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In Search of the Prosocial Personality: Personality Traits as Predictors of Prosociality and Prosocial Behavior Anja Wertag and Denis Bratko
Original Article
In Search of the Prosocial Personality
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Personality Traits as Predictors of Prosociality and Prosocial Behavior
Anja Wertag 1
and Denis Bratko 2
1
Institute of Social Sciences Ivo Pilar, Zagreb, Croatia 2
Department of Psychology, Faculty of Social Sciences and Humanities, University of Zagreb, Croatia
Abstract: Prosocial behavior is intended to benefit others rather than oneself and is positively linked to personality traits such as Agreeableness and Honesty-Humility, and usually negatively to the Dark Triad traits (i.e., Machiavellianism, narcissism, and psychopathy). However, a significant proportion of the research in this area is conducted solely on self-report measures of prosocial behavior. Therefore, the aim of this study was to investigate the relationship between prosociality and the basic (i.e., HEXACO) and dark personality traits, comparing their contribution in predicting both self-reported prosociality and prosocial behavior. Results of the hierarchical regression analyses showed that the Dark Triad traits explain prosociality and prosocial behavior above and beyond the HEXACO traits, emphasizing the importance of the Dark Triad in the personality space.
Keywords: personality, prosociality, prosocial behavior, Dark Triad, HEXACO
Prosocial behavior covers a broad range of actions that are intended to benefit others rather than oneself, such as cooperating, sharing, giving, helping, and comforting others (Batson & Powell, 2003). In order to organize research related to prosocial behavior, Penner, Dovidio, Piliavin, and Schroeder (2005) proposed a multilevel perspective of analyzing and understanding prosocial behavior. The meso level refers to studying helper–recipient dyads in specific situations and providing information on different forms of prosocial behavior as well as some circumstantial and situational factors that have an impact on the occurrence of prosocial behavior. The macro level focuses on prosocial actions within the context of groups, while the micro level is primarily concerned with origins of prosocial tendencies and etiology of individual differences in these tendencies. If prosociality is observed within the personality space, “among the major dimensions of the Big Five, Agreeableness is the single best predictor of prosocial tendencies and behavior” (Graziano & Habashi, 2015, pp. 214–242), which is not surprising, given that it encompasses characteristics such as forgiveness, generosity, helpfulness, and sympathy. However, Agreeableness is not a universal predictor of all forms of prosocial tendencies (Graziano & Habashi, 2015), and the empirical evidence concerning relations between these two is somewhat mixed.
The recently developed HEXACO model accommodates important constructs that are beyond the space of the Big Five model, including different forms of altruism (for details, see Ashton & Lee, 2007). Namely, while three dimensions of the HEXACO model are close analogues (i.e., Extraversion, Conscientiousness, and Openness to Experience) and the other two dimensions roughly correspond to rotated variants of their Big Five counterparts (i.e., Emotionality and Agreeableness), the biggest novelty of the HEXACO model is the sixth dimension of HonestyHumility. Honesty-Humility “represents the tendency to be fair and genuine in dealing with others, in the sense of cooperating with others even when one might exploit them without suffering retaliation” (Ashton & Lee, 2007, p. 156), while in this model, Agreeableness “represents the tendency to be forgiving and tolerant to others, in the sense of cooperating with others even when one might be suffering from exploitation” (Ashton & Lee, 2007, p. 156). Although Honesty-Humility explicitly contrasts prosocial and antisocial tendencies, Ashton and Lee (2007) propose that the general altruistic versus general antagonistic orientation is located between Honesty-Humility, Agreeableness, and Emotionality factors. More specifically, Emotionality is related to kin altruism (being related to attachment and empathy toward close others), while Honesty-Humility and Agreeableness are related to different forms of reciprocal altruism: Honesty-Humility to active, and Agreeableness to reactive cooperation (Ashton & Lee, 2007; Hilbig, Zettler, Leist, & Heydasch, 2013). On the other hand, there are some personality traits that are linked to being less likely to engage in helping behavior,
such as the Dark Triad traits (i.e., Machiavellianism, narcissism, and subclinical psychopathy; Bereczkei, Birkas, & Kerekes, 2010; Berger & Palacios, 2014; Lannin, Guyll, Krizan, Madon, & Cornish, 2014; White, 2014), which are linked to callousness, deception, exploitation, and manipulation, as well as antisocial behavior (Furnham, Richards, & Paulhus 2013). However, relations between antisocial and prosocial behavior are complex, and not always inverse (McGinley & Carlo, 2006), and Hawley (2003; 2006) suggested that both prosocial and aggressive behaviors can coexist in the same individual. Finally, although prosocial behavior can be motivated by altruistic reasons, there are other egoistic reasons for prosocial behavior such as to receive praise or attention, to reduce uncomfortable feelings such as guilt, or to receive something in return (Batson, 2011). In line with that, previous research suggests that there is a positive relationship between the dark traits and, at least, some forms of prosocial behavior, such as self-reported (Kauten & Barry, 2016; Zuo, Wang, Xu, Wang, & Zhao, 2016), public (Konrath, Ho, & Zarins, 2016; White, 2014), and opportunistic prosocial behavior (Eberly-Lewis & Coetzee, 2015). While the relationship between prosociality and the basic personality traits (i.e., Agreeableness and Honesty-Humility) has been well established, this is not the case with the dark traits. Namely, the relationship between prosociality