Does abusive supervision increase employees’ helping behavior? Exploring mediating and moderating mechanisms

Does abusive supervision increase employees’ helping behavior? 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Exploring mediating and moderating mechanisms Roghayeh Hekmat Nasab, Nahid Amrollahi biuki, Mahammad Sadegh Sharifirad This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3994783/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Typically, researchers believe that abusive supervision decreases employees' helping behavior. However, according to the emotional process theory of abusive supervision, subordinates show more helping behavior under certain conditions. The purpose of this study was to examine the impact of abusive supervision on employees' helping behavior, with a focus on the mediating role of self-blame and guilt, as well as the moderating effects of core self-evaluation (CSE) and power distance. Methods: In this study, the PROCESS Macro model was used to investigate the proposed moderated mediation model completely. Confirmatory factor analysis was tested with AMOS. Employees of diverse private and state service-offering organizations in Yazd, Iran, were invited to participate in the study (n=381) using simple random sampling. To gather the data, the abusive supervision scale (Mitchell & Ambrose, 2007), employees’ helping behavior was rated by the scale developed by Dalal and colleagues (2009), State Shame and Guilt Scale (SSGS), Self-blame questionnaire (Troester & Van Quaquebeke, 2021), Core Self-Evaluation Scale (Judge et al., 2003) and Power Distance scale from Dorfman and Howell (1988) were used. The hypothesized model was analyzed according to the procedure of the PROCESS Macro model. Results: The direct association between abusive supervision and employees’ helping behavior was significantly negative; however, the significant mediation by self-blame and guilt was negative. Moreover, more (less) core self-evaluation intensified (attenuated) the relationship between abusive supervision and self-blame. More (less) power distance decreased (increased) the association between self-blame and guilt. Conclusion: First, this study enriches the literature on abusive supervision and its aftermath by introducing self-blame and guilt as two mediators that can influence subordinates’ reactions to abusive supervision. Second, unprecedentedly, CSE was tested as a moderator between abusive supervision and self-blame. Third, in response to the previous call for research (Mackey et al. , 2017; Tepper, 2007), the moderation of subordinates’ power distance orientation on the relationship between self-blame and guilt was investigated. Abusive supervision employees’ helping behavior self-blame guilt core self-evaluation power distance. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Abusive supervision in the workplace, referring to "subordinates' perception of the extent to which supervisors engage in the sustained display of hostile verbal and nonverbal behaviors, excluding physical contact" (Tepper, 2000), is burgeoning and plaguing more workplaces (Eissa & Lester, 2021; Mackey et al., 2017; Zhang & Liao, 2015). Yao examines abusive supervision is related to suicide ideation (Yao et al., 2023). From the perspective of justice theories and reciprocity, supervisor abuse can be conducive to retaliating behaviors such as cooperation reduction (Rafferty & Restubog, 2011), knowledge-hiding behaviors (Khalid et al. , 2018), deviant behavior (Aryee et al. , 2007), and poor subordinate task performance (Tepper et al. , 2017). More recent research has revealed that subordinates may show helping behaviors after experiencing supervisor abuse (Troester & Van Quaquebeke, 2021). Drawing on the emotional process theory of abusive supervision (Oh & Farh, 2017), when subordinates point the finger at themselves after experiencing abuse, they may consequently blame themselves and feel guilt; hence, they try to compensate, thereby showing more helping behavior (Tangney et al., 1996; Troester & Van Quaquebeke, 2021). Moreover, considering that emotions are influenced by personality traits (Weiss & Cropanzano, 1996), this study endeavors to investigate the moderating impact of core self-evaluation (CSE) as a factor that is shown to increase one’s vulnerability when facing challenging and stressful situations (Kammeyer-Mueller et al. , 2009) and power distance orientation increasing or decreasing sensitivity toward abusive supervision (Lee et al. , 2000). This research contributes to the literature on abusive supervision and subordinates’ corresponding reactions. First, this study considers self-blame and guilt as two mediators that can influence the reaction of subordinates toward abusive supervision, thereby helping the perpetuation of abuse. Second, considering CSE as a dispositional variable, this research shows that diverse levels of CSE can affect the relationship between abusive supervision and self-blame and prevent self-blame after abuse. Third, this study responds to the call for research on how individual-level cultural values impact perceptions, evaluations, and outcomes of abusive supervision (Mackey et al. , 2017; Tepper, 2007) by investigating the moderation of subordinates’ power distance orientation on the relationship between self-blame and guilt. Abusive supervision and employees’ helping behavior Previous research has explicitly shown the detrimental effects of abusive supervision (Zhang & Liu, 2018), encompassing reduced job satisfaction and commitment (Guan & Hsu, 2020), organizational citizenship behavior (Zhang et al., 2019), knowledge sharing behavior (Lee et al., 2018), and voice behavior (Frieder et al., 2015), all of which can be justified through the lens of social exchange theory. Therefore, it is hypothesized that: Hypothesis 1: Abusive supervision has a negative direct effect on employees’ helping behavior . The mediating roles of self-blame and guilt Self-blame is a maladaptive cognitive coping strategy by which individuals attribute the reason for an unfavorable event to themselves (Alix et al., 2020). Research has shown that self-blaming is the first prevalent reaction to serious impairment from others (Schilpzand et al., 2016). Troester and Van Quaquebeke (2021) extended the emotional process theory of abusive supervision and considered self-blaming as a cognitive appraisal that can lead to feeling of guilt. Accordingly, after perceiving abusive supervision, employees may blame themselves, and if they deem themselves accountable, they feel guilty. Guilt is a conscious emotion that is generated in social interactions, and those who feel guilt prefer to compensate for their wrongdoings (Tangney et al., 1996). In other words, the feeling of guilt causes motivation and inclination through apologizing and making up for the loss (Tangney et al., 2007). Therefore, Hypothesis 2: Self-blame and guilt mediate the indirect effect of abusive supervision on employees’ helping behavior in a way that the indirect association of abusive supervision and helping behavior is significantly positive. The moderating role of core self-evaluation CSE, a stable personality construct, represents the fundamental judgment individuals make about their self-worth and capabilities. It includes individual subconscious appraisal of one’s abilities and self-control (Chang et al., 2012). This concept was initially employed by (Judge et al. , 1998) to evaluate job satisfaction and then utilized in other realms. Those who are high in CSE are more resilient when encountering challenges (Mäkikangas et al. , 2004). In contrast, those who are lower in CSE are weaker and more vulnerable because they have less self-confidence and are cynical about their competency and capabilities (Kammeyer-Mueller et al., 2009). Tepper and colleagues (2017) contend that abusive supervision is a more serious threat for those who are psychologically weaker and more vulnerable since they have more negative perceptions about their self-worth and performance. Looking through the lens of self-control, those who are higher in CSE are more faithful about their capabilities and self-control (Judge et al. , 2003; Judge & Bono, 2001); therefore, self-blame, which is done due to lack of self-control (Gudjonsson, 1984; Koi, 2021), can be employed to compensate for loss. Hence, Hypothesis 3: CSE moderates the relationship between abusive supervision and self-blame in a way that those who have higher (lower) CSE blame themselves less (more). The moderating role of power distance Power distance is a cultural value that represents the extent to which an individual expects and accepts an unequal distribution of power (Clugston et al. , 2000; Hofstede, 2011). Those who are high in power distance orientation accept hierarchy and, respect powerful individuals and obey them (Farh et al. , 2007) and tend to accept the supervisor’s decisions (Bochner & Hesketh, 1994). In contrast, individuals with a low power distance orientation deem themselves the peers of their supervisors and develop their relationships with them since they believe in the availability of their supervisors (Hofstede, 2011). Those subordinates who are high in power distance orientation accept unequal power distance more willfully and are therefore more likely to defer to supervisors (Kirkman et al. , 2009) due to their awareness of status differences during interactions, submissive and receptive to their supervisors’ decisions and their reactions toward their supervisors’ wrongdoing are less negative (Lee et al. , 2000). Such subordinates accept power imbalance (Tyler, 2000). In contrast, low power orientation leads to perceiving more rule violations and feeling less justice, thereby feeling more guilt (Leith & Baumeister, 1998). Based on the conservation of resources theory (Hobfoll, 1989), subordinates with higher power distance orientation are more likely to judge their supervisor as less abusive than subordinates with low power distance. Subordinates with a higher power distance orientation do not have to spend their resources as much to deal with abuse as subordinates with a lower power distance orientation. According to the power dependence theory (Emerson, 1972), they feel less violence of abuse due to their dependence on power sources; thus, in high power distance contexts, subordinates find abusive supervisors more tolerable (Lian et al. , 2012; Tepper, 2007). Hypothesis 4: Power distance moderates the relationship between self-blame and guilt in a way that subordinates with higher (lower) power distance orientation feel less (more) guilt after blaming themselves. The conceptual model is illustrated in Figure 1. Methods Participants and data collection The participants were employees of public and private service organizations in Iran, which were selected by a nonprobability convenience sampling technique. G*power software version 3.1.9.6, developed by Faul et al. (2007), is one of the most widely used software to calculate and evaluate sample size adequacy. A power of 0.9 and an α level of 0.05 were considered. Initially, 50 data points were collected, an effect size of 0.0448 was acquired, and a sample size of 373 was determined. After considering a 90% response rate (Hoerger, 2010), 410 questionnaires were distributed. Finally, 392 complete questionnaires were collected (response rate = 95.6%). According to the suggestion of Goldammer et al. (2020), the Mahalanobis distance was calculated, and 11 outliers were omitted. Therefore, the final sample size comprising fully completed surveys was 381, with a response rate of 93%. Measures Abusive supervision Abusive supervision was assessed by asking some follow-up questions after asking the participants to read one of the written scenarios randomly. The scenarios were adopted from (Troester & Van Quaquebeke, 2021), and the follow-up questions were from the five-item scale of abusive supervision (Mitchell & Ambrose, 2007). A sample item is “My supervisor ridicules me.” The Cronbach’s alpha was 0.94. Self-blame To measure self-blame, the 3-item scale developed by (Troester & Van Quaquebeke, 2021) was adopted. A sample item of this scale is “I think that I am responsible for damaging my relationship with my supervisor.” The Cronbach alpha was 0.83. Guilt To evaluate guilt, the 5-item scale of guilt from the State Shame and Guilt Scale (SSDS) (Marschall et al., 1994) was used. A sample item is “I feel like apologizing, confessing.” The Cronbach’s alpha was 0.89. employees’ helping behavior Employees’ helping behavior was rated by the scale developed by