman, 1984). According to this theory, appraisals are subjective experiences that are cognitively determined and vary as a function of the person and situation (Lazarus & Folkman, 1984; Peacock & Wong, 1990). Initial appraisals are the main precursors to subsequent responses including the activation of negative emotions (Lazarus, 1991). Although appraisal and negative affect activation play a central role in the stress process, they have rarely been studied (Sonnentag & Frese, 2013). And scholars have called for research examining the early stages of the stress process, specifically with regard to organizational politics (Cropanzano & Li, 2006; Perrewé et al., 2012).

Consistent with the transactional theory of stress (Lazarus & Folkman, 1984), exposure to potentially stressful events is not harmful unless the event represents a threat or potential risk to one’s well-being (threat appraisal). Given that NPITs are socially undesirable and illegitimate, they should elicit a threat appraisal that then triggers an adverse response in most individuals exposed to them. In addition, the behaviors themselves (e.g., intimidation, blaming) are likely to be counter to the personal goals and status of those who are exposed. Because NPITs can be seen as (1) socially undesirable and illegitimate and (2) counter to the personal goals and the status of those to whom they are exposed, they include both of the features that Lazarus and Smith (1988) describe as necessary to elicit threat appraisal. Because threat appraisals capture the employees’ perception that their well-being is at stake in a specific situation, which predicts the stress reaction in the form of acute negative affect that follows, we hypothesized that threat appraisal would fully mediate the positive relation between NPITs and negative affect activation (Hypothesis 1).

The Role of Gender in Occupational Stress

Researchers have begun to examine gender differences in the experience of occupational stress. Although some of that research suggests that women confront certain stressors (e.g., harassment and discrimination) more often than men (Cocchiara & Bell, 2009) and that they may cope with the aftermath of stressful encounters differently from men (Tamres, Janicki, & Helgeson, 2002), much of the research on the role of gender in the area of occupational stress has produced mixed results (Gyllensten & Palmer, 2005; Martocchio & O’Leary, 1989). Particularly relevant to the present study, the role of gender in the process linking stressor exposure to threat appraisals and subsequent outcomes remains unclear. Furthermore, the effects of gender are not directly addressed by the transactional theory of stress. To help reconcile the mixed research results and to theoretically inform our predictions regarding gender in the process linking NPITs to negative outcomes via threat appraisal, we drew on the social role theory of gender (Eagly, 1987) and the role of gender stereotypes (Heilman, 2001; Prentice & Carranza, 2002).

Social role theory (Eagly, 1987; Eagly & Wood, 2012) proposes that sex-differentiated behaviors, such as the traditional division of labor between women and men, have led to gender-differentiated social roles that women and men normatively inhabit. Through the process of socialization, people come to internalize the gender-typed behaviors that are associated with their own gender role, and they come to expect gender-typed behaviors that conform to the gendered roles of others. These shared expectations for gender-role-congruent behavior produce powerful norms and stereotypes for the behavior and attributes (e.g., sex-typed skills) of women and men (Eagly & Wood, 2012). Gender stereotypes can be descriptive, in that they indicate what women and men are perceived to be like, and also prescriptive, in that they specify what women and men should and should not be like (Heilman, 2001). In general, men are expected to behave in an agentic fashion characterized by being aggressive, forceful, ambitious, and concerned with individual achievement; whereas, women are expected to behave in a communal fashion characterized by being interpersonally sensitive, warm, nurturing, deferential, and concerned with building and maintaining interpersonal relationships (Eagly, 1987; Prentice & Carranza, 2002).

These socially and culturally constructed role-derived differences between women and men identified by social role theory (Eagly, 1987), and the constraining stereotypes associated with them (Prentice & Carranza, 2002), may ultimately lead women to react to work situations differently from men (Broadbridge, & Hearn, 2008; Heilman, 2001; O’Neil, Hopkins, & Bilimoria, 2008; Richardsen, Traavik, & Burke, 2016). For example, women and men tend to be sorted into different occupations and roles within organizations, partially through self-sorting and educational choices (Barbulescu & Bidwell, 2013; Charles & Bradley, 2009). Once they are in the workplace, women and men tend to advance to positions of greater responsibility in unequal proportions in part because of stereotypic views held by organizational decision makers about the relative suitability of men and women for advancement (Ragsdale, Beehr, & Elacqua, 2013). In addition, violating prescriptive stereotypes by behaving in a gender incongruent fashion has been shown to result in backlash (Rudman, 1998) in the form of negative sanctions in the areas of hiring, promotions, career progression, and compensation (see reviews by Heilman, 2012; Rudman & Phelan, 2008). We argue that in addition to these effects, gender differences in roles and constraints have the potential to differentially affect the experience of occupational stress as described by the transactional theory of stress (Lazarus & Folkman, 1984). That is, when confronted with the same stressor (e.g., NPITs) role-derived differences between men and women can influence the severity of the threat appraisal they elicit, ultimately resulting in different outcomes for women and men.

Based on social role theory (Eagly, 1987; Eagly & Wood, 2012), through the socialization and internalization of gender role prescriptions for communal behaviors and attributes, women may be more aware of issues arising in interpersonal interactions. This would seem especially the case for the negative types of interpersonal interactions that NPITs represent. Research shows that women experience behaviors that are similar to NPITs, such as harassment (Berdhal & Moore, 2006), bullying (Salin & Hoel, 2013), and incivility (Cortina, Kabat-Farr, Leskinen, Huerta, & Magley, 2013) more than men do. Research also suggests that women (vs. men) have a greater awareness of the unfair (e.g., illegitimate) treatment experienced by others, regardless of whether the others are members of their own group or not (e.g., Young, Vance, & Ensher, 2003). And research findings indicate women have lower thresholds than men for recognizing or rating the severity of a variety of negative social interactions including sexual harassment (Rotundo, Nguyen, & Sackett, 2001), bullying (Escartin, Salin, & Rodríguez-Carballeira, 2011), interpersonal conflict (Young et al., 2003), incivility (Montgomery, Kane, & Vance, 2004), and microaggressions (Basford, Offermann, & Behrend, 2014). This greater awareness may lead women to appraise the same NPITs as more threatening than men do.

