Journal of Individual Differences

Volume 40 / Number 1 / 2019

Journal of

Individual Differences Editor-in-Chief Martin Voracek Associate Editors André Beauducel Sam Gosling Jürgen Hennig Philipp Y. Herzberg Karl-Heinz Renner Willibald Ruch Astrid Schütz Andrzej Sekowski Jutta Stahl

The best ways to support the healthy development of children and adolescents and their families Kristin S. Mathiesen / Ann V. Sanson / Evalill B. Karevold (Editors)

Tracking Opportunities and Problems from Infancy to Adulthood 20 Years With the TOPP Study 2018, x + 272 pp.

US $49.80 / € 39.95 ISBN 978-0-88937-543-7 Also available as eBook The unique longitudinal study “Tracking Opportunities and Problems (TOPP)” began following nearly 1,000 children and their families in Norway in 1993. Few studies have ever accumulated such extensive information from such a large number of families.

Eight waves of data on many aspects of child and family life have been collected from children aged 18 months to 18 years. The TOPP Study has provided new knowledge about and insight into the precursors, developmental paths and predictors of both good adaptation and mental health problems of children, as well as into parenting and family relationships.

The editors have collated the key findings in three parts. Part 1 addressesthe mental health and development of children and adolescents. Part 2 focuses on parents, looking at individual

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parental and family-related factors, including parental couple relationships. Part 3 looks at methodological issues, including the sample, response rate and measurement and analytical approaches. Each chapter reviews the existing knowledge in these areas in relation to the TOPP findings and provides extensive reference lists for those who want to dig deeper.

This unique book provides thoughtprovoking insights into the TOPP findings to help guide therapeutic practice, to suggest new avenues of research, to inform teaching, and to shape policy planning and preventive actions. It is thus an invaluable resource for all professionals, researchers, educators, policy makers, and students working with children and adolescents and their families.

Journal of

Individual Differences Volume 40/Number 1/2019

Editor-in-Chief

Prof. Martin Voracek, Department of Basic Psychological Research and Research Methods, University of Vienna, Liebiggasse 5, 1010 Vienna, Austria

Associate Editors

André Beauducel, Germany Sam Gosling, USA Jürgen Hennig, Germany Philipp Y. Herzberg, Germany Karl-Heinz Renner, Germany

Willibald Ruch, Switzerland Astrid Schütz, Germany Andrzej Sekowski, Poland Jutta Stahl, Germany

Editorial Board

Philipp L. Ackerman, USA José Bermudez, Spain Peter Borkenau, Germany John Brebner, Australia Burkhard Brocke, Germany Ian Deary, UK Richard Depue, USA Richard Ebstein, Israel Aiden P. Gregg, UK Hartmut Häcker, Germany Willem B. Hofstee, The Netherlands Klaus Kubinger, Austria

Bernd Marcus, Germany Robert R. McCrae, USA Carolyn C. Morf, Switzerland Pierre Mormede, France Kurt Pawlik, Germany Robert Plomin, UK Rainer Riemann, Germany Kurt Stapf, Germany Bob Stelmack, Canada Gerhard Stemmler, Germany Jan Strelau, Poland

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Journal of Individual Differences (2019), 40(1)

Ó 2019 Hogrefe Publishing

Contents Original Articles

Ó 2019 Hogrefe Publishing

Open to Diversity: Openness to Experience Predicts Beliefs in Multiculturalism and Colorblindness Through Perspective Taking David J. Sparkman, Scott Eidelman, Aubrey R. Dueweke, Mikenna S. Marin, and Belkis Dominguez

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Variation in Personality States as Predicted by Interpersonal Context Jamie S. Churchyard, Karen J. Pine, Shivani Sharma, and Ben (C) Fletcher

13

Sandbagging and the Self: Does Narcissism Explain the Relationship Between Sandbagging and Self-Esteem?

Michael D. Barnett, Idalia V. Maciel, and Marley A. King

20

The Motivation for Facebook Use – Is it a Matter of Bonding or Control Over Others? Evidence From a Cross-Cultural Study Rayna Sariyska, Bernd Lachmann, Cecilia Cheng, Augusto Gnisci, Ida Sergi, Antonio Pace, Katarzyna Kaliszewska-Czeremska, Stéphanie Laconi, Songfa Zhong, Demet Toraman, Mattis Geiger, and Christian Montag

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Pursuing the Dark Triad: Psychometric properties of the Spanish Version of the Dirty Dozen Lorena Maneiro, Laura López-Romero, José Antonio Gómez-Fraguela, Olalla Cutrı́n, and Estrella Romero

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Time Perspective, Awareness of Narrative Identity, and the Perceived Coherence of Past Experiences Among Adults David John Hallford, Nicholas J. Fava, and David Mellor

45

In Search of the Prosocial Personality: Personality Traits as Predictors of Prosociality and Prosocial Behavior Anja Wertag and Denis Bratko

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Journal of Individual Differences (2019), 40(1)

Original Article

Open to Diversity Openness to Experience Predicts Beliefs in Multiculturalism and Colorblindness Through Perspective Taking David J. Sparkman, Scott Eidelman, Aubrey R. Dueweke, Mikenna S. Marin, and Belkis Dominguez Department of Psychological Science, University of Arkansas, Fayetteville, AR, USA

Abstract: The present research examines the influence of personality on ideologies about diversity in society. In two studies (N = 668), we test whether Openness to Experience predicts beliefs in multiculturalism and colorblindness, and whether these relationships are mediated by perspective-taking tendencies. In Study 1, Openness positively predicted multiculturalism but negatively predicted colorblindness through ethnic perspective taking – findings that were independent of empathy, age, gender, and race/ethnicity. In Study 2, we attempted to replicate and extend our findings by using different measures of multiculturalism and colorblindness and a more general, interpersonal operationalization of perspective taking. Results indicate Openness positively predicted both multiculturalism and colorblindness through interpersonal perspective taking (also independent of age, gender, and race/ethnicity), suggesting the pattern of findings varied as a function of perspective-taking type. Implications for the complexity of the Openness dimension and future research directions are discussed.

Keywords: Openness to Experience, perspective taking, multiculturalism, colorblindness, diversity ideologies

In the decades since the construction and validation of the Openness to Experience personality dimension, we have learned much about the influence of Openness on aesthetic and social experiences, including an appreciation for art, music, and mystery, varied interpersonal interactions, liberal and progressive values, and tolerant, non-prejudiced attitudes (McCrae, 1996; McCrae & Costa, 1997). But in a review of Openness and its social correlates, McCrae and Sutin (2009) called for more research into the association between Openness and prejudice, saying, “social psychologists have overlooked one of the key determinants in one of their most studied phenomena” (p. 266). In the years since, research has shown a reliable and negative relationship between Openness and prejudice across a range of racial, ethnic, and sexual minority groups (for meta-analytic evidence, see Sibley & Duckitt, 2008; cf. Brandt, Chambers, Crawford, Wetherell, & Reyna, 2015). Though such research has expanded our understanding of the relationship between Openness and prejudiced attitudes, we know comparatively little about whether and how Openness influences one’s perception or recognition of the racial, ethnic, or cultural group membership of others. Do those high in Openness believe in recognizing and appreciating the diverse group membership of others (multiculturalism), or ignoring and minimizing it for the sake of commonality (colorblindness)? This was the aim of the present work. Ó 2018 Hogrefe Publishing

We test whether Openness predicts multiculturalism or colorblindness (or both), and examine whether these associations are mediated by individual differences in perspective taking.

Openness to Experience and Diversity Ideologies Openness is conceptualized as an intrapsychic personality dimension describing individuals who are creative, imaginative, insatiably curious, unconventional, and broadminded (Costa & McCrae, 1992; McCrae, 1996). Historically, Openness was thought to represent a factor initially termed Culture (Norman, 1963; Tupes & Christal, 1961/1992), although not in the typical sense of the word. In fact, the Culture factor of openness largely meant cultured, or being sophisticated, intellectual, liberal in thought or education, and critical of accepted norms and values (McCrae & Costa, 1997; Sparkman, in press). Despite this overlap between Openness to Experience and being cultured (e.g., see Xu, Mar, & Peterson, 2013), there are also clear links between the Openness dimension and aspects of Culture. In the present work, we reinvestigate these links.

Multiculturalism is a diversity ideology reflecting beliefs about how to achieve harmonious intergroup relations in Journal of Individual Differences (2019), 40(1), 1–12 https://doi.org/10.1027/1614-0001/a000270

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society. Supporters of multiculturalism believe in recognizing and appreciating the specific racial, ethnic, or cultural identity of individuals, and argue the distinct experiences and contributions of ethnocultural groups should be maintained and celebrated (for a review, see Plaut, 2010).

Demonstrating a possible link between Openness to Experience and beliefs in multiculturalism, some researchers suggest one dimension of a “Multicultural Personality” is openness. While conceptually distinct from the Openness to Experience dimension, researchers conceptualized openness as an open, non-prejudiced orientation toward outgroups and those from different cultures (van der Zee & van Oudenhoven, 2000), drawing some similarity to a multicultural ideology. Other research suggests Openness to Experience positively predicts multicultural acquisition, a broad construct capturing (in part) one’s recognition of the importance of cultural diversity (Chen et al., 2016).

However, Chen and colleagues (2016) also included a more direct measure of multicultural ideology in their research, but reported a non-significant (albeit positive) relationship with Openness. Thus, previous research hints at a relationship between Openness and multiculturalism, but more research is needed.

Colorblindness, another widely held diversity ideology (particularly in the United States; e.g., see Plaut, 2002), suggests the best way to achieve harmonious intergroup relations is by ignoring or otherwise minimizing racial, ethnic, or cultural group differences (Plaut, 2010). Suggesting a possible link between Openness and colorblindness, McFarland, Webb, and Brown (2012) show Openness to Experience positively predicts identifying with “all of humanity” – an allencompassing human category that makes no distinction based on race, ethnicity, or culture. Researchers have broadly conceptualized multiculturalism and colorblindness as somewhat contrasting ideologies, the former focusing on diversity and intergroup differences (distinct groups exist and should be recognized) and the latter on interpersonal or intergroup similarities (all people are the same; Neville, Awad, Brooks, Flores, & Bluemel, 2013; Plaut, 2002, 2010; Rosenthal & Levy, 2010; cf. Park & Judd, 2005).

Recognition of similarities and differences may be an important distinction for Openness, but operationalizations of constructs in the literature have made this somewhat difficult to examine. For instance, Openness to Experience is positively correlated with a universal-diverse orientation (UDO), capturing one’s awareness of and appreciation for the similarities and differences among people, groups, and cultures (Thompson, Brossart, Carlozzi, & Miville, 2002; also see Miville et al., 1999). But UDO conflates similarities and differences together, making it difficult to determine which aspect – similarities, differences, or both – is uniquely related to Openness. Below, we discuss research on an intervening variable – perspective taking – that links together and Journal of Individual Differences (2019), 40(1), 1–12

D. J. Sparkman et al., Openness and Diversity Ideologies

has the potential to provide greater clarity on the relationship between Openness to Experience and diversity ideologies. In doing so, we gain a more nuanced understanding of whether (and how) Openness to Experience predicts beliefs in recognizing the intergroup differences embedded in multiculturalism, the overarching similarities inherent to colorblindness, or both.

Openness to Experience, Perspective Taking, and Diversity Ideologies Curious and cognitively reflective, open individuals are motivated to seek out – rather than avoid – alternative viewpoints and perspectives (McCrae & Costa, 1997; McCrae & Sutin, 2009). Indeed, Openness to Experience correlates positively with various forms of perspective taking, including cultural and interpersonal perspective taking (Sparkman & Blanchar, 2017). Research has also shown that, while distinct, perspective taking and multiculturalism share a reciprocal relationship. Not only does priming multiculturalism lead people to spontaneously take the perspective of racial outgroups, but taking the perspective of a racial outgroup member also increases endorsement of multiculturalism (Todd & Galinsky, 2012). This is perhaps because actively considering the perspective of those from other ethnocultural backgrounds highlights the importance and value of group identities to many minorities. If Openness influences tendencies to take the perspective of those from other ethnocultural backgrounds, this greater awareness of the psychological perspective of ethnocultural minorities, in turn, should be associated with stronger endorsement of multiculturalism, an ideology espousing the importance of recognizing and appreciating the diverse group memberships of others. At the same time, if Openness to Experience influences the desire to take others’ perspectives more generally – regardless of racial or ethnic background – doing so may highlight perceptions of interconnectedness and similarity (e.g., Davis, Conklin, Smith, & Luce, 1996) and, in turn, belief in the colorblind ideal that “we are all the same.” Each conceptual model has merit and may vary as a function of perspective-taking type. We test both in the present work.

Overview of the Current Research In two studies, we investigate the influence of Openness to Experience on diversity ideologies (multiculturalism, colorblindness), and examine whether this relationship is mediated by perspective-taking tendencies. We hypothesize that Openness will positively predict multiculturalism and colorblindness through greater perspective taking, but also Ó 2018 Hogrefe Publishing

D. J. Sparkman et al., Openness and Diversity Ideologies

consider the possibility that these relationships may depend upon the particular operationalization of perspective taking.

Study 1 tests whether Openness predicts beliefs in multiculturalism and colorblindness, and whether these relationships are mediated by tendencies to take the perspective of racial/ethnic outgroups. To account for possible alternative explanations, we control for age, gender, race/ethnicity, and a more affective form of perspective taking: empathy. In Study 2, we attempt to replicate and extend our findings. We use different measures of multiculturalism and colorblindness to assess the generalizability of our findings, and also broaden our operationalization of perspective taking to reflect a more general form of interpersonal perspective taking. Across studies, data are analyzed using a structural equation modeling (SEM) framework.

Study 1 Method Participants and Procedure Two hundred ninety-six undergraduates at the University of Arkansas completed an online study about public opinion and social perception in exchange for partial fulfillment of a course requirement. We excluded from the sample 27 participants who failed at least one of two attention checks (e.g., “This is an attention check item. Please select ‘slightly disagree’ for this answer.”), three participants who provided a response 3 SD from the mean on empathy, two participants with missing data, and one participant who identified as transgender and could not be used as a comparison group in subsequent analyses. This left a final sample of 263 participants for analyses (race/ethnicity: 85% White, 4% Black/African-American, 5% Hispanic/Latino, 3% Asian, 3% Other; gender: 69% female; age: M = 20.08 years, SD = 4.66). After providing informed consent, participants completed a series of measures presented in random order, followed by a demographics page. At the conclusion of the survey, participants were thanked and awarded credit.

Measures Measures of Openness to Experience, ethnic perspective taking, multiculturalism, colorblindness, empathy, and demographics were collected. Other variables unrelated to the current study were also collected (for additional details, see Sparkman & Eidelman, 2016) but not included in analyses.

Openness to Experience Openness was measured using items from the Big-Five Inventory (taken from John & Srivastava, 1999). Example Ó 2018 Hogrefe Publishing

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items include, “I see myself as someone who. . . is inventive,” “. . . has an active imagination,” and “. . . has few artistic interests” [reverse-scored]. All items were answered on a 1 (= not at all like me) to 5 (= just like me) scale, and averaging together all items created a reliable index of Openness to Experience (α = .82).

Ethnic Perspective Taking We modified Davis’ (1983) perspective-taking subscale of the Interpersonal Reactivity Index (IRI) to reflect cognitive tendencies to take the perspective of other races/ethnicities (Sparkman & Eidelman, 2016). In our modifications, we replaced general, interpersonal statements (e.g., “I sometimes find it difficult to see things from the ‘other guy’s’ point of view”) with statements including race/ethnicity (e.g., “I sometimes find it difficult to see things from the perspective of people from other racial/ethnic backgrounds” [reverse-scored]; for all items, see Electronic Supplementary Material, ESM 1). Each item was answered on a 1 (= not at all like me) to 5 (= very much like me) scale, and averaging together all modified items created a reliable index of ethnic perspective taking (α = .81).

Diversity Ideologies We adapted three items from previous research (Ryan, Hunt, Weible, Peterson, & Casas, 2007) measuring multicultural beliefs in recognizing and appreciating ethnic group differences in society (“I would say I take a multicultural perspective in life,” “People should recognize the ethnic group differences of others and be more sensitive to group differences,” and “People should recognize and appreciate the ethnic diversity in our country”). We also adapted three items from Ryan and colleagues (2007) measuring colorblind beliefs in ignoring or minimizing ethnic group differences (“It is important that people begin to think of themselves as an American and not African-American, Mexican-American, or Arab-American,” “People should ignore the ethnic group memberships of others and treat everyone as an individual,” and “I would say I take a colorblind perspective in life”). All items were answered using the same 1 (= strongly disagree) to 7 (= strongly agree) scale, and averaging together items created a reliable index of multiculturalism (α = .75) but not colorblindness (α = .55).

Multiculturalism and colorblindness were negatively correlated, r = .17, p < .01.

Covariates Participants completed demographics (age, gender, race/ ethnicity) along with a measure of empathy. Empathy was measured using the original items of Davis’ (1983) empathy subscale of the IRI (e.g., “I often have tender, concerned feelings for people less fortunate than me,” “I would describe myself as a pretty soft-hearted person,” and Journal of Individual Differences (2019), 40(1), 1–12

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D. J. Sparkman et al., Openness and Diversity Ideologies

Table 1. Descriptive statistics and bivariate correlations among variables in Study 1 Variable

M (SD)

1

1. Openness to Experience

3.45 (0.59)

–

2. Ethnic perspective taking

3.51 (0.65)

.30***

3. Multiculturalism

5.35 (1.11)

.18**

4. Colorblindness

4.93 (1.24)

.06

5. Empathy

3.89 (0.58)

.14*

2

3

4

– .54*** .10 .40***

– .17** .30***

– .02

Notes. Empathy was a covariate in the present study. All variables depicted are in total aggregate form. ***p < .001, **p < .01, *p < .05 (all two-tailed).

“Other people’s misfortunes do not usually disturb me a great deal” [reverse-scored]). Items were answered on the same 1–5 scale as ethnic perspective taking, and averaging together all items created a reliable index of empathy (α = .80).

Results Descriptive statistics and bivariate correlations are shown in Table 1. Openness to Experience was positively correlated with ethnic perspective taking and multiculturalism, but uncorrelated with colorblindness. Ethnic perspective taking was strongly and positively correlated with multiculturalism, but negatively (albeit nonsignificantly) correlated with colorblindness.

Structural Equation Modeling Given the low internal consistency of the colorblindness items, we decided to analyze our model using latent factors in an SEM framework because it takes measurement error (e.g., low reliability) into account (e.g., John & Benet-Martínez, 2000; Kline, 2005). Using AMOS 20 software, we represented Openness as a manifest variable1 and our adapted measures of ethnic perspective taking, multiculturalism, and colorblindness as latent factors (each with 7, 3, and 3 indicators, respectively). In line with the recommendations of Tabachnick & Fidell (2013), the goodness-of-fit of the model was assessed using the chi-square test (w2/df ratio of less than 2), comparative fit index (CFI; greater than or equal to .95), and root mean square error of approximation (RMSEA; less than or equal to .06). The proposed measurement model indicated an unacceptable fit to the data, w2/df = 140.27/72 = 1.95, p < .001, CFI = .94, RMSEA = .06.

To improve model fit, we removed one indicator from the 1

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latent factor of ethnic perspective taking (“I sometimes find it difficult to see things from the perspective of people from other racial/ethnic backgrounds”) because it did not load adequately on the factor (β = .26, R2 = .07) relative to other indicators. This modification to the measurement model yielded an acceptable fit to the data, w2/df = 109.20/ 60 = 1.82, p < .001, CFI = .96, RMSEA = .06.

To construct the structural model, we drew direct paths from Openness to ethnic perspective taking, multiculturalism, and colorblindness, and from ethnic perspective taking to multiculturalism and colorblindness. As our exogenous covariates, we drew direct paths from age, gender (0 = male, 1 = female), race/ethnicity (0 = ethnic majority/White, 1 = ethnic minority/non-White), and empathy to endogenous variables of ethnic perspective taking, multiculturalism, and colorblindness. We covaried all exogenous variables and also covaried the error terms of multiculturalism and colorblindness (to reflect their similar scale development and measurement). The proposed structural model indicated an acceptable fit to the data, w2/df = 158.63/ 96 = 1.65, p < .001, CFI = .95, RMSEA = .05. Given there were non-significant effects of age on all endogenous variables, gender on ethnic perspective taking, race/ethnicity on ethnic perspective taking and colorblindness, and empathy on multiculturalism, we iteratively2 deleted these nonsignificant variables and paths for greater model simplicity.

The parsimonious structural model (see Figure 1) indicated an acceptable fit to the data, w2/df = 152.90/91 = 1.68, p < .001, CFI = .95, RMSEA = .05, and was used in subsequent analyses.

Mediation As shown in Figure 1, Openness to Experience uniquely and positively predicted multiculturalism (total effect: β = .20, p = .01), but not colorblindness (total effect: β = .01,

We chose to represent Openness as a manifest, or total aggregate (Bagozzi & Heatherton, 1994), variable given our conceptualization of the scale as a direct, unifying measure of the Openness construct without measurement error. When all items of the Openness to Experience scale were used as single indicators of a latent factor, the Openness factor contributed negatively to the overall fit of the measurement model, w2/df = 527.78/224 = 2.36, p < .001, CFI = .85, RMSEA = .07.

We use the term “iteratively” to indicate our deletion of nonsignificant paths (and variables, if appropriate) occurred one at a time. To do so, we deleted whichever estimated path coefficient had a value closest to zero. After a single deletion, we reassessed the path coefficients and deleted the next path with a value closest to zero. This process continued until all estimated paths were at marginal or conventional levels of significance. In taking this approach, model fit did not differ from a structural model in which all variables and paths were retained.

Journal of Individual Differences (2019), 40(1), 1–12

Ó 2018 Hogrefe Publishing

D. J. Sparkman et al., Openness and Diversity Ideologies

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Figure 1. Structural equation model depicting the indirect effects of Openness to Experience on multiculturalism and colorblindness through ethnic perspective taking, controlling for age, gender (0 = male, 1 = female), race/ ethnicity (0 = ethnic majority/White, 1 = ethnic minority/non-White), and empathy. Dashed lines represent the removal of a variable or path in subsequent analyses. Coefficients are standardized and total effects are listed in parentheses. Model fit: w2/df = 152.90/91 = 1.68, p < .001, CFI = .95, RMSEA = .05. ***p < .001, **p < .01, *p < .05, yp < .10 (all twotailed).

p = .86). Openness uniquely and positively predicted ethnic perspective taking (β = .24, p < .001), and ethnic perspective taking uniquely and positively predicted multiculturalism (β = .61, p < .001), but negatively predicted colorblindness (β = .21, p = .03). To examine whether Openness predicted multiculturalism and colorblindness through ethnic perspective taking (after controlling for gender, race/ethnicity, and empathy), we tested for evidence of mediation using 95% bias-corrected confidence intervals based on 5,000 bootstrap samples. Results suggest the indirect effect of Openness on multiculturalism through ethnic perspective taking was positive and significant, β = .14, SE = 0.04, 95% CI [0.07, 0.23], p < .001; whereas the indirect effect of Openness on colorblindness through ethnic perspective taking was negative and significant, β = .05, SE = 0.03, 95% CI [ 0.12, 0.01], p = .01 (see Figure 1). When accounting for the indirect effect of ethnic perspective taking, the direct effect of Openness on multiculturalism was reduced to non-significance, suggesting full mediation, β = .06, SE = 0.07, 95% CI [ 0.08, 0.20], p = .43. However, because there was no significant total effect of Openness on colorblindness, β = 0.01, SE = 0.09, 95% CI [ 0.17, 0.16], p = .86, accounting for the indirect effect of ethnic perspective taking did not change the interpretation of the direct effect, which remained non-significant, β = .04, SE = 0.09, 95% CI [ 0.12, 0.22], p = .69. Thus, the only significant influence of Openness on colorblindness was negative and carried indirectly through ethnic perspective taking.