Dalal and colleagues (2009). This measure includes six questions. For example, “I would go out of my way to be nice to my supervisor.” The Cronbach alpha was 0.78. Core self - evaluation ) CSE ( The participants were asked to answer the questions of the 12-item scale of the Core Self-Evaluation Scale (Judge et al. , 2003). The validity of this scale is well accentuated by previous research (Kacmar et al. , 2009). A sample item is “When I try, I generally succeed.” The Cronbach’s alpha was 0.76. Power Distance The six-item scale from Dorfman and Howell (1988) was used to measure power distance orientation. A sample item is “I believe managers should seldom ask for the opinion of employees.” The Cronbach’s alpha was 0.76. Data Analysis In this study, bootstrapping was used to investigate the proposed moderated mediation model completely. The bootstrapping technique was employed (Edwards & Lambert, 2007) via the PROCESS macro and added to SPSS (Hayes, 2018). Common method variance (CMV) is caused by using a single method to collect data (i.e., self-report survey in this study). In this regard, a Harman one-factor test, comprising all the variables, demonstrated that a single factor can represent only 22.47% of the variants, which is considerably less than 50% (Podsakoff & Organ, 1986). This result shows no significant common variance (Lindell & Whitney, 2001; Podsakoff et al., 2003). Therefore, common method variance is not a major threat in this study. Results Prior to the testing of the proposed hypotheses, the data fitness of the measurement model, as well as the distinctiveness of the measures, were tested with AMOS (Arbuckle, 2006). The measurement model showed a good fit to the data (λ2=954.109, df=444, p<0.001, CFI=0.915, TLI=0.906, RMSEA=0.055). Table 1 Results of confirmatory factor analysis (CFA) Table 1 Results of confirmatory factor analysis Models χ 2 df χ2/df CFI TLI RMSEA Δχ 2 Six-factor model (Abusive supervision; CSE; PD; Self-Blame; Guilt; Employees’ helping behavior) 954.109 444 2.149 0.915 0.906 0.055 Five-factor model (Abusive supervision; CSE; PD; Self-Blame; Guilt and Employees’ helping behavior combined) 1572.78 449 3.503 0.814 0.794 0.081 618.673 *** Four-factor model (Abusive supervision; CSE; PD; Self-Blame and Guilt and Employees’ helping behavior combined) 1737.98 453 3.868 0.787 0.767 0.086 738.871 *** Teree-factor model (Abusive supervision and CSE combined; PD; Self-Blame and Guilt and Employees’ helping behavior combined) 2172.88 456 4.765 0.716 0.691 0.100 1218.771 *** Two-factor model (Abusive supervision and CSE and PD combined; Self-Blame and Guilt and Employees’ helping behavior combined) 2635.98 458 5.755 0.639 0.609 0.112 1681.871 *** One-factor 3287.14 459 7.162 0.531 0.494 0.127 2333.031 *** One-factor 3287.14 459 7.162 0.531 0.494 0.127 2333.031 *** Note: N = 381. All alternative models were compared to the six-factor model. Abbreviations: CFI (comparative fit index); RMSEA (root mean square error of approximation); SRMR (standardized root mean square residual). * p < .01; ** p < .001 Test of the hypothesized model Table 2 shows descriptive statistics, correlations, and Cronbach’s alpha of the variables. To test the hypotheses, the PROCESS macro for SPSS (Hayes, 2018) was utilized. The bootstrapping method with 5,000 interactions was used to calculate the indirect effects (Singh & Xie, 2008). Using the confidence interval, this method shows statistical significance if the interval excludes zero. Table 2 Descriptive statistics and zero-order correlations of the study variables Variable M SD 1 2 3 4 5 6 1. Abusive supervision 2.70 1.18 (0.94) 2. CSE 3.71 0.49 -.149 ** (0.76) 3. Self-blame 2.33 0.86 .414 ** -.130 * (0.83) 4. PD 2.03 0.68 .110 * -.057 .209 ** (0.76) 5. Guilt 2.78 0.90 .458 ** -.161 ** .695 ** .136 ** (0.89) 6. Employees’ helping behavior 2.98 0.69 -.227 ** .103 * .155 ** .128 * .164 ** (0.78) Note: N = 381. Cronbach's alphas are shown in the diagonal. * p < .01 ** p < .001 Hypothesis 1 outlined the significant negative direct association between abusive supervision and employees’ helping behavior. The results in Table 3 show that the direct effect of abusive supervision on employees’ helping behavior is negative ( b =0.235, p <0.001); therefore, Hypothesis 1 is supported. Table 3 Summary of analyses for Hypothesis 1 Variable B SE T p LLCI ULCI Abusive supervision -0.235 0.32 -7.447 0.000 -0.298 -0.173 Note: N = 381. Unstandardized beta coefficients are reported. Independent variables were mean centered. SE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval) The dependent variable is employees’ helping behavior * p <.01; ** p <.001. Hypothesis 2 asserts that the mediation of self-blame and guilt is significant. Based on Table 4, the indirect association between abusive supervisor and supervisor-directed helping via self-blame is 0.04 (boot SE=0.02). It is statistically significant since zero was not in the bias-corrected 95% confidence interval (CI= [0.002, 0.07]). Moreover, the indirect relationship between abusive supervision and employees’ helping behavior is 0.03 (boot SE=0.01) and is statistically significant since the confidence interval did not contain zero (0.95% CI= [0.008 and 0.054]). Last, the indirect effect of abusive supervision and employees’ helping behavior via both variables of self-blame and guilt was 0.04 (boot SE=0.01, CI= [0.013 and 0.062]) and significant. Juxtaposing these results, it was revealed that both self-blame and guilt significantly mediated the association between abusive supervision and employees’ helping behavior; thus, Hypothesis 2 is supported. Table 4 Summary of analyses for Hypothesis 2 Self-Blame Guilt employees’ helping behavior b SE t b SE t b SE t Abusive Supervision 0.3 0.03 8.85** 0.15 0.03 5.17** -0.24 0.032 -7.45** Guilt 0.64 0.04 15.33** 0.12 0.053 2.31* Self-Blame 0.18 0.052 3.52** Model R 2 0.17** 0.52** 0.15** Indirect effects of abusive supervision on employees’ helping behavior through self-blame and guilt Indirect effect Boot SE Lower 95% bootstrap confidence interval Higher 95% bootstrap confidence interval Self-Blame 0.04 0.02 0.002 0.07 Guilt 0.03 0.01 0.008 0.054 0.04 0.013 0.013 0.062 Note: N = 381. Unstandardized beta coefficients are reported. Independent variables were mean centered. SE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval) ** p < 0.001 * p <0.01 Hypothesis 3 posits that CSE moderates the relationship between abusive supervision and self-blame in a way that more (less) CSE causes this relationship to be less (more) positive. The figures in Table 5 delineate that after controlling for the main impact of abusive supervision and CSE, the abusive supervision by CSE interaction term accounts for significant incremental variance (2.32% because of interaction ( in self-blame ( b =0.22, p <0.001)). Additionally, simple slopes were depicted at one standard deviation above and below the mean of the CSE measure to accentuate the interaction effect directions (see Figure 2). The slope of the association between abusive supervision and self-blame was steeper for higher levels of CSE (simple slope=0.40, p <0.001). In contrast, when the levels of CSE were lower, the association was significantly weaker (simple slope=0.18, p <0.001). Table 5 Summary of analyses for Hypothesis 3 Self-blame Guilt Employees’ helping behavior B SE B SE b SE Abusive supervision 0.291** 0.034 0.157 0.030 -.235** 0.032 CSE -0.118 0.0812 Abusive supervision × CSE 0.224* 0.07 Self-blame 0.639 0.041 0.123** 0.053 Guilt 0.184** 0.052 R 2 0.199 0.518 0.155 F 31.297** 202.829** 22.960** Conditional effects of abusive supervision on self-blame for different levels of CSE Effect Boot SE Lower 95% bootstrap confidence interval Higher 95% bootstrap confidence interval Low 0.02 0.09 0.006 0.04 Mean 0.03 0.01 0.01 0.06 High 0.05 0.02 0.02 0.08 Index of moderated mediation Index Boot SE Boot LLCI Boot ULCI CSE 0.026 0.013 0.006 0.06 Note: N = 381. Unstandardized beta coefficients are reported. Independent variables were mean centered. CSE (Core Self-Evaluation); SE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval) ** p < 0.001 * p <0.01 To further our analysis, the PROCESS macro for SPSS (Hayes, 2017) was employed to test whether the conditional indirect effect of abusive supervision on employees’ helping behavior via the two mediators of self-blame and guilt was moderated by CSE (i.e., Hypothesis 3; see Table 5). The index of moderated mediation was significant (moderated mediation index=0.03, boot SE=0.01, 95% CI= [0.006 to 0.06]). The moderated mediation index indicates whether the indirect effects are influenced by the low and high levels of the moderator (Hayes, 2018). Excluding zero, the 95% bootstrapped confidence interval indicates that the indirect effect varies across diverse levels of CSE. Moreover, post hoc analyses utilizing the Johnson-Neyman technique postulate that the relationship between abusive supervision and self-blame is positive and significant for values above -0.85 standard deviation of the CSE mean (see Figure 3). On the whole, the findings contradict the proposed hypothesis. Therefore, Hypothesis 3 is not supported and is discussed later. Hypothesis 4 proposes that the association between self-blame and guilt is significantly moderated by power distance (see Table 6). To probe this, simple slope testing (Cohen et al. , 2014) and the Johnson-Neyman technique (Hayes & Matthes, 2009; Johnson & Neyman, 1936) were used to identify significant regions. Simple slope testing showed that more self-blame leads to more feelings of guilt when power distance is lower ( b =0.22, SE=0.053, p <0.001), and the confidence interval did not include zero for any of the high and low levels of power distance (see figure 4). Further analysis of the moderation showed that the moderation mediation index was also significant (moderated mediation index=-0.008, boot SE=0.004, 95% CI= [-0.017 to -0.001]). This demonstrates that the indirect effect of abusive supervision on employees’ helping behavior is impacted by power distance as the moderator. Based on Figure 5, the relationship between self-blame and guilt is negative for all the moderator values, ranging from -1.033 to 1.97 standard deviation of the power distance mean. Table 6 Summary of analyses for Hypothesis 4 Self-blame Guilt Employees’ helping behavior b SE b SE b SE Abusive supervision 0.304** 0.034 0.155** 0.030 -0.235** 0.032 Self-blame 0.637** 0.042 0.123* 0.053 PD -0.010 0.049 Self-blame × PD -0.140** 0.053 Guilt 0.184** 0.052 R 2 0.171 0.527 0.155 F 78.382** 104.531** 22.960** Conditional effects of Self-blame on Guilt for different levels of PD Effect Boot SE Lower 95% bootstrap confidence interval Higher 95% bootstrap confidence interval Low 0.732 0.054 0.626 0.837 Mean 0.637 0.042 0.555 0.719 High 0.543 0.056 0.432 0.653 Index of moderated mediation Index Boot SE Boot LLCI Boot ULCI PD -0.008 0.004 -0.017 -0.001 Note: N = 381. Unstandardized beta coefficients are reported. Independent variables were mean centered. PD (Power Distance); SE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval) ** p < 0.001 * p <0.01 Discussion In this study, the association between abusive supervision and employees’ helping behavior behavior and the mediating and moderating mechanisms between these two variables were investigated. In this regard, two sequential variables of self-blame as an internal attribution, a cognitive process accusing oneself of a negative event, and guilt as an adaptive emotion (Alix et al. , 2020) that facilitates and enhances cooperation (Deem & Ramsey, 2016), were considered. Heeding attention to personality and culture, CSE and power distance were chosen as the moderators of the two relationships. Direct effect First, the findings of this research demonstrated that there is a significantly negative association between abusive supervision and employees’ helping behavior. Most abusive supervision literature revolves around the hinge of processing injustice in a way that followers endeavor to make a balance, thereby refraining from helping such supervisors amend the unjust supervisor-subordinate relationship (Mackey et al. , 2017; Tepper, 2000; Zhang et al. , 2019). Drawing on resource conservation theory (Hobfoll, 2001), abuse drains resources such as self-esteem and social support (Lee et al. , 2014), which causes the maintenance of remaining resources; therefore, plausibly, subordinates do not invest their time and energy in extra role behaviors, including supervisor-directed helping (Lyu et al. , 2016). This happens when consequent self-blame and guilt are not