Elacqua, Beehr, Hanson, and Webster (2009) argued that gender role prescriptions and stereotypes described by social role theory (Eagly, 1987; Eagly & Wood, 2012) underlie the bias and discrimination that has historically disadvantaged women in the workplace. For example, considerable evidence demonstrates that women experience bias and discrimination owing to the mismatch between communal stereotypes of women and the agentic stereotypes people hold for leaders, which is one reason that women have been relegated to positions with less formal and informal power (Catalyst, 2016; Elliott & Smith, 2004; Welle & Heilman, 2005), and why they have had difficulty advancing to senior positions in organizations (Eagly & Karau, 2002). As noted earlier, these types of outcomes result from bias in the informal political component of organizational life rather than merit (Eagly et al., 2014; Lyness & Thompson, 2000). Research suggests that women do tend to perceive that they have experienced discrimination in the political component of organizational life based on their gender (Blodorn, O’Brien, & Kordys, 2012; Dambrun, 2007). Consistent with this reasoning, women may react more negatively (i.e., have stronger threat appraisals) to noxious political conditions encountered in the workplace.

In summary, social role theory (Eagly, 1987; Eagly & Wood, 2012) provides a rational explanation for why women would appraise NPITs as more threatening than men. Owing to socialization and internalization, women are better able than men to recognize NPITs when they experience or witness them. This greater awareness is not unfounded. Women have experienced the negative effects of gender role prescriptions and stereotypes in the form of discrimination and bias. These have disadvantaged women in political processes at work and limited their advancement. Consistent with Ragins, Singh, and Cornwell (2007) findings that groups that have faced such pervasive discrimination may find the situations that produce it more threatening, we would expect that women exposed to NPITs appraise those behaviors as a stronger threat than men. To formally test this proposition, we hypothesized that gender would moderate the relation between NPITs and threat appraisal such that the relation would be stronger for women than for men (Hypothesis 2).

According to stress theory, threat appraisal is a cognitive evaluative process that initiates a sequelae of negative outcomes beginning with activation of negative emotions (Lazarus, 1991; Lazarus & Folkman, 1984; Peacock & Wong, 1990). Studies in the occupational stress literature, including studies regarding gender differences, rarely make a distinction between the cognitive threat appraisal and the activation of negative emotions. For example, studies reporting gender differences often ask participants about the degree to which they find particular stressors to be “stressful” (Day & Livingstone, 2003; Eaton & Bradley, 2008; Matud, 2004). A common explanation given when women self-report higher stressfulness ratings than men is that women are more emotionally reactive than men (Fiorentini, 2013). Claiming gender differences in emotionality however is not only theoretically underspecified, it also confounds the cognitive appraisal of the stressor with the emotional response to it. This may lead to erroneous conclusions regarding gender’s influence in the stress process.

In the present study, we overcame this limitation by more clearly distinguishing between threat appraisal and the activation of negative emotions and, consistent with theory, we situated the effects of gender on the cognitive appraisal of stressors rather than in the emotional reaction that follows. Thus, for women (vs. men), we expected that exposure to NPITs would increase negative affect activation through its stronger effect on threat appraisal. We reasoned that gender would influence negative affect activation indirectly by increasing threat appraisal more for women than for men. To formally test this proposition, we hypothesized that gender would moderate the indirect relation between NPITs and negative affect activation via threat appraisal such that the indirect effect would be stronger for women than for men (Hypothesis 3).

Figure 1 provides a conceptual overview of our proposed model. In order to test the model as a whole and our hypotheses, we used a daily diary data collection method. This method allows for an examination of the role of appraisal at the early stages of the workplace politics → stress process, as has been called for in the literature (Cropanzano & Li, 2006; Perrewé et al., 2012).

Figure 1.
Conceptual model.

Method

Procedure and Participants

In the present daily diary research design, following “best practice” recommendations by Fisher and To (2012), we employed an interval-contingent strategy with participants responding once each day at a time near the end of their work day. This approach is especially useful for studying elements of the transactional theory of stress (Tennen, Affleck, Armeli, & Carney, 2000). It reduces retrospective biases (Fisher & To, 2012) in reports of stress and appraisal (Ptacek, Smith, Espe, & Raffety, 1994), while not interfering with the stress process as it occurs, for example, by asking someone to think intently about an event soon after it occurred and thereby affecting the appraisal of it (Tennen et al., 2000). For all these reasons, end of the workday interval-contingent designs have been used by a number of researchers studying occupational stress processes (e.g., Lee-Flynn, Pomaki, DeLongis, Biesanz, & Puterman, 2011; Piazza, Charles, Sliwinski, Mogle, & Almeida, 2013; Zhou, Yan, Che, & Meier, 2015). Consistent with these other studies and the transactional theory of stress, participants needed enough time to have been exposed to NPITs at work and subsequently engage in the threat appraisal process.

Data were collected over the course of 12 working days from 64 professional staff at the headquarters of a large construction company located in the Midwestern region of the United States. An email was sent to all (N = 84) office employees inviting them to participate. On the morning of Day 1 (Tuesday), we held a voluntary informational meeting for employees who agreed to participate (N = 64). Following a presentation, attendees signed up for the study and completed an initial paper–pencil questionnaire. The next day (Wednesday), we began collecting daily data on our main study variables. Participants were sent an email containing a link to a short online questionnaire at the end of each work day (3:00 pm) for 12 working days. We collected these data during Week 1 from Wednesday to Friday, Week 2 from Monday to Friday, and Week 3 from Monday to Thursday. In order to guarantee anonymity, participants entered a self-selected code each time they accessed the online data collection site. This procedure resulted in a total of 12 possible daily observations for 64 participants (or 768 observations, of which data were reported for 632). Of the 64 participants, 56 were exposed to one or more NPITs over all measurement days (8 participants reported no NPITs during the 12 days).