Discussion Results of Study 1 provide evidence to confirm Openness to Experience and multiculturalism are positively related, Ó 2018 Hogrefe Publishing

though conclusions to be drawn about colorblindness are different and potentially less clear. Regarding the former finding, the positive association between Openness and multiculturalism persisted after controlling for other variables (most notably empathy, a more affective form of perspective taking), and results further suggested Openness independently predicted beliefs in multiculturalism through greater ethnic perspective taking. A potential limitation of the present finding, however, is the strong correlation between ethnic perspective taking and multiculturalism (r = .53). With such highly overlapping constructs, it is no surprise ethnic perspective taking mediates the relationship between Openness and multiculturalism (see Fiedler, Schott, & Meiser, 2011). In Study 2, we address this limitation and investigate whether the link between Openness and multiculturalism is mediated through a more general perspective-taking process.

The pattern of findings related to colorblindness differed from those of multiculturalism. Openness independently and negatively predicted beliefs in colorblindness, but only through ethnic perspective taking. This result appears to be, in part, because ethnic perspective taking negatively predicted colorblindness, suggesting the more individuals take the perspective of those from other racial/ethnic backgrounds, the less likely they are to believe colorblindness is a viable option for a diverse society. To be clear, however, Openness did not significantly predict colorblindness in its own right. It is a common assumption that, in order to establish evidence of mediation, an independent variable must directly impact an outcome variable. Recently, however, researchers and statisticians have demonstrated that an independent variable need not have a direct impact on the outcome variable to establish mediation (see Hayes, 2013).

In line with this thinking, results suggest Openness had no direct impact on colorblindness, but did negatively impact Journal of Individual Differences (2019), 40(1), 1–12

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colorblindness indirectly through ethnic perspective taking.

Thus, those high in Openness were more likely to report taking the perspective of racial/ethnic outgroups, and this ethnic perspective taking, in turn, was associated with greater disagreement with colorblindness. To provide more clarity on this pattern of findings, we reinvestigate the link between Openness and colorblindness in our next study.

Study 2 In Study 2, we attempted to replicate and extend our findings while improving upon an operational limitation of Study 1.

First, we included different measures of multiculturalism and colorblindness (each from the same validated scale; Hahn, Banchefsky, Park, & Judd, 2015) to assess the generalizability of our findings. Second, we operationalized perspective taking more generally – as interpersonal perspective taking – to examine whether Openness only predicts multiculturalism through a specific perspective-taking process (toward those from other races/ethnicities) or a more general perspective-taking process as well. The inclusion of interpersonal perspective taking also allowed us to examine whether the pattern of findings would differ for beliefs in colorblindness. As in Study 1, we controlled for demographic variables, but did not include a measure of empathy. Together, these additions test whether Openness uniquely predicts multiculturalism and colorblindness through more general, interpersonal perspective-taking tendencies.

Method Participants and Procedure Four hundred forty-seven undergraduates at the University of Arkansas completed an online study about public opinion and social perception. Roughly half completed the study in exchange for partial fulfillment of a course requirement, whereas the other half were approached around the student union in exchange for a piece of candy. We excluded from the sample 34 participants who failed an attention check (i.e., “This is an attention check item. Please select ‘somewhat agree’ to indicate you are paying attention.”), an additional five participants who provided a response more than 3 SD from the mean on one or more dependent variables, two participants for missing data, and one participant who identified as transgender and could not be used as a comparison group in subsequent analyses. This left a final sample of 405 participants for analyses (race/ethnicity: 68% White, 4% Black/African-American, 10% Hispanic/Latino, 6% Asian/Pacific Islander, 1% Native American, 1% Arab/ Middle Eastern, 9% Bi-racial; 1% Other; gender: 61%

Journal of Individual Differences (2019), 40(1), 1–12

D. J. Sparkman et al., Openness and Diversity Ideologies

female; age: M = 20.31 years, SD = 3.58). After providing informed or verbal consent, participants completed a series of dependent measures presented in random order, followed by a demographics page. At the conclusion of the survey, participants were thanked and awarded credit or a piece of candy.

Measures Measures of Openness to Experience, interpersonal perspective taking, multiculturalism, colorblindness, and demographics were completed. No other measures were presented in the survey.

Openness to Experience Openness (α = .80) was measured using the same scale as in Study 1.

Interpersonal Perspective Taking To provide a more general measure of interpersonal perspective taking, we used the original perspective-taking subscale of the IRI (Davis, 1983). We selected only four items from this measure to save space on our survey (see ESM 1), three of which come from a recently validated brief form of the perspective-taking subscale (B-IRI; Ingoglia, Lo Coco, & Albiero, 2016). Each item was answered on 1 (= not at all like me) to 5 (= very much like me) scales, and averaging together all items created a reliable index of interpersonal perspective taking (α = .78).

Diversity Ideologies To measure multiculturalism and colorblindness, we consulted work by Hahn and colleagues (2015). Four items measuring multiculturalism (e.g., “Learning about the ways that different ethnic groups resolve conflict will help us develop a more harmonious society,” “I would like my children to be exposed to the language and cultural traditions of different ethnic groups”) and four items measuring colorblindness (e.g., “You can find commonalities with every person no matter what their background is,” “All humans are fundamentally the same, regardless of where they come from or what their background is”) were answered on 1 (= strongly disagree) to 7 (= strongly agree) scales. Averaging together the multiculturalism items created a reliable index of multiculturalism (α = .81), but the internal consistency of the colorblindness scale was poor (α = .59). In contrast to Study 1, multiculturalism and colorblindness were positively correlated, r = .47, p < .001.

Covariates Participants reported demographics (age, gender, race/ ethnicity).

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Table 2. Descriptive statistics and bivariate correlations among variables in Study 2 Variable

M (SD)

1

2

3

1. Openness to Experience

3.47 (0.59)

–

2. Interpersonal perspective taking

3.81 (0.71)

.23***

–

3. Multiculturalism

6.08 (0.83)

.20***

.21***

–

4. Colorblindness

5.91 (0.85)

.12*

.15**

.47***

Notes. All variables depicted are in total aggregate form. ***p < .001, **p < .01, *p < .05 (all two-tailed).

Results Descriptive statistics and bivariate correlations are shown in Table 2. Openness to Experience was positively correlated with interpersonal perspective taking and multiculturalism, but, in contrast to Study 1, Openness and colorblindness were positively correlated. Additionally, interpersonal perspective taking was positively correlated with multiculturalism and colorblindness.

Structural Equation Modeling Given the low reliability of the colorblindness scale, we again decided to analyze our model using latent factors in SEM to account for measurement error (e.g., John & Benet-Martínez, 2000; Kline, 2005). Using AMOS 20 software, we represented Openness as a manifest variable and interpersonal perspective taking, multiculturalism, and colorblindness as latent factors (each with 4 indicators). The goodness-of-fit of the model was assessed using the same guidelines as in Study 1 (see Tabachnick & Fidell, 2013).

The proposed measurement model indicated a good fit to the data, w2/df = 116.41/60 = 1.89, p < .001, CFI = .96, RMSEA = .05.

To construct the structural model, we drew direct paths from Openness to interpersonal perspective taking, multiculturalism, and colorblindness, and from interpersonal perspective taking to multiculturalism and colorblindness.

As our exogenous covariates, we drew direct paths from age, gender (0 = male, 1 = female), and race/ethnicity (0 = ethnic majority/White, 1 = ethnic minority/non-White) to endogenous variables of interpersonal perspective taking, multiculturalism, and colorblindness. As in Study 1, we covaried all exogenous variables and also covaried the error terms of multiculturalism and colorblindness (to reflect their similar scale development and measurement; see Hahn et al., 2015). The proposed structural model indicated a good fit to the data, w2/df = 152.87/87 = 1.76, p < .001, CFI = .95, RMSEA = .04. Given there were non-significant effects of age on all endogenous variables and gender on interpersonal perspective taking, we iteratively (for description see Footnote 2) deleted these nonsignificant variables and paths for simplicity. The parsimonious structural model (see Figure 2) indicated a good fit to the data, Ó 2018 Hogrefe Publishing

w2/df = 148.60/79 = 1.88, p < .001, CFI = .95, RMSEA = .05, and was used in subsequent analyses.

Mediation As shown in Figure 2, Openness to Experience uniquely and positively predicted multiculturalism (total effect: β = .25, p < .001) as well as colorblindness (total effect: β = .20, p = .01). Openness uniquely and positively predicted interpersonal perspective taking (β = .26, p < .001), and interpersonal perspective taking uniquely and positively predicted both multiculturalism (β = .17, p = .01) and colorblindness (β = .17, p = .02). To examine whether Openness to Experience uniquely predicted beliefs in multiculturalism and colorblindness through interpersonal perspective taking (after controlling for gender and race/ethnicity), we tested for evidence of mediation using 95% bias-corrected confidence intervals based on 5,000 bootstrap samples. Results suggest the indirect effect of Openness on multiculturalism through interpersonal perspective taking was positive and significant, β = .04, SE = 0.02, 95% CI [0.01, 0.10], p = .01; as was the indirect effect of Openness on colorblindness through interpersonal perspective taking, β = .05, SE = 0.03, 95% CI [0.003, 0.11], p = .03 (see Figure 2). When accounting for the indirect effect of interpersonal perspective taking, the direct effect of Openness on multiculturalism remained significant, suggesting partial mediation, β = .21, SE = 0.06, 95% CI [0.10, 0.32], p < .001; whereas the direct effect of Openness on colorblindness was reduced to marginal significance, β = .15, SE = 0.08, 95% CI [ 0.004, 0.30], p = .06.

Discussion In brief, results largely replicate and extend those of Study 1. Replicating previous findings, Openness to Experience positively predicted beliefs in multiculturalism. Extending previous findings, results show Openness also predicted multiculturalism through a more general, interpersonal perspective-taking process. Again, these findings occurred independently of age, gender, and race/ethnicity. In contrast to Study 1 but consistent with our initial theorizing, Openness to Experience also uniquely and positively Journal of Individual Differences (2019), 40(1), 1–12

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D. J. Sparkman et al., Openness and Diversity Ideologies

Figure 2. Structural equation model depicting the indirect effects of Openness to Experience on multiculturalism and colorblindness through perspective taking, controlling for age, gender (0 = male, 1 = female), and race/ ethnicity (0 = ethnic majority/White, 1 = ethnic minority/non-White). Dashed lines represent the removal of a variable or path in subsequent analyses.

Coefficients are standardized and total effects are listed in parentheses. Model fit: w2/df = 148.60/79 = 1.88, p < .001, CFI = .95, RMSEA = .05. ***p < .001, **p < .01, *p < .05, yp < .10 (all twotailed).

predicted beliefs in colorblindness, and did so through greater interpersonal perspective taking.

General Discussion In two studies, we tested whether Openness to Experience predicted one’s belief in the importance of recognizing and appreciating diversity and intergroup differences (multiculturalism), or ignoring and minimizing such differences in favor of “sameness” (colorblindness). We further examined whether this relationship between Openness and diversity ideologies was mediated by perspective-taking tendencies. In Study 1, Openness positively predicted support for multiculturalism through greater ethnic perspective taking, but negatively predicted support for colorblindness through the same underlying mechanism. In Study 2, with different measures of multiculturalism and colorblindness and a more general operationalization of perspective taking, results suggest Openness positively predicted support for multiculturalism and colorblindness, and did so through greater interpersonal perspective taking. Importantly, all findings persisted after controlling for variables such as empathy (Study 1 only), age, gender, and race/ethnicity.

Together, these data suggest individuals who are artistic, imaginative, unconventional, and curious may be just as likely to believe the racial, ethnic, or cultural group membership of others should be recognized and appreciated, as they are to believe such categories should be minimized or ignored. These seemingly contradictory findings are largely driven by motivations to reflect on the psychological viewpoint of other people, and the particular downstream consequences depend on the type of perspective taking. Openness Journal of Individual Differences (2019), 40(1), 1–12

influences one’s tendency to take the perspective of those from different racial/ethnic backgrounds, and in doing so, is associated with stronger beliefs in multiculturalism but weaker beliefs in colorblindness. However, Openness also influences interpersonal perspective taking toward everyone, and in doing so, is associated with stronger beliefs in both multiculturalism and colorblindness. Thus, the influence of Openness on believing we should recognize ethnocultural differences may have rather broad perspectivetaking roots, facilitated not only by ethnic perspective taking but also perspective taking more generally. The influence of Openness on believing we should recognize our shared commonalities, however, may have more narrow perspective-taking roots, often varying as a function of the particular perspective-taking process engaged.

Contextualizing the Present Findings and Examining Future Directions Although previous research has investigated links between Openness and multiculturalism (e.g., Chen et al., 2016; van der Zee & van Oudenhoven, 2000), we provide additional evidence to confirm Openness is related to multiculturalism. Other research has shown Openness positively predicts a UDO, an appreciation for the similarities and differences among people (Thompson et al., 2002), but this combination of colorblind and multicultural tenets makes disentangling their potential independent influences somewhat difficult. Our research provides more clarity and complexity on this issue. In Study 2, for instance, we show Openness independently and positively predicted colorblindness and multiculturalism when these constructs were measured separately. Regarding complexity, we show Openness Ó 2018 Hogrefe Publishing

D. J. Sparkman et al., Openness and Diversity Ideologies

predicted these diversity ideologies through a particular perspective-taking mechanism. While past research indicates Openness predicts perspective taking (Sparkman & Blanchar, 2017), and perspective taking influences diversity ideologies (Todd & Galinsky, 2012), this is the first research (to our knowledge) integrating them together in a mediational framework. Overall, we interpret the present findings as evidence of the complexity and often contradictory impact of the Openness dimension on social perception.

Openness has a reliable and negative influence on prejudice (Sibley & Duckitt, 2008), but this depends on the conventionality of the target group (Brandt et al., 2015). Openness positively predicts recognizing and appreciating the differences among people (e.g., Chen et al., 2016; Thompson et al., 2002), but it also predicts recognizing broad similarities, including the universalism of human nature (ParksLeduc, Feldman, & Bardi, 2015), seeing all of humanity as part of the ingroup (McFarland et al., 2012), and, now, beliefs in colorblindness.

Though the pattern of findings for multiculturalism was consistent across studies, we should note this was not always the case for colorblindness and therefore caution the interpretation of findings outlined above. When perspective taking was operationalized as ethnic perspective taking in Study 1, colorblindness was negatively correlated with perspective-taking tendencies. But when operationalized as interpersonal perspective taking in Study 2, colorblindness was positively correlated with perspective-taking tendencies. This could be due to the different operationalizations of perspective taking, but could also be a function of the different measures of colorblindness between studies. Indeed, previous research shows that when colorblindness is operationalized as an ideology denying the outright existence of race, racism, and unequal opportunity in society (color-blind racial attitudes scale, or CoBRAS; Neville, Lilly, Duran, Lee, & Browne, 2000), colorblindness and interpersonal perspective taking were negatively correlated (Burkard & Knox, 2004). Thus, the relationship between perspective taking and colorblindness likely depends on important contextual factors, and future research should continue to investigate these relationships by examining yet additional measures of each construct. Related to this point, we also suspect Openness may yield different associations with colorblindness depending on the measure used, such as a possible negative correlation with the CoBRAS. As such, future research should investigate moderators of the relationship between Openness and diversity ideologies to examine under what conditions Openness predicts multiculturalism versus colorblindness.

How might other relevant broadband personality dimensions, such as Agreeableness, influence beliefs in multiculturalism and colorblindness? Agreeableness typically has a stronger influence on pro-social behaviors and Ó 2018 Hogrefe Publishing

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affective reactions to the experiences of others (Graziano & Eisenberg, 1997), and thus Agreeableness should more strongly and uniquely predict behavioral dimensions of diversity through affective empathy (e.g., Butrus & Witenberg, 2013). In contrast, Openness to Experience is recognized as having a stronger cognitive component than other personality dimensions (McCrae & Costa, 1997; Onraet, Van Hiel, Roets, & Cornelis, 2011; Parks-Leduc et al., 2015), and thus Openness should more strongly and uniquely predict attitude/belief dimensions of diversity through cognitive perspective taking (Butrus & Witenberg, 2013). In Study 1, the influence of Openness on multiculturalism through cognitive (ethnic) perspective taking occurred independently of affective empathy, providing some preliminary support for these ideas. However, they must be followed up more directly with Agreeableness. Overall, the contribution of this future research is twofold: (1) it could highlight the potentially nuanced and independent effects of Agreeableness and Openness on different dimensions of diversity, and (2) it could address how these associations are explained through different affective and cognitive mechanisms.

In the present research, we took an individual difference approach and examined whether dispositional traits (openness) drive relevant behavior (perspective taking) that in turn influences attitudes and beliefs (i.e., multiculturalism, colorblindness). However, we wonder if the reverse model might also be possible. For example, can multiculturalism facilitate ethnic perspective taking (e.g., Todd & Galinsky, 2012) and, in turn, self-perceptions of Openness to Experience? This is a rather provocative suggestion given the stability of the openness dimension and personality in general (Caspi & Roberts, 2001; Costa & McCrae, 1988; McCrae & Costa, 1994; Terracciano, Costa, & McCrae, 2006). But personality is not inevitably fixed throughout the lifespan and does show some degree of change (e.g., Roberts, Walton, & Viechtbauer, 2006). One potential cause of personality change is a shift in the sociocultural norms surrounding the individual. If social norms guide behavior (Cialdini & Trost, 1998), norms about the importance of recognizing and appreciating group memberships might influence one’s desire to engage in novel behavior, such as taking the perspective of someone from a different ethnocultural background (see Todd & Galinsky, 2012). When individuals watch themselves engage in novel behavior they may begin to draw different conclusions about their personality as a function of these behaviors (e.g., Caspi & Roberts, 2001). In this way, consistent shifts in perspective-taking behavior over time might ultimately change one’s selfperception as someone who actively seeks out alternative viewpoints and perspectives, a core feature of the Openness dimension (McCrae & Costa, 1997; McCrae & Sutin, 2009).

While such a reverse social-personality process model is Journal of Individual Differences (2019), 40(1), 1–12

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possible, few studies have investigated its merits. Future research in this area may help bridge the divide between personality and social psychological perspectives.

Limitations The present research provides new insights into the relationships among Openness to Experience, perspective taking, and diversity ideologies, but it is not without its limitations. First, the data are based on samples of college students, limiting the generalizability of our findings. Second, the cross-sectional design prevents us from making causal inferences from the data and suggests a number of alternative mediation models may also be supported. Third, all responses were based on self-report measures, suggesting the results may be due to social desirability concerns (for which we did not control). There is, however, typically little indication that social desirability influences participants to present themselves as “open-minded” or high in Openness. Only highly open individuals admire Openness; those low in Openness abhor it (McCrae & Sutin, 2009).

Conclusion Our research illustrates how personality influences perspective-taking behavior and, in turn, beliefs about the best way to achieve intergroup harmony in society. Individuals characterized by their rich imagination and intellectual curiosity, cognitive flexibility, and preference for social change tend to seek out other psychological perspectives – including those from racial/ethnic outgroups, in particular, but also people, in general. This tendency to engage in and reflect on the perspectives of others underlies why highly open individuals not only believe in recognizing and appreciating the ethnocultural differences among people, but also recognizing our shared commonalities.

Electronic Supplementary Material The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/ 1614-0001/a000270 ESM 1. Text (.docx) Perspective-taking measures of Study 1 and 2.

Acknowledgments We would like to thank Ana J. Bridges and Juventino Hernandez Rodriguez for their help with feedback on this research and an earlier draft of the manuscript.

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Xu, X., Mar, R. A., & Peterson, J. B. (2013). Does cultural exposure partially explain the association between personality and political orientation? Personality and Social Psychology Bulletin, 39, 1497–1517. https://doi.org/10.1177/0146167213499235 Received May 9, 2017 Revision received January 30, 2018 Accepted January 31, 2018 Published online September 3, 2018

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David J. Sparkman Department of Psychological Science University of Arkansas 216 Memorial Hall Fayetteville, AR 72701 USA djsparkm@uark.edu

Ó 2018 Hogrefe Publishing

Original Article

Variation in Personality States as Predicted by Interpersonal Context Jamie S. Churchyard, Karen J. Pine, Shivani Sharma, and Ben (C) Fletcher Department of Psychology, School of Life and Medical Sciences, University of Hertfordshire, UK

Abstract: Diary studies of personality have shown that personality is variable, and can help the person deal appropriately with the different interpersonal demands they encounter. This study aims to demonstrate how interpersonal context predicts personality states. Thirty-six participants (9 male, 27 female, Mage = 24.72, SD = 7.11) kept an online diary for one month. The diary recorded measurements of HEXACO personality states, momentary interpersonal factors including current interpersonal role (with friend, family member, partner, as employee/ student, alone), and social goal orientation (socializing with others, avoidance of others, asserting yourself, personal/work achievement), and dispositional anxiety and depression. Individuals’ personality states were found to vary considerably across measurements in a normal distribution. Multilevel modelling analyses showed that interpersonal factors did predict within subject personality variation. Social goal orientations had a greater relative impact than interpersonal roles. Depression had a significant effect on between subject variance in state emotionality. These findings highlight the importance of interpersonal context in predicting stable personality variation.

Keywords: intraindividual variation, HEXACO model, personality state, interpersonal context, diary study

This study examines variations in personality trait measures that occur in people moment-by-moment, and examines some of the interpersonal factors that affect this variation.

The prominent perspectives in personality research are trait (e.g., Ashton, Lee, & Son, 2000; McCrae & Costa, 1996) and social-cognitive processing theories (Fletcher & Stead, 2000; Mischel & Shoda, 1995). Research shows that personality states measured using trait dimensions are not fixed and can vary moment-by-moment as states (Baird, Le, & Lucas, 2006; Beckmann, Wood, & Minbashian, 2010; Fleeson, 2007; Fleeson & Gallagher, 2009). McCrae & Costa (1996), in their five-factor personality system, acknowledge that characteristic adaptations do occur.