triggered. Second, despite the plethora of research indicating that those subordinates who blame supervisor abuse decrease their helping behavior and increase their deviant behavior to establish a balance (Mackey et al. , 2017). Indirect effect The findings showed that subordinates’ self-blaming after experiencing abuse can engender guilt, which ultimately functions as a motive to help the supervisor. It is aligned with the emotional process theory of abusive supervision, positing that self-blame is contingent on time and situation and causes diverse feelings such as anger, fear, and guilt and may lead to different behaviors (Oh & Farh, 2017). Therefore, when, during the initial appraisal, subordinates determine that the abuse is due to their faults, self-blame is initiated, which can become more profound after the second appraisal and manifest itself as guilt (Troester & Van Quaquebeke, 2021). As a self-conscious feeling that is closely related to pity, retaliation, and helping behavior (Miranda et al. , 2020), guilt can lead to more helping behavior toward supervisors. Third, CSE was introduced as a moderator to further help the literature on abusive supervision and related self-blaming. It was hypothesized that those with lower (higher) CSE are more likely to blame themselves (less) after encountering abusive supervision. Nevertheless, the findings showed the opposite. The possible reason is that drawing on self-verification theory (Swann Jr & Brooks, 2012), individuals prefer to be seen as they perceive themselves. Accordingly, when subordinates with higher CSE perceive abuse from their supervisors, they feel more of a threat to their self-schemas and feel more devastation (Duffy et al. , 2006). Individuals with higher CSE have more self-esteem and self-efficacy with an external locus of control and are less neurotic (Kammeyer-Mueller et al. , 2009). Therefore, supervisor abuse is deemed a threat to their characteristics, thereby reacting to abuse more intensely. Looking through the lens of resource conservation theory (Hobfoll, 2001), abusive supervision threatens important resources such as self-esteem (Lee et al. , 2014); hence, those with higher CSE make more effort to maintain their depleting resources since they perceive the threat more severely, and once they judge themselves faulty, then self-blame may occur. Research has shown that those with higher self-esteem blame themselves more, indicating their effort to control and prevent abuse (Janoff-Bulman, 1979). Fourth, the role of power distance as a moderating factor in the relationship between self-blame and guilt was verified. Aligned with previous findings (Lian et al. , 2012; Vogel et al. , 2015), when power distance orientation is lower, more self-blame leads to more guilt. Subordinates with a higher power distance orientation tend to be more passive. They are more likely to tolerate abuse to maintain work relationships (Lian et al. , 2012) and negative consequences (Vogel et al. , 2015). In terms of stress, the stress caused by abusive supervision taxes cognitive-emotional resources in a way that reduces emotional regulation capacity due to decreased emotional awareness. This is accentuated by stress theories (Hobfoll, 2001), positing that the accumulation of stressors may deplete necessary resources to cope with subsequent stressors. Abusive supervision is associated with a range of acute and chronic stressors (Tepper, 2007), and guilt levels may be elevated for those with conflictual intimate relationships (i.e., lower power distance orientation). Both supervisor abuse and the experience of guilt can uniquely tax cognitive emotional resources (Taverna et al. , 2021). Those with a higher power distance orientation are likely to be more inclined to employ avoidance coping in response to uncomfortable moral emotions, which could decrease guilt awareness and reduce distress over time (Litz et al. , 2009). Limitations of future research There are several inherent limitations to this research. First, the data were collected through self-reporting questionnaires, which can raise concerns of common method bias. Based on the recommendations of researchers (for example, Conway and Lance, 2010), various initiations were performed to control it. The participants were selected from diverse public and private service-offering organizations. Moreover, they were reassured about the confidentiality of their responses. Valid scales were also employed to assess the variables. Last but not least, a one-factor Harman test was also conducted to show that common method bias is not a concern. Nevertheless, future research may use other methods, such as experimental and longitudinal research methods. Second, it was shown that abusive supervision can increase employees’ helping behavior, thereby burgeoning productivity if helping behavior is aligned with organizational goals. However, this assertion has not yet been tested and is solely deduced from previous research (Tepper et al. , 2017). Future research may delve into how and when helping abusive supervision can have positive organizational consequences. Third, to evaluate abuse, some assumed scenarios were designed, and the reality of workplaces was not considered; hence, future studies may consider critical incident interview techniques (CIT) to obtain in-depth details of the reactions to abusive supervision. This can lead to close-to-reality research. Last, the sample of this study was limited to service-offering organizations in Iran, which may limit the generalizability of the results. Further research can be conducted in other countries with different national cultures and in different organizations. Conclusion Research has already demonstrated that abusive supervision hampers helping supervisors; nevertheless, very sparse research has explored whether a specific mechanism can lead to more helping of abusive supervisors. In this regard, two sequential mediators of self-blame and guilt were selected. The findings showed that although the direct impact of abusive supervision on employees’ helping behavior is negative and significant, the suppressing effects of self-blame and guilt are, to an extent, negative and significant. More importantly, two boundary conditions of a personality trait variable (i.e., core self-evaluation) and a cultural context variable (i.e., power distance) on two relationships of abusive supervision and self-blame and self-blame and guilt, respectively, demonstrated that those who are higher (lower) in core self-evaluation blame themselves more (less) when they encounter abuse. Additionally, those who are higher (lower) in power distance orientation feel less (more) guilt after blaming themselves. Declarations Acknowledgments We would like to acknowledge all the staff for their participation. Many thanks to the editors and reviewers who worked hard on this paper and reviewed our article. We also thank Amir Hussein Mohammad Karimi Yazdi from windsor University for language edition services. Author contributions Conception and design of the research: Mahammad Sadegh Sharifirad, Nahid Amrollahi Biuki; cquisition of data: Roghye Hekmat Nasab; Analysis and interpretation of the data: Mahammad Sadegh Sharifirad, Nahid Amrollahi Biuki; Statistical analysis: Roghye Hekmat Nasab; Writing of the manuscript: Roghye Hekmat Nasab, Nahid Amrollahi Biuki; Critical revision of the manuscript for intellectual content: Nahid Amrollahi Biuki, Mahammad Sadegh Sharifirad. All authors read and approved the final draft. Funding This research did not receive any specifc grant from funding agencies in the public, commercial, or not-for-proft sectors. We thank all the Employees participated in the study. Data availability The datasets during and/or analyzed during the current study available from the corresponding author on reasonable request. Ethics approval and consent to participate I confirm that I have read the Editorial Policy pages. The study was the result of Mrs. Ruqieh Hekmat's master's thesis. The approval of the proposal and the thesis in the defense meeting were obtained from the Institutional Review Board of the Author's University (Ardakan University) for ethical review. This study was conducted in accordance with the declaration of Helsinki Written informed consent was obtained from all participants. This article does not contain any studies with human participants or animals performed by any of the authors. Consent for publication Not applicable. Competing interests The authors declare no competing interests. References Aiken, L.S., West, S.G. and Reno, R.R. (1991), Multiple Regression: Testing and Interpreting Interactions , sage. Alix, S., Cossette, L., Cyr, M., Frappier, J.-Y., Caron, P.-O. and Hébert, M. (2020), “Self-blame, shame, avoidance, and suicidal ideation in sexually abused adolescent girls: a longitudinal study”, Journal of Child Sexual Abuse , Taylor & Francis, Vol. 29 No. 4, pp. 432–447. 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06:25:49","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":45335,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInteraction of abusive supervision and CSE (core self-evaluation) on self-blame\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3994783/v1/8f963bab9e62a91a4ffc2642.jpg"},{"id":53226696,"identity":"110bfdf7-908b-4b84-ae96-8955286fc629","added_by":"auto","created_at":"2024-03-22 06:33:49","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":73253,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eJohnson-Neyman regions representing the threshold for the significance of the effect of abusive supervision on self-blame for different levels of CSE (core self-evaluation)\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3994783/v1/85df3a8b784bf4d08b29cd7f.jpg"},{"id":53225857,"identity":"d873451a-0aef-404a-8a52-5c61f0314c2d","added_by":"auto","created_at":"2024-03-22 06:25:49","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":42181,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eInteraction of self-blame and power distance on guilt\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3994783/v1/d9a573eadd0d93f418b9b24b.jpg"},{"id":53225854,"identity":"a1836a0c-3cdf-489e-9fa0-abf538970c3b","added_by":"auto","created_at":"2024-03-22 06:25:49","extension":"jpg","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":81481,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eJohnson-Neyman regions representing the threshold for the significance of the effect of self-blame on guilt for different levels of power distance\u003c/strong\u003e\u003c/p\u003e","description":"","filename":"5.jpg","url":"https://assets-eu.researchsquare.com/files/rs-3994783/v1/a1b064cc05a1795345c6e5a4.jpg"},{"id":54330037,"identity":"7208e57c-5946-410a-9468-c0a3eec850c7","added_by":"auto","created_at":"2024-04-09 01:05:37","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":763675,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3994783/v1/52080c99-71bb-4972-87dd-de1ea6826f18.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Does abusive supervision increase employees’ helping behavior? Exploring mediating and moderating mechanisms","fulltext":[{"header":"Introduction","content":"\u003cp\u003eAbusive supervision in the workplace, referring to \"subordinates' perception of the extent to which supervisors engage in the sustained display of hostile verbal and nonverbal behaviors, excluding physical contact\" (Tepper, 2000), is burgeoning and plaguing more workplaces (Eissa \u0026amp; Lester, 2021; Mackey et al., 2017; Zhang \u0026amp; Liao, 2015). Yao examines abusive supervision is related to suicide ideation (Yao et al., 2023). From the perspective of justice theories and reciprocity, supervisor abuse can be conducive to retaliating behaviors such as cooperation reduction (Rafferty \u0026amp; Restubog, 2011), knowledge-hiding behaviors (Khalid \u003cem\u003eet al.\u003c/em\u003e, 2018), deviant behavior (Aryee \u003cem\u003eet al.\u003c/em\u003e, 2007), and poor subordinate task performance (Tepper \u003cem\u003eet al.\u003c/em\u003e, 2017). More recent research has revealed that subordinates may show helping behaviors after experiencing supervisor abuse (Troester \u0026amp; Van Quaquebeke, 2021). Drawing on the emotional process theory of abusive supervision (Oh \u0026amp; Farh, 2017), when subordinates point the finger at themselves after experiencing abuse, they may consequently blame themselves and feel guilt; hence, they try to compensate, thereby showing more helping behavior (Tangney et al., 1996; Troester \u0026amp; Van Quaquebeke, 2021).