Of those who participated, 42% were women and 58% were men. In terms of race/ethnicity, 83% were White, 2% Latino/a, 2% Asian American, and 13% did not respond to this item. Nine percent of participants were between 18 and 24 years old, 25% were between 25 and 34 years old, 34% were between 35 and 44 years old, 20% were between 45 and 55 years old, and 12% did not respond to the age question. In terms of education, 5% of the sample reported having completed high school or some college, 6% completed a 2-year college degree, 72% completed a 4-year college degree, 7% completed a master’s degree, and 10% did not respond to the item. Sixteen percent reported working at the organization for less than 3 years, 22% reported a tenure of 4–6 years, 23% reported a tenure of 7–10 years, 17% reported a tenure of 11–15 years, 7% reported a tenure of 16 years or more, and 15% did not respond to the item. Participants held jobs in estimation and preconstruction (14%), engineering (14%), project management (23%), business services (accounting, marketing, safety quality; 25%), operating group leadership (9%), and 15% did not respond.

The participants came from a section of an organization that was relatively gender-equal (i.e., front office of corporate headquarters) but in a male-dominated industry (construction). Because of this, part of the organization’s culture could be shaped by the male-dominated nature of industry. This would likely lead to more male-normed expectations and behaviors, which would have the effect of situating the female workers in a moderately role-incongruent situation. That is, the women in the organization could experience more bias, prejudice, or simply feeling out of place at times compared to the men in the sample. This would be consistent with role congruency theory (e.g., Eagly & Karau, 2002; Eagly & Wood, 2012), although in the present study the incongruence is more related to the industrial context than to the more specific role or position of the employee within the organization. Because of this, the sample may be an especially good setting to examine differences between women and men in their social experiences.

The sample itself reflects the corporate headquarters environment of the company from which the data were obtained. The gender composition of the sample (42% women) reflected the gender composition of the corporate headquarters (40% women). The headquarters unit of a construction company is composed of people in professional staff jobs, not actual laborers, construction trade workers, supervisors/foremen, and so on, that might be commonly associated with the construction industry. Many of the respondents worked primarily in the field and were assigned to cross-functional teams whose members change from one construction project to another. While there is a clear hierarchy, employees work cooperatively across levels to address issues as they arise.

Initial Questionnaire Measures

Based on previous research, we controlled for two demographic variables, age and race, as well as interpersonal mistreatment, a type of social stressor that may exacerbate the effects of daily NPITs (Brewer & Shapard, 2004; Hershcovis & Barling, 2010; Nielsen & Einarsen, 2012). Interpersonal mistreatment was measured using Cortina, Magley, Williams, and Langhout’s (2001) 7-item Workplace Incivility Scale (WIS). Participants rated the extent to which they had experienced behaviors in the prior year from 1 (never) to 5 (always) from other employees in their organization. Example items included “Put you down or was condescending to you” and “Made demeaning or derogatory remarks about you.” Previous studies have reported high internal consistency estimates (α = .83 to .87; Dineen, Duffy, Henle, & Lee, 2017; Gallus, Bunk, Matthews, Barnes-Farrell, & Magley, 2014, respectively) and good convergent validity. For example, Sakurai and Jex (2012) found a negative correlation between Cortina and colleagues’ (2001) WIS and work effort and a positive correlation with counterproductive work behaviors.

Daily Questionnaire Measures

NPITs

At the end of each workday, participants were asked to indicate whether they experienced three distinct NPITs over the course of their day: intimidation, manipulation, and blaming or attacking others, taken from Zanzi and O’Neill’s (2001) non-sanctioned political tactics measure. These particular behaviors were chosen because they can be readily observed by others. For example, we did not measure participants’ exposure to the political tactic of controlling information (i.e., regulating the access to information based on one’s own self-interest) because it would be less visible to others. Participants were asked to respond to 3 items: (1) “Did someone try to use intimidation, threats, strong language, or coercion to influence you or others?” (2) “At work did someone manipulate you or others by misrepresentation, distorting the facts, or hiding the truth?” and (3) “Did anyone at work today try to get what they want by blaming you or others, minimizing others’ contribution, or attacking others to make them look bad (‘throw them under the bus’)?” Each of the items was answered in a 1 = yes, 2 = no format and then summed to create an index of exposure. Since NPITs were composed of three separate and distinct types of political behavior experienced daily by the participants, it was not relevant to calculate the internal consistency of the measure (Spector & Jex, 1998; Wang, Liao, Zhan, & Shi, 2011). Lastly, we examined the daily frequencies with which the individual NPITs (intimidation, manipulation, and blaming) occurred across days. Barring any systemic “shocks,” we did not expect to see a great deal of fluctuation in these behaviors across days and this is what was found (see Table 1).

Table 1.
Number of Participants Reporting Each of the Three Types of Non-Sanctioned Political Influence Tactics Each Day.

Day Number of Manipulation Number of Coercion Number of Blame

Day 1 4 2 4

Day 2 4 1 4

Day 3 7 3 5

Day 4 3 2 6

Day 5 3 6 2

Day 6 7 3 2

Day 7 3 4 2

Day 8 3 3 5

Day 9 4 1 4

Day 10 2 0 5

Day 11 6 3 5

Day 12 4 1 4

M 4.17 2.42 4.00

SD 1.64 1.62 1.35

Note. Manipulation, coercion, and blame are the three non-sanctioned political influence tactics items. M = mean; SD = standard deviation.

Threat appraisal

Threat appraisal was measured using 3 items that are consistent with Lazarus and Folkman’s (1984) definition of threat appraisal. Lazarus and Folkman define threat appraisal as an appraisal of a situation as having the potential to threaten, harm, or hinder one’s personal well-being. From this definition, we created a measure that asked people to rate the extent to which they appraised each political behavior as a (1) threat, (2) hindrance, and (3) obstruction to their well-being for each of the NPITs that was experienced in a workday. All items were scored on a 5-point scale ranging from 1 (strongly disagree) to 5 (strongly agree) and then averaged.