and the Dark Triad traits, when assessed, is usually only with one or two of the dark traits (e.g., Bereczkei & Czibor, 2014; Berger, Batanova, & Cance, 2015; Böckler, Sharifi, Kanske, Dziobek, & Singer, 2017; Curry, Chesters, & Viding, 2011; Eberly-Lewis & Coetzee, 2015), or relies solely on self-reports (e.g., Aghababaeia, Mohammadtabara, & Saffariniab, 2014; Zuo et al., 2016). Therefore, the aim of this study was to investigate the relationship between prosociality and the basic (i.e., HEXACO) and the dark traits, expecting the relationship to be positive in the case of the basic traits, and negative in the case of the dark traits. More precisely, we expect a positive relationship between prosociality and Honesty-Humility, Agreeableness, and Emotionality traits that accommodate a general altruistic orientation (Ashton & Lee, 2007). Moreover, the aim of this study was to explore the contributions of both basic and the dark traits in prediction of prosociality, which represents a unique contribution to the field of prosociality research. Given that the common core of the Dark Triad has a substantial overlap with Honesty-Humility (Lee et al., 2013), we wanted to explore whether the Dark Triad would have an incremental predictive validity over the HEXACO traits in predicting prosociality, or are the basic personality traits sufficient for prediction of prosociality. Finally, although there are some findings on relations between personality traits and prosocial behavior in economic games (for review, see Zhao & Smillie, 2015), the significant proportion of research in this area is conducted solely on selfreport measures of prosocial behavior, and research that combines self-report measures with other measures is still scarce (but for exception, see Böckler, Tusche, & Singer, 2016; Hubbard, Harbaugh, Srivastava, Degras, & Mayr, 2016). Therefore, the aim of the present study was to determine which personality traits contribute best in predicting actual prosocial behavior, hypothesizing that the relations of personality traits and prosociality observed with the self-report measure will be consistent with the behavioral measure.
Methods
Participants and Procedure
A total of 680 students (80% females), aged 18–39 years (M = 22.04, SD = 2.95), were recruited from various universities in Croatia to participate in a larger online survey. The invitation to participate in the study together with the link to the questionnaire was announced on the faculties’ web pages, student mailing lists, and social networks. Participants responded to the survey once they ticked the consent box. The approval of the ethical review board was obtained for all aspects of the study.
Out of the initial sample, 336 students (83% female; M age = 22.09, SD = 3.72) gave their consent in the first part of the study for participating in future studies. These students were contacted by the researcher’s assistant approximately 1 month later with a kind request to fill in the survey again, as something went wrong with the collected data and it became unusable. The researcher’s assistant emphasized that their help is crucial for the completion of the project and that his/her job depended upon it. The average time for completing the whole online survey was 33 min (SD = 15.8, range: 15–75), and the repeated completion of the survey was conceptualized as the measure of prosocial behavior.
Measures
Apart from the above-described measure of prosocial behavior, all other variables were assessed via self-report measures, where the participants estimated to which extent they agree or disagree with every item on a 5-point Likert scale (1 = totally disagree; 5 = totally agree) or how often they performed a certain behavior (1 = never, 5 = very often).
The Prosocial Personality Battery The 30-item Prosocial Personality Battery (PSB; Penner, Fritzsche, Craiger, & Freifeld, 1995) was used to assess prosocial tendencies. The PSB consists of seven subscales: Social Responsibility, Empathic Concern, Perspective Taking, Personal Distress, Mutual Moral Reasoning, Otheroriented Reasoning, and Self-reported Altruism, and the total result was calculated in accordance with the author’s recommendations, with higher scores indicating more pronounced prosocial tendencies. Cronbach’s α coefficient of the PSB in the current study was .78. PSB was translated into Croatian by two independent translators. After reaching the consensus on all items, they were translated back to English. Several minor inconsistencies were amended through a discussion between the translators and the backtranslator.
Short Dark Triad Scale The 27-item Short Dark Triad scale (SD3; Jones & Paulhus, 2014; for the Croatian version, see Wertag, Vrselja, & Tomić, 2011) was used to measure Machiavellianism, narcissism, and psychopathy. The total score is calculated for each of the traits by summing up referring items, with higher scores indicating more pronounced traits. Cronbach’s α coefficients in the current study were .77, .66, and .73 for Machiavellianism, narcissism, and psychopathy, respectively.
The HEXACO Personality Inventory The HEXACO factors (Honesty-Humility, Emotionality, Extraversion, Agreeableness, Consciousness, and Openness to Experience) were measured using the 60-item HEXACO Personality Inventory-Revised (HEXACO-60; Ashton & Lee, 2009; for the Croatian version, see Babarović & Šverko, 2013). Cronbach’s α coefficient in the current study ranged from .75 to .81.
Statistical Analyses
The relationship between prosociality and personality traits was investigated through zero-order and partial correlations. The contribution of personality traits in the prediction of prosociality was explored through hierarchical multiple regression analysis in the case of self-report prosociality and hierarchical binary logistic regression analysis in the case of behavioral measure of prosociality (as it was conceptualized as a dichotomous variable of either the presence or absence of prosocial behavior), which enabled the investigation of incremental predictive validity of the Dark Triad over the HEXACO traits in predicting prosociality.