\u003c/p\u003e\n\u003cp\u003eMoreover, considering that emotions are influenced by personality traits (Weiss \u0026amp; Cropanzano, 1996), this study endeavors to investigate the moderating impact of core self-evaluation (CSE) as a factor that is shown to increase one’s vulnerability when facing challenging and stressful situations (Kammeyer-Mueller \u003cem\u003eet al.\u003c/em\u003e, 2009) and power distance orientation increasing or decreasing sensitivity toward abusive supervision (Lee \u003cem\u003eet al.\u003c/em\u003e, 2000).\u003c/p\u003e\n\u003cp\u003eThis research contributes to the literature on abusive supervision and subordinates’ corresponding reactions. First, this study considers self-blame and guilt as two mediators that can influence the reaction of subordinates toward abusive supervision, thereby helping the perpetuation of abuse. Second, considering CSE as a dispositional variable, this research shows that diverse levels of CSE can affect the relationship between abusive supervision and self-blame and prevent self-blame after abuse. Third, this study responds to the call for research on how individual-level cultural values impact perceptions, evaluations, and outcomes of abusive supervision (Mackey \u003cem\u003eet al.\u003c/em\u003e, 2017; Tepper, 2007) by investigating the moderation of subordinates’ power distance orientation on the relationship between self-blame and guilt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAbusive supervision and employees’ helping behavior\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePrevious research has explicitly shown the detrimental effects of abusive supervision (Zhang \u0026amp; Liu, 2018), encompassing reduced job satisfaction and commitment (Guan \u0026amp; Hsu, 2020), organizational citizenship behavior (Zhang et al., 2019), knowledge sharing behavior (Lee et al., 2018), and voice behavior (Frieder et al., 2015), all of which can be justified through the lens of social exchange theory.\u003c/p\u003e\n\u003cp\u003eTherefore, it is hypothesized that:\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 1:\u003c/strong\u003e Abusive supervision has a negative direct effect on employees’ helping behavior\u003cstrong\u003e.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe mediating roles of self-blame and guilt\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSelf-blame is a maladaptive cognitive coping strategy by which individuals attribute the reason for an unfavorable event to themselves (Alix et al., 2020). Research has shown that self-blaming is the first prevalent reaction to serious impairment from others (Schilpzand et al., 2016). Troester and Van Quaquebeke (2021) extended the emotional process theory of abusive supervision and considered self-blaming as a cognitive appraisal that can lead to feeling of guilt. Accordingly, after perceiving abusive supervision, employees may blame themselves, and if they deem themselves accountable, they feel guilty. Guilt is a conscious emotion that is generated in social interactions, and those who feel guilt prefer to compensate for their wrongdoings (Tangney et al., 1996). In other words, the feeling of guilt causes motivation and inclination through apologizing and making up for the loss (Tangney et al., 2007). Therefore,\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 2:\u003c/strong\u003e Self-blame and guilt mediate the indirect effect of abusive supervision on employees’ helping behavior\u0026nbsp;in a way that the indirect association of abusive supervision and helping behavior is significantly positive.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe moderating role of core self-evaluation\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCSE, a stable personality construct, represents the fundamental judgment individuals make about their self-worth and capabilities. It includes individual subconscious appraisal of one’s abilities and self-control (Chang et al., 2012). This concept was initially employed by (Judge \u003cem\u003eet al.\u003c/em\u003e, 1998) to evaluate job satisfaction and then utilized in other realms.\u003c/p\u003e\n\u003cp\u003eThose who are high in CSE are more resilient when encountering challenges (Mäkikangas \u003cem\u003eet al.\u003c/em\u003e, 2004). In contrast, those who are lower in CSE are weaker and more vulnerable because they have less self-confidence and are cynical about their competency and capabilities (Kammeyer-Mueller et al., 2009). Tepper and colleagues (2017) contend that abusive supervision is a more serious threat for those who are psychologically weaker and more vulnerable since they have more negative perceptions about their self-worth and performance. Looking through the lens of self-control, those who are higher in CSE are more faithful about their capabilities and self-control (Judge \u003cem\u003eet al.\u003c/em\u003e, 2003; Judge \u0026amp; Bono, 2001); therefore, self-blame, which is done due to lack of self-control (Gudjonsson, 1984; Koi, 2021), can be employed to compensate for loss. Hence,\u003c/p\u003e\n\u003cp\u003eHypothesis 3: CSE moderates the relationship between abusive supervision and self-blame in a way that those who have higher (lower) CSE blame themselves less (more).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eThe moderating role of power distance\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePower distance is a cultural value that represents the extent to which an individual expects and accepts an unequal distribution of power (Clugston \u003cem\u003eet al.\u003c/em\u003e, 2000; Hofstede, 2011). Those who are high in power distance orientation accept hierarchy and, respect powerful individuals and obey them (Farh \u003cem\u003eet al.\u003c/em\u003e, 2007) and tend to accept the supervisor’s decisions (Bochner \u0026amp; Hesketh, 1994). In contrast, individuals with a low power distance orientation deem themselves the peers of their supervisors and develop their relationships with them since they believe in the availability of their supervisors (Hofstede, 2011).\u003c/p\u003e\n\u003cp\u003eThose subordinates who are high in power distance orientation accept unequal power distance more willfully and are therefore more likely to defer to supervisors (Kirkman \u003cem\u003eet al.\u003c/em\u003e, 2009) due to their awareness of status differences during interactions, submissive and receptive to their supervisors’ decisions and their reactions toward their supervisors’ wrongdoing are less negative (Lee \u003cem\u003eet al.\u003c/em\u003e, 2000). Such subordinates accept power imbalance (Tyler, 2000). In contrast, low power orientation leads to perceiving more rule violations and feeling less justice, thereby feeling more guilt (Leith \u0026amp; Baumeister, 1998). Based on the conservation of resources theory (Hobfoll, 1989), subordinates with higher power distance orientation are more likely to judge their supervisor as less abusive than subordinates with low power distance.\u003c/p\u003e\n\u003cp\u003eSubordinates with a higher power distance orientation do not have to spend their resources as much to deal with abuse as subordinates with a lower power distance orientation. According to the power dependence theory (Emerson, 1972), they feel less violence of abuse due to their dependence on power sources; thus, in high power distance contexts, subordinates find abusive supervisors more tolerable (Lian \u003cem\u003eet al.\u003c/em\u003e, 2012; Tepper, 2007).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eHypothesis 4:\u003c/strong\u003e Power distance moderates the relationship between self-blame and guilt in a way that subordinates with higher (lower) power distance orientation feel less (more) guilt after blaming themselves.\u003c/p\u003e\n\u003cp\u003eThe conceptual model is illustrated in Figure 1.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eParticipants and data collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants were employees of public and private service organizations in Iran, which were selected by a nonprobability convenience sampling technique. G*power software version 3.1.9.6, developed by Faul et al. (2007), is one of the most widely used software to calculate and evaluate sample size adequacy. A power of 0.9 and an α level of 0.05 were considered. Initially, 50 data points were collected, an effect size of 0.0448 was acquired, and a sample size of 373 was determined. After considering a 90% response rate (Hoerger, 2010), 410 questionnaires were distributed. Finally, 392 complete questionnaires were collected (response rate = 95.6%). According to the suggestion of Goldammer et al. (2020), the Mahalanobis distance was calculated, and 11 outliers were omitted. Therefore, the final sample size comprising fully completed surveys was 381, with a response rate of 93%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAbusive supervision\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAbusive supervision was assessed by asking some follow-up questions after asking the participants to read one of the written scenarios randomly. The scenarios were adopted from (Troester \u0026amp; Van Quaquebeke, 2021), and the follow-up questions were from the five-item scale of abusive supervision (Mitchell \u0026amp; Ambrose, 2007). A sample item is “My supervisor ridicules me.” The Cronbach’s alpha was 0.94.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eSelf-blame\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo measure self-blame, the 3-item scale developed by (Troester \u0026amp; Van Quaquebeke, 2021) was adopted. A sample item of this scale is “I think that I am responsible for damaging my relationship with my supervisor.” The Cronbach alpha was 0.83.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eGuilt\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo evaluate guilt, the 5-item scale of guilt from the State Shame and Guilt Scale (SSDS) (Marschall et al., 1994) was used. A sample item is “I feel like apologizing, confessing.” The Cronbach’s alpha was 0.89.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eemployees’ helping behavior\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEmployees’ helping behavior was rated by the scale developed by Dalal and colleagues (2009). This measure includes six questions. For example, “I would go out of my way to be nice to my supervisor.” The Cronbach alpha was 0.78.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCore self\u003cspan dir=\"RTL\"\u003e-\u003c/span\u003eevaluation\u003cspan dir=\"RTL\"\u003e)\u0026nbsp;\u003c/span\u003eCSE\u003cspan dir=\"RTL\"\u003e\u0026nbsp;(\u003c/span\u003e\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants were asked to answer the questions of the 12-item scale of the Core Self-Evaluation Scale (Judge \u003cem\u003eet al.\u003c/em\u003e, 2003). The validity of this scale is well accentuated by previous research (Kacmar \u003cem\u003eet al.\u003c/em\u003e, 2009). A sample item is “When I try, I generally succeed.” The Cronbach’s alpha was 0.76.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003ePower Distance\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe six-item scale from Dorfman and Howell (1988) was used to measure power distance orientation. A sample item is “I believe managers should seldom ask for the opinion of employees.” The Cronbach’s alpha was 0.76.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIn this study, bootstrapping was used to investigate the proposed moderated mediation model completely. The bootstrapping technique was employed (Edwards \u0026amp; Lambert, 2007) via the PROCESS macro and added to SPSS (Hayes, 2018). Common method variance (CMV) is caused by using a single method to collect data (i.e., self-report survey in this study). In this regard, a Harman one-factor test, comprising all the variables, demonstrated that a single factor can represent only 22.47% of the variants, which is considerably less than 50% (Podsakoff \u0026amp; Organ, 1986). This result shows no significant common variance (Lindell \u0026amp; Whitney, 2001; Podsakoff et al., 2003). Therefore, common method variance is not a major threat in this study.\u003c/p\u003e\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n"},{"header":"Results","content":"\u003cp\u003ePrior to the testing of the proposed hypotheses, the data fitness of the measurement model, as well as the distinctiveness of the measures, were tested with AMOS (Arbuckle, 2006). The measurement model showed a good fit to the data (λ2=954.109, df=444, p\u0026lt;0.001, CFI=0.915, TLI=0.906, RMSEA=0.055).