Negative affect activation

Negative affect activation was measured using Mackinnon et al.’s (1999) shortened version of Watson, Clark, and Tellegen’s (1988) negative affect scale. Participants were asked to rate the degree to which they felt distressed, afraid, upset, nervous, scared, or angry when they experienced each of the NPITs (intimidation, manipulation, and blaming others) on a scale ranging from 1 (not at all) to 5 (very much). A negative affect activation score was calculated by averaging participant responses to these 6 items across the influence tactics that they were exposed to each day. In previous studies, acceptable internal consistencies have been reported (α = .75 to .81; Schmitt, Zacher, & Frese, 2012; Scott, Barnes, & Wagner, 2012). The measure has also demonstrated convergent validity in previous studies. For example, Koopman, Lanaj, and Scott (2016) found the measure to be positively related to emotional exhaustion and negatively related to job satisfaction in a sample of administrative, service, clerical, or technical positions from a variety of organizations.

Assessment of Measures

Within-level confirmatory factor analysis (CFA)

To examine whether the variables measured were distinct constructs, we conducted a within-person level CFA using Mplus Version 8 (Muthén & Muthén, 2017). We tested a model specifying our daily measures (i.e., NPITs, threat appraisal, and negative affect activation) to load on their respective factors. Three error variances for the negative affect activation measure were allowed to covary because of their similar item content (Landis, Edwards, & Cortina, 2009). This model yielded an acceptable fit, χ² = 95.02, df = 51, p < .05, comparative fit index (CFI) = .94, root-mean-square error of approximation (RMSEA) = .03, and all standardized factor loadings were statistically significant and in the expected direction. Since it is well-established that the χ² test is overly sensitive to sample size (Bollen, 1989; Lance & Vandenberg, 2001), we calculated the ratio of the magnitude of χ² and number of degrees of freedom (i.e., χ²/df = 2.18), which was below the recommended standard of three, and thus suggestive of a good data-model fit (Schermelleh-Engel, Moosbrugger, & Muller, 2003). In addition, the CFI was above the rule of thumb for a reasonable minimum for model acceptance of .90 (Bentler & Bonett, 1980), and the RMSEA was below the recommended standard of .05 (Browne & Cudeck, 1993; Steiger, 1990). Thus, taken together, the results suggest a good data-model fit. For NPITs, the factor loadings ranged from .40 to .54 and had an average loading of .47. For threat appraisal, the factor loadings ranged from .64 to .91 with an average loading of .81. Lastly, for negative affect activation, factor loadings ranged from .72 to .88 with an average loading of .80. We then compared this model to a model where all of the items in the model were specified to load on a single factor, χ² = 206.34, df = 54, p < .05, CFI = .79, RMSEA = .06. The result of the comparison suggests that the hypothesized model does fit the data better than the alternative model (Δχ² = 111.32, df = 3, p < .01). Thus, it can be concluded that the variables represent distinct constructs.

To further substantiate the measures, we examined the within-person correlations among the latent variables. NPITs were significantly correlated with threat appraisal (r = .05, p < .05), and threat appraisal was significantly correlated with negative affect activation (r = .50, p < .01), whereas NPITs were not significantly correlated with negative affect activation (r = .01, p > .05). These results show that threat appraisal and negative affect activation are significantly more highly correlated with one another than they are with NPITs (z = 2.75, p < .01 and z = 3.05, p < .01, respectively). This is to be expected, as these are both reports of internal states wherein NPIT is a report of an external event.

Analytical Strategy

Given the hierarchical structure of the data (days nested within people), we conducted a path analysis using the multilevel structural equations modeling framework with Mplus Version 8 (Muthén & Muthén, 2017). This approach to estimating multilevel effects separates the variances of the observations into two groups, the between-person variances and within-person variances. There are several advantages to using this approach: (1) its ability to simultaneously test Level-1 effects while taking Level-2 effects into account, (2) provides more reliable and robust estimates of parameters and standard errors, and (3) its ability to test multilevel mediation as well as cross-level moderation. We used Bayesian estimation for all inferential statistical tests because of its usefulness in testing complex models with a small sample (Kruschke, Aguinis, & Joo, 2012; Kruschke & Vanpaemel, 2015; Zyphur & Oswald, 2015).

Before testing the hypotheses, we first tested a null model to investigate the intraclass correlation coefficient (ICC) values for threat appraisal and negative affect activation (Aguinis, Gottfredson, & Culpepper, 2013; Heck, 2009). The ICC value for threat appraisal (ICC = .64) and negative affect activation (ICC = .66) indicated that 64% of the variance in threat appraisal and 66% of the variance in negative affect activation were attributed to between-person variation, leaving at least one-third of the variance attributed to within-person variation. Thus, a substantial portion of the variance can be attributed to both within- and between-person variation.

To test the multilevel mediation hypothesis (Hypothesis 1), we first examined a model that included NPITs, threat appraisal, negative affect activation, and the control variables. This model did not include gender; it tested the direct and mediating effects among the within-person variables. Because NPITs, threat appraisal, and negative affect activation were measured at the within-person level (Level-1), we estimated a 1-1-1 mediated model using the approach recommended by Preacher, Zyphur, and Zhang (2010). At the within-person level, threat appraisal was modeled as a function of NPITs, and negative affect activation was modeled as a function of threat appraisal; the intercepts of the variables were estimated as well as the within-person direct effects. As recommended by Preacher et al. (2010), we allowed the constructs to covary. Next, we examined the cross-level moderation hypothesis (Hypothesis 2) by testing a model that included gender as a predictor of the within-person random slope between NPITs and threat appraisal. To test this model, the Level-1 slope (NPITs on threat appraisal) was specified to be random, and the covariance among the random effects was estimated (Bauer, Preacher, & Gil, 2006). Finally, to test the cross-level moderated mediation hypothesis (Hypothesis 3), we ran a model that estimated the indirect effects of NPITs for men and women on negative affect activation. To appropriately test and interpret the between-person relations, gender was grand-mean centered to eliminate confounding within-person relations by between-person variance (Hofmann & Gavin, 1998).

Results

Table 2 shows the means, standard deviations, within- and between-person correlations, and coefficient αs. As shown, scores on each measure had an acceptable degree of internal consistency reliability. Further, participants reported between 0 and 12 NPITs over the course of the 12 days (M = 1.98, SD = 2.30, total = 127). At the within-person level, exposure to influence tactics was correlated with threat appraisal, and threat appraisal was related to negative affect activation. These results provided initial support for the relations suggested in the hypotheses.