These are responses triggered by expressions of a trait that are appropriate for the current context. There is reason to believe that interpersonal factors can influence this stable variation in personality (Bleidorn, 2009; Churchyard, Pine, Sharma, & Fletcher, 2013; Heller, Komar, & Lee, 2007; Robinson, 2009).

How sensitive is personality expression to the specific context? The Cognitive and Affective Personality System (CAPS) theory (Mischel & Shoda, 1995) suggests individuals’ responses to particular contexts are influenced by various cognitive-affective units (CAUs) including goals and values, affects, self-regulatory plans and competencies, expectancies of outcomes, encodings of the self, others and situation, and feedback received from previously applying the behavior in similar contexts. This creates if situation Ó 2018 Hogrefe Publishing

– then behavior relationships. Specific situational context learning will result in apparently different expressions of a higher order behavioral trait (a state that differs from the standard trait disposition). CAPS theory has been discussed in the interpersonal context in terms of relational selves by Andersen & Chen, (2002), who proposed the idea that we have different selves which elicit behavior for different relationships.

The Current Study We used a diary study method to examine which interpersonal contextual factors have a greater impact on individual variation in personality, and to consider how this variation relates to dispositional affective factors. Interpersonal contextual predictors included a range of interpersonal roles and social goal orientations. Bleidorn (2009) and Heller et al. (2007) have examined interpersonal roles and social goal orientations previously, although they have not yet been examined in the same study, a recommendation that Heller, Perunovic, & Reichman (2009) make. To take account of affective factors we measured dispositional anxiety and depression. Heller et al. (2007) findings suggest that dispositional anxiety and depression will be positively related to emotional (neurotic) personality states but negatively related to more positive personality states such as honesty, extraversion, agreeableness, conscientiousness, Journal of Individual Differences (2019), 40(1), 13–19 https://doi.org/10.1027/1614-0001/a000271

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and openness to experience, as they previously found current mood measures of positive affect to be positively predicted by state extraversion, and negative affect to be positively predicted by state neuroticism.

We took multiple diary recording measurements of individuals’ HEXACO personality states. The HEXACO personality model consists of the big-five traits and an additional honesty component (Ashton et al., 2000). This addition is valuable because it might be expected to show lower within subject variation than the other states reflecting stability in levels of honesty across relational context.

Honesty levels may differ between people, but might be more invariant to context within a person because of the nature of the construct being measured. This study, therefore, examines the degree of personality state variation that occurs and examines some of the important interpersonal and affective reasons for it.

Method Participants and Procedure Thirty-six participants took part (9 male, 27 female, Mage = 24.72, SD = 7.11) after responding to online research recruitment sites and the University participant pool. The participants accessed the diary via a UK Bristol online survey hyperlink and were asked to fill out diary recordings at least once a day for up to 1 month until 30 recordings were completed. Participants were asked to leave at least 5 hr between entries, to avoid overlap in entries. Response rates varied between completing at least 20 of 30 possible days.

Overall, 1,062 repeated measurements were collected for all the participants.

Measures HEXACO Personality State Items Eighteen bipolar adjective items were used to measure the HEXACO states. For example, to measure diligence in the conscientiousness state, lazy-diligent was used. These 18 items were each measured on a 1–7 Likert scale (where in the previous example, 1 would represent extremely lazy, while 7 would represent extremely diligent). Each of the six personality states measured consisted of three items, based on three of the facet categories out of the four that form each trait in the HEXACO model (Ashton et al., 2000). As an example, we decided to use the following three items of insincere-sincere, unfair-fair and arrogant-modest, based on the honesty facet categories of sincerity, fairness, and modesty from the honesty trait of the HEXACO model. In terms of reliability,

Journal of Individual Differences (2019), 40(1), 13–19

the honesty (α = .77), emotionality (α = .73), and agreeableness (α = .80) state measures were found to be reliable, while extraversion (α = .64), conscientiousness (α = .63), and openness to experience state measures were found to be moderately reliable (α = .67) across every repeated measurement for every participant. These reliability values were decent considering each state measure only consisted of three items for ease of repeated completion.

Interpersonal Role and Social Goal Orientation Markers To measure interpersonal roles, five options were included (with friend, with family member, with partner, as an employee/student, and alone). To measure social goal orientations, four options were included (socializing with others, avoidance of others, asserting yourself, and personal or work achievement). These options were each rated using a Yes/No tick response option, when the participant was asked to tick which categories their activities came under within the past few hours. The interpersonal roles were drawn from those listed by Bleidorn (2009), while the social goal orientation categories were based on the outcome of a factor analysis of four social motives (affiliation, avoidance, power, and achievement) onto the big-five personality traits conducted by Engeser & Langens (2010).

Affiliation was relabelled as socializing, and power relabelled as asserting yourself to make them easier to understand and applicable for the contextual measurements of this study (these labels were considered appropriate based on the factor structure and correlations Engeser and Langens reported).

Thoughts and Feelings Scale The Thoughts and Feelings scale from the FIT profiler (Fletcher & Stead, 2000) was administered at the beginning of the study to measure dispositional anxiety and depression. This measures frequency of feeling anxious (4 items), and depressed (4 items) over the last month.

Each item uses a 4 point response scale: 1 = Never, 2 = Very rarely, 3 = Now and again, and 4 = Frequently/often. This gives total anxiety and depression scores between 0 and 12. Both scales have been shown to display high reliability (anxiety α = .80, depression α = .78) and have been validated against other measures (Sharma, 2010).

Results To provide a descriptive measure of how personality states varied within the subject, repeated measurement standard deviations were calculated for each participant on each

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J. S. Churchyard et al., Variation in Personality States as Predicted by Interpersonal Context

Figure 1. An example density distribution from a participant who varied in state conscientiousness (the state conscientiousness score being the mean of its three facet items).

state. Considering these states were measured on a 7 point scale, an average state SD of 0.81 (honesty), 1.03 (emotionality), 1.05 (extraversion), 0.99 (agreeableness), 0.86 (conscientiousness), or 0.82 (openness to experience) in both directions reflects a good degree of variation in personality states over repeated measures in the sample. The state scores for most individuals displayed a normal distribution around their mean score. Figure 1 provides an example of this for a participantâ&#x20AC;&#x2122;s variation in state conscientiousness.

We determined multi-models using the MLWin software (Rasbash, Charlton, Browne, Healy, & Cameron, 2009), using maximum likelihood estimation, to examine which interpersonal and affective variables predict particular personality states in multivariate multilevel regression models.

Multivariate Multilevel Regression Modelling Analyses Three-level multivariate regression modelling analyses with interpersonal role and social goal orientation as repeated measure predictors, and anxiety and depression as between subject predictors of personality states were conducted. The analysis procedure followed was based on Bleidorn (2009) analysis procedure, except with six rather than five factors, as the HEXACO model includes the additional honesty component as well as the big five. The first level is a measurement model, while levels 2 and 3 are within subject and between subject levels respectively. The main benefits of Ă&#x201C; 2018 Hogrefe Publishing

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this multivariate procedure in comparison to separate univariate procedures are that it does not require balanced data or equidistant time measurement occasions, and it provides more powerful and accurate tests of the fixed effects and standard errors (Snijders & Bosker, 1999). Multivariate analysis was also conducted as the deviations were all found to be correlated (between r = .39 and r = .74, all at least p < .05).

Variance partition coefficients were calculated at baseline to determine the ratio of variance at the within subject (level 2) and between subject (level 3). Variance partition coefficients closer to 1, indicate more variance at the between subject level than the within subject level. The analyses suggested that there is more within subject variance present in the honesty (VPC = .41), emotionality (.32), extraversion (.11), agreeableness (.22), conscientiousness (.35), and openness to experience states (.39). The honesty state displayed the greatest degree of between subject variation.

These multilevel modelling analyses are performed under the assumption that the level 2 and level 3 residuals are normally distributed. Residual analyses were conducted which indicated the level 2 residuals were normally distributed for all six states, and the level 3 residuals were normally distributed for every state except honesty which displayed mild skew to the left of the distribution. As this skew was only mild, it was deemed appropriate to continue the analyses.

The interpersonal role, social goal orientation, anxiety and depression explanatory variables were applied to give fixed effects that predict variance in personality states at levels 2 and 3. In every instance of adding the repeated measures contextual predictors, the 2log likelihood statistic significantly decreased compared to the baseline model (at p < .05 at least, based on the chi square distribution).

When depression was then added to the multivariate model, it did not lead to a significant decrease in the 2log likelihood statistic when compared to the baseline statistic, or in addition after adding any repeated measures predictor. However, there were several consistent patterns of significant fixed effects for depression in the multivariate model, that were worth mentioning and so these have been reported. The change in 2log likelihood statistic was most likely nonsignificant, with some fixed effects being significant due to depression only having a considerable impact on the between subject variance, of which there was little in comparison to within subject variation. When anxiety was added to the multivariate model as a single predictor or in addition after a repeated measures predictor had been added to the baseline, there was not a significant change in the 2log likelihood statistic (anxiety displayed a very similar pattern of 2log statistics to depression). However, with anxiety no significant fixed effects were present in the full Journal of Individual Differences (2019), 40(1), 13â&#x20AC;&#x201C;19

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multivariate model, so the findings for anxiety have not been reported.

Table 1 reports the impact of the fixed effect of a contextual predictor βc and fixed effect of dispositional depression βd on the personality state when added to the baseline equations (for each state); and how the unexplained within subject σ2up and between subject σ2vp variance changes after the addition of the fixed effects. To determine whether the significance of specific fixed effects was p < .05, the fixed effect was compared against the value of the standard error of that fixed effect multiplied by 1.96 (the t statistic value that reflects 95% coverage of the normal distribution).

If the effect value was greater than its standard error multiplied by 1.96, then p < .05. The friend role and the personal or work achievement orientation predictors were also found to have an impact when the effect of the predictor was allowed to vary according to the participant in random slope models. Of the models that converged when depression was added as well (some did not converge, most likely due to the complex structure of the data), only these two were found to be significant, and have been reported.

The altered fixed effect of these two predictors and their impact on the unexplained variances has been reported separately to the results for the standard form of these two predictors in Table 1.

The extraverted state was significantly predicted by every role or orientation. Extraverted states were positively predicted by the with friend role, with partner role, with family member role, as an employee/student role, socializing with others orientation, asserting yourself orientation, and personal/work achievement orientation. Extraverted states were negatively predicted by the alone role and avoiding others orientation. State openness to experience was predicted by every role or orientation, except the with partner role. The effects were all in the same direction as those for the extraverted state. State agreeableness was positively predicted by the with friend role, the socializing with others and personal/work achievement orientations. Agreeableness states were negatively predicted by the alone role and avoiding others orientation. The emotionality state was negatively predicted by the socializing with others and asserting yourself orientations, but positively predicted by the avoiding others orientation. State honesty was also positively predicted by socializing with others, asserting yourself, and personal/work achievement orientations, as well as being negatively predicted by avoiding others orientation.

State conscientiousness was positively predicted by the as an employee/student role, and the socializing with others, asserting yourself, and personal/work achievement orientations. The unexplained within subject variance in personality state for the predictor always showed a significant decrease. When the significant random slope effects for

Journal of Individual Differences (2019), 40(1), 13–19

the friend role and achievement orientation were added to the baseline model, the within subject variance decreased, but the unexplained between subject variance also increased. This means part of the within subject variance in personality state is sensitive to each participant’s expression of the particular predictor considered.

When depression was entered with all but one of the repeated measure predictors (the exception being the with friend predictor when random slope effects were applied), it showed a significant positive fixed effect on state emotionality, with the unexplained between subject variance decreasing considerably. The unexplained within subject variance also showed a small decrease. Depression was found to negatively predict state extraversion, agreeableness, conscientiousness, and openness to experience, and positively predict state emotionality, when entered with the achievement predictor (when random slope effects were applied). In the state extraversion, agreeableness, and conscientiousness models, the unexplained between subject variance increased, but decreased in the state emotionality and openness to experience models.

Discussion Previous diary studies have shown that behavior within five factor personality states varies (Fleeson & Gallagher, 2009), and that it can be predicted by context (Bleidorn, 2009; Fleeson, 2007; Heller et al., 2007). The aim of this study was to further identify and compare the role of moment-by-moment interpersonal factors in the variability of personality. We found good evidence to support personality varying moment-by-moment, as measured by the HEXACO model, and that the variation is predicted by who the individual is with and what their goals are.

The attributes in the traditional five-factor model followed the variance partition pattern displayed in previous research (Bleidorn, 2009; Fleeson, 2007; Fleeson & Gallagher, 2009; Heller et al., 2007). The additional honesty state was found to display a greater degree of between subject variation in the variance than the other states (although again there was still considerable within subject variation). Honesty might be expected to be more stable than the other states – as honesty is required across all interpersonal contexts. If an individual’s honesty varied to the same degree as the other states this would likely indicate poor interpersonal functioning. There was mild skew of the level 3 honesty residuals toward the left of the distribution, indicating between subject honesty was high on average, supporting this.

The results of the multilevel modelling strongly support interpersonal roles or social goal orientations predicting

Ó 2018 Hogrefe Publishing

J. S. Churchyard et al., Variation in Personality States as Predicted by Interpersonal Context

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Table 1. The fixed effects of each contextual predictor and depression on the HEXACO states State Base Depression Friend and Friend (k) Partner FM and ES and Alone and SWO and AO and line (DP) DP and DP and DP DP DP DP DP DP

AY and Achieving Achieving (k) DP and DP and DP

H N/A

N/A

0.114

0.093

0.147

0.006

0.097

0.099

N/A

N/A

(0.061)

(0.066)

(0.080)

(0.064)

(0.064)

(0.061)

N/A

0.044

0.042

0.002

0.039

0.044

0.043

0.044

0.038

0.040

0.041

0.042

0.040

N/A

(0.053)

(0.053)

(0.048)

(0.053)

(0.053)

(0.053)

(0.053)

(0.053)

(0.053)

(0.053)

(0.053)

(0.051)

σ2up 0.774

0.774

0.771

0.767

0.772

0.774

0.773

0.773

0.765

0.763

0.765

0.769

0.754

σ2vp 0.533

0.522

0.529

0.551

0.518

0.523

0.523

0.517

0.517

0.521

0.529

0.515

0.565

βc

N/A

0.062

0.075

0.180

0.087

0.109

0.002

0.248

0.315

0.151

0.037

0.014

N/A

N/A

(0.075)

(0.075)

(0.097)

(0.078)

(0.078)

(0.075)

(0.073)

(0.088)

(0.074)

(0.072)

(0.102)

N/A

0.116

0.114

0.092

0.110

0.118

0.118

0.116

0.109

0.111

0.113

0.115

0.129

N/A

(0.052)

(0.053)

(0.050)

(0.052)

(0.052)

(0.052)

(0.052)

(0.052)

(0.052)

(0.052)

(0.053)

(0.045)

σ2up 1.166

1.166

1.165

1.165

1.162

1.165

1.165

1.166

1.153

1.152

1.161

1.166

1.123

σ2vp 0.570

0.497

0.503

0.508

0.486

0.495

0.479

0.497

0.495

0.487

0.495

0.497

0.528

0.613

0.734

0.552

βc βd

0.214 (0.059)

0.283 (0.072)

0.208

0.166

0.166

(0.060)

(0.058)

(0.072)

E

βd

N/A

X βc βd

N/A

N/A

0.569

0.604

0.425

0.213

0.225

N/A

N/A

(0.072)

(0.113)

(0.092)

(0.076)

(0.076)

N/A

0.053

0.040

0.010

0.038

0.060

0.050

0.050

0.033

0.044

0.044

0.051

N/A

(0.072)

(0.070)

(0.087)

0.567

0.168

0.169

(0.072)

(0.071)

(0.100) 0.072

(0.030)

(0.032)

(0.028)

(0.031)

(0.031)

(0.031)

(0.029)

(0.033)

(0.031)

(0.031)

(0.030)

(0.026)

σ2up 1.200

1.200

1.130

1.072

1.169

1.190

1.189

1.123

1.080

1.153

1.127

1.194

1.146

σ2vp 0.155

0.140

0.156

0.165

0.150

0.146

0.145

0.128

0.169

0.142

0.146

0.136

0.228

0.196

0.455

0.453

A N/A

N/A

0.282

0.280

0.153

0.033

0.047

N/A

N/A

(0.070)

(0.083)

(0.090)

(0.073)

(0.074)

N/A

0.063

0.056

0.025

0.058

0.062

0.062

0.062

0.050

0.056

0.062

0.061

N/A

(0.040)

(0.041)

(0.034)

(0.040)

(0.040)

(0.040)

(0.039)

(0.040)

(0.040)

(0.040)

(0.040)

(0.034)

σ2up 1.067

1.067

1.048

1.037

1.063

1.066

1.066

1.060

1.020

1.036

1.065

1.059

1.055

σ2vp

0.297

0.275

0.293

0.352

0.272

0.275

0.276

0.257

0.282

0.271

0.278

0.274

0.345

N/A

N/A

0.112

0.091

0.062

0.034

0.300

0.119

0.177

0.106

βc

N/A

N/A

(0.062)

(0.073)

(0.081)

(0.065)

N/A

0.075

0.072

0.033

0.077

0.074

0.070

0.074

0.070

0.073

0.069

0.068

βd

N/A

(0.047)

(0.047)

(0.044)

(0.047)

(0.047)

(0.048)

(0.046)

(0.047)

(0.047)

(0.047)

(0.045)

(0.039)

σ2up 0.801

0.801

0.798

0.787

0.800

0.800

0.783

0.799

0.794

0.799

0.776

0.744

0.726

σ2vp 0.434

0.404

0.407

0.408

0.408

0.403

0.425

0.389

0.404

0.398

0.396

0.375

0.438

0.121

0.185

0.267

βc βd

(0.071)

(0.068)

(0.083)

0.074

0.175

0.166

(0.070)

(0.068)

(0.073) 0.082

C (0.065)

(0.062)

(0.061)

(0.074)

0.358

0.519

0.525

(0.061)

(0.057)

(0.074) 0.089

O βc

N/A

N/A

0.148

0.150

0.125

0.153

0.169

N/A

N/A

(0.060)

(0.062)

(0.078)

(0.063)

(0.063)

βd

N/A

0.089

0.085

0.090

0.085

0.093

0.086

0.088

0.084

0.085

0.084

0.086

σ2up

N/A

(0.049)

(0.049)

0.046

(0.048)

(0.049)

(0.049)

(0.049)

(0.050)

(0.049)

(0.048)

(0.048)

(0.046)

σ2vp 0.750

0.750

0.745

0.746

0.748

0.745

0.745

0.747

0.742

0.739

0.734

0.740

0.728

0.486

0.443

0.449

0.499

0.430

0.444

0.441

0.442

0.454

0.444

0.420

0.430

0.418

(0.060)

(0.059)

(0.071)

0.280

0.223

0.215

(0.059)

(0.057)

(0.068) 0.095

Notes. Each column represents a single multivariate model. Each cell contains in descending order the contextual fixed effect βc, SE of contextual fixed effect (in parentheses), depression fixed effect βd, SE of depression fixed effect (in parentheses), unexplained within subject variance ðσ2up ), in italics, and unexplained between subject variance σ2vp in that order. H = Honesty, E = Emotionality, X = Extraversion, A = Agreeableness, C = Conscientiousness, O = Openness to experience. FM = Family member, ES = Employee/student, SWO = Socialising with others, AO = Avoiding others, AY = Asserting yourself.

Friend (k) and Achieving (k) are the contextual effects allowed to vary by participant. Fixed effect and SE values in bold are significant at the .05 level at least.

The intercepts were similar across models, considerable change to the intercept only occurred for very strong effects on particular states (extraversion mainly).

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Journal of Individual Differences (2019), 40(1), 13–19

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J. S. Churchyard et al., Variation in Personality States as Predicted by Interpersonal Context

personality states. Relative to specific interpersonal roles, the social goal orientations generally had a greater impact on personality states. Personality states with more positive connotations (higher honesty, extraversion, conscientiousness, and openness to experience) were positively predicted by roles and orientations focused on engaging with other people and achieving, while the opposing alone role and avoiding others orientation negatively predicted these states (honesty, extraversion, agreeableness, openness to experience). The alone role and avoiding others orientation were found to positively predict state emotionality. The finding that particular personality states are predicted by specific roles and goals provides support for the view that situational dispositions are a result of the individual’s experiences and feedback from the social environment (as proposed within CAPS theory, Mischel & Shoda, 1995).

Although the interpersonal roles and social goal orientations displayed different relative effect strengths across states, the effects displayed similar directions in terms of positive and negative behavior states, suggesting they are associated and important to consider together as suggested

by Heller et al. (2009). The difference in strength of the predictors across the different states suggests there is differentiation in degree of state behavior by interpersonal context. For example, the with friend role had a much stronger impact on extraversion, in comparison to agreeableness and openness to experience, whereas the personal or work achievement orientation had a much stronger impact on state conscientiousness, when compared to honesty, extraversion, agreeableness, and openness to experience. This suggests some states were particularly facilitated by certain interpersonal factors. As these are fixed effects, relevant across participants, this indicates that they are appropriate ways to act in particular contexts.

The FIT Science framework would suggest that variability or flexibility in behavioral states has a beneficial effect on the individual’s engagement with their differing environments (Fletcher & Stead, 2000). This is supported by the lack of any predictive effects for anxiety on personality states and the finding here that depression only consistently predicted state emotionality. These findings have interesting implications for behavior change approaches and therapies because behavioral flexibility – or greater variation in personality states – is required to adapt to different circumstances (Fletcher, Hanson, Pine, & Page, 2011).

Limitations and Future Directions We only examined a limited range of predictors, and there may have been benefits of splitting the as employee/student and personal/work achievement markers into separate marker categories, or adding others. However, every addition would have expanded the demands on the participants Journal of Individual Differences (2019), 40(1), 13–19

and this would itself introduce other difficulties. Although we examined both interpersonal roles and social goal orientations together, we did not report interaction analyses, due to the excessive amount of analysis entailed for all the potential combinations of predictors. To explore the potential interactions, future studies could examine specific interpersonal roles and social goal orientations that are likely to interact, based on these findings. For example, the with friend role and socializing with others orientation are likely to interact based on their contextual compatibility. Also those roles and orientations sharing a similar directionality in findings in these analyses could be considered.

Conclusion Overall, this study provides support for people displaying meaningful intraindividual variation across all HEXACO personality states, which were predicted by both interpersonal role and social goal orientation contextual variables.

Anxiety levels did not predict the expression of personality state, although dispositional depression did so to a limited degree. Taken together, the results provide support for considering the implications of moment-by-moment fluctuations in personality state due to interpersonal contextual factors.