Results
Correlation Analysis
The correlation matrix (Table 1) indicated that zero-order correlations between prosocial tendencies and personality were positive for HEXACO and negative for the Dark Triad. As the correlations between Honesty-Humility and the Dark Triad indicated a substantial overlap, partial correlations of these traits with PSB were calculated: when controlling for Honesty-Humility, partial correlations between prosocial tendencies and the Dark Triad were .33 (p < .001), .01 (p = .75), and .35 (p < .001) for Machiavellianism, narcissism, and psychopathy, respectively, while the partial correlation (controlling for the Dark Triad) between prosocial tendencies and Honesty-Humility was .19 (p < .001).
Hierarchical Regression Analyses
A hierarchical multiple regression analysis was conducted to determine contributions of the basic and dark personality traits in predicting prosocial tendencies. Given that the dark traits are more pronounced in men (Jonason, Li, Webster, & Schmitt, 2009) and that there is a trend of increase in these traits among newer cohorts (Gunnthorsdottir, McCabe, & Smith 2002; Twenge & Foster, 2010; Twenge et al., 2010), gender and age were entered into the hierarchical regression analyses as the control variables in the first step. In the second step, HEXACO personality traits were entered, and in the third step, the Dark Triad traits (all VIFs were lower than 1.83). Results showed that, after controlling for demographical variables, HEXACO dimensions explained 31% of prosocial tendencies variance, F(6, 671) = 54.32, p < .001, while the Dark Triad explained an additional 5% of the variance, F(3, 668) = 17.10, p < .001. In the final model, all personality variables except narcissism (β = .04, p = .26) contributed significantly in explaining prosocial tendencies (Table 2).
Hierarchical Logistic Regression Analysis
Before exploring the contribution of the basic and dark personality traits in predicting prosocial behavior, we examined whether there were some differences in these traits between participants who gave their consent in the first part of the study for participating in future studies and those who did not: the differences were found only on HonestyHumility (t = 3.23, p < .001; d = 0.40) and Machiavellianism (t = 2.13, p = .03; d = 0.16), with those who gave
Gender Age PSB H E X A C O M N P
Age .10** PSB .15** .18** (.78) H .12** .03 .40** (.77) E .46** .02 .17** .02 (.81) X .00 .07 .18** .08* .18** (.81) A .10* .00 .34** .26** .10* .07 (.75) C .01 .01 .16** .06 .01 .19** .05 (.76) O .01 .14** .26** .10** .10** .07 .06 .07 (.78) M .13** .03 .45** .52** .13** .15** .32** .07 .05 (.77)
N .08* .03 P .15** .01
.16** .45**
.40** .38**
.12** .43** .16** .14**
.19** .12** .11** .30** (.66) .42** .18** .01 .57** .28** (.73)
M SD
22.04 96.12 3.37 3.36 3.25 3.00 3.47 3.69 2.91 2.70 2.07
2.95 9.84 0.50 0.69 0.64 0.60 0.57 0.62 0.62 0.54 0.57
Notes. N = 680. Cronbach’s α appears in the diagonal (see brackets). Gender: 1 = female, 2 = male. PSB = Prosocial Personality Battery; H = HonestyHumility; E = Emotionality, X = Extraversion; A = Agreeableness; C = Conscientiousness; O = Openness to Experience; M = Machiavellianism; N = Narcissism; P = Psychopathy. *p < .05, **p < .01, all two-tailed.
Table 2. Summary of hierarchical regression analysis for variables predicting self-reported prosocial tendencies
Model 1 Model 2 Model 3 B SE B β B SE B β B SE B
β
Gender 4.18 0.92 .17** 1.23 0.88 .05 0.91 0.85 .04 Age 0.67 0.12 .20** 0.48 0.10 .14** 0.48 0.10 .14** H 0.57 0.06 .29** 0.32 0.07 .16** E 0.32 0.05 .22** 0.24 0.05 .17**
X 0.21 0.05 .14** 0.19 0.06 .12**
A 0.44 0.05 .27** 0.28 0.06 .17**
C 0.15 0.05 .09** 0.12 0.05 .07*
O 0.32 0.05 .21** 0.34 0.05 .22**
M
N
P R 2
F
2.19 0.63 0.81 0.72 2.74 0.69 .06 .37 .41 22.51** 49.03** 42.89**
.14** .04 .16**
Notes. N = 680. Gender: 1 = female, 2 = male. H = Honesty-Humility; E = Emotionality, X = Extraversion; A = Agreeableness; C = Conscientiousness; O = Openness to Experience; M = Machiavellianism; N = Narcissism; P = Psychopathy. *p < .05, **p < .01, all two-tailed.
consent having higher scores on Honesty-Humility and lower on Machiavellianism. 1 A total of 121 students completed the survey again. A hierarchical binary logistic regression analysis was conducted to determine the contribution of the basic and dark personality traits in predicting prosocial behavior. The results showed that the baseline model predicted prosocial behavior correctly in 64% of the cases. Among control variables, age was a significant predictor of prosocial behavior, neither one of the HEXACO dimensions had a significant contribution to the prediction of prosocial behavior in the second step (w 2
= 5.21, df= 6, p = .52), while with the Dark Triad, narcissism had a significant contribution in the third step (w 2
= 9.24, df= 3, p = .03; Table 3).