\u003c/p\u003e\u003cp\u003eTable 1 Results of confirmatory factor analysis (CFA)\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Results of confirmatory factor analysis\u003c/strong\u003e\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"102%\"\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd width=\"42.857142857142854%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eModels\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.29%;\"\u003e\n \u003cp\u003eχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.1020408163265305%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003edf\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003eχ2/df\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003eCFI\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003eTLI\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003eRMSEA\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.244897959183673%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003eΔχ\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"42.857142857142854%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eSix-factor model (Abusive supervision; CSE; PD; Self-Blame; Guilt; Employees’ helping behavior)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.29%;\"\u003e\n \u003cp\u003e954.109\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.1020408163265305%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003e444\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003e2.149\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.915\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.906\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e0.055\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.244897959183673%\" style=\"width: 12.9796%;\"\u003e\u003cbr\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"42.857142857142854%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eFive-factor model (Abusive supervision; CSE; PD; Self-Blame; Guilt and Employees’ helping behavior \u0026nbsp;combined)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.29%;\"\u003e\n \u003cp\u003e1572.78\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.1020408163265305%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003e449\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003e3.503\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.814\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.794\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.244897959183673%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e618.673\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"42.857142857142854%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eFour-factor model (Abusive supervision; CSE; PD; Self-Blame and Guilt and Employees’ helping behavior \u0026nbsp;combined)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.29%;\"\u003e\n \u003cp\u003e1737.98\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.1020408163265305%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003e453\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003e3.868\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.767\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.244897959183673%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e738.871\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"42.857142857142854%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eTeree-factor model (Abusive supervision and CSE combined; PD; Self-Blame and Guilt and Employees’ helping behavior \u0026nbsp;combined)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.29%;\"\u003e\n \u003cp\u003e2172.88\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.1020408163265305%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003e456\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003e4.765\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.716\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.691\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e0.100\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.244897959183673%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e1218.771\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"42.857142857142854%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eTwo-factor model (Abusive supervision and CSE and PD combined; Self-Blame and Guilt and Employees’ helping behavior \u0026nbsp;combined)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.29%;\"\u003e\n \u003cp\u003e2635.98\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.1020408163265305%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003e458\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003e5.755\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.609\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e0.112\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.244897959183673%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e1681.871\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"42.857142857142854%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eOne-factor\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.29%;\"\u003e\n \u003cp\u003e3287.14\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.1020408163265305%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003e459\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003e7.162\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.142857142857143%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.183673469387756%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.244897959183673%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e2333.031\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"44.21052631578947%\" style=\"width: 21.6326%;\"\u003e\n \u003cp\u003eOne-factor\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.421052631578947%\" style=\"width: 9.5995%;\"\u003e\n \u003cp\u003e3287.14\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"5.2631578947368425%\" style=\"width: 8.653%;\"\u003e\n \u003cp\u003e459\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"6.315789473684211%\" style=\"width: 9.8699%;\"\u003e\n \u003cp\u003e7.162\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"6.315789473684211%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.531\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"6.315789473684211%\" style=\"width: 10.5459%;\"\u003e\n \u003cp\u003e0.494\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.421052631578947%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.631578947368421%\" style=\"width: 12.9796%;\"\u003e\n \u003cp\u003e2333.031\u003csup\u003e***\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003e\u003cem\u003eNote: N\u0026nbsp;\u003c/em\u003e= 381. All alternative models were compared to the six-factor model.\u003cbr\u003e\u0026nbsp;Abbreviations: CFI (comparative fit index); RMSEA (root mean square error of approximation); SRMR (standardized root mean square residual).\u003cbr\u003e* \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .01; ** \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .001\u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTest of\u0026nbsp;the\u0026nbsp;hypothesized model\u003c/strong\u003e\u003c/p\u003e\u003cp\u003eTable 2 shows descriptive statistics, correlations, and Cronbach’s alpha of the variables. To test the hypotheses, the PROCESS macro for SPSS (Hayes, 2018) was utilized. The bootstrapping method with 5,000 interactions was used to calculate the indirect effects (Singh \u0026amp; Xie, 2008). Using the confidence interval, this method shows statistical significance if the interval excludes zero.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e2\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Descriptive statistics and zero-order correlations of the study variables\u003c/strong\u003e\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"600\"\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd width=\"30%\"\u003e\n \u003cp\u003eVariable\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e\u003cem\u003eM\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e\u003cem\u003eSD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.833333333333334%\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.5%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"30%\"\u003e\n \u003cp\u003e1. Abusive supervision\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e2.70\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e1.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.833333333333334%\"\u003e\n \u003cp\u003e(0.94)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.5%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"30%\"\u003e\n \u003cp\u003e2. CSE\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e3.71\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e0.49\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.833333333333334%\"\u003e\n \u003cp\u003e-.149\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.5%\"\u003e\n \u003cp\u003e(0.76)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"30%\"\u003e\n \u003cp\u003e3. Self-blame\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e2.33\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e0.86\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.833333333333334%\"\u003e\n \u003cp\u003e.414\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.5%\"\u003e\n \u003cp\u003e-.130\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e(0.83)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"30%\"\u003e\n \u003cp\u003e4. PD\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e2.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e0.68\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.833333333333334%\"\u003e\n \u003cp\u003e.110\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.5%\"\u003e\n \u003cp\u003e-.057\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e.209\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e(0.76)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"30%\"\u003e\n \u003cp\u003e5. Guilt\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e2.78\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e0.90\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.833333333333334%\"\u003e\n \u003cp\u003e.458\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.5%\"\u003e\n \u003cp\u003e-.161\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e.695\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e.136\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e(0.89)\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"30%\"\u003e\n \u003cp\u003e6. Employees’ helping behavior\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e2.98\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"7.666666666666667%\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.833333333333334%\"\u003e\n \u003cp\u003e-.227\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"9.5%\"\u003e\n \u003cp\u003e.103\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e.155\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e.128\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.666666666666666%\"\u003e\n \u003cp\u003e.164\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.333333333333334%\"\u003e\n \u003cp\u003e(0.78)\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cem\u003eNote: N\u0026nbsp;\u003c/em\u003e= 381. Cronbach's alphas are shown in the diagonal.\u003cbr\u003e* \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .01 \u0026nbsp;** \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003eHypothesis 1 outlined the significant negative direct association between abusive supervision and employees’ helping behavior. The results in Table 3\u0026nbsp;show\u0026nbsp;that the direct effect of abusive supervision on employees’ helping behavior is negative (\u003cem\u003eb\u003c/em\u003e=0.235, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001); therefore, Hypothesis 1 is supported.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Summary of analyses for Hypothesis 1\u003c/strong\u003e\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd width=\"21.21212121212121%\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariable\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eB\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eT\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eLLCI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eULCI\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.21212121212121%\"\u003e\n \u003cp\u003eAbusive supervision\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e-0.235\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e-7.447\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e0.000\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e-0.298\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"13.131313131313131%\"\u003e\n \u003cp\u003e-0.173\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003e\u003cem\u003eNote: N\u0026nbsp;\u003c/em\u003e= 381. Unstandardized beta coefficients are reported. Independent variables were mean centered.