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Journal of Personality and Social Psychology, 97, 1097–1114. https://doi.org/10.1037/a0016786 Fletcher, B. (C)., Hanson, J., Page, N., & Pine, K. J. (2011). FIT – do something different: A new psychological intervention tool for facilitating weight loss. Swiss Journal of Psychology, 70, 25–34. https://doi.org/10.1024/1421-0185/a000035 Fletcher, B. (C)., & Stead, B. (2000). (Inner) FITness & the FIT Corporation. International Thomson Press: London, UK. Heller, D., Komar, J., & Lee, W. B. (2007). The dynamics of personality states, goals, and well-being. Personality and Social Psychology Bulletin, 33, 898–910. https://doi.org/10.1177/ 0146167207301010 Heller, D., Perunovic, W. Q. E., & Reichman, D. (2009). The future of person-situation integration in the interface between traits and goals: A bottom-up framework. Journal of Research in Personality, 43, 171–178. https://doi.org/10.1016/j.jrp.2008.12.011 McCrae, R. R., & Costa, P. T. Jr. (1996). Toward a new generation of personality theories: Theoretical contexts for the five-factor model. In J. S. Wiggins (Ed.), The five-factor model of personality: Theoretical perspectives (pp. 51–87). New York, NY: Guilford Press.

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dynamics, and invariance in personality structure. Psychological Review, 102, 246–268. https://doi.org/10.1037/0033-295X. 102.2.246 Rasbash, J., Charlton, C., Browne, W.J., Healy, M., & Cameron, B. (2009). MLwiN (Version 2.1). Bristol, UK: Centre for Multilevel Modelling, University of Bristol.

Robinson, O. C. (2009). On the Social malleability of traits variability and consistency in Big 5 Trait expression across three interpersonal contexts. Journal of Individual Differences, 30, 201–208. https://doi.org/10.1027/1614-0001.30.4.201 Sharma, S. (2010). FIT science for improving family functioning and parenting stress (Unpublished doctoral dissertation). University of Hertfordshire, Hatfield, UK Snijders, T. A. B., & Bosker, R. J. (1999). Multi-level analysis: An introduction to basic and advanced multi-level modelling.

London, UK: Sage.

Received May 17, 2013 Accepted February 1, 2018 Published online August 31, 2018 Jamie S. Churchyard Department of Psychology School of Human and Social Sciences University of West London Brentford, TW8 9GA London UK jamie.churchyard@uwl.ac.uk

Journal of Individual Differences (2019), 40(1), 13–19

Original Article

Sandbagging and the Self Does Narcissism Explain the Relationship Between Sandbagging and Self-Esteem?

Michael D. Barnett, Idalia V. Maciel, and Marley A. King Department of Psychology, University of North Texas, Denton, TX, USA Abstract: Sandbagging – a self-presentation strategy defined by feigned performance or false claims of inability – has been associated with lower self-esteem. The purpose of this study was to investigate whether narcissism explains the relationship between sandbagging and selfesteem. College students (N = 813) completed a survey. Grandiose and vulnerable narcissism explained variance in sandbagging beyond what was explained by self-esteem. When grandiose or vulnerable narcissism was included, the relationship between self-esteem and sandbagging was no longer significant. Overall, the results were consistent with the notion that the relationship between lower self-esteem and sandbagging may be subsumed by narcissism.

Keywords: sandbagging, narcissism, self-esteem, self-concept, fragile self-esteem

Sandbagging refers to an individual withholding initial performance effort (Kräkel, 2014), or falsely claiming inability, in order to portray themselves as weaker or more incompetent than they actually are so as to establish a low expectation baseline from their audience or opponents (Gibson, Sachau, Doll, & Shumate 2002; Petersen, 2013). Sandbagging is a self-presentational strategy (Brown, 2006; Gibson & Sachau, 2000) in which individuals understate their abilities in order to lower audience expectations, reduce personal performance pressure, or surprise others. Individuals may engage in sandbagging even when they are confident about their ability to carry out the task or when they have no apparent reason to “undersell” themselves (Gibson & Sachau, 2000), suggesting that sandbagging behavior may originate within the self – that is, serve a psychological need – rather than reflect an individual’s assessment of their ability in a specific domain.

Sandbagging and Self-Esteem Individuals with lower self-esteem tend to engage in more sandbagging (Brown, 2006; Gibson & Sachau, 2000; Petersen, 2013). This may represent a tendency for sandbaggers to genuinely convince themselves that they have lower ability as a result of constantly undermining and minimizing their strengths and successes (Gibson & Sachau, 2000). It is also possible that individuals with lower self-esteem have a negative self-concept that may drive them to offer harsher self-assessment. Individuals with low self-esteem are more Journal of Individual Differences (2019), 40(1), 20–25 https://doi.org/10.1027/1614-0001/a000272

sensitive to high stress events and are more susceptible to threats to their self-esteem (Spencer, Josephs, & Steele, 1993); thus, they may engage in sandbagging behavior in order to reduce performance pressure by lowering audience expectations in order to lower their feelings of anxiety from this possible threat to their already low self-image (Gibson & Sachau, 2000). Alternatively, it is possible that the relationship between self-esteem and sandbagging is subsumed by other variables such as narcissism.

Narcissism Narcissism can be conceptualized as a category (e.g., a diagnosis of Narcissistic Personality Disorder in the DSM-5; APA, 2013) or a trait. In this study, we focused on narcissism as a trait. Narcissism has been broken down into grandiose and vulnerable facets (Boldero, Higgins, & Hulbert, 2015; Cain, Pincus, & Ansell, 2008; Miller, Gentile, Wilson, & Campbell, 2013; Pincus et al., 2009; Wink, 1991). Narcissistic grandiosity is characterized by feelings of superiority, arrogance, a sense of entitlement, exploiting others, reactivity to criticism, and envy (Besser & Priel, 2010; Dickinson & Pincus, 2003).

Narcissistic vulnerability reflects feelings of shame, helplessness, inferiority, incompetence, inadequacy, and hypersensitivity to evaluation (Boldero et al., 2015; Rose, 2002).

Narcissists have fragile self-esteem, particularly when faced with competition (Geukes et al., 2017), and this fragility is thought to account for certain narcissistic behaviors such as aggression (for review, see Kernis, 2003; Zeigler-Hill, Clark, Ó 2018 Hogrefe Publishing

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& Pickard, 2008). Grandiose narcissistic behaviors are an attempt to hide feelings of inferiority (Bosson et al., 2008).

Specifically, the high explicit self-esteem observed in narcissists is an attempt to cover up underlying low implicit selfesteem and vulnerability (Vater et al., 2013).

Current Study Individuals with lower self-esteem engage in more sandbagging behavior; however, previous studies have not explored the possible role of narcissism. We propose a model in which the relationship between self-esteem and sandbagging is at least partially explained by narcissism.

Specifically, we propose that narcissists may engage in sandbagging in order to cope with fragile self-esteem. Vulnerable narcissism makes individuals hypersensitive to evaluation; this may motivate sandbagging as a protective strategy in which they are lowering expectations ahead of a performance in order to protect their self-esteem. On the other hand, the inflated self-image and manipulativeness found in grandiose narcissism could mean that narcissists might enjoy lowering expectations in order to surprise others with their ability. And given that vulnerable narcissism and grandiose narcissism are highly related to themselves, we expected that both processes could motivate the same sandbagging behavior. We hypothesized that, consistent with previous research (Brown, 2006; Gibson & Sachau, 2000; Petersen, 2013), individuals lower in self-esteem would engage in more sandbagging (Hypothesis 1, H1). We also hypothesized that grandiose narcissism and vulnerable narcissism (H2) would explain variance in sandbagging beyond that which is explained by self-esteem (H3). Additionally, because previous research has found that men have higher levels of narcissism (Foster, Campbell, & Twenge, 2003; Grijalva et al., 2015), self-esteem (Bleidorn et al., 2016; Feingold, 1994; Gentile et al., 2009), and sandbagging (Gibson & Sachau, 2000), we explored gender differences in these variables.

Method Participants Participants consisted of undergraduate students (N = 813) aged 18–30 years (M = 20.57, SD = 20.20; 71.2% female) enrolled in a psychology course at a large public university in the southern US Regarding ethnicity, 52.8% identified as white/Caucasian, 16.5% as black/African American, 19.7% as Hispanic, 8.0% as Asian/Pacific Islander, and 3.0% as another ethnicity. Participants were recruited through the department research website, where students can sign up Ó 2018 Hogrefe Publishing

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to participate in research studies in exchange for course credit. Students volunteered to take a personality survey.

Procedure This study was approved by the university committee for the protection of human subjects. Informed consent was obtained from all participants. Participants completed a survey online remotely.

Measures Sandbagging The Sandbagging Scale (SS; Gibson & Sachau, 2000) is a self-report measure of the tendency to withhold performance effort or falsely claim a lack of ability. The 12 items in the SS make up three subscales intended to represent the two hypothesized motivations for sandbagging: the desire to lower performance pressure (e.g., “The less others expect of me the better I like it”) and desire to exceed audience expectations (e.g., “It’s important that I surpass people’s expectations for my performance”); as well as the behavioral tendency to sandbag (e.g., “I understate my skills, ability, or knowledge”). Participants respond on a Likert-type scale ranging from 1 = disagree very much to 6 = agree very much.

Scores are summed to form a total score, with higher scores representing higher levels of sandbagging. In this study, Cronbach’s α for each subscale was: pressure (α = .78), exceeding expectations (α = .68), behavior (α = .64), and total sandbagging (α = .86).

Self-Esteem The Rosenberg Self-Esteem Scale (SES; Rosenberg, 1965) is a self-report measure of self-worth. The SES consists of 10 items (e.g., “I take a positive attitude toward myself”) to which participants respond using a 4-point Likert-type scale ranging from 1= disagree very much to 4 = agree very much. Item responses are summed to form a total score in which higher scores represent higher self-esteem (Cronbach’s α = .88).

Narcissism The Pathological Narcissism Inventory (PNI; for review, see Pincus et al., 2009) is a self-report measure of pathological narcissism. The PNI measures seven dimensions of narcissism, which are categorized into the subscales of narcissistic vulnerability and narcissistic grandiosity (Pincus, 2013; Pincus et al., 2009). Narcissistic vulnerability consists of contingent self-esteem (e.g., “I need others to acknowledge me”), hiding the self (e.g., “I hate asking for help”), devaluing (e.g., “When others disappoint me, I often get angry at myself”), and entitlement rage (e.g., “I will never be satisfied until I get all that I deserve”). Narcissistic grandiosity consists Journal of Individual Differences (2019), 40(1), 20–25

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M. D. Barnett et al., Sandbagging and the Self

Table 1. Bivariate correlations and descriptive statistics for all study variables (N = 813) 1

2

3

4

5

1. Gender

–

2. Sandbagging

.007

–

3. Pressure

.006

.86*

–

4. Exceeding Expectations

.05

.60*

.17*

–

5. Behavior

.03

.71*

.51*

.29*

6

7

8

–

6. Grandiose Narcissism

.01

.50*

.39*

.37*

.34*

–

7. Vulnerable Narcissism

.04

.48*

.48*

.18*

.35*

.76*

–

8. Self-Esteem

.04

.20*

.33*

.15*

.18*

.21*

.52*

–

M

SD

0.28

0.45

45.45

9.81

20.19

6.47

17.79

4.10

7.45

2.42

95.42

18.90

87.82

23.19

29.38

5.79

Notes. In analyses, gender was coded as 0 = female, 1 = male. *p < .001 (all two-tailed).

of exploitativeness (e.g., “I can make anyone believe anything I want them to”), grandiose fantasy (e.g., “I often fantasize about being admired and respected”), and self-sacrificing self-enhancement (e.g., “I help others in order to prove I’m a good person”). The PNI consists of 52 items to which participants respond using a 6-point Likert-type scale ranging from 1 = not at all like me to 6 = very much like me. Item scores were summed so that higher scores indicated higher levels of vulnerable narcissism (Cronbach’s α = .95) or grandiose narcissism (α = .89).

Results

sandbagging beyond that which is explained by self-esteem – we conducted two hierarchical multiple regressions. In both, sandbagging was the dependent variable, and selfesteem was the independent variable in the first step. In the first model, grandiose narcissism was entered as the independent variable in the second step; the second model was identical to the first except that vulnerable narcissism was used instead of grandiose narcissism. Both grandiose and vulnerable narcissism explained variance in sandbagging beyond that which was explained by self-esteem (ΔR2 = .26 and .24, respectively). Additionally, in both models, when the subfacet of narcissism was added to the model, the relationship between self-esteem and sandbagging was no longer significant.

Because of the large sample size and in order to minimize the risk of Type I error, we set α at the more stringent level of .01 rather than the traditional .05.

Post Hoc Analyses

Preliminary Analyses We conducted preliminary analyses to ensure that there were no violation of assumptions, including ruling out common method bias (Antonakis, Bendahan, Jacquart, & Lalive, 2010). In the Harman single-factor test, a single factor explained only 27.84% of the variance in observed variables. Additionally, the common latent factor method did not find large differences between the regressions with and without the common latent factor in the model. No gender differences were found on any study variables.

Bivariate correlations and descriptive statistics for all study variables are displayed in Table 1.

Primary Analyses In order to test H1 – that sandbagging is associated with lower self-esteem – we conducted a linear regression. Self-esteem (β = .20) explained 4.0% of the variance in sandbagging, F(1, 811) = 34.07. In order to test H2 and H3 – that grandiose and vulnerable narcissism would explain variance in Journal of Individual Differences (2019), 40(1), 20–25

As an exploratory component of the study, we investigated relationships between self-esteem, vulnerable and grandiose narcissism, and the three subfacets of sandbagging of reducing pressure, exceeding expectations, and behavior.

In order to do so, we conducted six additional hierarchical multiple regression analyses that were identical to the previous ones except that, instead of using the total sandbagging of the dependent variable, each one used one of the three subfacets as the dependent variable. As in the primary analyses, grandiose narcissism and vulnerable narcissism explained variance in each subfacet of sandbagging beyond that which was explained by self-esteem. Similar to the primary analyses in which self-esteem was associated with lower total sandbagging, self-esteem was associated with lower motivation to reduce pressure and sandbagging behavior; however, self-esteem was associated with higher motivation to exceed expectations. For the motivation to exceed expectations, adding grandiose narcissism increased the strength of the relationship between self-esteem and sandbagging. And, finally, the only two models that found that self-esteem was no longer significant with a narcissism variable in the model was vulnerable narcissism for the Ó 2018 Hogrefe Publishing

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Table 2. Summary of hierarchical regression analyses for grandiose and vulnerable narcissism on sandbagging, reducing pressure, exceeding expectations, and sandbagging behavior (N = 813) Regression analysis

β

B

SE B

95% CI

.34

.05

.20*

.45,

.22

Self-Esteem

.16

.05

.09

.26,

.06

Grandiose Narcissism

.25

.01

.48*

.21, .28

.34

.05

.20*

.45,

Self-Esteem

.12

.06

.07

.006, .24

Vulnerable Narcissism

.22

.01

.52*

.19, .25

.36

.03

.33*

.44,

.29

Self-Esteem

.28

.03

.25*

.35,

.21

Grandiose Narcissism

.11

.01

.34*

.09, .13

ΔR2

Primary analyses DV: Sandbagging Step 1 Self-Esteem

.04*

Step 2

.26*

DV: Sandbagging Step 1 Self-Esteem

.04* .22

Step 2

.24*

Post-Hoc analyses DV: Reduce Pressure Step 1 Self-Esteem

.10*

Step 2

.22*

DV: Reduce Pressure Step 1 Self-Esteem

.10* .36

.03

.33*

.44,

.29

Self-Esteem

.11

.04

.10

.19,

.03

Vulnerable Narcissism

.12

.01

.43*

.10, .14

.10

.02

.15*

.05, .15

Step 2

.24*

DV: Exceed Expectations Step 1 Self-Esteem

.02*

Step 2

.19*

Self-Esteem

.17

.02

.24*

.12, .21

Grandiose Narcissism

.09

.007

.42*

.07, .10

.10

.02

.15*

.05, .15

Self-Esteem

.24

.02

.34*

.19, .29

Vulnerable Narcissism

.06

.007

.26*

.05, .07

.07

.01

.18*

.10,

.05

Self-Esteem

.05

.01

.11*

.07,

.02

Grandiose Narcissism

.04

.004

.32*

.03, .05

.07

.01

.18*

.10,

DV: Exceed Expectations Step 1 Self-Esteem

.02*

Step 2

.12*

DV: Behavior Step 1 Self-Esteem

.03*

Step 2

.13*

DV: Behavior Step 1 Self-Esteem

.03* .05

Step 2

.12*

Self-Esteem

.001

.01

.002

.03, .03

Vulnerable Narcissism

.03

.004

.35*

.02, .04

Notes. B = unstandardized regression coefficient; DV = Dependent Variable. *p < .001 (two-tailed).

Ó 2018 Hogrefe Publishing

Journal of Individual Differences (2019), 40(1), 20–25

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motivation to reduce pressure and sandbagging behavior.

The summary of all hierarchical multiple regression results are displayed in Table 2.

Discussion Previous research has found gender differences in narcissism (Foster et al., 2003; Grijalva et al., 2015), self-esteem (Bleidorn et al., 2016; Feingold, 1994; Gentile et al., 2009), and sandbagging (Gibson & Sachau, 2000). We found no gender differences in any of these variables. Consistent with previous research (Brown, 2006; Gibson & Sachau, 2000; Petersen, 2013), lower self-esteem was associated with more sandbagging, supporting H1. After controlling for self-esteem, both grandiose and vulnerable narcissism explained additional variance in sandbagging, supporting H2 and H3. In fact, when grandiose or vulnerable narcissism was added to the model, the relationship between selfesteem and sandbagging was no longer significant, suggesting that narcissism may subsume the relationship between self-esteem and sandbagging.

Grandiose and vulnerable narcissism explained variance in each subfacet of sandbagging beyond that which was accounted for by self-esteem. Self-esteem was associated with lower motivation to reduce pressure and sandbagging behavior; however, it was associated with higher motivation to exceed expectations. The exceeding expectations’ dimension resembles achievement motivation, the extent individuals differ in their need topursue goals toattain rewards such as praise from others and mastering skills (Rabideau, 2005).

Previous research has found that self-esteem is associated with higher achievement motivation (Nwankwo, Obi, & Agu, 2013). The motivation to exceed expectations was associated with higher self-esteem, grandiose narcissism, and vulnerable narcissism. In fact, when the narcissism variables were included in the models, the relationship between selfesteem and the motivation to exceed expectations became stronger. This suggests a suppressor effect in which narcissism purges self-esteem of any unstable (grandiose or vulnerable) component, thereby increasing the strength of the relationship between self-esteem and the motivation to exceed expectations. Finally, two models found that selfesteem was no longer significant withnarcissism in themodel.

Vulnerable narcissism fully explained the relationship between self-esteem and the motivation to reduce pressure and sandbagging behavior. This suggests that the fragile self-esteem of vulnerable narcissism may motivate sandbagging in order to reduce pressure – presumably because vulnerable narcissists are hypersensitive to criticism.

Limitations of this study include the use of a convenience sample, which was predominantly female (71.2%), limiting Journal of Individual Differences (2019), 40(1), 20–25

M. D. Barnett et al., Sandbagging and the Self

the generalizability of the findings. The cross-sectional design limits conclusions that can be drawn about causality and the directionality of the results. The use of self-report measures means that the study variables were subject to response biases. Despite these limitations, this study suggests directions for future research. Experimental or longitudinal research designs may help clarify questions related to the causality and directionality of results as well as allow for the testing of narcissism as a mediator between sandbagging and self-esteem. Exploring self-efficacy or perceived likelihood of success or failure may expand this research; it is possible that vulnerable narcissism may be involved in situations in which an individual feels that failure is more likely and grandiose narcissism is involved in those with which success is more likely. Future studies should include analyses of the subfacets of sandbagging since unique relationships were found.

Overall, the results of this study suggest that the relationship between low self-esteem and sandbagging may be largely attributed to underlying vulnerable and grandiose narcissism. Narcissists may engage in more sandbagging because they are hypersensitive to evaluation (Boldero et al., 2015; Rose, 2002), and their self-esteem is particularly fragile when they are faced with competition (Geukes et al., 2017).Narcissists may engage in sandbagging before a performance in order to resolve the dissonance that stems from viewing themselves as superior yet potentially being negatively evaluated. By sandbagging, they are attempting to manage their fragile self-esteem by trying to convince themselves and others that their self-esteem is not at stake in the performance. Thus, sandbagging may stem not from self-esteem or the lack thereof but rather from the fragility of self-esteem.

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Vater, A., Ritter, K., Schröder-Abé, M., Schütz, A., Lammers, C., Bosson, J., & Roepke, S. (2013). When grandiosity and vulnerability collide: Implicit and explicit self-esteem in patients with narcissistic personality disorder. Journal of Behavior Therapy and Experimental Psychiatry, 44, 37–47. https://doi.org/ 10.1016/j.jbtep.2012.07.001 Wink, P. (1991). Two faces of narcissism. Journal of Personality and Social Psychology, 61, 590–597. https://doi.org/10.1037/ 0022-3514.61.4.590 Zeigler-Hill, V., Clark, C. B., & Pickard, J. D. (2008). Narcissistic subtypes and contingent self-esteem: Do all narcissists base their self-esteem on the same domains? Journal of Personality, 76, 753–774. https://doi.org/10.1111/j.1467-6494.2008.00503.x Received February 9, 2017 Revision received February 13, 2018 Accepted February 21, 2018 Published online August 31, 2018 Michael D. Barnett Department of Psychology University of North Texas 1155 Union Circle #311280 Denton TX 76203 USA michael.barnett@unt.edu

Journal of Individual Differences (2019), 40(1), 20–25

Original Article

The Motivation for Facebook Use – Is it a Matter of Bonding or Control Over Others?

Evidence From a Cross-Cultural Study Rayna Sariyska,1 Bernd Lachmann,1 Cecilia Cheng,2 Augusto Gnisci,3 Ida Sergi,3 Antonio Pace,3 Katarzyna Kaliszewska-Czeremska,4 Stéphanie Laconi,5 Songfa Zhong,6 Demet Toraman,7 Mattis Geiger,1 and Christian Montag1,8 1

Institute of Psychology and Education, Ulm University, Ulm, Germany

2

Department of Psychology, University of Hong Kong, Hong Kong Department of Psychology, University of Campania “Luigi Vanvitelli”, Italy

3 4

Institute of Psychology, The Jesuit University Ignatianum in Krakow, Poland Department of Psychology, University of Toulouse II – Le Mirail, Toulouse, France Department of Economics, University of Singapore, Singapore

5 6 7

Department of Psychology, University of Bonn, Germany

8

The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, China

Abstract: In the present study, we investigated individual differences in the motivation for Facebook use. In total N = 736 participants from Europe and Asia took part in the study. They filled in the Facebook questionnaire (FQ), including the two factors Attitude toward Facebook and Online Sociability, and the Unified Motive Scale (UMS-3), measuring the motives Achievement, Affiliation, Intimacy, Power, and Fear. The results showed that the Attitude toward Facebook was more positive in the subsample from Asia, but no differences could be found between the Asian and European sample with respect to the frequency of use of different activities on Facebook. The motives Fear, Power, Affiliation, and Intimacy significantly predicted the FQ factor Attitudes. Furthermore, the Attitude toward Facebook mediated the associations between the motives Power/Affiliation and Online Sociability. However, these results were only found for the European sample. The associations found suggest the important role of different motives such as Power/Affiliation for the study of Facebook use. The present work shows the possibility of motivational factors for Facebook use to differ depending on the culture. The study adds to the literature by investigating a classic motivation theory in the context of Facebook use.