Model 1 Model 2 Model 3 B SE B OR [95% CI] B SE B OR [95% CI] B SE B OR [95% CI]
Gender 0.51 0.32 0.60 [0.32, 1.14] 0.23 0.37 0.80 [0.39, 1.64] 0.24 0.37 0.79 [0.38, 1.63] Age 0.09* 0.04 1.10 [1.02, 1.17] 0.09* 0.04 1.09 [1.02, 1.17] 0.09* 0.04 1.10 [1.02, 1.18] H 0.04 0.02 1.04 [0.99, 1.09] 0.00 0.03 1.00 [0.94, 1.06] E 0.03 0.02 1.03 [0.99, 1.07] 0.02 0.02 1.02 [0.98, 1.06] X 0.00 0.02 1.00 [0.96, 1.04] 0.02 0.02 1.02 [0.98, 1.07] A 0.00 0.02 1.00 [0.96, 1.04] 0.01 0.02 0.99 [0.95, 1.04] C 0.01 0.02 1.01 [0.97, 1.06] 0.01 0.02 1.01 [0.97, 1.06] O 0.01 0.02 0.99 [0.95, 1.03] 0.00 0.02 1.00 [0.96, 1.04]
0.06 0.26 0.94 [0.56, 1.56] 0.74** 0.29 0.48 [0.27, 0.84]
0.17 0.29 0.84 [0.48, 1.49]
Constant w 2
2.41 0.79 0.09 4.92 1.80 0.01 1.59 2.55 0.20 8.12* 13.33 22.57*
df Pseudo-R 2
2 8 11 .03 .05 .09
% 64.6 64.9 65.5
Notes. N = 336. Gender: 1 = female, 2 = male. OR = odds ratio; CI = confidence interval. H = Honesty-Humility; E = Emotionality, X = Extraversion; A = Agreeableness; C = Conscientiousness; O = Openness to Experience; M = Machiavellianism; N = Narcissism; P = Psychopathy. *p < .05, **p < .01, all twotailed.
Discussion
The main aim of this paper was to examine the relationship between prosociality and the basic and dark traits, and to compare their contribution in predicting self-reported prosocial tendencies and actual prosocial behavior. In line with expectations, the dark traits had negative relations with prosociality, while basic personality traits had positive relations with prosocial tendencies. Descriptive comparisons of effect sizes indicated that, among the Dark Triad traits, Machiavellianism and psychopathy were more negatively related to prosocial tendencies than narcissism (with small effect size of narcissism compared to medium to large of the former two). This is not surprising, given that Machiavellianism and psychopathy are considered to be the “darker” side of the Dark Triad (Rauthmann & Kolar, 2012). Among basic personality traits, prosocial tendencies were especially related to Honesty-Humility and Agreeableness (with medium to large effect size), and Openness to Experience (with medium effect size), which was partly expected, given that Ashton and Lee (2007) proposed that the general altruistic versus general antagonistic orientation is located between Honesty-Humility, Agreeableness, and Emotionality factors. The reasons for a relatively lower correlation of prosocial tendencies and Emotionality compared to Openness can be found on the facet level. 2
Namely, Emotionality encompasses characteristics such as fearfulness, anxiety, need for emotional support from others, and empathy. Among these characteristics, empathy is most strongly related to prosocial behavior; it is considered to be its important precursor and a motivator. Therefore, it seems logical that the Emotionality factor would be related to prosocial tendencies primarily through its Sentimentality subscale, which was the case in our study. On the other hand, Openness on its positive pole encompasses characteristics such as enjoyment of beauty in art and in nature, inquisitiveness about various domains of knowledge, creativity, and a tendency to accept the unusual, and the results of our study suggest that these also tend to be characteristics of prosocially oriented people. It is possible that people who appreciate nature and art at the same time appreciate others, and are more prone to engaging in prosocial behavior.