\u003c/p\u003e\u003cp\u003eSE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval)\u003c/p\u003e\u003cp\u003eThe dependent variable is employees’ helping behavior\u0026nbsp;\u003cbr\u003e* \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt;.01; ** \u003cem\u003ep\u0026nbsp;\u003c/em\u003e\u0026lt;.001.\u003c/p\u003e\u003cp\u003eHypothesis 2 asserts that the mediation of self-blame and guilt is significant. Based on Table 4, the indirect association between abusive supervisor and supervisor-directed helping via self-blame is 0.04 (boot SE=0.02). It is statistically significant since zero was not in the bias-corrected 95% confidence interval (CI= [0.002, 0.07]). Moreover, the indirect relationship between abusive supervision and employees’ helping behavior is 0.03 (boot SE=0.01) and is statistically significant since the confidence interval did not contain zero (0.95% CI= [0.008 and 0.054]). Last, the indirect effect of abusive supervision and employees’ helping behavior via both variables of self-blame and guilt was 0.04 (boot SE=0.01, CI= [0.013 and 0.062]) and significant. Juxtaposing these results, it was revealed that both self-blame and guilt significantly mediated the association between abusive supervision and employees’ helping behavior; thus, Hypothesis 2 is supported.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e4\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Summary of analyses for Hypothesis 2\u003c/strong\u003e\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-Blame\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eGuilt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003eemployees’ helping behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003et\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\n \u003cp\u003eAbusive Supervision\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.3\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e8.85**\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.15\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e5.17**\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e-0.24\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e-7.45**\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\n \u003cp\u003eGuilt\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.64\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e15.33**\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e2.31*\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\n \u003cp\u003eSelf-Blame\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e3.52**\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\n \u003cp\u003eModel \u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.17**\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.52**\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.15**\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd colspan=\"12\"\u003e\n \u003cp\u003eIndirect effects of abusive supervision on employees’ helping behavior \u0026nbsp;through self-blame and guilt\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eIndirect effect\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003eBoot SE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eLower 95% bootstrap confidence interval\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e\u003cem\u003eHigher 95% bootstrap confidence interval\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\n \u003cp\u003eSelf-Blame\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\n \u003cp\u003eGuilt\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd\u003e\u003cbr\u003e\u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\u003ctd\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd colspan=\"3\"\u003e\n \u003cp\u003e0.062\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"100%\" colspan=\"12\"\u003e\n \u003cp\u003eNote: N = 381. Unstandardized beta coefficients are reported. Independent variables were mean centered.\u003c/p\u003e\n \u003cp\u003eSE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval)\u003c/p\u003e\n \u003cp\u003e** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003eHypothesis 3 posits that CSE moderates the relationship between abusive supervision and self-blame in a way that more (less) CSE causes this relationship to be less (more) positive. The figures in Table 5 delineate that after controlling for the main impact of abusive supervision and CSE, the abusive supervision by CSE interaction term accounts for significant incremental variance (2.32% because of interaction\u003cspan dir=\"RTL\"\u003e\u0026nbsp;(\u003c/span\u003ein self-blame (\u003cem\u003eb\u003c/em\u003e=0.22, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001)). Additionally, simple slopes were depicted at one standard deviation above and below the mean of the CSE measure to accentuate the interaction effect directions (see Figure 2). The slope of the association between abusive supervision and self-blame was steeper for higher levels of CSE (simple slope=0.40, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001). In contrast, when the levels of CSE were lower, the association was significantly weaker (simple slope=0.18, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001).\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Summary of analyses for Hypothesis 3\u003c/strong\u003e\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"563\"\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-blame\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGuilt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployees’ helping behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eB\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.23404255319149%\"\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.865248226950355%\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eAbusive supervision\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.291**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.157\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.23404255319149%\"\u003e\n \u003cp\u003e-.235**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.865248226950355%\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eCSE\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e-0.118\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.0812\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.23404255319149%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.865248226950355%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eAbusive supervision × CSE\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.224*\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.23404255319149%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.865248226950355%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eSelf-blame\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.639\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.041\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.23404255319149%\"\u003e\n \u003cp\u003e0.123**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.865248226950355%\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eGuilt\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.23404255319149%\"\u003e\n \u003cp\u003e0.184**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"8.865248226950355%\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.199\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.518\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e31.297**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e202.829**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e22.960**\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cem\u003eConditional effects of abusive supervision on self-blame for different levels of CSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eEffect\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eBoot SE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eLower 95% bootstrap confidence interval\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eHigher 95% bootstrap confidence interval\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.09\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.05\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.492007104795736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"78.50799289520427%\" colspan=\"8\"\u003e\n \u003cp\u003eIndex of moderated mediation\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eIndex\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eBoot SE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eBoot LLCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eBoot ULCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eCSE\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"21.099290780141843%\" colspan=\"2\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003eNote: N = 381. Unstandardized beta coefficients are reported. Independent variables were mean centered.\u003c/p\u003e\n \u003cp\u003eCSE (Core Self-Evaluation); SE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval)\u003c/p\u003e\n \u003cp\u003e** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e\u003cp\u003eTo further our analysis, the PROCESS macro for SPSS (Hayes, 2017) was employed to test whether the conditional indirect effect of abusive supervision on employees’ helping behavior via the two mediators of self-blame and guilt was moderated by CSE (i.e., Hypothesis 3; see Table 5). The index of moderated mediation was significant (moderated mediation index=0.03, boot SE=0.01, 95% CI= [0.006 to 0.06]). The moderated mediation index indicates whether the indirect effects are influenced by the low and high levels of the moderator (Hayes, 2018). Excluding zero, the 95% bootstrapped confidence interval indicates that the indirect effect varies across diverse levels of CSE. Moreover, post hoc analyses utilizing the Johnson-Neyman technique postulate that the relationship between abusive supervision and self-blame is positive and significant for values above -0.85 standard deviation of the CSE mean (see Figure 3). On the whole, the findings contradict the proposed hypothesis. Therefore, Hypothesis 3 is not supported and is discussed later.\u003c/p\u003e\u003cp\u003eHypothesis 4 proposes that the association between self-blame and guilt is significantly moderated by power distance (see Table 6). To probe this, simple slope testing (Cohen \u003cem\u003eet al.\u003c/em\u003e, 2014) and the Johnson-Neyman technique (Hayes \u0026amp; Matthes, 2009; Johnson \u0026amp; Neyman, 1936) were used to identify significant regions. Simple slope testing showed that more self-blame leads to more feelings of guilt when power distance is lower (\u003cem\u003eb\u003c/em\u003e=0.22, SE=0.053, \u003cem\u003ep\u003c/em\u003e\u0026lt;0.001), and the confidence interval did not include zero for any of the high and low levels of power distance (see figure 4). Further analysis of the moderation showed that the moderation mediation index was also significant (moderated mediation index=-0.008, boot SE=0.004, 95% CI= [-0.017 to -0.001]). This demonstrates that the indirect effect of abusive supervision on employees’ helping behavior is impacted by power distance as the moderator. Based on Figure 5, the relationship between self-blame and guilt is negative for all the moderator values, ranging from -1.033 to 1.97 standard deviation of the power distance mean.