Keywords: motives, Facebook, personality, cross-cultural

The increasing popularity of the Internet and one of its most prominent social network platforms – Facebook – raises numerous questions about its impact on society. As a consequence, research in Internet and in particular Facebook usage is rapidly growing in the last years. The present study aims to examine potential motivational factors underlying Facebook use. Therefore, this work tries to carve out factors explaining why humans spend much of their everyday lives on this digital platform.

Facebook is to date one of the most popular online social networking sites (SNS; see Sigerson & Cheng, 2018 for a review). It was launched in the year 2004 as a platform for Harvard University students and later expanded

Journal of Individual Differences (2019), 40(1), 26–35 https://doi.org/10.1027/1614-0001/a000273

dramatically (Facebook, 2016), after allowing access to the general population. Facebook originated in the US, but approximately 83.6% of daily active users are outside the US and Canada (Facebook, 2016), with Facebook available in over 70 languages (Schonfeld, 2010). Because of its growing importance as a tool for communication among others, a growing body of research concentrates on exploring different factors behind the (problematic) use of Facebook like personality and psychopathological tendencies (Ross et al., 2009; Ryan & Xenos, 2011). Of particular importance are studies trying to disentangle the motivation behind Facebook use and addictive tendencies in social network use.

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R. Sariyska et al., Facebook use and Motivation

Among the theories on the motivations behind Internet use, the Uses and gratifications theory (shortly called U&G), a mass communication theory, has been an important theoretical platform. This theory suggests that individuals actively choose the kind of media they use, depending on their needs and goals (see Cutler & Danowski, 1980; Lin, 1977; Ruggiero, 2000).

Several studies investigated the associations between U&G theory and SNS use. Ryan, Chester, Reece, and Xenos (2014) reported that the main uses and gratifications of Facebook are relationship maintenance (fostering existing relationships) and passing time.1 Entertainment (“using Facebook to engage in socially passive activities, such as (. . .) playing games”, p. 136), companionship (“to avoid loneliness and gratify interpersonal needs”, p. 136), and escapism (using Facebook to escape from negative mood), although less often, were also reported to be linked to Facebook use. Chabrol, Laconi, Delfour, and Moreau (2017) reported that passing time, virtual community,2 and entertainment were predictors of Facebook Use Disorder (FUD).3 Bischof-Kastner, Kuntsche, and Wolstein (2014) examined the motivation for Internet use as based on the Motivational Model of Alcohol Use (Cox & Klinger, 1988), which was later applied to the context of Facebook use. The authors adapted a questionnaire, measuring motives for drinking into an Internet Motive Questionnaire for Adolescents (IMQ-A). Based on the presumption that striving for positive emotions and decreasing/eliminating negative feelings is the primal root of motivation for humans’ behavior (McClelland, 1987), the Motivational Model of Alcohol Use assesses motivation with respect to the dimensions valence (enhancing positive emotions/diminishing or eliminating negative emotions) and origin of affective change (internal or external source) (Cox & Klinger, 1988). Four motives result from this model: enhancement (increase positive feelings, internal source), coping (reduce negative feelings, internal source), conformity (reduce negative feelings, external source), and social (increase positive feelings, external source). Regarding Internet use, Bischof-Kastner et al. (2014) reported that the motives for enhancement and coping were associated with the high-risk group of Internet users, whereas the low-risk group primarily used the Internet to fulfill social needs.

Marino, Vieno, Moss, et al. (2016) applied the same questionnaire in the context of FUD. The motives for coping and conformism mediated the relationship between emotional stability and FUD. Additionally, the motive enhancement directly predicted FUD. However, social motivation was 1 2 3

4

27

not linked to FUD, suggesting different mechanisms underlying dysfunctional use of Facebook compared to using Facebook for social purposes.

The aim of the present article is to further examine the motivation for Facebook use by applying the Unified Motive Scale (UMS; Schönbrodt & Gerstenberg, 2012). The UMS questionnaire measures the motives Achievement, Power, Affiliation (McClelland, 1987), and Intimacy (McAdams, 1980). Achievement can be described as pursuing excellence in all areas of life and Power as the concern to control others. While Affiliation is often characterized as the need for social bonding to rather unfamiliar people, Intimacy focuses on closer relationships between individuals (Schönbrodt & Gerstenberg, 2012). Described in the Three Needs Theory (McClelland, 1987; and later extended by McAdams, 1980) these motives are thought to affect human’s actions and shape human’s behavior. Combining these four motives in terms of approach motivation, the UMS was designed to also measure their counterparts, incorporated in the Fear scale (e.g., Fear of failure, Fear of losing control and Fear of rejection) on the side of avoidance motivation (Schönbrodt & Gerstenberg, 2012). To the authors’ knowledge, this theoretical framework has not been investigated in the context of Facebook use so far.

Probably the most obvious motivation for using Facebook is the opportunities that it offers for socializing. In this context, the motives Affiliation and Intimacy might be of particular importance. Next to the studies reported above, Ellison, Steinfield, and Lampe (2007) showed a strong association between the use of Facebook and social capital.4 Marino, Vieno, Pastore, et al. (2016) demonstrated the role of social influence processes such as subjective and group norms for FUD and frequency of Facebook use. In a review of over 400 articles on Facebook research, Wilson, Gosling, and Graham (2012) reported that staying connected with friends is among the most common motives for using Facebook. Moreover, the same review also indicated reducing loneliness as an important motivation for Facebook use.

Wegmann and Brand (2016) demonstrated the particular importance of social aspects such as social loneliness and loss of social support for the development of Internet-Communication Disorder. These results point out the importance to also include further person and environmental factors in the context of Facebook use (disorder) and again suggest a link between the motives Affiliation/Intimacy and Facebook use.

However, personality traits linked to negative emotionality were also associated with Facebook use. Shepherd and

Passing time means occupying time when bored (Sheldon, 2008).

Virtual community describes interaction with people met online (Sheldon, 2008).

The terms Facebook Use Disorder and Internet-Communication Disorder (another term for SNS addiction) are derived from the latest developments in DSM-5, where Internet-Gaming Disorder was included into Section III: Conditions for further study (DSM History, 2017).

Social capital refers to acquiring benefits through interactions with others (Ellison et al., 2007).

Ó 2018 Hogrefe Publishing

Journal of Individual Differences (2019), 40(1), 26–35

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Edelmann (2005) proposed that the Internet may offer an alternative for face-to-face interactions for people, who are rather anxious. Bodroža and Jovanović (2016) reported that among different personality characteristics, high social anxiety was the most robust predictor of different aspects of Facebook use such as compensatory use, self-presentation, or addiction. A couple of studies demonstrated the role of Fear of Missing out (FoMO; “(. . .) a pervasive apprehension that others might be having rewarding experiences from which one is absent (. . .)”, Przybylski, Murayama, DeHaan, & Gladwell, 2013, p. 1841) for SNS/Facebook use (disorder) (Beyens, Frison, & Eggermont, 2016; Wegmann, Oberst, Stodt, & Brand, 2017).

Further research, linking individual differences in neuroticism or similar traits to individual differences in human motives explicitly shows a link between neuroticism and avoidance motivation (Engeser & Langens, 2010), as well as the motive for Fear reduction (Schönbrodt & Gerstenberg, 2012). Based on the presented empirical studies, we assume that the Fear motive might also predict Facebook use. However, despite the link between Fear and emotional instability, these concepts should not be assumed to be equal (this is also mirrored in the medium-size correlation between Fear and neuroticism as reported by Schönbrodt & Gerstenberg, 2012). It is rather assumed that personality and motivation interact to affect behavior (on the other hand, individual differences in motivational traits can be also seen as part of personality, Montag & Panksepp, 2017). Thus, investigating the motive Fear will add to the literature and further shed light on the mechanisms, which direct the use of Facebook.

While the potential link between Affiliation, Intimacy, Fear, and the use of Facebook is rather obvious, the motive Power might be another candidate to explain Facebook use.

The fact that we gain a lot of information about others based on their Facebook activities and posts, might make interaction with others easier and, in turn, help to maintain interpersonal relationships. However, there is also a dark side of information sharing through social media since it can be used to control others and even for the purpose of manipulative behavior. The motivation to control others (mirrored in the Power motive) has rarely been investigated in the context of Facebook use to date. However, personality research points toward a link between narcissism,5 psychopathy,6 and Machiavellianism7 (also known as the Dark Triad of personality) and different Facebook activities such as semantic content of status updates (Garcia & Sikström, 2014) or (dishonest) self-promotion through Facebook

5

6 7

R. Sariyska et al., Facebook use and Motivation

(Abell & Brewer, 2014). These results show that manipulation of others’ behavior can be performed also in the online world through (dishonest) self-presentation, embarrassing others, etc., and that SNS like Facebook offer a platform for such behaviors. Also the concept of being an influencer (vs. a follower), hence a person, who is strongly visible online and followed by many on platforms such as Facebook, Instagram, and Twitter could manifest in a higher Power motive. Thus, it is of high relevance to examine the role of motivational factors next to classic personality variables in this context.

Last but not least, since Facebook is an international online platform, it is of interest to consider the potential influence of different cultures on Facebook use. In this context Vasalou, Joinson, and Courvoisier (2010) reported that the importance of use of various Facebook activities differed with respect to country. In a recent study, Błachnio et al. (2016) pointed toward some potential differences in the associations between FUD and personality variables, depending on the culture (in this study also universal predictors of FUD were found).

Compared to prior approaches to describe motivation for Facebook use which stem from mass communication research (e.g., U&G theory) or base on models for substance use (e.g., Motivational Model of Alcohol use), in the current study we focused on a well-established psychological theory (The Three-Need Theory) and applied an elaborate (conceptually and empirically) questionnaire (UMS-3) to measure explicit motives. This study aims at helping to place results from studies, exploring different motivational factors in the context of Facebook use, into an elaborated theoretical framework. Moreover, next to the role of social motivation and avoidance motivation for the use of Facebook, the potential link between the motivation to control others (mirrored in the Power motive) and Facebook use will also be examined. Last but not least, because of its cross-cultural character, the study allows to consider potential differences in the relationship between motivation and Facebook use across different countries/cultures.

Based on the literature, presented above, we focus on the following hypotheses: Hypothesis 1: We expect positive associations between the motives for Affiliation, Intimacy, Fear, and Facebook use, measured with the Facebook questionnaire (FQ) variables, described in detail in the section Material and Methods.

Narcissism is a personality characteristic that describes persons having a “(. . .) grandiose sense of self (. . .)” (Ames, Rose, & Anderson, 2006, p.

440).

Psychopathy describes a more impulsive personality, further characterised with low empathy (Hare, 1985).

Machiavellianism as a personality trait depicts a tendency to manipulative behaviour and cynism (Abell & Brewer, 2014).

Journal of Individual Differences (2019), 40(1), 26–35

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29

Affiliation

Fear FQ Attitudes

FQ Online Sociability

Intimacy

Power

Figure 1. Proposed structural equation model on the associations between explicit motives and the Facebook questionnaire (FQ) factors.

Hypothesis 2: We expect that Power will be linked to the FQ variables. Here, we refrain from postulating a direction for this potential relationship because of sparse research in this field. Nevertheless, given the modern concept of being an influencer versus a follower, a positive association would be meaningful.

Hypothesis 3: We expect that the Attitude toward Facebook would mediate the relationship between the motives Affiliation, Intimacy, Power, Fear, and the Facebook factor Online Sociability (see Figure 1). Both Attitude and Online Sociability are assessed with the FQ.

Material and Methods Participants Participants from seven different countries took part in an online survey. After excluding participants due to missing values or because they did not own a Facebook account at the time the study was conducted, the whole sample resulted in N = 736 participants. The distribution of the subsamples was n = 54 from France (n = 20 males), n = 97 from Germany (n = 21 males), n = 259 from Italy (n = 79 males), n = 60 from Poland (n = 17 males), n = 105 from Turkey (n = 45 males), n = 103 from Hong Kong (n = 44 males), and n = 58 from Singapore (n = 27 males). The average age for the total sample was M = 22.97 (SD = 5.99). Seven participants reported being younger than 18 years of age.

The choice of countries, which participated in the project, was based on our efforts to represent different parts of the world like Western Europe (Germany, France), Eastern Europe (Poland), Southern Europe (Italy), and Asia (Turkey, Hong Kong, Singapore). Please note, that we explain below in more detail, why the Turkish sample is part of the Asian group.

The recruitment of the participants in the different countries was accomplished by our cooperation partners mostly Ó 2018 Hogrefe Publishing

at universities. Each participant was informed about the study, before giving a digital consent. Participants did not receive any monetary compensation for their participation.

The study was approved by the Local Ethic Committee of the University of Bonn, Germany.

Materials The Facebook questionnaire (FQ, Ross et al., 2009) in its original form includes 28 items on Facebook usage, which are assessed on different scale format: Response alternatives range from yes/no to 9-point scale multiple-choice options. Of particular interest for the present study are two factors, extracted by Ross et al. (2009) through a factor analysis: Attitudes (e.g., “How satisfied are you with Facebook overall?”) and Online Sociability functions (e.g., “How often do you send private messages?”). However, this questionnaire was shortened due to economic reasons (a list of the items, measuring Attitudes and Online Sociability, used in this study is presented in the Electronic Supplementary Material, ESM 1, Table 1). This resulted in reducing the number of items of the variables Attitudes (from 7 to 6) and Online Sociability (from 5 to 4). Cronbach’s α for the whole sample was satisfying: α = .83 (Attitudes) and α = .75 (Online Sociability). Internal consistencies for the subsamples can be found in ESM 1, Table 2.

The Unified Motive Scale (UMS-3, Schönbrodt & Gerstenberg, 2012) is a short measure of explicit motives, consisting of three items per motive. It measures the motives Achievement, Power, Affiliation, Intimacy, and Fear. Three Fear facets can be assessed with this questionnaire: Fear of being rejected, Fear of failure, and Fear of losing control.

However, for reliability reasons the authors of the questionnaire suggest to apply the whole scale since every of the Fear subscales is measured with one item respectively.

Seven items are rated on a 6-point scale from 1 = strongly disagree to 6 = strongly agree and eight items are rated on a scale from 1 = not important to me to 6 = extremely important to me. Cronbach’s α for the total sample was .62 for Power, .72 for Achievement, .70 for Affiliation, .67 for Intimacy, and .70 for Fear (see detailed results for the subsamples in ESM 1, Table 2).

Conceptual and Measurement Equivalence First, we examined possible measurement variability with respect to country/language. Conceptual equivalence was established with the help of experts in the area of psychology in the different countries under investigation. Translation and back-translation in English were conducted by psychologists, whose native language is the language of the particular country and who are also fluent in English.

Journal of Individual Differences (2019), 40(1), 26–35

30

The reason for this course of action was that experts in psychology would deliver most precise translation because of their expertise. When receiving the back-translation we were able to communicate problems, if any, concerning the constructs measured and the way they are understood in the particular country. Measurement invariance8 was examined using the package Lavaan in R (Rosseel, 2012).

As our samples per nation were not large enough to conduct invariance testing, we merged them to larger groups.

Here, we focused on samples stemming from similar geographical regions, in order to take into account potential cultural differences. Moreover, samples were combined when their composition was similar with regard to gender and age distribution. Following this approach, we combined samples from France, Germany, Italy, Poland to one group (referred to as “Europe,” n = 470) and samples from Hong Kong, Singapore, Turkey9 to another group (we will refer to it as “Asia,” n = 266). The following analyses were conducted, using those two samples.

Statistical Analyses As part of assessing measurement invariance, confirmatory factor analyses (CFAs) were conducted for every questionnaire and every sample. Structural equation modeling (SEM) was used to test Hypothesis 3. The CFA and SEM were conducted, using R. To assess the model fit we used root mean square error of approximation (RMSEA), the standardized root mean square residual (SRMR), and comparative fit index (CFI). CFI values > .90 represent an acceptable fit, > .95 a good fit. RMSEA values close to .06 represent a good model fit while values < .08 indicate an acceptable model fit. SRMR values close to .08 indicate a good fit (Hu & Bentler, 1995, 1999; MacCallum, Browne, & Sugawara, 1996). To evaluate measurement invariance, the following cut-off criteria were applied for loading invariance for samples with n > 300 a change of .010 in CFI, a change of .015 in RMSEA, and a change of .030 in SRMR indicate measurement variance. For n < 300 a change of .005 in CFI, a change of .010 in RMSEA, and a change of .025 in SRMR indicate measurement variance (Chen, 2007).

Descriptive statistics on demographics, FQ variables, and motives were computed. Then, variables were assessed for

R. Sariyska et al., Facebook use and Motivation

normal distribution, by evaluating the skewness and kurtosis of the variables (Miles & Shevlin, 2001; see ESM 1, Table 3). Correlation analyses were conducted using the latent variables. When testing for mediating effects as part of the SEM model, it was required that all variables correlated with each other.

Results CFA and Measurement Invariance First, we combined the samples as described in the Conceptual and Measurement Equivalence section. CFAs were conducted for each sample separately. Here, for the UMS-310 questionnaire, the following results were observed: for the European sample w2(79) = 219.501, p < .001, CFI = .901, RMSEA = .062, SRMR = .054; for the Asian sample w2(79) = 204.590, p < .001, CFI = .906, RMSEA = .077, SRMR = .067. For the Facebook questionnaire (two-factor solution), the following results were observed: for the European sample w2(34) = 128.274, p < .001, CFI = .933, RMSEA = .077, SRMR = .064; for the Asian sample w2(34) = 101.068, p < .001, CFI = .936, RMSEA = .086, SRMR = .061. Thus, the models for both questionnaires showed an acceptable fit in both samples.

Next, we tested for measurement invariance (fit indices are presented in Table 1).

Here, results showed that metric invariance was fulfilled for both the UMS-3 and the Facebook questionnaires (see cut-off criteria, described in the Statistical Analyses section). Here the factor loadings were set to be equal across both the European and Asian samples. Further analyses showed that the requirements for scalar11 and strict12 invariance were not fulfilled. However, since metric invariance was given, we proceeded with testing our hypotheses based on the same measurement models (Chen, 2007).

Descriptive Statistics In total 47% of participants in the European sample and 41% of participants in the Asian sample spent one or more hours daily on Facebook. Descriptive statistics for all of the

Measurement invariance implies that “(. . .) an instrument has the same psychometric properties across heterogenous groups (. . .)” (Chen, 2007, p. 465).

9 We are aware of the fact that a small part of Turkey is located in Europe. However, according to our cooperation partner, responsible for recruiting the Turkish sample, participants were recruited mostly in cities, positioned on the Asian continent (Ankara and Samsun) and some of the participants in Istanbul. Nevertheless, for transparency reasons we report the results for the Turkish sample separately in the ESM 1 (Table 4).

10 In order to achieve an acceptable model fit and based on content similarities, we allowed the residuals of the items “I like to have the final say.” and “I become scared when I lose control over things.” to correlate.

11 Here the intercepts are set to be equal in different groups (Chen, 2007).

12 Here residuals are set to be equal in different groups (Chen, 2007).

8

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Table 1. Fit indices for measurement invariance w2(df)

RMSEA

SRMR

CFI

Configural

424.09 (158)

.068

.055

.903

n/a

n/a

Metric

436.89 (168)

.066

.058

.902

.001

.235

Scalar

532.39 (178)

.074

.067

.871

.031

.000

Strict

759.15 (183)

.092

.095

.790

.081

.000

Configural

229.34 (68)

.080

.058

.934

n/a

n/a

Metric

240.12 (76)

.077

.062

.933

.001

.215

Scalar

284.64 (84)

.081

.067

.918

.015

.000

Strict

299.19 (86)

.082

.073

.913

.005

.000

Model

Change CFI

Sign.

UMS-3

FQ

Note. Sign. = Significance; UMS-3 = Unified Motive Scale; FQ = Facebook Questionnaire.

Table 2. Descriptive statistics and comparison of means for the variables Power, Achievement, Affiliation, Intimacy, Fear, Attitudes and Online Sociability for both subsamples under investigation Group

Power

Achievement

Affiliation

Intimacy

Fear

Attitudes

Online Sociability

Europe (470)

10.56 (3.10)

14.07 (2.46)

13.37 (2.79)

14.72 (2.60)

11.76 (3.36)

2.87 (0.76)

5.59 (1.66)

Asia (266)

11.83 (2.65)

13.15 (2.86)

12.85 (2.83)

13.14 (2.62)

10.83 (3.35)

3.07 (0.86)

5.45 (1.81)

p < .01

p < .01

p < .05

p < .01

p < .01

p < .01

ns

t-test

Note. p values are two-tailed.

Table 3. Associations between the latent variables Power

Achievement

Affiliation

Intimacy

Fear

Europe (470) Attitudes

.170**

.076

.229**

Online Sociability

.214**

.111

.133*

.016 –.081

.187** –.007

Asia (266) Attitudes

.141

.013

.076

.160

Online Sociability

.062

–.085

.110

–.079

.188* –.056

Note. **p < .01, *p < .05 (all two-tailed).

variables under investigation, including mean, standard deviations and comparison of the means for both samples (using t-test since the variables were normally distributed) are presented in Table 2. Here, significant differences between both samples were found regarding all motives and for the FQ factor Attitudes. The samples did not differ in the frequency of use of different activities on Facebook (Online Sociability).

Facebook Use and Motivation (Hypotheses 1 and 2) The results from the correlation analyses with latent variables are presented in Table 3. Affiliation and Power were positively linked to the FQ variables in the European Ó 2018 Hogrefe Publishing

sample. Fear was positively linked to Attitudes in both samples. The associations between the latent variables Attitudes and Online Sociability were r = .574 (p < .01) for the European sample and r = .512 (p < .01) for the Asian sample. Thus, we found partial support for Hypotheses 1 and 2.

SEM (Hypothesis 3) Next, we tested the structural model depicted in Figure 1.

Since the condition for mediation analysis was that all of the variables are correlated, we only tested the mediation between Power – Attitudes – Online Sociability and Affiliation – Attitudes – Online Sociability, respectively (see Table 3).

The motives Fear and Intimacy were only set to predict Attitudes. The structural model was tested separately for the Journal of Individual Differences (2019), 40(1), 26–35

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R. Sariyska et al., Facebook use and Motivation

Discussion

Affiliation

Fear FQ Attitudes

.557

FQ Online Sociability

Intimacy

Power

Figure 2. Structural equation modeling results for the European sample. FQ = Facebook Questionnaire; solid line p < .05, dashed line p > .05, p values are two-tailed.

Affiliation

Fear FQ Attitudes

.522

FQ Online Sociability

Intimacy

Power

Figure 3. Structural equation modeling results for the Asian sample. FQ = Facebook Questionnaire; solid line p < .05, dashed line p > .05, p values are two-tailed.