Regarding the contribution of HEXACO and the Dark Triad in predicting prosocial tendencies, the results of the hierarchical regression analyses showed that, after controlling for demographical variables, HEXACO explained 31% of the variance. Although all of the HEXACO traits had a significant contribution, the highest contribution to the explanation of prosocial tendencies was (based on the descriptive comparison of regression coefficients) of the three theoretically expected traits: Honesty-Humility, Agreeableness, and Emotionality. Above HEXACO, the Dark Triad (more specifically, Machiavellianism and
psychopathy) explained an additional 5% variance of prosocial tendencies. Unlike the HEXACO traits, the more pronounced dark traits were linked to less self-reported prosocial tendencies, which is in line with previous findings that those rating high on the Dark Triad are generally less prone to helping behaviors (Bereczkei et al., 2010; Berger & Palacios, 2014; Lannin et al., 2014; White, 2014). When comparing the predictability of specific dark traits, Machiavellianism emerged as the strongest negative predictor of prosocial tendencies, which is in accordance with previous findings (e.g., Aghababaeia et al., 2014). Although Hawley (2003, 2006) suggested that Machiavellians use both aggressive and prosocial strategies, which gives them evolutionary advantages, our results do not seem to support this. One of the possible explanations lies in the fact that we measured prosocial tendencies anonymously, in an online study, where it is doubtful whether one can have an interest in expressing prosociality. Namely, one of the characteristics that distinguishes Machiavellianism from the other two Dark Triad traits is intentional planning and care about reputation (Jones & Paulhus, 2011), and Machiavellians seem to be willing to help only in the presence of others (Bereczkei et al., 2010). After comparing the contribution of the basic and dark traits in predicting self-reported prosocial tendencies, in the second part of the study, we investigated these relations with the actual behavior. The results showed that the Dark Triad predicted prosocial behavior above and beyond the HEXACO traits, which did not contribute significantly in predicting prosocial behavior. However, general trait measures usually do not predict specific behaviors very strongly, and the correct classification of cases in this study was not very high (up to 65%). Among the dark traits, only narcissism emerged as a significant predictor of prosocial behavior, indicating that grandiosity and self-centeredness could be the most pronounced characteristics of those who are not likely to engage in prosocial behavior. These findings are not consistent with findings from the first part of the study showing that dark traits which accounted for prosocial tendencies were Machiavellianism and psychopathy, while narcissism was unrelated to prosocial tendencies. This is in line with previous findings indicating that selfreported prosocial behavior is just one factor of prosociality, and is distinct from other forms of prosocial behavior (Böckler et al., 2016), so the different personality traits might be related to different forms of prosociality.
Limitations and Future Directions
Although the results of this study showing that the Dark Triad explains prosociality above and beyond the HEXACO traits are compelling, some of the limitations need to be addressed. First, the study was conducted on a student
sample, imbalanced in gender ratio. Namely, in both parts of the study, approximately 80% of the participants were females. Although it seems that women and men are similar in engaging in prosocial behavior, there are differences in types of prosocial behavior that they engage in: women’s prosocial behaviors are more communal and relational, while men’s are more agentic and collectively oriented as well as strength intensive (see Eagly, 2009). It is possible that the relations between prosociality and basic and dark personality traits would be different depending on gender; however, due to relatively small number of male participants in our studies, we did not conduct within-gender analyses. Moreover, the sample in the second part of the study might systematically differ from the rest of the sample, as they might be generally more willing to invest time for psychological research.
As this study was a part of a larger study, we used short measures of both basic and dark personality traits, which only enabled getting a general overview of the studied variables and their relations. Namely, only some facets of Honesty-Humility are related to prosocial behavior (Hilbig, Glöckner, & Zettler, 2014), and analyzing studied relations on a facet level would certainly enhance the understanding of these relations. Furthermore, a longer measure of HEXACO (100-item version) also includes the interstitial scale altruism that divides its loadings on Honesty-Humility, Emotionality, and Agreeableness dimensions, assessing a tendency to be sympathetic and soft-hearted toward others, which would be predictive for the outcomes investigated in this research. Therefore, conducting future research with longer measures is highly recommended. Moreover, in the second part of the study, participants received a somewhat deceiving information regarding the purpose of filling in the survey again, which was intended for reflecting a more real-life situation; however, future research should avoid the use of deceptive techniques whenever possible.
Although we used two measures of prosociality (selfreport and a behavioral measure), it seems plausible that both of the measures are saturated with empathy, which is highly related to the Dark Triad (Furnham et al., 2013). However, PSB might be more saturated with empathy than our behavioral measure, as it encompasses a higher-order factor labeled as other-oriented empathy (Penner et al., 1995), and there were some differences between the two prosociality measures in their relations with the basic and dark traits: while the effect size of correlations was similar to PSB, with the behavioral measure, they were trivial for the basic traits, and small for the dark traits. Moreover, our results indicated that the prosocial behavior might be influenced by other variables than prosociality.
There are indices that the Dark Triad can be positively associated with some forms of prosocial behavior, like public prosociality, and inversely with anonymous prosociality
(Bereczkei et al., 2010; Konrath et al., 2016; White, 2014), so it would be useful to explore relationships between each of the dark traits and different forms of prosocial behavior. Furthermore, as each of the Dark Triad traits are actually multidimensional (Cain, Pincus, & Ansell, 2008; Hare & Neumann, 2005; Rauthmann & Will, 2011), the relations between specific forms of each trait and prosociality should be explored, as specific forms of each trait can be differentially related to exhibiting prosocial behavior, and specific forms can be related to exhibiting prosocial behavior under different conditions (Lannin et al., 2014). Finally, future studies could also explore some potential moderators and mediators of the relationship between personality and prosociality, like empathy (White, 2014), that were not included in this study as it was dealing primarily with the micro level of analyzing prosocial behavior (Penner et al., 2005).
Conclusion
The results of this study showed that, although it is hard to predict prosocial behavior on the basis of personality traits, the Dark Triad explained both self-reported prosocial tendencies and prosocial behavior above and beyond the HEXACO traits (with the Dark Triad being negatively linked to prosocial tendencies and prosocial behavior), emphasizing the importance of the Dark Triad in the personality space.
Electronic Supplementary Material The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/ 1614-0001/a000276
ESM 1. Table 1 (.docx) Summary of means, SDs and Pearson’s correlations among variables for the second part of the study, and PSB.