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eTable\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e6\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;Summary of analyses for Hypothesis 4\u003c/strong\u003e\u003c/p\u003e\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"563\"\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"24.29078014184397%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eSelf-blame\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eGuilt\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployees’ helping behavior\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u003cem\u003eb\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.815602836879433%\"\u003e\n \u003cp\u003e\u003cem\u003eSE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eAbusive supervision\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e0.304**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.155**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.030\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e-0.235**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.815602836879433%\"\u003e\n \u003cp\u003e0.032\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eSelf-blame\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.637**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e0.123*\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.815602836879433%\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e-0.010\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.049\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.815602836879433%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eSelf-blame × PD\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e-0.140**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.815602836879433%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eGuilt\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e0.184**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.815602836879433%\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u003cem\u003eR\u003c/em\u003e\u003csup\u003e2\u003c/sup\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"24.29078014184397%\" colspan=\"2\"\u003e\n \u003cp\u003e0.171\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.527\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u003cem\u003eF\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"24.29078014184397%\" colspan=\"2\"\u003e\n \u003cp\u003e78.382**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e104.531**\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e22.960**\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"10.815602836879433%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003e\u003cem\u003eConditional effects of Self-blame on Guilt for different levels of PD\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u003cem\u003eEffect\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eBoot SE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eLower 95% bootstrap confidence interval\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eHigher 95% bootstrap confidence interval\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eLow\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.626\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e0.837\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eMean\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e0.637\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.042\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.555\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e0.719\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e0.543\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.056\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e0.432\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e0.653\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.492007104795736%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"78.50799289520427%\" colspan=\"8\"\u003e\n \u003cp\u003eIndex of moderated mediation\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e\u003cem\u003eIndex\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e\u003cem\u003eBoot SE\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eBoot LLCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u003cem\u003e\u0026nbsp;\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e\u003cem\u003eBoot ULCI\u003c/em\u003e\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"21.45390070921986%\"\u003e\n \u003cp\u003ePD\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"11.52482269503546%\"\u003e\n \u003cp\u003e-0.008\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"12.76595744680851%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"25.53191489361702%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.017\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"3.1914893617021276%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\u003ctd width=\"22.340425531914892%\" colspan=\"2\"\u003e\n \u003cp\u003e-0.001\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd width=\"100%\" colspan=\"9\"\u003e\n \u003cp\u003eNote: N = 381. Unstandardized beta coefficients are reported. Independent variables were mean centered.\u003c/p\u003e\n \u003cp\u003ePD (Power Distance); SE (Standard error); LLCI (Lower Limit Confidence Interval); ULCI (Upper Limit Confidence Interval)\u003c/p\u003e\n \u003cp\u003e** \u003cem\u003ep\u003c/em\u003e \u0026lt; 0.001 \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; * \u003cem\u003ep\u003c/em\u003e\u0026lt;0.01\u003c/p\u003e\n \u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/table\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this study, the association between abusive supervision and employees’ helping behavior behavior and the mediating and moderating mechanisms between these two variables were investigated. In this regard, two sequential variables of self-blame as an internal attribution, a cognitive process accusing oneself of a negative event, and guilt as an adaptive emotion (Alix \u003cem\u003eet al.\u003c/em\u003e, 2020) that facilitates and enhances cooperation (Deem \u0026amp; Ramsey, 2016), were considered. Heeding attention to personality and culture, CSE and power distance were chosen as the moderators of the two relationships.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDirect\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;effect\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirst, the findings of this research demonstrated that there is a significantly negative association between abusive supervision and employees’ helping behavior. Most abusive supervision literature revolves around the hinge of processing injustice in a way that followers endeavor to make a balance, thereby refraining from helping such supervisors amend the unjust supervisor-subordinate relationship\u0026nbsp;(Mackey \u003cem\u003eet al.\u003c/em\u003e, 2017; Tepper, 2000; Zhang \u003cem\u003eet al.\u003c/em\u003e, 2019). Drawing on resource conservation theory\u0026nbsp;(Hobfoll, 2001), abuse drains resources such as self-esteem and social support\u0026nbsp;(Lee \u003cem\u003eet al.\u003c/em\u003e, 2014), which causes the\u0026nbsp;maintenance\u0026nbsp;of remaining resources; therefore, plausibly, subordinates do not invest their time and energy in\u0026nbsp;extra role\u0026nbsp;behaviors,\u0026nbsp;including supervisor-directed helping\u0026nbsp;(Lyu \u003cem\u003eet al.\u003c/em\u003e, 2016). This happens when consequent self-blame and guilt are not triggered.\u003c/p\u003e\n\u003cp\u003eSecond, despite the plethora of research indicating that those subordinates who blame supervisor abuse decrease their helping behavior and increase their deviant behavior to establish a balance\u0026nbsp;(Mackey \u003cem\u003eet al.\u003c/em\u003e, 2017).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIndirect\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eeffect\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe findings showed that subordinates’ self-blaming after experiencing abuse can engender guilt, which ultimately functions as a motive to help the supervisor. It is aligned with the emotional process theory of abusive supervision, positing that self-blame is contingent on time and situation and causes diverse feelings such as anger, fear, and guilt and may lead to different behaviors (Oh \u0026amp; Farh, 2017). Therefore, when, during the initial appraisal, subordinates determine that the abuse is due to their faults, self-blame is initiated, which can become more profound after the second appraisal and manifest itself as guilt (Troester \u0026amp; Van Quaquebeke, 2021). As a self-conscious feeling that is closely related to pity, retaliation, and helping behavior (Miranda \u003cem\u003eet al.\u003c/em\u003e, 2020), guilt can lead to more helping behavior toward supervisors.\u003c/p\u003e\n\u003cp\u003eThird, CSE was introduced as a moderator to further help the literature on abusive supervision and related self-blaming. It was hypothesized that those with lower (higher) CSE are more likely to blame themselves (less) after encountering abusive supervision. Nevertheless, the findings showed the opposite. The possible reason is that drawing on self-verification theory (Swann Jr \u0026amp; Brooks, 2012), individuals prefer to be seen as they perceive themselves. Accordingly, when subordinates with higher CSE perceive abuse from their supervisors, they feel more of a threat to their self-schemas and feel more devastation (Duffy \u003cem\u003eet al.\u003c/em\u003e, 2006). Individuals with higher CSE have more self-esteem and self-efficacy with an external locus of control and are less neurotic (Kammeyer-Mueller \u003cem\u003eet al.\u003c/em\u003e, 2009). Therefore, supervisor abuse is deemed a threat to their characteristics, thereby reacting to abuse more intensely. Looking through the lens of resource conservation theory (Hobfoll, 2001), abusive supervision threatens important resources such as self-esteem (Lee \u003cem\u003eet al.\u003c/em\u003e, 2014); hence, those with higher CSE make more effort to maintain their depleting resources since they perceive the threat more severely, and once they judge themselves faulty, then self-blame may occur. Research has shown that those with higher self-esteem blame themselves more, indicating their effort to control and prevent abuse (Janoff-Bulman, 1979).\u003c/p\u003e\n\u003cp\u003eFourth, the role of power distance as a moderating factor in the relationship between self-blame and guilt was verified. Aligned with previous findings (Lian \u003cem\u003eet al.\u003c/em\u003e, 2012; Vogel \u003cem\u003eet al.\u003c/em\u003e, 2015), when power distance orientation is lower, more self-blame leads to more guilt. Subordinates with a higher power distance orientation tend to be more passive. They are more likely to tolerate abuse to maintain work relationships (Lian \u003cem\u003eet al.\u003c/em\u003e, 2012) and negative consequences (Vogel \u003cem\u003eet al.\u003c/em\u003e, 2015). In terms of stress, the stress caused by abusive supervision taxes cognitive-emotional resources in a way that reduces emotional regulation capacity due to decreased emotional awareness. This is accentuated by stress theories (Hobfoll, 2001), positing that the accumulation of stressors may deplete necessary resources to cope with subsequent stressors. Abusive supervision is associated with a range of acute and chronic stressors (Tepper, 2007), and guilt levels may be elevated for those with conflictual intimate relationships (i.e., lower power distance orientation). Both supervisor abuse and the experience of guilt can uniquely tax cognitive emotional resources (Taverna \u003cem\u003eet al.\u003c/em\u003e, 2021). Those with a higher power distance orientation are likely to be more inclined to employ avoidance coping in response to uncomfortable moral emotions, which could decrease guilt awareness and reduce distress over time (Litz \u003cem\u003eet al.\u003c/em\u003e, 2009).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitations\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eof\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;future research\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThere are several inherent limitations to this research. First, the data were collected through self-reporting questionnaires, which can raise concerns of common method bias. Based on the recommendations of researchers (for example, Conway and Lance, 2010), various initiations were performed to control it. The participants were selected from diverse public and private service-offering organizations. Moreover, they were reassured about the confidentiality of their responses. Valid scales were also employed to assess the variables.\u003c/p\u003e\n\u003cp\u003eLast but not least, a one-factor Harman test was also conducted to show that common method bias is not a concern. Nevertheless, future research may use other methods, such as experimental and longitudinal research methods. Second, it was shown that abusive supervision can increase employees’ helping behavior, thereby burgeoning productivity if helping behavior is aligned with organizational goals. However, this assertion has not yet been tested and is solely deduced from previous research (Tepper \u003cem\u003eet al.