European and the Asian sample. Despite mostly nonsignificant associations between the variables in the Asian sample, the structural equation model was conducted for the purpose of consistency.

The results for the European and Asian sample are presented in Figures 2 and 3, respectively. The proposed model showed the following fit for the European sample: w2(195) = 466.141, p < .001, CFI = .894, RMSEA = .054, SRMR = .057. Both, the indirect effect for Power and Affiliation gained significance: β = .078, p < .05 and β = .162, p < .01, respectively. Moreover, Fear and Intimacy significantly predicted the FQ factor Attitudes.

The model fit for the Asian sample was as follows: w2(195) = 414.269, p < .001, CFI = .888, RMSEA = .065, SRMR = .072. Here none of the indirect effects for Power and Affiliation gained significance (p = .677 and p = .731, respectively). Furthermore, none of the associations between motives and the FQ factors gained significance.

13

The aim of the present study was to investigate the role of classic motives in the context of Facebook use and, thus, provide a grounded theoretical framework for the relationship between motivation and the use of Facebook. The results of the study showed that the motives Affiliation, Power, and Fear were positively and Intimacy negatively associated with the FQ factor Attitudes in the European sample. In addition, the FQ variable Attitudes significantly mediated the relationship between the motives Affiliation, Power and the FQ variable Online Sociability. These results could not be replicated for the Asian sample where mostly nonsignificant associations were found.

In general, the positive association between the motive Affiliation and the FQ factors, reported for the European sample, confirms already existing findings (Ellison et al., 2007; Marino, Vieno, Pastore, et al., 2016; Ryan et al., 2014). In the present study, the motive Affiliation was directly related to the Attitude toward Facebook and indirectly to Online Sociability. Thus, participants who are motivated to maintain relationships with others (high Affiliation motive) have a rather positive Attitude toward Facebook and consequently use it more often for different social activities.

However, the association between Attitude and the motive Intimacy was negative. This could be explained through the fact that, although both motives describe the desire to be part of social groups and to belong, the motive Affiliation is more concerned with (loose) relationships with rather unfamiliar people, whereas Intimacy focuses more on close relationships (Sokolowski & Heckhausen, 2008). These findings further shed light on the kind of relationships, maintained through Facebook, adding to studies, having reported an off-to-online manner13 of relationships through Facebook (Ellison et al., 2007).

The Fear motive, also embodying the dimension of avoidance motivation, was positively related to the FQ factor Attitudes. This means, the stronger the fear of losing control or being rejected (in the real world), the more positive the Attitude toward Facebook. As outlined in the introductory section of this article, people might exert preference for online communication, because this allows more distance to the communication partner, anonymity and, thus, less direct vulnerability to negative feedback (Caplan, 2010). In the context of Internet Use Disorder, Caplan (2010) demonstrated that the preference for online social interaction predicted using the Internet for mood regulation, deficient self-regulation and, in turn, negative outcomes due to Internet use. The model by Caplan (2010) has also shown its applicability in the context of Facebook

An off-to-online use is characterized by using Facebook to maintain offline relationships, compared to building new online friendships (Ellison et al., 2007).

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use (see Marino, Vieno, Altoè, & Spada, 2016; Marino, Vieno, Moss, et al., 2016; Marino, Vieno, Pastore, et al., 2016). Thus, it is possible that avoidance motivation (here measured with the Fear motive) might lead to a positive Attitude toward SNS and to a preference for online social interaction, which might then result in more frequent SNS use/addiction. However, this assumption is beyond the scope of this article and should be tested in future studies.

Interestingly, Fear was associated with the Attitude toward Facebook, but not with the frequency of social Facebook use (Online Sociability). Future studies should incorporate more variables next to the motives investigated in the current study to be able to reliably predict behavior (see recently proposed I-PACE model for specific Internet Use Disorder by Brand, Young, Laier, Wölfling, & Potenza, 2016). In this context, Graham and Gosling (2013) investigated the link between personality and motives for playing World of Warcraft and reported different personality profiles, depending on the motivation for playing. For instance, social motivation was positively linked to extraversion, agreeableness, neuroticism, and openness, whereas achievement motivation was negatively linked to agreeableness, conscientiousness, and openness as well as positively linked to extraversion and neuroticism. Similar investigations might be of interest in the area of Facebook use (disorder).

The results of the present study also support the assumption that people are motivated to use Facebook to control others, since Power was associated with Attitudes and Online Sociability (in the European sample). Thus, next to the opportunity to communicate with others and participate in online social activities, Facebook also offers a platform where information is exchanged, which can be used to control or manipulate behavior. These results also add to studies showing a link between (the Dark Triad of) personality and Facebook use. Discussing the exact mechanisms of exerting control over others through Facebook is beyond the scope of this article. However, existing literature stemming from personality research suggests a link between the use of “cheater strategies” like editing pictures before posting or relational aggression (e.g., embarrassing people on Facebook through posts) and the Dark Triad of personality (Abell & Brewer, 2014; Fox & Rooney, 2015). Here again, investigating the interplay between the Power motive and personality variables might shed more light on manipulative behavior on Facebook.

It is important to notice that the FQ variables were related to the motives Affiliation, Intimacy, Power, and Fear only in the European sample. As outlined in the Introduction of this article, a couple of studies already reported cultural differences regarding Facebook use (Błachnio et al., 2016; Vasalou et al., 2010; Wilson et al., 2012). Moreover, in the current study differences between the European Ó 2018 Hogrefe Publishing

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and Asian sample were reported with respect to motivation (see Table 2). Thus, it is possible that patterns of motivation for Facebook use differ depending on the culture. However, these results need to be replicated in future studies.

Last but not least, different kinds of external motivation/pressure, supported by Facebook, such as the possibility to add content or the birthday reminder function to name a few were shown to have an impact on Facebook use (see Wilson et al., 2012). Thus, the combined investigation of external and internal motivational factors might be important to fully understand what drives people to spend large amount of time using this social networking platform.

Strengths and Limitations One strength of the present study is the foundation of the research question on a theoretical framework concerning the relationship between Facebook use and motivation (McClelland, 1987) incorporated in the model of Schönbrodt and Gerstenberg (2012). In addition, this approach is, to some extent, suited to organize repetitive results of earlier studies in a more comprehensive way. Another strength of this study is its cross-cultural design with multiple samples, which allows cross-cultural comparisons. However, since the assignment to one of the two samples was based on geographical location and sample composition, the cultural comparison results need to be interpreted with caution. Future studies might consider applying a measure of culture to further justify the combination of samples to larger ones. A limitation of the present study is its cross-sectional design, which does not allow for causal implications.

Moreover, some samples were relatively small and homogenous (most of the participants were students), hence, possibly restraining the generalizability of the effects to some extent. Further, self-report measures are used and these measures are susceptible to response biases such as social desirability and acquiescence bias (Sigerson & Cheng, 2018), and future studies may replicate the present study with objective data such as application programming interface and objective logs.

Conclusion In summary, for the European sample a stronger motivation for social bonding (Affiliation – concerning rather loose relationships with acquaintances) and the need to control others (Power) were linked to a positive Attitude toward Facebook. Furthermore, the Attitude toward Facebook mediated

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the relationship between the motives Affiliation/Power and the frequency of Facebook use (Online Sociability). Fear was positively linked to Attitudes, whereas the motivation for bonding with significant others (mirrored in the motive Intimacy) was negatively linked to the Attitude toward Facebook. Regarding the Asian sample, no significant associations between explicit motives and Facebook use could be found in the Structural Equation Model. Future investigations are needed to replicate the results of the current study.

Acknowledgments Funding: German Research Foundation (DFG, MO 2363/2-1).

The position of CM is funded by a Heisenberg grant awarded to him by the German Research Foundation (DFG, MO2363/3-2).

Electronic Supplementary Material The electronic supplementary material is available with the online version of the article at https://doi.org/10.1027/ 1614-0001/a000273 ESM 1. Tables 1–4 (.xlsx) Reliabilities, skewness/kurtosis and additional structural equation modeling results for the Turkish sample.

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Schonfeld, E. (2010). Facebook closing in on 500 million visitors a month. TechCrunch. Retrieved from https://techcrunch.com/ 2010/04/21/facebook-500-million-visitors-comscore/ Sheldon, P. (2008). The relationship between unwillingness-tocommunicate and students’ Facebook use. Journal of Media Psychology, 20, 67–75. https://doi.org/10.1027/18641105.20.2.67 Shepherd, R., & Edelmann, R. J. (2005). Reasons for internet use and social anxiety. Personality and Individual Differences, 39, 949–958. https://doi.org/10.1016/j.paid.2005.04.001 Sigerson, L., & Cheng, C. (2018). Scales for measuring user engagement with social network sites: A systematic review of psychometric properties. Computers in Human Behavior, 83, 87–105. https://doi.org/10.1016/j.chb.2018.01.023 Sokolowski, K., & Heckhausen, H. (2008). Social bonding: Affiliation motivation and intimacy motivation. In J. Heckhausen & H. Heckhausen (Eds.), Motivation and action (pp. 184–201). New York, NY: Cambridge University Press.

Vasalou, A., Joinson, A. N., & Courvoisier, D. (2010). Cultural differences, experience with social networks and the nature of “true commitment” in Facebook. International Journal of Human-Computer Studies, 68, 719–728. https://doi.org/ 10.1016/j.ijhcs.2010.06.002 Wegmann, E., & Brand, M. (2016). Internet-communication disorder: It’s a matter of social aspects, coping, and internet-use expectancies. Frontiers in Psychology, 7, 1–13. https://doi.org/ 10.3389/fpsyg.2016.01747 Wegmann, E., Oberst, U., Stodt, B., & Brand, M. (2017). Onlinespecific fear of missing out and internet-use expectancies contribute to symptoms of internet-communication disorder.

Addictive Behaviors Reports, 5, 33–42. https://doi.org/10.1016/ j.abrep.2017.04.001 Wilson, R. E., Gosling, S. D., & Graham, L. T. (2012). A review of Facebook research in the social sciences. Perspectives on Psychological Science, 7, 203–220. https://doi.org/10.1177/ 1745691612442904 Received November 5, 2016 Revision received February 9, 2018 Accepted March 8, 2018 Published online November 16, 2018 Rayna Sariyska Institute of Psychology and Education Ulm University 1.40 Helmholtzstr. 8/1 89081 Ulm Germany rayna.sariyska@uni-ulm.de

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Original Article

Pursuing the Dark Triad Psychometric properties of the Spanish Version of the Dirty Dozen Lorena Maneiro,1 Laura López-Romero,1,2 José Antonio Gómez-Fraguela,1 Olalla Cutrín,1 and Estrella Romero1 1

Department of Clinical and Psychobiological Psychology, Universidade de Santiago de Compostela, Spain

2

Center for Criminological and PsychoSocial research (CAPS), School of Law, Psychology and Social Work, Örebro Universitet, Sweden

Abstract: The Dirty Dozen scale is a short measure developed to assess the Dark Triad traits, namely Machiavellianism, psychopathy, and narcissism, which has previously shown good psychometric properties. The aim of this study was to validate a Spanish version of the Dirty Dozen through the assessment of its psychometric properties in a sample constituted by 326 young adults aged 18–34 (M = 20.55; SD = 1.89) from Spain. The Spanish version of the Dirty Dozen showed good internal consistency and acceptable test-retest stability. Likewise, the analysis of the factorial structure supported the three-factor solution and showed a best fit for the bifactorial model. The latent factor of the general Dark Triad was associated with low levels of Honesty/Humility, psychopathic traits, impulsivity, and sensation seeking; whereas a differential pattern of associations between the three specific Dark Triad latent factors and the nomological network was found. Furthermore, the Dark Triad traits showed differential relations with reactive and proactive aggression, verifying the external validity of the Spanish version of the Dirty Dozen. Results support the distinctiveness of the Dark Triad traits and justify the Dirty Dozen as an efficient measure for dark personalities in Spanish-speaking contexts.

Keywords: Dirty Dozen, Dark Triad, Machiavellianism, psychopathy, narcissism

The Dark Triad of personality has been proposed as a constellation of three socially aversive personality constructs in the subclinical range, namely Machiavellianism, psychopathy, and narcissism (Paulhus & Williams, 2002). Machiavellianism is characterized by a cynical disregard for morality and a focus on self-interest and personal gain, and involves strategic manipulation, callous affect, and alliance building (Christie & Geis, 1970). Psychopathy describes a complex of callousness and shallow affect, along with interpersonal manipulation and lack of self-control (Hare & Neumann, 2008). Lastly, narcissism concerns grandiose sense of self, manipulation, exploitative entitlement, and callousness (Campbell & Miller, 2011). Previous research on Dark Triad has evidenced meaningful associations with psychosocial correlates such as risky behaviors (Crysel, Crosier, & Webster, 2013), criminal offending (Flexon, Meldrum, Young, & Lehmann, 2016), aggression (Vize, Lynam, Collison, & Miller, 2018), substance use (Flexon et al., 2016), short-term mating preferences (Jonason, Li, Webster, & Schmitt, 2009), and fast-life strategies (Jonason, Koenig, & Tost, 2010).

The overlap among the Dark Triad traits has suggested the existence of a common antagonistic core of disagreeableness (Paulhus & Williams, 2002), lack of Honesty/Humility (Lee & Ashton, 2014), callousness and manipulation Journal of Individual Differences (2019), 40(1), 36–44 https://doi.org/10.1027/1614-0001/a000274

(Jones & Figueredo, 2013), and an exploitative social style (Jonason et al., 2009), nevertheless the unique pattern of correlations with different personality traits and behavioral outcomes supports the distinctiveness of the Dark Triad traits (Furham, Richards, & Paulhus, 2013; Jones & Paulhus, 2011a). Specifically, empirical evidence suggests that Machiavellianism, psychopathy, and narcissism may be best described by a single latent construct of callousness and antagonistic tendencies in conjunction with three specific factors, instead of independent, yet overlapping, traits (Bertl, Pietschnig, Tran, Stieger, & Voracek, 2017; McLarnon & Tarraf, 2017).

In order to evaluate the Dark Triad traits, Jonason and Webster (2010) developed the Dark Triad Dirty Dozen, a concise measure which overcomes the limitations of the use of single long measures regarding time consumption, while incorporating flexibility in the assessment of the Dark Triad as either a single, or a three-dimensional construct.

Despite some criticisms mainly derived from the high overlap between Machiavellianism and psychopathy, along with the reduction in the content in some of the subscales (Miller et al., 2012; Muris, Merckelbach, Otgaar, & Meijer, 2017), the Dirty Dozen scale has shown good and stable psychometric properties (e.g., Jonason & Luévano, 2013; Jonason & Webster, 2010; Webster & Jonason, 2013) and its utility Ó 2018 Hogrefe Publishing

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was proved across different populations and nationalities (e.g., Czarna, Jonason, Dufner, & Kossowska, 2016; Özsoy, Rauthmann, Jonason, & Ardıç, 2017).

The evaluation of Machiavellianism, psychopathy, and narcissism simultaneously contribute to the determination of the mutual and distinct effects of the Dark Triad traits.

Thus, given the lack of instruments of these characteristics in the Spanish language, the main goal of the current study was to validate a Spanish version of the Dirty Dozen. The psychometric properties regarding reliability (i.e., internal consistency and test-retest stability), factorial structure, and external validity were explored in a Spanish sample.

The nomological network of the Dark Triad was assessed regarding the HEXACO model (Lee & Ashton, 2004) and other specific personality traits such as impulsivity, sensation seeking, and psychopathic traits, as well as reactive and proactive aggression. Following the recommendations of Sleep, Lynam, Hyatt, and Miller (2017), structural equation models were carried out in order to overcome the limitations of partialing redux.

According to the predictions established, the Spanish version of the Dirty Dozen must show a three-factor solution and the factorial structure should be best explained by a bifactorial model, composed of a latent factor of the global Dark Triad, and three specific latent factors associated with the Dirty Dozen’s three subscales (i.e., Machiavellianism, psychopathy, and narcissism) (Bertl et al., 2017; Jonason & Luévano, 2013; McLarnon & Tarraf, 2017). Regarding nomological network, all Dark Triad traits are expected to show the highest relations with the HEXACO Honesty/Humility factor (Jonason & McCain, 2012; Muris et al., 2017). Likewise, psychopathy would be related to impulsivity, sensation seeking, and alternative measures of psychopathic traits, but impulsivity and sensation seeking are not expected to be associated with Machiavellianism and to a lesser extent with narcissism (Jones, & Paulhus, 2011a). Machiavellianism and narcissism would also be positively related to the callousness facet of psychopathy (Jones & Figueredo, 2013). In contrast, differential associations are expected with proactive and reactive aggression, with psychopathy showing the highest association (Jonason, Duineveld, & Middleton, 2015).

Machiavellianism would be higher associated with proactive aggression, while narcissism would be related to a larger extent with reactive aggression.

Method Participants The initial sample was composed of 326 young adults (47% males), aged 18–34 (M = 20.55; SD = 1.89), coming from Galicia (NW Spain). Part of the sample were participants Ó 2018 Hogrefe Publishing

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enrolled in the Faculty of Psychology who completed the questionnaires during seminar time (N = 157). These subjects were asked about potential participants through their personal contacts (N = 169). A six-month follow-up study was carried out whereby 112 participants of the initial sample took part (43.8% males), aged 19–28 (M = 21.12; SD = 1.69). In order to carry out the follow-up study after 6 months, all the questionnaires were identified with an individual password. Confidentiality and anonymity were ensured following the legal and ethic standards.

Measures The Spanish version of the Dirty Dozen was completed by all the participants. The Dirty Dozen (Jonason & Webster, 2010) is composed of 12 items divided in three subscales (4 items each) which assess Machiavellianism (e.g., I tend to manipulate others to get my way), psychopathy (e.g., I tend to lack remorse), and narcissism (e.g., I tend to want others to admire me), measured using a 7-point Likert scale from 1 (= strongly disagree) to 7 (= strongly agree). The original scale was translated into Spanish and then back-translated into English by two professional translators. Spanish items are presented in Table 1.

The 60-item Spanish version of the HEXACO (Romero, Villar, & López-Romero, 2015) was used to assess the broad personality traits of Honesty/Humility (e.g., I would never accept a bribe, even if it were very large), Emotionality (e.g., I sometimes can’t help worrying about little things), Extraversion (e.g., I rarely express my opinions in group meetings), Agreeableness (e.g., people sometimes tell me that I am too critical of others), Conscientiousness (e.g., I often push myself very hard when trying to achieve a goal), and Openness (e.g., I would be quite bored by a visit to an art gallery). Participants were asked their agreement with the statements from 1 (= strongly disagree) to 5 (= strongly agree).

Impulsivity traits were assessed by the short Spanish version of the UPPS-P (Cándido, Orduña, Perales, VerdejoGarcía, & Billieux, 2012), a 20-item measure composed of 5 subscales (4 items each): Positive Urgency (e.g., I tend to act without thinking when I am really excited), Negative Urgency (e.g., when I am upset I often act without thinking), (lack of) Premeditation (e.g., I usually think carefully before doing anything), (lack of) Perseverance (e.g., I finish what I start), and Sensation Seeking (e.g., I quite enjoy taking risks). The items were scored on a Likert scale from 1 (= totally disagree) to 4 (= totally agree). The global score was used in the current study.

The Spanish version of the Brief Sensation Seeking Scale (BSSS, Hoyle, Stephenson, Palmgreen, Lorch, & Donohew, 2002) is composed of 8 items (e.g., I would like to explore Journal of Individual Differences (2019), 40(1), 36–44

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L. Maneiro et al., Spanish Version of the Dirty Dozen

Table 1. Spanish items of the Dark Triad Dirty Dozen, their respective factors, and their loadings on each component of the principal component analysis Component Factor or item

1

2

3

Machiavellianism (1) Tiendo a manipular a los demás [I tend to manipulate others to get my way]

.01

.85

.02

(2) He usado el engaño y mentido [I have used deceit or lied to get my way]

.13

.91

.00

(3) He usado halagos [I have used flattery to get my way]

.13

.79

.14

(4) Suelo utilizar a los demás [I tend to exploit others toward my own end]

.09

.73

.10

Psychopathy (5) No suelo tener remordimientos [I tend to lack remorse]

.05

.20

.83

(6) No me preocupa la moralidad [I tend to be unconcerned with the morality of my actions]

.01

.06

.83

(7) Suelo ser duro e insensible [I tend to be callous or insensitive]

.11

.31

.59

(8) Suelo ser cínico [I tend to be cynical]

.07

.29

.56

.90

.07

.12

Narcissism (9) Quiero que me admiren [I tend to want others to admire me] (10) Quiero que me presten atención [I tend to want others to pay attention to me]

.91

.07

.04

(11) Suelo buscar prestigio [I tend to seek prestige or status]

.89

.03

.08

(12) Suelo esperar un trato de favor [I tend to expect special favors from others]

.64

.20

.09

Note. Factor loadings > .40 are boldfaced.

strange places) measured by a 5-point Likert scale from 1 (= strongly disagree) to 5 (= strongly agree).

Psychopathic traits were assessed through the Youth Psychopathic Traits Inventory-Short Version (YPI-S, Van Baardewijk et al., 2010), an 18-item self-report which comprises three factors (6 items each), namely Grandiose-Manipulative (e.g., it’s easy for me to manipulate people), CallousUnemotional (e.g., to be nervous and worried is a sign of weakness), and Impulsive-Irresponsible (e.g., I consider myself as a pretty impulsive person). Each item is scored on a 4-point Likert scale ranging from 0 (= does not apply at all) to 3 (= apply very well).

Aggression was assessed by the Reactive and Proactive Aggression Questionnaire (RPQ, Raine et al., 2006). The scale consists of 23 items rated on a 3-point scale from 0 (= never) to 2 (= often) which distinguish between reactive (e.g., I reacted angrily when provoked by others) and proactive aggression (e.g., I had fights with others to show who was on top).

Results Descriptive statistics at both Time 1 and Time 2 are presented in Table A1 (see Appendix) for a more in-depth view.

The analysis of sex differences was carried out through a multivariate analysis of variance (MANOVA). Men scored higher than women in Machiavellianism, F(313) = 8.45, p < .01, ηp2 = .03; psychopathy, F(313) = 25.16, p < .001, ηp2 = .07; narcissism, F(313) = 5.03, p < .05, ηp2 = .02; and the global score of the Dark Triad, F(313) = 20.41, p < .001, ηp2 = .06.

Journal of Individual Differences (2019), 40(1), 36–44

The internal consistencies (i.e., Cronbach’s α) for the global Dark Triad, Machiavellianism, and narcissism were good, while the internal consistency for psychopathy was acceptable, as can be seen in Table A1 (see Appendix).

Test-retest reliability was analyzed by correlating Time 1 and Time 2 scores. The test-retest correlations displayed moderated coefficients for Machiavellianism (r = .60), psychopathy (r = .59), and for the global scale (r = .63) as well as a high coefficient for narcissism (r = .70). All the three Dark Triad traits were positively intercorrelated, with the highest correlation found between Machiavellianism and psychopathy (r = .43, p < .001), similar to that between Machiavellianism and narcissism (r = .41, p < .001), and the lowest found between psychopathy and narcissism (r = .13, p < .05).