References
Aghababaeia, N., Mohammadtabara, S., & Saffariniab, M. (2014). Dirty Dozen vs. the H factor: Comparison of the Dark Triad and Honesty-Humility in prosociality, religiosity, and happiness. Personality and Individual Differences, 67, 6–10. https://doi. org/10.1016/j.paid.2014.03.026 Ashton, M. C., & Lee, K. (2007). Empirical, theoretical, and practical advantages of the HEXACO model of personality structure. Personality and Social Psychology Review, 11 , 150–166. https://doi.org/10.1177/1088868306294907 Ashton, M. C., & Lee, K. (2009). The HEXACO-60: A short measure of the major dimensions of personality. Journal of Personality Assessment, 91 , 340–345. https://doi.org/10.1080/ 00223890902935878 Babarović, T., & Šverko, I. (2013). The HEXACO personality domains in the Croatian sample. Društvena istraživanja, 22, 397–411. https://doi.org/10.5559/di.22.3.01 61
Batson, C. D. (2011). Altruism in humans. New York, NY: Oxford University Press. Batson, C. D., & Powell, A. (2003). Altruism and prosocial behavior. In T. Millon & M. Lerner (Eds.), Handbook of psychology. Personality and social psychology (Vol. 5, pp. 463–484). Hoboken, NJ: Wiley. https://doi.org/10.1002/0471264385.wei0519 Bereczkei, T., Birkas, B., & Kerekes, Z. (2010). The presence of others, prosocial traits, Machiavellianism. Social Psychology, 41 , 238–245. Bereczkei, T., & Czibor, A. (2014). Personality and situational factors differently influence high Mach and low Mach persons’ decisions in a social dilemma game. Personality and Individual Differences, 64, 168–173. https://doi.org/10.1016/j.paid.2014. 02.035 Berger, C., Batanova, M., & Cance, J. D. (2015). Aggressive and prosocial? Examining latent profiles of behavior, social status, Machiavellianism, and empathy. Journal of Youth and Adolescence, 44, 2230–2244. https://doi.org/10.1007/s10964-015- 0298-9 Berger, C., & Palacios, D. (2014). Associations between prosocial behavior, Machiavellianism, and social status: Effects of peer norms and classroom social contexts. Journal of Latino/Latin American Studies, 6, 19–30. https://doi.org/10.5555/llas.6.1. h0728270l7533862 Böckler, A., Sharifi, M., Kanske, P., Dziobek, I., & Singer, T. (2017). Social decision making in narcissism: Reduced generosity and increased retaliation are driven by alterations in perspectivetaking and anger. Personality and Individual Differences, 104, 1 –7. https://doi.org/10.1016/j.paid.2014.02.035 Böckler, A., Tusche, A., & Singer, T. (2016). The structure of human prosociality: Differentiating altruistically motivated, norm motivated, strategically motivated, and self-reported prosocial behavior. Social Psychological and Personality Science, 7, 530–541. https://doi.org/10.1177/1948550616639650 Cain, N. M., Pincus, A. L., & Ansell, E. B. (2008). Narcissism at the crossroads: Phenotypic description of pathological narcissism across clinical theory, social/personality psychology, and psychiatric diagnosis. Clinical psychology review, 28 , 638–656. https://doi.org/10.1016/j.cpr.2007.09.006 Curry, O., Chesters, M. J., & Viding, E. (2011). The psychopath’s dilemma: The effects of psychopathic personality traits in oneshot games. Personality and Individual Differences, 50, 804–809. https://doi.org/10.1016/j.paid.2010.12.036 Eagly, A. H. (2009). The his and hers of prosocial behavior: an examination of the social psychology of gender. American Psychologist, 64, 644–658. https://doi.org/10.1037/0003- 066X.64.8.644 Eberly-Lewis, M. B., & Coetzee, T. M. (2015). Dimensionality in adolescent prosocial tendencies: Individual differences in serving others versus serving the self. Personality and Individual Differences, 82, 1 –6. https://doi.org/10.1016/j.paid.2015. 02.032 Furnham, A., Richards, S. R., & Paulhus, D. L. (2013). The Dark Triad of personality: A 10-year review. Social and Personality Psychology Compass, 7, 199–216. https://doi.org/10.1111/ spc3.12018 Graziano, W. G., & Habashi, M. M. (2015). Searching for the prosocial personality. In D. A. Schroeder & W. G. Graziano (Eds.), The Oxford handbook of prosocial behavior (pp. 231 –255). Oxford, UK: Oxford University Press. https://doi.org/ 10.1093/oxfordhb/9780195399813.013.017 Gunnthorsdottir, A., McCabe, K., & Smith, V. (2002). Using the Machiavellianism instrument to predict trustworthiness in a bargaining game. Journal of Economic Psychology, 23, 49–66. https://doi.org/10.1016/S0167-4870(01)00067-8
Hare, R. D., & Neumann, C. S. (2005). Structural models of psychopathy. Current psychiatry reports, 7, 57–64. https://doi. org/10.1007/s11920-005-0026-3 Hawley, P. H. (2003). Strategies of control, aggression, and morality in preschoolers: An evolutionary perspective. Journal of Experimental Child Psychology, 85, 213–235. https://doi.org/ 10.1016/S0022-0965(03)00073-0 Hawley, P. H. (2006). Evolution and personality: A new look at Machiavellianism. In D. Mroczek & T. Little (Eds.), Handbook of personality development (pp. 147–161). Mahwah, NJ: Erlbaum https://doi.org/10.4324/9781315805610.ch8 Hilbig, B. E., Glöckner, A., & Zettler, I. (2014). Personality and prosocial behavior: Linking basic traits and social value orientations. Journal of Personality and Social Psychology, 107, 529–539. https://doi.org/10.1037/a0036074 Hilbig, B. E., Zettler, I., Leist, F., & Heydasch, T. (2013). It takes two: Honesty-Humility and Agreeableness differentially predict active versus reactive cooperation. Personality and Individual Differences, 54, 598–603. https://doi.org/10.1016/j.paid.2012. 