Table 2.
Means, Standard Deviations, Correlations,^a and Coefficient αs Among Variables.

Variables M SD 1 2 3 4 5 6

1. Age 3.67 1.09 —

2. Race 0.89 0.32 .42** —

3. NPITs 1.98 2.30 −.01 .12 — .08* .04

4. Threat appraisal 2.52 0.96 −.16 −.07 .20 (.86) .53

5. Negative affect activation 2.55 0.75 −.11 −.03 .13 .79 (.82)

6. Gender^b 0.42 0.50 .25 −.10 .05 −.05 .16 —

7. Interpersonal mistreatment 2.58 0.65 −.16 .10 .37 .50 .42** −.11 (.92)

Note. Coefficient αs for day-level variables are mean internal consistencies averaged across days. NPITs = non-sanctioned political influence tactics.

^aCorrelations below the diagonal are between-person correlations (N = 64). Between-person correlations for threat appraisal and negative affect activation are calculated by averaging across days and for NPITs by calculating the total number exposed across days. Correlations above the diagonal represent within-person correlations (N = 632). ^bGender was coded as 0 for men and 1 for women.

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

Threat Appraisal as a Mediator Between NPITs and Negative Affect

Table 3 provides the parameter estimates, standard deviations of the posterior distribution, and 95% credibility intervals (CIs; analogous to confidence intervals) for the within- and between-person level parameters for the multilevel mediation model (gender was not included in this analysis). At the within-person level, the mean value of the random slope for NPITs on threat appraisal was significant, γ₁₀ = .44, p < .05, CI [.06, .88]. This suggests that on the days when participants were exposed to more NPITs, they reported higher levels of threat appraisal. The variance for the random slope was also significant, τ₁ = .31, p < .01, CI [.04, 2.37], which suggests that the variance could be further accounted for by Level-2 predictors. Further, threat appraisal was positively related to negative affect activation, γ = .27, p < .01, CI [.10, .44], after controlling for the covariates. The results also showed a significant indirect relation between NPITs and negative affect activation via threat appraisal, estimate = .11, p < .05, CI [.02, .28]. There was no direct relation between NPITs and negative affect activation, thus showing the relation was fully mediated by threat appraisal. These results suggest that at the person level, the more NPITs a person is exposed to during the day, the more likely that person will report high levels of threat appraisal and ultimately experience heightened levels of negative affect activation. Thus, Hypothesis 1 was supported.

Table 3.
Unstandardized Coefficients for Main and Mediating Effects.

Effect Type Coefficient SD 95% CI

Within-person effects

Random slope

NPITs → threat appraisal

Intercept 0.44* .21 [0.06, 0.88]

Variance 0.31 .61 [0.04, 2.37]

Fixed slope

Threat appraisal → negative affect activation 0.27 .09 [0.10, 0.44]

Variance

NPITs 0.21 .01 [0.19, 0.23]

Residual variances

Threat appraisal 0.34 .08 [0.23, 0.55]

Negative affect activation 0.20** .04 [0.14, 0.28]

Indirect effect

NPITs → threat appraisal → negative affect activation 0.11* .07 [0.02, 0.28]

Between-person effects

Variances

Threat appraisal 1.76** .97 [0.61, 4.27]

Negative affect activation 0.51* .07 [0.26, 1.01]

Age 1.25 .26 [0.88, 1.90]

Race 0.11 .02 [0.08, 0.16]

Interpersonal mistreatment 0.59** .12 [0.41, 0.89]

Note. Level 1: N = 632; Level 2: N = 64. Gender was coded as 0 for men and 1 for women. NPITs = non-sanctioned political influence tactics; coefficient = unstandardized coefficients; SD = standard deviation of the posterior distribution; CI = credibility interval.

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

Gender as a Moderator of the Relation Between NPITs and Threat Appraisal

We posited (Hypothesis 2) that gender would moderate the relation between NPITs and threat appraisal. As shown above, the variance of the random slope between NPITs and threat appraisal was significant, τ₁ = .31, p < .01, CI [.04, 2.37], suggesting that a Level-2 predictor could account for this variance. We tested a Level-2 predictor, gender, and its effect on the within-person random slope of NPITs on threat appraisal. Table 4 provides the results for the cross-level moderation effects. After controlling for the covariates, we found that gender was significantly related to the slope between NPITs and threat appraisal, γ = .44, p < .01, CI [.09, .85]. To probe this interaction further, we plotted the interaction for women and men with threat appraisal on the y-axis (Cohen, Cohen, West, & Aiken, 2003; Preacher, Curran, & Bauer, 2003). As shown in Figure 2, the relation between daily exposure to NPITs and end of day threat appraisal was stronger for women than for men. This hypothesis was supported.

Figure 2.
Interaction of daily non-sanctioned political influence tactics and gender on threat appraisal.

Table 4.
Unstandardized Coefficients for Moderation Effects.

Effect Type Coefficient SD 95% CI

Within-person effects

Random slope

NPITs → threat appraisal

Intercept 0.42* .23 [0.01, 0.88]

Gender 0.44 .20 [0.09, 0.85]

Residual variance 0.89 .50 [0.26, 2.15]

Fixed slope

Threat appraisal → negative affect activation 0.24 .10 [0.07, 0.45]

Between-person effects

Variances

Threat appraisal 2.68 .86 [1.53, 4.77]

Negative affect activation 0.73 .21 [0.41, 0.86]

Gender 0.98 .23 [0.41, 1.28]

Age 1.26 .26 [0.87, 1.86]

Race 0.11 .02 [.08, 0.16]

Interpersonal mistreatment 0.58** .12 [0.41, 1.28]

Note. Level 1: N = 632; Level 2: N = 64. Gender was coded as 0 for men and 1 for women. NPITs = non-sanctioned political influence tactics; coefficient = unstandardized coefficients; SD = standard deviation of the posterior distribution; CI = credibility interval.