In order to replicate the factorial structure of the scale, a Principal Component Analysis (PCA) with promax oblique rotation (k = 4) was carried out in the Spanish version of the Dirty Dozen using the SPSS 20.0 statistical package.

The PCA showed a three-factor solution, namely Machiavellianism, psychopathy, and narcissism, which explained 67.27% of the total variance. Factor 1, which reflected narcissism, accounted for 37.55% of the variance and had an eigenvalue of 4.51. Factor 2, which referred to Machiavellianism, accounted for 19.03% of the variance and had an eigenvalue of 2.28. Factor 3, which referred to psychopathy, explained 10.69% of the variance and had an eigenvalue of 1.28. Results of the PCA are displayed in Table 1.

A confirmatory factor analysis (CFA) with a weighted least squares, mean and variance adjusted (WLSMV) estimation was subsequently carried out to test the factorial structure of the scale using MPlus 7. Three models were Ó 2018 Hogrefe Publishing

L. Maneiro et al., Spanish Version of the Dirty Dozen

39

Figure 1. Bifactorial model of the Spanish version of Dirty Dozen Measure of the Dark Triad. Estimates are standardized coefficients. All the factor loadings were statistically significant at p < .001, with the exception of the paths from global Dark Triad to the items 5 and 6 and the path from narcissism to item 12 that were not statistically significant. The factor loading of the path from global Dark Triad to the item 7 was statistically significant at p < .05.

computed in the CFA. The first model holds that there is a single, unitary Dark Triad construct. The second model identifies three interrelated Dark Triad traits. Lastly, a bifactorial model was tested, which includes a latent factor of the global Dark Triad, and three latent factors associated with the Dirty Dozen’s subscales. The results of the CFA showed a better fit for the bifactorial model (CFI = .98, TLI = .97, RMSEA = .08, 90% CI [.06, .09]), compared to the single dimension model (CFI = .75, TLI = .70, RMSEA = .25, 90% CI [.24, .27]), and three interrelated Dark Triad traits (CFI = .96, TLI = .95, RMSEA = .10, 90% CI [.09, .11]). The bifactorial model is presented in Figure 1. Likewise, configural invariance across gender was assessed, that is, the invariance of factor structure across males and females. The bifactorial model showed acceptable goodness of fit both for males (CFI = .99, TLI = .98, RMSEA = .07, 90% CI [.05, .12]) and females (CFI = .98, TLI = .97, RMSEA = .07, 90% CI [.05, .10]) and resulted invariant across gender (ΔCFI < .01).

Table 2 shows zero-order correlations between Dirty Dozen’s subscales and the variables that form the nomological network of the Dark Triad, as well as with aggression, both reactive and proactive. All the Dark Triad traits were related to low levels of Honesty/Humility and Ó 2018 Hogrefe Publishing

Agreeableness, whilst Machiavellians and psychopaths also evidenced lack of Emotionality and lack of Conscientiousness. Likewise, Machiavellianism, psychopathy, narcissism, and the global Dark Triad were correlated with high levels of psychopathic traits (i.e., grandiose-deceitful, callous-unemotional, and impulsivity-need of stimulation), impulsivity, sensation seeking, and aggression, both reactive and proactive.

A series of structural equation models were carried out in order to test the latent contribution of the Dirty Dozen. All the models included the three latent factors associated with the Dirty Dozen’s subscales as well as a latent factor of the global Dark Triad according to the bifactorial structure of the scale. Specifically, ten different models were analyzed: one for each facet of the HEXACO (i.e., Honesty/Humility, Emotionality, Extraversion, Agreeableness, Conscientiousness, and Openness); another which included the three dimensions of the YPI-S (i.e., grandiose-manipulative, callous-unemotional, and impulsive-irresponsible); one for impulsivity and other for sensation seeking; and the last one for aggression, including proactive and reactive aggression as latent variables. The goodness of fit indexes is presented in Table 3. All the models presented an acceptable goodness of fit, nevertheless in the models which included Journal of Individual Differences (2019), 40(1), 36–44

40

L. Maneiro et al., Spanish Version of the Dirty Dozen

Table 2. Zero-order correlations between the Dirty Dozen subscales and the different facets of the personality correlates and behavioral outcomes Cronbach’s α

Machiavellianism

Psychopathy

Narcissism

Dirty Dozen

HEXACO model Honesty-Humility

.82

.54***

.36***

.36***

.56***

Emotionality

.84

.30***

.48***

.00

.33***

Extraversion

.82

.02

.02

.08

.02

Agreeableness

.80

.26***

.17**

.13*

.25***

Conscientiousness

.88

.32***

.26***

.05

.27***

Openness

.81

.02

.10

.00

.03

Psychopathic traits Grandiose-deceitful

.81

.56**

.35***

.33***

.55***

Callous-unemotional

.75

.40***

.42***

.24***

.46***

Impulsivity-need of stimulation

.74

.35***

.20***

.17*

.31***

Impulsivity

.73

.33***

.18***

.12*

.28***

Sensation seeking

.71

.29***

.12*

.13*

.24***

Reactive aggression

.81

.36***

.19**

.30***

.38***

Proactive aggression

.76

.50***

.36***

.31***

.52***

Aggression

Note. *p < .05, **p < .01, ***p < .001 (all two-tailed).

Table 3. Goodness of fit of the different computed models w2(df)

RMSEA [90% CI]

CFI

TLI

HEXACO Honesty/humility

448.30 (189)

.06 [.06, .07]

.90

.90

Emotionality

401.74 (190)

.06 [.05, .07]

.92

.90

Extraversion

423.43 (188)

.06 [.05, .07]

.90

.88

Agreeableness

405.78 (190)

.06 [.05, .07]

.90

.88

Conscientiousness

347.86 (188)

.05 [.04, .06]

.94

.93

Openness

345.23 (189)

.05 [.04, .06]

.94

.92

Psychopathic traits

731.40 (374)

.05 [.05, .06]

.90

.89

Impulsivity

194.74 (98)

.05 [.04, .07]

.96

.93

Sensation seeking

285.82 (151)

.05 [.04, .06]

.94

.92

1,134.54 (536)

.06 [.05, .06]

.84

.82

Aggression

Notes. Psychopathic traits included the three facets of the YPI-S in the model (i.e., Grandiose-manipulative, Callous-unemotional, and Impulsiveirresponsible). Aggression included Proactive and Reactive aggression in the model.

Honesty/Humility, Extraversion, Conscientiousness, Openness, psychopathic traits, and impulsivity, modification indexes were used in order to improve the fit.

The Dark Triad factors, both global and three specific factors, showed a different pattern of associations with other personality traits and behavioral outcomes. Regarding the general personality model, Machiavellians evidenced low levels of Agreeableness, whereas psychopaths were associated to lack Honesty/Humility, lack of Emotionality, and lack of Conscientiousness. The general factor of the Dark Triad was only related to lack of Honesty/Humility. Machiavellians also showed high levels of grandiose-manipulative and impulsive-irresponsible traits, as well as sensation seeking and aggression, both proactive and reactive. Psychopaths revealed high levels of callous-unemotional traits and Journal of Individual Differences (2019), 40(1), 36–44

proactive aggression, while the general Dark Triad factor was associated with grandiose-manipulative and callousunemotional traits, impulsivity, sensation seeking, and both reactive and proactive aggression. Narcissism was not related neither to other personality traits nor behavioral outcomes once the shared variance was controlled for. Results are displayed in Table 4.

Discussion The Spanish version of the Dirty Dozen showed good psychometric properties regarding reliability, construct validity, and external validity. According to prior studies, internal Ó 2018 Hogrefe Publishing

L. Maneiro et al., Spanish Version of the Dirty Dozen

41

Table 4. Structural equation modeling including the Dark Triad traits and their relations with other personality traits and behavioral outcomes Dirty Dozen

Machiavellianism

Psychopathy

Narcissism

β

β

β

β

HEXACO Honesty/humility

.65***

.01

.45*

.12

Emotionality

.02

.01

.68***

.14

Extraversion

.10

.04

.09

.04

Agreeableness

.11

.35**

.03

.17

Conscientiousness

.11

.17

.29*

.17

Openness

.21

.52

.52

.29

Grandiose-manipulative

.39***

.53***

.10

.02

Callous-unemotional

.37***

.09

.67***

.20

Impulsive-irresponsible

.14

.31**

.06

.06

Impulsivity

.29**

.17

.14

.21

Sensation seeking

.22*

.30*

.01

.05

Proactive aggression

.37***

.31**

.25*

.07

Reactive aggression

.32***

.27**

.03

.13

Psychopathic traits

Aggression

Notes. Estimates are standardized regression coefficients. *p < .05, **p < .01, ***p < .001 (all two-tailed).

consistency and test-retest displayed good and acceptable values, respectively, for each of the Dirty Dozen subscales as well as for the global scale (Jonason & Webster, 2010).

The three Dirty Dozen subscales were positively intercorrelated. As expected, the highest correlation was observed between psychopathy and Machiavellianism (Furnham, Richards, Rangel, & Jones, 2014). Likewise, the three-factor structure of the scale was replicated in the Spanish version of the Dirty Dozen and, as predicted, the analysis of the factorial structure showed a best fit for the bifactorial model.

This result supports the existence of a latent global Dark Triad factor which measures the residual Dark Triad after the variance attributable to the three subscales latent factors are removed (Bertl, et al., 2017; McLarnon & Tarraf, 2017). Therefore, the Dark Triad traits can be considered as individual personality traits as well as a higher-order dark personality dimension (Jonason & Luévano, 2013).

The Spanish version of the Dirty Dozen has shown differential pattern of associations with the facets of the HEXACO model of personality. The Honesty/Humility factor displayed the highest negative correlations with all the Dark Triad traits. Given this factor is defined by the facets of sincerity, fairness, greed avoidance, and modesty (Lee & Ashton, 2004), and is considered an indicator of an antagonistic social style, the correlations with the Dark Triad traits were expected (Jonason & McCain, 2012; Muris et al., 2017). Likewise, although the psychopathy latent variable was related to low levels of Honesty/Humility, the largest relation was found with the general Dark Triad latent factor. This fact supports the assumption that the Ó 2018 Hogrefe Publishing

core of the Dark Triad can be understood in terms of general personality as a lack of Honesty/Humility and, as a new study has posited (Hodson et al., 2018), it would be reasonable that the Dark Triad and the Honesty/Humility facet would be “two ends of a common dimension” (Hodson et al., 2018, p. 124). On the other hand, in terms of correlations, the results regarding the other facets are consistent with previous findings (Jonason & McCain, 2012; Muris et al., 2017). However, when more powerful statistic analyses were used, Machiavellians only remained related to lack of Agreeableness whilst psychopaths evidenced the largest associations with lack of Emotionality followed by lack of Honesty/Humility and low levels of Conscientiousness. These findings support the bifactorial structure of the Dirty Dozen which could be explained by a general Dark Triad factor defined by low levels of Honesty/Humility and specific association of the Dark Triad traits with different facets of the general personality model (Lee & Ashton, 2014).

The analysis of the relations with psychopathic traits evidenced significant positive associations of all the Dark Triad traits with grandiose-manipulative, callous-unemotional, and impulsive-irresponsible facets of psychopathy.

Nevertheless, when the latent contribution of the Dark Triad was analyzed, only the general factor remained related to grandiose-manipulative and callous-unemotional traits. These results go along with prior studies which suggest that all dark personalities share a common core of callousness and interpersonal coldness, related to primary psychopathy (Jones & Figueredo, 2013). Furthermore, Journal of Individual Differences (2019), 40(1), 36–44

42

Machiavellians displayed high levels of grandiose-manipulative traits, which is in line with the expectations since both facets share an interpersonal domain of manipulation. Contrary to the predictions, Machiavellians exhibited more impulsive-irresponsible traits, specific to the behavioral dimension of the psychopathy construct. Although this finding is in accordance with previous studies (Crysel et al., 2013; Vize et al., 2018), the conceptual framework posits that Machiavellian individuals are neither erratic nor impulsive, but they involve strategic planning (e.g., Jones & Paulhus, 2011b). Finally, psychopaths showed the largest relation with callous-unemotional traits. This result supports previous findings which posit that the psychopathy Dirty Dozen subscale assesses mainly primary psychopathy but fails to capture interpersonal and disinhibitory traits characteristic of secondary psychopathy (Maples, Lamkin, & Miller, 2014; Miller et al., 2012).

Despite all, the Dark Triad traits were significantly positive associated with impulsivity and sensation seeking; only the general Dark Triad factor remained significantly related to both of them once the latent contribution was evaluated.

The idea of an underlying common behavioral dimension could be derived from a functional – dysfunctional impulsivity perspective. That is, it could be feasible that Machiavellians and narcissists use functional impulsivity in order to reach their goals, whereas dysfunctional impulsivity would be characteristic of psychopaths because of their self-control deficits (Jones & Paulhus, 2011b). These impulsive tendencies are not explained by the specific Dark Triad factors but seem that they take part in the core of the construct. Contrary to the expectations, Machiavellians also showed high levels of sensation seeking (Jones & Paulhus, 2011a).

The results of the current study partially support the initial predictions regarding aggression. All the Dark Triad traits were significantly related to aggression, both reactive and proactive, a finding that replicates past work (Barlett, 2016; Vize et al., 2018). However, once controlling for the other dimensions, the general Dark Triad factor and Machiavellianism remained associated with both forms of aggression, and psychopathy was related to proactive aggression.

It is not surprising that all Dark Triad traits share a core of aggression because of the malevolent side of this construct (Paulhus & Williams, 2002). Likewise, proactive aggression has previously shown strong relations with psychopathy (Jonason et al., 2015), which defines a more severe and persistent pattern of antisocial behavior (López-Romero, Romero, & Villar, 2017). Nevertheless, although obtained results of Machiavellianism could be expected regarding proactive aggression, that is, Machiavellians could use tactics such as aggression to achieve their goals (Paulhus & Williams, 2002); with regards to reactive aggression results are unexpected, mainly because reactive aggression tends Journal of Individual Differences (2019), 40(1), 36–44

L. Maneiro et al., Spanish Version of the Dirty Dozen

to be associated with more impulsivity self-regulation problems (Jonason et al., 2015).

This study has some theoretical and practical implications. One of the main contributions refers to the use of latent variable modeling, which supported the bifactorial structure of the scale. The confirmation of the bifactorial structure of the Dark Triad justifies the use of a unique measure of the Dark Triad which includes all the Dark Triad traits instead of the use of individual measures for Machiavellianism, psychopathy, and narcissism, since there is a common variance of the construct that is not captured with these individual measures. This fact is important for the development of effective strategies adapted to each personality profile in the field of prevention and intervention.

Thus, the current study provides a Spanish validation of the Dirty Dozen which shows good psychometric properties and may be considered as a relatively efficient measure for Dark personalities in Spanish-speaking contexts.

Limitations This study is not exempt of some limitations. Firstly, the use of brief measures might not well capture the core aspects of the respective constructs. Secondly, gender moderation was not assessed because of the sample size. Lastly, data used in this study were collected through self-report questionnaires therefore results might be partially influenced by shared method variance. These limitations should be addressed in future studies.

Conclusions The Spanish version of Dirty Dozen shows good psychometric properties and supports the distinctiveness of the Dark Triad traits through specific associations with other personality traits and behavioral outcomes. Nevertheless, all Dark Triad traits seem to share a common core of lack of honesty/humility, grandiose-manipulative traits, callousunemotional, impulsivity, and sensation seeking. Therefore the Spanish version of the Dirty Dozen may be considered as a relatively efficient measure for Dark personalities in Spanish-speaking contexts.

Acknowledgments This work was supported by the Spanish Ministry of Economy and Competitiveness [Ministerio de Economía y Competitividad] under Grant PSI2015-65766-R, and cofunded by the European Regional Development Fund [Fondo Europero de Desarrollo Regional, FEDER] corresponding to the multiannual financial framework Ó 2018 Hogrefe Publishing

L. Maneiro et al., Spanish Version of the Dirty Dozen

2014–2020. Data, analytic methods, and study materials will be available to other researchers upon request to the corresponding author. The research is not pre-registered in an independent, institutional registry.

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Received October 18, 2017 Revision received March 8, 2018 Accepted March 14, 2018 Published online September 13, 2018 Lorena Maneiro Department of Clinical and Psychobiological Psychology Universidade de Santiago de Compostela C/Xosé María Suárez Núñez, s/n, Campus Sur 15782 Santiago de Compostela Spain lorena.maneiro@usc.es

Appendix Table A1. Descriptive statistics and internal consistency for all scales used, both T1 and T2 T1

T1

M (SD)

α

M (SD)

α

34.59 (11.23)

.84

34.55 (10.80)

.82

10.65 (4.84)

.85

10.60 (4.86)

.84

9.88 (4.69)

.73

9.59 (4.73)

.74

14.05 (5.64)

.87

14.35 (5.45)

.86

Honesty/Humility

33.99 (7.70)

.82

–

–

Emotionality

33.57 (7.11)

.84

–

–

Extraversion

33.55 (6.44)

.82

–

–

Agreeableness

30.14 (6.34)

.80

–

–

Conscientiousness

34.60 (7.56)

.88

–

–

Openness

34.18 (8.25)

.81

–

–

Grandiose-manipulative

5.59 (3.82)

.81

10.51 (4.06)

.86

Callous-unemotional

4.31 (3.65)

.75

9.07 (3.28)

.76

Dark Triad Machiavellianism Psychopathy Narcissism HEXACO

YPI

Impulsive-irresponsible

8.24 (3.63)

.74

13.01 (4.06)

.65

47.40 (8.78)

.73

51.73 (8.51)

.71

3.51 (0.64)

.71

2.30 (0.75)

.77

Proactive aggression

15.29 (3.13)

.81

14.34 (2.30)

.72

Reactive aggression

20.02 (3.82)

.76

19.29 (3.49)

.78

Impulsivity Sensation seeking Aggression

Notes. YPI = Youth Psychopathic Traits Inventory Short version. HEXACO was not filled out in T2.

Journal of Individual Differences (2019), 40(1), 36–44

Ó 2018 Hogrefe Publishing

Original Article

Time Perspective, Awareness of Narrative Identity, and the Perceived Coherence of Past Experiences Among Adults David John Hallford, Nicholas J. Fava, and David Mellor Deakin University, School of Psychology, Melbourne, Victoria, Australia

Abstract: The ability to mentally project oneself into the past and future is theoretically central to perception of a salient and cohesive narrative identity. Despite these theorized links, to date, the relationship between time perspective and narrative identity has not been empirically studied. We examined the association between these constructs in a sample of 212 participants (Mage = 28.3 years, SD = 10.9) who completed the Balanced Time Perspective Scale and the Awareness of Narrative Identity Questionnaire (ANIQ). Congruent with our hypotheses, stronger past perspective and a bias for past perspective over future were associated with a stronger awareness of having a narrative identity and the perception of temporal, causal, and thematic coherency of past experiences. When the past and future time perspective scales were examined together as predictors of the ANIQ subscales, past time perspective emerged as a significant predictor of stronger awareness of a narrative identity through dimensions of perceived coherence of past experiences, whereas future time perspective was a weak, direct predictor of lower awareness. The findings indicate that individual differences in time perspective, and in particular a bias for past time perspective, are associated with a potentially more adaptive perception of narrative identity.

Keywords: time perspective, narrative identity, autobiographical coherence

Narrative identity refers to the evolving stories that people develop about themselves and their lives. These stories relate to the reconstructed past, help us guide or predict the anticipated future (McAdams, 2008, p. 243), and are formed by meaningfully integrating information we possess about ourselves and the world. The development of a narrative identity, which emerges through adolescence (Habermas & Bluck, 2000; Habermas & Paha, 2001), helps us to organize and abstract memories of our experiences. Such self-defining narratives are considered fundamental components of the framework of personality, providing unity and purpose to the lives of individuals, as well as shaping behavior (McAdams & Pals, 2006; Singer 2004).

As a construct closely related to other domains of psychological inquiry, such as memory, cognitive-affective states, and psychosocial development, narrative identity has garnered broad research interest. This research has often focused on the content of narratives, whereby individuals provide verbal or written accounts of events or sequences of events in their lives, which are then coded on various dimensions. This approach to narrative identity has borne much useful information, for example, that narrative themes of agency and redemption are associated with more positive well-being (McAdams & McLean, 2013) and Ó 2018 Hogrefe Publishing

predict behavioral change over time (Dunlop & Tracy, 2013), that autonomy and connectedness are related to meaning making about one’s one life (McLean, Breen, & Fournier, 2010), and that changes in agency in narrative identity precede positive mental health outcomes in psychotherapy (Adler, 2012).

We recently proposed that the awareness that people have of their life stories, including how conscious they are of drawing on these to understand themselves and their lives, is also an important dimension of narrative identity to consider (Hallford & Mellor, 2017). This dimension, of awareness of life stories, might be thought of as a basic metacognition that experiences can be represented as stories that inform oneself of one’s identity. The salience of life stories is clearly related to their personal meaning and, inherently, their ability to be remembered (McLean, Syed, & Shucard, 2016; McLean, Syed, Yoder, & Greenhoot, 2014). However, salience and meaning are not synonymous constructs, theoretically or empirically (Hallford & Mellor, 2017). We have proposed that a stronger awareness of having life stories, even those with negative content, might be adaptive in general, given they still provide a sense that one’s experiences are interpretable, and potentially predictable in some way also. This is congruent with our Journal of Individual Differences (2019), 40(1), 45–54 https://doi.org/10.1027/1614-0001/a000275

46

findings that a stronger awareness of narrative identity correlates with personal resources such as meaning in life, selfesteem, and self-efficacy (Hallford & Mellor, 2017). Further, this suggests that an awareness of narrative identity might be influenced by, but partially independent of, other factors of interest in narrative identity, such as emotional valence (Berntsen & Rubin, 2002), growth (Bauer, McAdams, & Sakaeda, 2005), and the aforementioned personal meaning (Singer, 2004).

In addition to a basic awareness of life stories, their cohesiveness is an important factor related to well-being (Baerger & McAdams, 1999; Bauer, McAdams, & Pals, 2008).

Indeed, for individuals to form meaningful narratives about their lives, they must be able to integrate autobiographical information, and clearly identify emergent stories through self-reflection or interaction with others. Habermas and Bluck (2000) propose four types of coherence that develop throughout childhood and adolescence, namely perceiving the order or sequence of events over time, understanding the causal associations between different events and the self, identifying overarching themes from multiple events or circumstances, and cultural norms about what a narrative should contain or the accepted sociocultural significance of particular events. The coherence of narratives is typically coded from transcripts using an objective scale referencing abilities in some or all of these types of coherence (e.g., Reese et al., 2011). However, in addition to this, the subjective perception of coherence – that is, the metacognitive awareness that one can perceive relationships between past experiences in terms of temporal ordering, causal connections, and abstracted themes – might also be a useful approach of inquiry. Indeed, the subjective perception of having coherence in and across past experiences is related to higher well-being, as well as objective assessments of the coherence of written narratives of past events (Hallford & Mellor, 2017). Further, these different forms of perceived coherence predict independent variance in the awareness of having a life narrative (Hallford & Mellor, 2017), therefore uniquely contributing to the subjective salience of life stories. Notably, a stronger awareness of a narrative identity may not necessitate that these stories are coherent. Indeed, one might have a strong awareness of incoherence in life stories. One group who exemplifies this is those individuals with borderline personality disorder, which has the defining characteristics of an awareness of an unstable and fragmented identity (American Psychiatric Association, 2013). Individuals with this personality disorder demonstrate poorer coherence of life stories compared to healthy controls (Adler, Chin, Kolisetty, & Oltmanns, 2012).