\u003c/em\u003e, 2017). Future research may delve into how and when helping abusive supervision can have positive organizational consequences. Third, to evaluate abuse, some assumed scenarios were designed, and the reality of workplaces was not considered; hence, future studies may consider critical incident interview techniques (CIT) to obtain in-depth details of the reactions to abusive supervision. This can lead to close-to-reality research. Last, the sample of this study was limited to service-offering organizations in Iran, which may limit the generalizability of the results. Further research can be conducted in other countries with different national cultures and in different organizations.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eResearch has already demonstrated that abusive supervision hampers helping supervisors; nevertheless, very sparse research has explored whether a specific mechanism can lead to more helping of abusive supervisors. In this regard, two sequential mediators of self-blame and guilt were selected. The findings showed that although the direct impact of abusive supervision on employees\u0026rsquo; helping behavior is negative and significant, the suppressing effects of self-blame and guilt are, to an extent, negative and significant. More importantly, two boundary conditions of a personality trait variable (i.e., core self-evaluation) and a cultural context variable (i.e., power distance) on two relationships of abusive supervision and self-blame and self-blame and guilt, respectively, demonstrated that those who are higher (lower) in core self-evaluation blame themselves more (less) when they encounter abuse. Additionally, those who are higher (lower) in power distance orientation feel less (more) guilt after blaming themselves.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to acknowledge all the staff for their participation. Many thanks to the editors and reviewers who worked hard on this paper and reviewed our article. We also\u0026nbsp;thank Amir Hussein\u0026nbsp;Mohammad\u0026nbsp;Karimi Yazdi from windsor University for language edition services.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design of the research: Mahammad Sadegh Sharifirad, Nahid Amrollahi Biuki; cquisition of data: Roghye Hekmat Nasab; Analysis and interpretation of the data: Mahammad Sadegh Sharifirad, Nahid Amrollahi Biuki; Statistical analysis: Roghye Hekmat Nasab; Writing of the manuscript: Roghye Hekmat Nasab, Nahid Amrollahi Biuki; Critical revision of the manuscript for intellectual content: Nahid Amrollahi Biuki, Mahammad Sadegh Sharifirad. All authors read and approved the final draft.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specifc grant from funding agencies in the public, commercial, or not-for-proft sectors. We thank all the Employees participated in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets during and/or analyzed during the current study available from the corresponding author on reasonable request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eI confirm that I have read the Editorial Policy pages. The study was the result of Mrs. Ruqieh Hekmat\u0026apos;s master\u0026apos;s thesis. The approval of the proposal and the thesis in the defense meeting were obtained from the Institutional Review Board of the Author\u0026apos;s University (Ardakan University) \u0026nbsp;for ethical review. This study was conducted in accordance with the declaration of Helsinki Written informed consent was obtained from all participants. This article does not contain any studies with human participants or animals performed by any of the authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;Not applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eAiken, L.S., West, S.G. and Reno, R.R. (1991), \u003cem\u003eMultiple Regression: Testing and Interpreting Interactions\u003c/em\u003e, sage.\u003c/li\u003e\n\u003cli\u003eAlix, S., Cossette, L., Cyr, M., Frappier, J.-Y., Caron, P.-O. and H\u0026eacute;bert, M. (2020), \u0026ldquo;Self-blame, shame, avoidance, and suicidal ideation in sexually abused adolescent girls: a longitudinal study\u0026rdquo;, \u003cem\u003eJournal of Child Sexual Abuse\u003c/em\u003e, Taylor \u0026amp; Francis, Vol. 29 No. 4, pp. 432\u0026ndash;447.\u003c/li\u003e\n\u003cli\u003eArbuckle, J.L. (2006), \u0026ldquo;Amos (version 7.0)[computer program]\u0026rdquo;, \u003cem\u003eChicago: SpSS\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eAryee, S., Chen, Z.X., Sun, L.-Y. and Debrah, Y.A. (2007), \u0026ldquo;Antecedents and outcomes of abusive supervision: test of a trickle-down model.\u0026rdquo;, \u003cem\u003eJournal of Applied Psychology\u003c/em\u003e, American Psychological Association, Vol. 92 No. 1, pp. 191\u0026ndash;201.\u003c/li\u003e\n\u003cli\u003eBennett, K.K., Compas, B.E., Beckjord, E. and Glinder, J.G. (2005), \u0026ldquo;Self-blame and distress among women with newly diagnosed breast cancer\u0026rdquo;, \u003cem\u003eJournal of Behavioral Medicine\u003c/em\u003e, Springer, Vol. 28 No. 4, pp. 313\u0026ndash;323.\u003c/li\u003e\n\u003cli\u003eBochner, S. and Hesketh, B. (1994), \u0026ldquo;Power distance, individualism/collectivism, and job-related attitudes in a culturally diverse work group\u0026rdquo;, \u003cem\u003eJournal of Cross-Cultural Psychology\u003c/em\u003e, Sage Publications Sage CA: Thousand Oaks, CA, Vol. 25 No. 2, pp. 233\u0026ndash;257.\u003c/li\u003e\n\u003cli\u003eBrislin, R.W. 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(2009), \u0026ldquo;Moral injury and moral repair in war veterans: A preliminary model and intervention strategy\u0026rdquo;, \u003cem\u003eClinical Psychology Review\u003c/em\u003e, Elsevier, Vol. 29 No. 8, pp. 695\u0026ndash;706.\u003c/li\u003e\n\u003cli\u003eLyu, Y., Zhu, H., Zhong, H.-J. and Hu, L. (2016), \u0026ldquo;Abusive supervision and customer-oriented organizational citizenship behavior: The roles of hostile attribution bias and work engagement\u0026rdquo;, \u003cem\u003eInternational Journal of Hospitality Management\u003c/em\u003e, Elsevier, Vol. 53, pp. 69\u0026ndash;80.\u003c/li\u003e\n\u003cli\u003eMackey, J.D., Frieder, R.E., Brees, J.R. and Martinko, M.J. (2017), \u0026ldquo;Abusive supervision: A meta-analysis and empirical review\u0026rdquo;, \u003cem\u003eJournal of Management\u003c/em\u003e, Sage Publications Sage CA: Los Angeles, CA, Vol. 43 No. 6, pp. 1940\u0026ndash;1965.\u003c/li\u003e\n\u003cli\u003eM\u0026auml;kikangas, A., Kinnunen, U. and Feldt, T. (2004), \u0026ldquo;Self-esteem, dispositional optimism, and health: Evidence from cross-lagged data on employees\u0026rdquo;, \u003cem\u003eJournal of Research in Personality\u003c/em\u003e, Elsevier, Vol. 38 No. 6, pp. 556\u0026ndash;575.\u003c/li\u003e\n\u003cli\u003eMarschall, D., Sanftner, J. and Tangney, J.P. (1994), \u0026ldquo;The state shame and guilt scale\u0026rdquo;, \u003cem\u003eFairfax, VA: George Mason University\u003c/em\u003e.\u003c/li\u003e\n\u003cli\u003eMiranda, G.A., Welbourne, J.L. and Sariol, A.M. (2020), \u0026ldquo;Feeling shame and guilt when observing workplace incivility: Elicitors and behavioral responses\u0026rdquo;, \u003cem\u003eHuman Resource Development Quarterly\u003c/em\u003e, Wiley Online Library, Vol. 31 No. 4, pp. 371\u0026ndash;392.\u003c/li\u003e\n\u003cli\u003eMitchell, M.S. and Ambrose, M.L. 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(2019), \u0026ldquo;Abusive leadership and helping behavior: Capability or mood, which matters?\u0026rdquo;, \u003cem\u003eCurrent Psychology\u003c/em\u003e, Springer, Vol. 38 No. 1, pp. 50\u0026ndash;58.\u003c/li\u003e\n\u003cli\u003eZellars, K.L., Tepper, B.J. and Duffy, M.K. (2002), \u0026ldquo;Abusive supervision and subordinates\u0026rsquo; organizational citizenship behavior.\u0026rdquo;, \u003cem\u003eJournal of Applied Psychology\u003c/em\u003e, American Psychological Association, Vol. 87 No. 6, pp. 1068\u0026ndash;1076.\u003c/li\u003e\n\u003cli\u003eZhang, J. and Liu, J. (2018), \u0026ldquo;Is abusive supervision an absolute devil? Literature review and research agenda\u0026rdquo;, \u003cem\u003eAsia Pacific Journal of Management\u003c/em\u003e, Springer, Vol. 35 No. 3, pp. 719\u0026ndash;744.\u003c/li\u003e\n\u003cli\u003eZhang, Y. and Liao, Z. (2015), \u0026ldquo;Consequences of abusive supervision: A meta-analytic review\u0026rdquo;, \u003cem\u003eAsia Pacific Journal of Management\u003c/em\u003e, Springer, Vol. 32 No. 4, pp. 959\u0026ndash;987.\u003c/li\u003e\n\u003cli\u003eZhang, Y., Liu, X., Xu, S., Yang, L.-Q. and Bednall, T.C. (2019), \u0026ldquo;Why abusive supervision impacts employee OCB and CWB: A meta-analytic review of competing mediating mechanisms\u0026rdquo;, \u003cem\u003eJournal of Management\u003c/em\u003e, Sage Publications Sage CA: Los Angeles, CA, Vol. 45 No. 6, pp. 2474\u0026ndash;2497.\u003c/li\u003e\n\u003cli\u003eYao, Y., Dong, F., \u0026amp; Qiao, Z. (2023). Perceived abusive supervision and graduate students\u0026rsquo; suicidal ideation: from the perspective of interpersonal psychological theory of suicide. \u003cem\u003eBMC psychology\u003c/em\u003e, \u003cem\u003e11\u003c/em\u003e(1), 80. \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Abusive supervision, employees’ helping behavior, self-blame, guilt, core self-evaluation, power distance.","lastPublishedDoi":"10.21203/rs.3.rs-3994783/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3994783/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e Typically, researchers believe that abusive supervision decreases employees' helping behavior. However, according to the emotional process theory of abusive supervision, subordinates show more helping behavior under certain conditions. The purpose of this study was to examine the impact of abusive supervision on employees' helping behavior, with a focus on the mediating role of self-blame and guilt, as well as the moderating effects of core self-evaluation (CSE) and power distance.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e In this study, the PROCESS Macro model was used to investigate the proposed moderated mediation model completely. Confirmatory factor analysis was tested with AMOS. Employees of diverse private and state service-offering organizations in Yazd, Iran, were invited to participate in the study (n=381) using simple random sampling. To gather the data, the abusive supervision scale (Mitchell \u0026amp; Ambrose, 2007), employees’ helping behavior was rated by the scale developed by Dalal and colleagues (2009), State Shame and Guilt Scale (SSGS), Self-blame questionnaire (Troester \u0026amp; Van Quaquebeke, 2021), Core Self-Evaluation Scale (Judge et al., 2003) and Power Distance scale from Dorfman and Howell (1988) were used. The hypothesized model was analyzed according to the procedure of the PROCESS Macro model.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eThe direct association between abusive supervision and employees’ helping behavior was significantly negative; however, the significant mediation by self-blame and guilt was negative. Moreover, more (less) core self-evaluation intensified (attenuated) the relationship between abusive supervision and self-blame. More (less) power distance decreased (increased) the association between self-blame and guilt.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eFirst, this study enriches the literature on abusive supervision and its aftermath by introducing self-blame and guilt as two mediators that can influence subordinates’ reactions to abusive supervision. Second, unprecedentedly, CSE was tested as a moderator between abusive supervision and self-blame. Third, in response to the previous call for research (Mackey \u003cem\u003eet al.\u003c/em\u003e, 2017; Tepper, 2007), the moderation of subordinates’ power distance orientation on the relationship between self-blame and guilt was investigated.\u003c/p\u003e","manuscriptTitle":"Does abusive supervision increase employees’ helping behavior? Exploring mediating and moderating mechanisms","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-03-22 06:25:38","doi":"10.21203/rs.3.rs-3994783/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"9f23c7fd-acc8-4312-854e-790aaacdf932","owner":[],"postedDate":"March 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-04-09T00:57:30+00:00","versionOfRecord":[],"versionCreatedAt":"2024-03-22 06:25:38","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3994783","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3994783","identity":"rs-3994783","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}