11.008 Hubbard, J., Harbaugh, W. T., Srivastava, S., Degras, D., & Mayr, U. (2016). A general benevolence dimension that links neural, psychological, economic, and life-span data on altruistic tendencies. Journal of Experimental Psychology: General, 145, 1351 –1358. https://doi.org/10.1037/xge0000209 Jonason, P. K., Li, N. P., Webster, G. W., & Schmitt, D. P. (2009). The Dark Triad: Facilitating short-term mating in men. European Journal of Personality, 23, 5–18. https://doi.org/10.1002/ per.698 Jones, D. N., & Paulhus, D. L. (2011). Differentiating the Dark Triad within the interpersonal circumplex. In L. M. Horowitz & S. Starck (Eds.), Handbook of interpersonal psychology: Theory, research, assessment, and therapeutic interventions (pp. 249–269). New York, NY: Wiley. https://doi.org/10.1002/ 9781118001868.ch15 Jones, D. N., & Paulhus, D. L. (2014). Introducing the Short Dark Triad (SD3): A brief measure of dark personalities. Journal of Research in Personality, 21 , 28–41. https://doi.org/10.1177/ 1073191113514105 Kauten, R. L., & Barry, C. T. (2016). Adolescent narcissism and its association with different indices of prosocial behavior. Journal of Research in Personality, 6, 36–45. https://doi.org/10.1016/j. jrp.2015.11.004 Konrath, S., Ho, M. H., & Zarins, S. (2016). The strategic helper: Narcissism and prosocial motives and behaviors. Current Psychology, 35, 182–194. https://doi.org/10.1007/s12144- 016-9417-3 Lannin, D. G., Guyll, M., Krizan, Z., Madon, S., & Cornish, M. (2014). When are grandiose and vulnerable narcissists least helpful? Personality and Individual Differences, 56, 127–132. https://doi. org/10.1016/j.paid.2013.08.035 Lee, K., Ashton, M. C., Wiltshire, J., Bourdage, J. S., Visser, B. A., & Gallucci, A. (2013). Sex, power, and money: Prediction from the Dark Triad and Honesty-Humility. European Journal of Personality, 27, 169 –184. https://doi.org/10.1002/per.1860 McGinley, M., & Carlo, G. (2006). Two sides of the same coin? The relations between prosocial and physically aggressive behaviors. Journal of Youth and Adolescence, 36, 337–349. https:// doi.org/10.1007/s10964-006-9095-9 Penner, L. A., Dovidio, J. F., Piliavin, J. A., & Schroeder, D. A. (2005). Prosocial behavior: Multilevel perspectives. Annual Review of Psychology, 56, 365–392. https://doi.org/10.1146/ annurev.psych.56.091103.070141 Penner, L. A., Fritzsche, B. A., Craiger, J. P., & Freifeld, T. R. (1995). Measuring the prosocial personality. In J. Butcher & C. D. Spielberger (Eds.), Advances in personality assessment (Vol. 10, pp. 147–163). Hillsdale, NJ: Erlbaum. Rauthmann, J. F., & Kolar, G. P. (2012). How “dark” are the Dark Triad traits? Examining the perceived darkness of narcissism, Machiavellianism, and psychopathy. Personality and Individual Differences, 53, 884–889. https://doi.org/10.1016/j.paid.2012. 06.020 Rauthmann, J. F., & Will, T. (2011). Proposing a multidimensional Machiavellianism conceptualization. Social Behavior and Personality: An International Journal, 39, 391 –403. https://doi.org/ 10.2224/sbp.2011.39.3.391 Twenge, J. M., & Foster, J. D. (2010). Birth cohort increases in narcissistic personality traits among American college students, 1982–2009. Social Psychological and Personality Science, 1 , 99–106. https://doi.org/10.1177/1948550609355719 Twenge, J. M., Gentile, B., DeWall, C. N., Ma, D. S., Lacefield, K., & Schurtz, D. R. (2010). Birth cohort increases in psychopathology among young Americans, 1938–2007: A cross-temporal metaanalysis of the MMPI. Clinical Psychology Review, 3, 145–154. https://doi.org/10.1016/j.cpr.2009.10.005 Wertag, A., Vrselja, I., & Tomić, T. (2011, October). Assessing Construct Validity of Paulhus’s and Williams’s (2002) Dark Triad Questionnaire D3–27 [Provjera konstruktne valjanosti Paulhusovog i Williamsovog (2002) upitnika Mračne trijade D3–27]. Poster presentation at 19th Annual Conference of Croatian Psychologists, Osijek, Croatia. White, B. A. (2014). Who cares when nobody is watching? Psychopathic traits and empathy in prosocial behaviors. Personality and Individual Differences, 56, 116–121. https://doi. org/10.1016/j.paid.2013.08.033 Zhao, K., & Smillie, L. D. (2015). The role of interpersonal traits in social decision making: Exploring sources of behavioral heterogeneity in economic games. Personality and Social Psychology Review, 19, 277–302. https://doi.org/10.1177/ 1088868314553709 Zuo, S., Wang, F., Xu, Y., Wang, F., & Zhao, X. (2016). The fragile but bright facet in the Dark Gem: Narcissism positively predicts personal morality when individual’s self-esteem is at low level. Personality and Individual Differences, 97, 272–276. https://doi. org/10.1016/j.paid.2016.03.076
Received July 4, 2017 Revision received March 21, 2018 Accepted March 29, 2018 Published online November 26, 2018
Anja Wertag Institute of Social Sciences Ivo Pilar Marulićev trg 19 10000 Zagreb Croatia anja.wertag@pilar.hr
The Journal of Individual Differences publishes manuscripts dealing with individual differences in behavior, emotion, cognition, and their developmental aspects. This includes human as well as animal research. The Journal of Individual Differences is conceptualized to bring together researchers working in different areas ranging from, for example, molecular genetics to theories of complex behavior. Moreover, it places emphasis on papers dealing with special methodological and conceptual issues in basic science as well as in their applied fields (assessment of personality and intelligence).