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

Gender as a Moderator of the Indirect Relation Between NPITs and Negative Affect Activation via Threat Appraisal

We expected (Hypothesis 3) gender to moderate the indirect relation between NPITs and negative affect activation via threat appraisal, such that the indirect effect would be stronger for women than for men. To test the moderated mediation effects, we followed the recommended approach developed by Bauer et al. (2006). Specifically, we estimated the indirect relation between NPITs and negative affect activation via threat appraisal for women and men together after controlling for the covariates. As reported in Table 5, the indirect effect was significant for women, estimate = .21, p < .01, with 95% CI [.05, .48]; but not significant for men, estimate = −.01, ns, CI [−.20, .15]. Thus, Hypothesis 3 was supported suggesting that, unlike men, women who are exposed to more NPITs have a heightened threat appraisal and in turn experience heightened levels of negative affect activation.

Table 5.
Conditional Indirect Effects of Daily Non-Sanctioned Political Influence Tactics on Negative Affect Activation via Threat Appraisal.

Gender Negative Affect Activation

Coefficient SD 95% CI

Average .09* .07 [.01, .26]

Women .21** .12 [.05, .48]

Men −.01 .08 [−.20, .15]

Note. Gender was coded as 0 for men and 1 for women. Coefficient = unstandardized coefficients; SD = standard deviation of the posterior distribution; CI = credibility interval.

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

Discussion

Exposure to noxious political behavior and the experience of dirty politics in the workplace is a reality that both women and men face on a daily basis. Therefore, it is important for researchers and organizational decision makers to understand the impact that these experiences have on those who encounter them. Previous research has shown that workplace politics exert significant influence on women’s experiences in the workplace and represent one source of barriers that limit women’s career advancement (Ibarra, Carter, & Silva, 2010). Although such knowledge is valuable for efforts to eradicate women’s disadvantage in the workplace, far less has been known about the means by which “dirty” politics may differentially affect women’s health and well-being.

We integrated principles from social role theory (Eagly, 1987) and gender role stereotypes (Heilman, 2001; Prentice & Carranza, 2002) with the transactional theory of stress (Lazarus & Folkman, 1984) to build a model that explicates the role of gender in the workplace politics → stress process. Three key findings emerged from our study. First, exposure to NPITs (i.e., “dirty politics”) was associated with threat appraisals that, in turn, related to negative affect activation. Second, contrary to the idea that women experience greater exposure to a stressor such as NPITs than men (Roxburgh, 1996), women and men reported similar levels of exposure to NPITs overall. Third, the more that women were exposed to NPITs, the more strongly they appraised those behaviors as threatening and, in turn, experienced higher levels of negative affect activation. This was unlike men who did not react as strongly when they experienced more NPITs.

Theoretical Contributions

The finding that workplace stressors differentially affect men and women, as predicted by social role theory (Eagly, 1987) and gender role stereotypes (Heilman, 2001; Prentice & Carranza, 2002), represents an important extension of these theories to help explain differences between women and men in the area of occupational stress. Even though women and men did not experience NPITs at different rates (gender was not significantly related to NPITs as noted in Table 3), women did react to NPITs more adversely; as exposure to NPITs increased, women were likely to appraise them as more threatening than men (Figure 2). The higher threat appraisal women experience in turn increases the activation of negative emotions. Our findings regarding these workplace political behaviors suggest that not only do gendered roles and stereotypes affect women’s experiences in the workplace, but that they may take a greater toll on women’s health and well-being.

Based on theory, we argued that women may appraise NPITs as more threatening than men due to the culturally constructed roles for women and men. Through socialization and the internalization of communal behaviors and attributes, women may come to view the types of behaviors represented by NPITs as particularly threatening and especially so in light of the fact that such political behavior has tended to disadvantage women in the past. Researchers could examine the potential for gender differences in rates of engaging in NPITs. Women may engage in fewer NPITs if they perceive these behaviors as more threatening and harmful, as suggested by the results of the current study.

By extending social role theory (Eagly, 1987) and gender role stereotypes (Heilman, 2001; Prentice & Carranza, 2002) to inform the transactional theory of stress (Lazarus & Folkman, 1984), we also helped overcome the limitations of past research and allowed for more specific predictions to be made regarding the role of gender in the occupational stress process. Past research has often confounded the cognitive appraisal process with the activation of subsequent emotion and concluded that women are more emotionally reactive (e.g., Eaton & Bradley, 2008). In the present study, cognitive appraisal and emotional activation were measured separately. We predicted and found that rather than directly activating negative emotions, NPITs indirectly increased negative affect activation for women through women’s stronger appraisals of threat as the frequency of NPIT exposure increased. Thus, women’s cognitive appraisal of threat, which research shows is based on reality (Webster, Beehr, & Elacqua, 2011), appears to be an important mechanism for explaining women’s emotional reactions to stressors such as NPITs.

Our results also inform past theory on the workplace politics → stress process. While the transactional theory of stress is often used to frame investigations in this area (e.g., Kane-Frieder, Hochwarter, & Ferris, 2014) and plays a key role in models linking workplace politics to stress outcomes (Perrewé et al., 2012), the actual mechanisms posited by the transactional theory of stress had gone untested. This is unfortunate because, as Cropanzano and Li (2006) point out, there is considerable “conceptual confusion” (p. 139) in research relating politics in the workplace to occupational stress; some researchers define stress in terms of appraisal but operationalize it in terms of strains (e.g., Rosen, Harris, & Kacmar, 2009). Even when appraisal has been measured, it has not been operationalized in terms of threat appraisal as specified by the transactional theory of stress (e.g., Webster, Beehr, & Love, 2011). The present study contributes to the literature by testing the theory’s proposed causal mechanism, threat appraisal, more directly than has been done in previous studies of organizational stress outcomes. As specified by theory, we made a distinction between exposure to NPITs, threat appraisal, and subsequent negative reaction, showing that women’s greater susceptibility to NPITs occurs via threat appraisal. This study was the first to test these linkages directly.