Journal of Individual Differences publishes the following types of articles: Regular Research Articles, Extended Research Articles, Meta-Analyses, and Reviews.
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August 2016
Assessment and treatment of Internet addiction
Hilarie Cash, PhD, Chief Clinical Officer and Co-Founder of reSTART Life, PLLC, Fall City, WA – the first residential treatment program for Internet addiction in the US
Daria J. Kuss /Halley M. Pontes Internet Addiction
(Series: Advances in Psychotherapy –Evidence-Based Practice – Volume 41) 2019, iv + 86 pp. US $29.80 /€ 24.95 ISBN 978-0-88937-501-7 Also available as eBook
This book examines how you can identify, assess, and treat Internet addiction in the most effective manner. Internet use has become an integral part of our daily lives, but at what point does it become problematic? What are the different kinds of Internet addiction? And how can professionals best help clients? This compact, evidence-based guide written by leading experts from the field helps disentangle the debates and controversies around Internet addiction, including social media addiction and Internet gaming disorder, and outlines the current assessment and treatment methods. The book presents a 12–15 session treatment plan for Internet and gaming addiction using the method and setting with the best evidence: group CBT. Printable tools in the appendix help clinicians implement therapy. This accessible book is essential reading for clinical psychologists, psychiatrists, psychotherapists, counsellors, social workers, teachers, as well as students.
Cultural diversity – challenge and opportunity
Bruna Zani, Professor of Social and Community Psychology, Department of Psychology, Alma Mater Studiorum-University of Bologna, Bologna, Italy; EFPA Executive Council Member
Alexander Thomas (Editor) Cultural and Ethnic Diversity How European Psychologists Can Meet the Challenges
2018, x + 222 pp. US $56.00 /€ 44.95 ISBN 978-0-88937-490-4 Also available as eBook
Culture and diversity are both challenge and opportunity. This volume looks at what psychologists are and can be doing to help society meet the challenges and grasp the opportunities in education, at work, and in clinical practice. The increasingly international and globalized nature of modern societies means that psychologists in particular face new challenges and have new opportunities in all areas of practice and research.
The contributions from leading European experts cover relevant intercultural issues and topics in areas as diverse as personality, education and training, work and organizational psychology, clinical and counselling psychlogy, migration and international youth exchanges.
As well as looking at the new challenges and opportunities that psychologists face in dealing with people from increasingly varied cultural backgrounds, perhaps more importantly they also explain and discuss how psychologists can deepen and acquire the intercultural competencies that are now needed in our professional lives.
How to provide culturally sensitive care for clients with PTSD and related disorders
Andrew G. Ryder, PhD, Associate Professor of Psychology, Concordia University, Montreal, QC, Canada
Andreas Maercker/Eva Heim /Laurence J. Kirmayer (Editors) Cultural Clinical Psychology and PTSD
2019, x + 236 pp. US $62.00 /€ 49.95 ISBN 978-0-88937-497-3 Also available as eBook
This book, written and edited by leading experts from around the world, looks critically at how culture impacts on the way posttraumatic stress disorder (PTSD) and related disorders are diagnosed and treated. There have been important advances in clinical treatment and research on PTSD, partly as a result of researchers and clinicians increasingly taking into account how “culture matters.”
For mental health professionals who strive to respond to the needs of people from diverse cultures who have experienced traumatic events, this book is invaluable. It presents recent research and and practical approaches on key topics, including: • How culture shapes mental health and recovery • How to integrate culture and context into PTSD theory • How trauma-related distress is experienced and expressed in different cultures, reflecting local values, idioms, and metaphors • How to integrate cultural dimensions into psychological interventions
Providing new theoretical insights as well as practical advice, it will be of interest to clinical psychologists, psychiatrists, and other health professionals, as well as researchers and students engaged with mental health issues, both globally and locally.