In addition, methodologically, the transactional theory of stress posits that threat appraisal is the proximal evaluation of a stressful encounter that predicts subsequent negative reactions. We employed a daily diary design to directly capture threat appraisal as the proximal evaluation of NPITs and related it to negative affect activation. Through this approach, we were able to more accurately capture the dynamic relations among workplace politics, appraisal, and subsequent negative reaction while reducing retrospective bias, recency, and memory effects (Reis & Gable, 2000).

Practice Implications

The findings of the study also have implications for practice. Negative affect activation is important because it is related to many important workplace outcomes. In its more stable or dispositional form, negative affectivity is related to workplace deviance (Chen, Chen, & Liu, 2013) and to negative employee health outcomes (Klainin, 2009). It is frequently studied as a control variable (e.g., in studies of attributions about negative events experienced in married couples, Karney, Bradbury, Fincham, & Sullivan, 1994; and in models explaining workplace ostracism, Quade, Greenbaum, & Petrenko, 2017) and also as a moderator variable in work-related studies (e.g., between stressors and strains, Jex & Spector, 1996; and between organizational support and emotional exhaustion, Marchand & Vandenberghe, 2016). In the present study, however, we examined negative affect activation in its state form, as it gets activated by NPITs and daily threat appraisals. Like its dispositional form, daily negative affect activation should also affect important health and workplace outcomes, but because negative affect activation is more state-like, it can be more readily affected by the work situation. Managers may be able to decrease negative affect activation through actions that reduce the incidence of daily NPITs.

The finding that compared to men, women experience greater threat appraisal when exposed to high levels of NPITs, which in turn increases negative affect activation, provides one focal point for stress prevention. This finding suggests that greater attention should be focused on characteristics of the work environment that discourage the use of non-sanctioned political behavior by others, as exposure to them appears to hinder the well-being of women. Focusing on the work environment in this way requires a shift in thinking from a women’s deficit model to an organizational deficit model (O’Neil & Hopkins, 2015). This shift is particularly appropriate, given our finding that women appraise low levels of NPITs as less threatening than men––it is only at high levels that threat appraisal increases, leading to higher negative affect activation with its greater negative impact on women’s health and well-being. In addition, many organizations are governed by unwritten rules (informal, implicitly communicated workplace norms and behaviors) that influence career development. Organizations should formally communicate clear information about career progression and expectations (Sabattini & Dinolfo, 2010). These communication strategies may reduce the effectiveness of NPITs and represent important steps toward the development of an organizational culture that supports the advancement and well-being of both women and men.

Because of our daily data collection design, the findings provide insight into the early stages of the stress process, that is, the relatively immediate effects of NPITs on negative affect activation. Our results suggest that leaders and managers should attempt to reduce the effects of NPITs, before the stress reaction occurs. Organizations are not likely to ever be completely free of the types of NPITs examined in the present study (i.e., intimidation, manipulation, and denigration), but it may be possible to reduce their use through primary prevention efforts. Manipulation could be reduced by establishing greater transparency through formal information sharing and increased communication. Intimidation and denigration could be reduced by instituting civility policies and trainings (Cortina et al., 2013).

Many organizations already try to offer equal career opportunities to both women and men. They may do this because they believe in fairness, because it should lead to the placement of more effective employees in key positions, or because they simply are trying to follow labor laws. The present study, by identifying a workplace contextual factor (NPITs) that may strengthen the stress response for women, offers still another reason for organizations to reduce potential career disadvantages for women—it is good for (female) employees’ health.

Limitations, Strengths, and Directions for Future Research

The present study has limitations that should be addressed in future research. Although our use of a daily diary design was consistent with our theory, these types of designs do present several limitations. Owing to the demands placed on participants during a daily data collection process, it is often difficult to secure large samples. Our sample size was not small for a daily diary study (Maas & Hox, 2005; Scherbaum & Ferreter, 2009; Uy, Foo, & Aguinis, 2010), and we were able to obtain a fairly large proportion of women employees from a male-dominated industry. Most daily diary studies are run for about 1 week. We ran our study for about 2 weeks to get a larger number of observations because we were studying somewhat low base rate events. As noted earlier, and as seen in Table 1, the mean value of the specific NPITs ranged from 2.42 to 4.17 (SD = 1.35–1.64) across the 64 participants, and the mean number of total NPITs across the 12 days at individual level was 1.98 (SD = 2.30). While it is heartening that these statistics indicate NPITs are a workplace phenomenon with low occurrence in this sample, it does raise a concern about low statistical power and may help explain the somewhat large CIs for some of the relations. It is possible that some of the relations in the present study would have been statistically significant with a larger sample or an even longer period of observation.

Another potential concern is the generalizability of the results. Although the construction industry is male-dominated in the immediate work environment in which the participants in the present study worked, the headquarters office was not. As noted, the gender composition of this unit (40% women) well exceeds the 20% cutoff below which Kanter (1977) and others suggest tokenism is likely to occur. We also examined the gender composition of the sample within the specific jobs. In most cases, women and men were quite evenly represented––estimation and preconstruction (5 men/4 women), project management (8 men/7 women), business service (8 men/8 women), and operating group leadership (3 men/3 women). The only job type that had a relatively unequal gender representation was engineers (7 men/2 women), which is not unexpected given that only 11% of practicing engineers are women (National Science Foundation and Division of Science Resources Statistics, 2011). Taken together, the types of jobs studied and the distribution of gender across those job types show that women were not generally in different jobs from men, not concentrated in jobs lower in the hierarchy of the organization, and they did not have token status in the organization where this study took place. We encourage future research to replicate our findings in different samples and industries in order to determine whether different gender distributions across jobs and in the work environment generally alter the effects of “noxious” politics on the occupational stress process.

Another possible limitation is that all data came from a single source, that is, they were self-reported, which can affect relations between psychological variables. We attempted to mitigate this limitation by using other methods. First, as noted in the Method section, one psychological variable was used as a control, and because it was also measured by the same method, the method was controlled when it was entered into the statistical analyses. Second, although gender was measured by self-report, it is a mostly objective variable and less susceptible to biased reporting, such as response biases. Third, part of the study, the moderator analyses, has been shown to be relatively immune to common method effects (Siemsen, Roth, & Oliveira, 2010).

One of the main contributions of this study was the use of the social role theory of gender to identify and hypothesize more specifically how women and men systematically differ in the stress process. The pattern of relations in the model provided support for a more contingent view of the stress process than is commonly taken. Using a contingent view might help reconcile the oftentimes conflicting results of studies reporting gender differences in the occupational stress literature (Desmarais & Alksnis, 2005; Martocchio & O’Leary, 1989). Rather than having direct effects on stress variables (such as the stressor NPITs), gender might exert its influence as a moderator. Researchers could also use this approach to help inform theorizing about differences in the stress response among those with stigmatized identities. For example, it seems that people who are lesbian, gay, bisexual, or transgender may experience more NPITs or react more strongly to them owing to their experiences of discrimination and ostracism at work (Grant et al., 2010; Sears & Mallory, 2011).

We also suggest researchers investigate whether the gender of the perpetrators and the targets of NPITs differentially influence employees’ perceptions of NPITs and the stress reactions they evince. The same borderline-political behaviors may be encoded differently by women and men (e.g., Are women’s political behaviors more likely to be perceived as NPIT because they might be considered gender atypical?). A recent study found that women reported being targeted more by women than by men for mild workplace incivility, and this targeting resulted in worse well-being outcomes for women who were more agentic (Gabriel, Butts, Yuan, Rosen, & Sliter, 2017). Researchers could investigate whether parallel results would be obtained regarding NPITs.

We asked about NPITs directed at the focal respondent or others within the same question, looking for an overall assessment of the existence of NPITs in the organization. If future researchers ask for reports of these events separately for those directed to self versus others, they could investigate whether there are differences in reactions when a woman is a target versus “only” a witness. If women react more strongly than men to NPITs when they are witnesses, it might be because women believe they themselves are more likely than men to be the next target or, alternatively, it might be because women tend to be more empathetic. These more detailed questions could be examined in future research.

By identifying a mechanism through which gender influences the occupational stress process, our findings have implications for the paradigm that accepts the current male-centered organizational model and the premise that women simply need to change themselves to fit in. There are important differences between women and men (Annis & Merron, 2014), and recognizing and valuing these differences requires the development of “gender intelligent” people who understand how these gender differences manifest themselves so that they can be leveraged to attain organizational goals and individual well-being.

Conclusions

Dirty politics (NPITs) lead to threat appraisals by employees, which result in negative emotional activation. Men and women may not be exposed differentially to political behavior in their organization, but women cognitively appraise such behaviors more negatively (i.e., as a greater threat) than men and thus have stronger emotional responses to them. Our model was based on social role theory (e.g., Eagly, 1987) and gender stereotyping (e.g., Heilman, 2001), and we used the principle of stress appraisal from the transactional stress theory (Lazarus & Folkman, 1984). The data confirmed that male and female employees are differentially affected by dirty politics as a workplace stressor because women appraise the politics more negatively (i.e., as a greater threat), and such appraisals are key to experiencing more stress. In light of our findings, we encourage practitioners to reduce NPITs in their organizations and take active steps to reduce the threat women experience when exposed to them.

Day	Number of Manipulation	Number of Coercion	Number of Blame
Day 1	4	2	4
Day 2	4	1	4
Day 3	7	3	5
Day 4	3	2	6
Day 5	3	6	2
Day 6	7	3	2
Day 7	3	4	2
Day 8	3	3	5
Day 9	4	1	4
Day 10	2	0	5
Day 11	6	3	5
Day 12	4	1	4
M	4.17	2.42	4.00
SD	1.64	1.62	1.35

Variables	M	SD	1	2	3	4	5	6
1. Age	3.67	1.09	—
2. Race	0.89	0.32	.42**	—
3. NPITs	1.98	2.30	−.01	.12	—	.08*	.04
4. Threat appraisal	2.52	0.96	−.16	−.07	.20	(.86)	.53**
5. Negative affect activation	2.55	0.75	−.11	−.03	.13	.79**	(.82)
6. Gender^b	0.42	0.50	.25	−.10	.05	−.05	.16	—
7. Interpersonal mistreatment	2.58	0.65	−.16	.10	.37**	.50**	.42**	−.11	(.92)

Effect Type	Coefficient	SD	95% CI
Within-person effects
Random slope
NPITs → threat appraisal
Intercept	0.44*	.21	[0.06, 0.88]
Variance	0.31**	.61	[0.04, 2.37]
Fixed slope
Threat appraisal → negative affect activation	0.27**	.09	[0.10, 0.44]
Variance
NPITs	0.21**	.01	[0.19, 0.23]
Residual variances
Threat appraisal	0.34**	.08	[0.23, 0.55]
Negative affect activation	0.20**	.04	[0.14, 0.28]
Indirect effect
NPITs → threat appraisal → negative affect activation	0.11*	.07	[0.02, 0.28]
Between-person effects
Variances
Threat appraisal	1.76**	.97	[0.61, 4.27]
Negative affect activation	0.51*	.07	[0.26, 1.01]
Age	1.25**	.26	[0.88, 1.90]
Race	0.11**	.02	[0.08, 0.16]
Interpersonal mistreatment	0.59**	.12	[0.41, 0.89]

Effect Type	Coefficient	SD	95% CI
Within-person effects
Random slope
NPITs → threat appraisal
Intercept	0.42*	.23	[0.01, 0.88]
Gender	0.44**	.20	[0.09, 0.85]
Residual variance	0.89**	.50	[0.26, 2.15]
Fixed slope
Threat appraisal → negative affect activation	0.24**	.10	[0.07, 0.45]
Between-person effects
Variances
Threat appraisal	2.68**	.86	[1.53, 4.77]
Negative affect activation	0.73**	.21	[0.41, 0.86]
Gender	0.98**	.23	[0.41, 1.28]
Age	1.26**	.26	[0.87, 1.86]
Race	0.11**	.02	[.08, 0.16]
Interpersonal mistreatment	0.58**	.12	[0.41, 1.28]

Gender	Negative Affect Activation
Average	.09*	.07	[.01, .26]
Women	.21**	.12	[.05, .48]
Men	−.01	.08	[−.20, .15]

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Note

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