Adler, Lodi-Smith, Philippe, and Houle (2016) suggest that narrative identity can provide valid, incremental prediction of well-being alongside common dispositional Journal of Individual Differences (2019), 40(1), 45–54

D. J. Hallford et al., Time Perspective and Narrative Identity

personality traits, and dimensions of salience and cohesiveness might be relevant factors in this, as they are related to higher psychological well-being (Baerger & McAdams, 1999; Waters & Fivush, 2015). Given this, further understanding of individual differences that affect the awareness and perceived cohesiveness of life stories may clarify how they develop and are maintained, and point to methods of strengthening narrative identity on these dimensions.

One individual difference that may be associated with the salience and cohesion of our life stories, but to date has not been examined in detail, is time perspective. Time perspective refers to the orientation of one’s cognitive processing to emphasize particular time frames, that is, the past, present, or future. Zimbardo and Boyd (1999) proposed that people develop tendencies in the use of time perspective which lead to dominant or dispositional frames through which they interpret the world. For example, during decision-making, individuals may show a tendency to preferentially use information from their personal past experience, place higher value on present contextual variables, or more strongly rely on anticipated outcomes.

Numerous studies have provided evidence for the influence of time perspective on various judgments, decisions, and actions. For example, present time perspective has been shown to be an independent predictor of risky driving behavior (Zimbardo, Keough, & Boyd, 1997) and future time perspective has been found to be a predictor of career commitment (Park & Jung, 2015).

We contend that differences in time perspective may be associated with the salience and perceived coherence of a narrative identity. Moreover, differences in time perspective may influence the perceived coherence of past experiences, that is, how we interpret their relationship to one another in terms of temporal ordering, causal associations, and the abstraction of experiences into themes about the self (Habermas & Bluck, 2000). Perhaps most essential to this contention is that people must possess some basic metacognitive awareness of a temporal frame in order to develop and perceive a narrative identity, to understand that stories about one’s life are extended over time.

To develop meaningful narratives that connect personal experiences to one another, one must possess the capacity to explore temporal frames beyond the present. A tendency to reminisce on past experiences may mean more time thinking about when they occurred and how they are related, as well as a stronger integration of events into cohesive stories that are better encoded and more familiar. Conversely, having a dominant futurist time perspective, while useful in many respects (e.g., in motivation or goal setting; Boniwell, 2009; Zimbardo & Boyd, 1999), might potentially be limiting in the development and salience of a narrative identity due to the marginalization of past, identity-shaping Ó 2018 Hogrefe Publishing

D. J. Hallford et al., Time Perspective and Narrative Identity

experiences. The imagined future and its relationship with self-narrative have been somewhat neglected in research (Syed & McLean, 2016). We suggest that this is due to future thinking providing information about what one’s future identity might become, rather than what it is, and therefore that anticipated experiences have the potential to shape identity in the future rather than defining it in the present. Given this, having a predominantly futurist time perspective might be related to less awareness of life stories as shaped by past experiences, and less coherence of personal memories due to a reduced propensity to think about past experiences and how they relate to one another.

In contrast to the above, an expansive time perspective, whereby past and future temporal frames are both emphasized in cognitive processing, may be the most adaptive and flexible time-related disposition to possess (Boniwell & Zimbardo, 2004). Indeed, having an expansive time perspective, relative to a more restrictive time perspective, is related to increased satisfaction with life, happiness, and self-determination (Zhang, Howell, & Stolarski, 2013), and more positive mood states (Stolarski, Matthews, Postek, Zimbardo, & Bitner, 2014). An expansive time perspective may also be predictive of a more salient and cohesive narrative identity, as it may facilitate the extension of narratives over a bidirectional temporal plane to incorporate the events of one’s past with anticipation of one’s future (Boniwell & Zimbardo, 2015). Conversely, a disposition to be more restrictive in terms of time perspective may be associated with less rich and integrated narratives about the self.

To date, little research has investigated time perspective in relation to the salience of narrative identity and the subjective coherence of past experiences. The current study aimed to address this gap in the literature by examining whether different temporal frames might be associated with the awareness of a narrative identity. Further, we investigated whether time perspective is associated with how coherent we perceive our past experiences to be in terms of their temporal ordering, causal connection to another, and relatedness in terms of abstract themes about the self.

Finally, given that the ability to establish coherency across past experience, structurally and in a way that integrates various experiences and information about the self, is essential to the development of meaningful narrative identity (Habermas & Bluck, 2000; Habermas, Bluck, & McAdams, 2001), we also sought to test a mediation model to assess whether time perspective was indirectly associated with a stronger awareness of narrative identity via perception of coherency in past experiences.

It was hypothesized that higher reported levels of past and future time perspectives would correlate with a stronger awareness of a narrative identity and perceived temporal, causal, and thematic coherence of past experiÓ 2018 Hogrefe Publishing

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ences. Further, it was hypothesized that when these time perspectives were considered together, a bias for past time perspective would, relative to future, be more strongly associated with these narrative identity variables, and that they would interact so that awareness and perceived coherence would be strongest for those concurrently high on past and future time perspectives. Lastly, it was predicted that the association between time perspective and awareness of narrative identity would be mediated by higher perceived coherence of past experiences.

Method Participants The sample comprised 212 participants, with a mean age of 28.3 years (SD = 10.9). Sixty-nine percent of the sample were females. With respect to country of origin, 40.6% participants were from Australia, 27.8% from the USA, 6.1% from Canada, 4.7% from India, 3.3% from the UK, 1.9% from New Zealand, and the remaining were from various other countries. The participants were recruited online from Amazon’s Mechanical Turk (MTurk). MTurk is a crowdsourcing website that facilitates recruitment of participants to complete tasks in exchange for token payment. Data from MTurk have been shown to be psychometrically reliable and valid (Paolacci & Chandler, 2014). Using G*Power 3.1.9.2, we estimated that at .80 power and an alpha level set at .05, the study was powered to detect correlations of at least a small effect (r = .17), small-to-moderate amounts of variance in the regression analyses (f 2 = .05), and would provide at least 10 cases for each parameter estimated in the mediation model, as recommended by Kline (2015).

Materials Narrative Identity and Perceived Coherence of Past Experiences The Awareness of Narrative Identity Questionnaire (ANIQ; Hallford & Mellor, 2017) is a self-report measure comprised of 20 items. Respondents are prompted to think generally about their lives, rather than retrieving specific memories.

A 5-item subscale measures the awareness of having stories about one’s life that provide information about personal identity (e.g., “My sense of self is embedded in memories of my life”). The three remaining 5-item subscales measure the perception of how coherent one’s autobiographical memories are with respect to understanding when, and the order in which, events occurred in one’s life (temporal coherence. e.g., “I can put the events of my life in the order of when they occurred”), how events are causally linked with Journal of Individual Differences (2019), 40(1), 45–54

48

one another (causal coherence, e.g., “I understand how my life experiences are associated with one another”), and how clearly themes about the self can be interpreted by assessing events over the lifetime (thematic coherence, e.g., “When I think or talk about experiences in my past I can see themes about the kind of person that I am”). Participants responded to the ANIQ items on an end-defined scale ranging from 0 (= completely disagree) to 10 (= completely agree).

The ANIQ has shown good psychometric properties, including high test–retest reliability and convergent and divergent validity. Importantly, criterion validity has been shown across two studies where subjective ratings on the ANIQ subscales have been shown to significantly correlate with objective ratings of the coherence of written narratives about significant personal events that were turning points in people’s lives (Hallford & Mellor, 2017) and important relationships (Soroko, Janowicz, Frackowiak, Siatka, & Hallford, 2017). In the current study, the subscales were found to have good internal reliability, with Cronbach’s α of .94 for the awareness subscale, .97 for temporal coherence, .91 for causal coherence, and .93 for thematic coherence.

Time Perspective The Balanced Time Perspective Scale (Webster, 2011) is a 28-item questionnaire that includes two subscales, past and future, that assess temporal bias. Examples of items from the past subscale are “Reminiscing about my past gives me a sense of purpose in life” and “Tapping into my past is a source of comfort for me” and from the future subscale “I enjoy thinking about where I’ll be a few years from now” and “My future development is something I frequently think about”. Participants responded to the BTPS on an 11-point, end-defined scale ranging from 0 (= completely disagree) to 10 (= completely agree). The BTPS past and future subscales have been shown to have high internal reliability, as well as construct and criterion validity (Webster, 2011). The scales were observed to have high internal reliability in the current study (past, α = .95; and future, α = .97). To assess bias in past or future time perspective, an additional subscale was created by subtracting standardized future scores from standardized past scores, with higher scores reflecting a bias toward past time perspective. To assess an expansive or restrictive time perspective, an interaction term was created from the standardized past and future scores, with higher scores indicating a more expansive time perspective.

Procedure Ethics approval was obtained from the university human research ethics committee prior to commencement of the study. Participants elected to take part in the study from Journal of Individual Differences (2019), 40(1), 45–54

D. J. Hallford et al., Time Perspective and Narrative Identity

Figure 1. Hypothesized path model of direct and indirect effects of time perspective on awareness of narrative identity.

the MTurk website and were then directed to an external website that hosted the study survey. They were first presented with the plain language statement describing the study and participant requirements, and then prompted to complete demographic information and the study questionnaires. Informed consent was implied by completion and submission of the questionnaire. Participants were compensated with a nominal sum of money for their time.

Data Analyses SPSS 23.0 was used to perform all statistical analyses. Pearson correlation analyses were conducted to assess the zeroorder correlations between the study variables using standardized scores. Fisher’s z-test was used to assess for significant differences between the magnitude of correlation between the ANIQ and time perspective subscales. Following this, a series of regression analyses were conducted where each of the ANIQ subscales was regressed onto the time perspective subscales and their interaction term to ascertain the unique variance accounted.

Path analysis was used to test the mediation model. Figure 1 shows the mediation model to be tested. As indicated, pathways were estimated from the past and future time perspective variables (for which a correlation was estimated) to the perceived coherence variables, and also directly to the awareness of narrative identity variable. The coherence variances were correlated with one another, and pathways were estimated between these variables and awareness. A single-step model with maximum likelihood estimation was conducted in AMOS 22.0 to assess for direct and indirect effects simultaneously. Bootstrapping with 5,000 samples (Hayes, 2009) was used to test for indirect effects, as it Ó 2018 Hogrefe Publishing

D. J. Hallford et al., Time Perspective and Narrative Identity

49

Table 1. Means (standard deviations in parentheses), and correlations between time perspective and ANIQ variables ANIQ Awareness ANIQ Temporal ANIQ Causal ANIQ Thematic ANIQ Awareness

Past TP

Future TP TP Bias TP Expansive

–

Mean (SD) 33.2 (11.6)

–

ANIQ Temporal

.55***

ANIQ Causal

.83***

.63***

–

34.3 (11.8)

ANIQ Thematic

.83***

.49***

.83***

Past TP

.72***

.38***

.67***

.66***

Future TP

.30***

.23**

.34***

.31***

.53***

–

TP Bias

.43***

.16*

.34***

.36***

.48***

.48***

TP Expansive

.04

.06

.06

.08

.51***

.08

34.7 (9.9) –

34.6 (10.8) –

78.7 (32.2) 97.3 (31.2) – .44***

–

/

Notes. ANIQ = Awareness of Narrative Identity Questionnaire, TP = Time Perspective. Higher scores on the TP Bias variable indicate favoring past TP, while lower scores indicate favour future TP. TP Expansive represents the interaction between past and future TP, with higher scores indicating a more expansive TP. ***p < .001, **p < .01, *p < .05, all two-tailed.

is the most statistically powerful approach available (MacKinnon, Lockwood, & Williams, 2004; Williams & MacKinnon, 2008). A bias-corrected and accelerated 95% confidence interval (CI) was obtained, whereby confidence intervals that did not span across zero were indicative of significant indirect effects at the p < .05 level. The following fit indices were used to assess how well the data fit the model: the chi-square value (CMIN) and corresponding p-value, the relative chi-square statistic (CMIN/df), the root-mean-square error of approximation (RMSEA), the standardized root-mean-square residual (SRMR), and the comparative fit index (CFI). Guidelines by Hu and Bentler (1999) were used for the purpose of assessing model fit (RMSEA .06, SRMR .09, and CFI .95).

Results Table 1 shows the means and standard deviations of the study variables and their intercorrelations. To assess whether there might be differences in these intercorrelations based on country of origin, we compared the strength of correlations between the two largest groups (i.e., Australia and USA) using Fisher’s z-tests. There were no significant differences in how the ANIQ or time perspectives variables correlated with one another (Fisher’s z-test all z < 1.31, all p-values > .190). Given the small size of the other country of origin groups, we deemed that other such comparisons would be unreliable.

Regarding the total sample, as hypothesized, past and future time perspectives were found to correlate with the awareness of narrative identity and perceived coherence subscales of the ANIQ. The results of Fisher’s z-tests (Table 2) showed that the awareness of narrative identity and causal and thematic coherence subscales on the ANIQ correlated more strongly with past time perspective compared to future time perspective, whereas the strength of Ó 2018 Hogrefe Publishing

correlations between past and future perspectives were not found to significantly differ for the temporal coherence subscale. The correlations between the time perspective balance variable and subscales of the ANIQ indicated that more strongly favoring a past time perspective was associated with a stronger awareness of narrative identity and more perceived coherence of past experiences.

Table 3 shows the results of a series of multiple regressions indicating that time perspective predicted a substantial amount of variance in the ANIQ subscales (adjusted R2 = .44–.53), although notably less for temporal coherence (adjusted R2 = .15). For the three perceived coherence subscales, only past time perspective predicted unique variance. However, for the awareness subscale, the past subscales predicted more awareness, while the future subscale predicted less awareness. The interaction term for temporal coherence was significant and indicated that an interaction of higher past and future time perspectives predicted more perceived temporal coherence.

As the results of the multiple regressions showed that future time perspective did not contribute unique variance to any of the coherence variables, these pathways were not estimated in the path analysis. The results showed that the model was a good fit to the data, CMIN = 0.83 (df = 3, p = .478), CMIN/df = 2.49, RMSEA = .00 (95% CI [.00, .10]), SRMR = .014, CFI = 1.00. Figure 2 shows the final model with estimated pathways. Past and future time perspectives correlated with one another (r = .53, p < .001), and all three coherence subscales correlated significantly with one another (r = .34–.69, all p < .001). Past time perspective was observed to have direct, significant associations with all three coherence variables, as well as a direct significant association with awareness of narrative identity. The results from the bootstrapping tests showed that higher scores on past time perspective also had a significant indirect association with higher awareness of narrative identity through higher scores on the coherence variables with a large standardized indirect effect of .49, Journal of Individual Differences (2019), 40(1), 45–54

50

D. J. Hallford et al., Time Perspective and Narrative Identity

Table 2. Fisher’s z-test comparing correlations across rows (N = 212) ANIQ subscale

Past time perspective

Future time perspective

Fisher’s z-test

Awareness

.73***

.30***

z = 6.33, p < .001

Temporal coherence

.38***

.23**

z = 1.82, p = .068

Causal coherence

.67***

.34***

z = 4.67, p < .001

Thematic coherence

.66***

.31***

z = 4.94, p < .001

Notes. ANIQ = Awareness of Narrative Identity Questionnaire. ***p < .001, **p < .01.

Table 3. Summary of regression analyses of time perspective subscales and interaction terms predicting ANIQ subscales Awareness β

Temporal coherence

p-value

β

p-value

Causal coherence β

p-value

Thematic coherence β

p-value

Past

.80

< .001

.32

.000

.69

< .001

.71

.000

Future

.15

.023

.14

.112

.04

.563

.11

.123

Past Future interaction F

.05 122.0

.343 < .001

.16 14.3

.029 < .001

.03 57.4

.624 < .001

.07 56.8

R2

.54

.17

.45

.45

Adjusted R2

.53

.15

.44

.44

.201 < .001

Notes. ANIQ = Awareness of Narrative Identity Questionnaire. All variable scores are standardized.

Figure 2. Results of the final path analysis model, showing standardized regression coefficients and squared multiple correlations (underlined), *p < .05, ***p < .001.

95% CI [.43, 56], p < .001. Consistent with the results of the multiple regressions, future time perspective was observed to have a small, but significant negative association with awareness of narrative identity. All three coherence variJournal of Individual Differences (2019), 40(1), 45–54

ables had significant associations with awareness of narrative identity, although temporal coherence’s effect was smaller than that of causal and thematic coherence (p < .05, as indicated by nonoverlapping 95% CI). Ó 2018 Hogrefe Publishing

D. J. Hallford et al., Time Perspective and Narrative Identity

Discussion This study examined the relationship between time perspective, awareness of narrative identity, and the perceived coherence of past experiences. Congruent with our hypotheses, stronger past and future time perspectives correlated with a stronger awareness of having a narrative identity and the perception that past experiences were coherent in relation to one another. This indicated that the tendency to have positive attitudes toward remembering the personal past and imagining the future, and in particular drawing significance and comfort from favoring a past perspective in particular, was related to stronger awareness of having stories about one’s life that facilitate self-understanding. Further, these tendencies were related to more perceived coherency of past experiences in terms of the perceived timing and order in which experiences in life occurred, how they were causally related to one another, and how different experiences could be abstracted into themes about one’s life and oneself.

However, when the time perspective scales were examined together as predictors of the ANIQ subscales through multiple regressions and path analysis, only past time perspective emerged as a significant positive predictor of awareness of narrative identity and perceived coherence.

These findings contrast with the zero-order correlations showing future time perspective to be positively associated with awareness and all types of coherence, albeit of a lower magnitude than past time perspective. It is possible that the past and future time perspective scales are associated with a shared, latent variable of mentally representing life experiences. Indeed, these two cognitive processes are sometimes referred to jointly as mental time travel and overlap in terms of their component processes and brain networks (Schacter et al., 2012). This may explain why future time perspective was no longer a positive predictor when this shared variance was accounted for by other variables. This was supported by a lack of interaction effect, with the exception of temporal coherence (discussed below), indicating that there was no additive effect when these variables were considered together in predicting awareness or perceived coherence. Indeed, the predilection to think about the future was observed to be predictive of lower salience of life stories, although this effect size was small.

Narrative identity is generally considered to involve not only information in storied form about the past, but also some narration of the anticipated future (McAdams, 1985). Indeed, just as thinking about past experiences can contribute to a sense of self and identity, so too can the anticipation of significant future events that we might experience (D’Argembeau, Lardi, & Van der Linden, 2012).

However, in this study, we found that a future time perspective was not related to higher awareness of narrative idenÓ 2018 Hogrefe Publishing

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tity, rather it was related to lower awareness. As noted, this may reflect the possibility that while we create narratives of our possible futures, they represent events that have the potential to alter our identity, rather than experiences by which we define our identity. This points to a possible distinction between narratives of the past or present self, and narratives of the future self, with future time perspective not uniquely related to the former two. The exception in our study was temporal coherence, whereby a more positive disposition toward past and future thinking both independently predicted stronger perceived coherence of the ordering of events. This might reflect an overlap in how thinking about sequences of past and or possible future events requires, and might promote, the basic ability to sequence mental representations. Moving forward, researchers may wish to examine written narratives about future events, and assess how closely they approximate, or differ from, narratives derived from past experiences. A range of research questions arise from this line of inquiry, such as do stories of redemption in one’s past also predict narratives about oneself in the future that involve overcoming adversity, or does perception of narrative coherence differ in nature between past or future narratives.

The findings from this study indicate that a disposition to emphasize a past temporal frame as having significance and providing comfort is strongly associated with more subjectively coherent and integrated understandings of past experiences, possibly through better encoding in memory and an increased sense of familiarity. Our path analysis supports the prediction that this disposition is also associated with more salient life stories directly, and indirectly through subjectively coherent personal memories. A stronger tendency to recall and review past experiences in life might promote familiarity and better encoding in memory of the order in which these memories occurred, the way in which experiences lead to one another in a manner, and how they might be abstracted to form overarching themes. This increased coherence then provides the basis from which higher-order and abstracted stories about the self can be constructed. Indeed, all three of these types of perceived coherence were observed to predict unique variance in the salience of having life stories. This is consistent with previous findings (Hallford & Mellor, 2017), and the notion that each type of coherence contributes uniquely to the process of developing narratives about oneself.

Narratives about one’s experiences are considered to be somewhat prerequisite to the extraction of meaning about one’s life, and a meaningful self-identity (Singer, 2004).

Similarly, although future time perspective is associated with more goal-directed behavior (Lens, Paixao, Herrera, & Grobler, 2012), one may be less likely to feel self-efficacious and capable of achieving goals in the absence of Journal of Individual Differences (2019), 40(1), 45–54

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self-narratives with content relating to agency and the past overcoming of challenges in one’s life (e.g., Adler, Skalina, & McAdams 2008). Narratives may be understood as a guide for future behavior, but these findings suggest that the subjective coherence and awareness of these narratives, and by extension their possible contribution toward adaptive psychological functioning (Baerger & McAdams, 1999; Pennebaker & Seagal, 1999), seem to be associated primarily with thinking about the past.

Research utilizing this self-report measure of the awareness of life stories and perceived coherence of experiences is in early infancy. Although it has been shown that awareness of narrative identity correlates with adaptive psychological resources, and can be increased through specific reminiscence activities (see Hallford & Mellor, 2016), many questions regarding its role in psychological functioning are yet to be answered. For example, although a future temporal bias did not contribute to awareness of life stories in our study, this may be different in younger individuals. Given the stronger emphasis on future events observed in adolescence and emerging adulthood (Carstensen, 2006), individuals at this age might imagine possible future events more often to conceptualize their current identity, drawing inspiration for their identity from what they anticipate they will experience. Future studies might also test whether awareness of narrative identity moderates the previously demonstrated relationship between objectively assessed coherence and psychological well-being (Baerger & McAdams, 1999; Bauer et al., 2008). More broadly, the incremental validity of narrative identity in well-being (Adler et al., 2016) might be accounted for, in part, by a stronger awareness of life stories, with perceived coherence and past time perspective both contributing to this awareness. Further, it would be interesting to assess whether coherent objective accounts of life stories might interact with stronger self-reported awareness of these stories to produce more coherent narratives of the future self, as assessed objectively or subjectively.

Several limitations of this study should be noted, such as the modest sample size. Replication may assist in establishing the robustness of these findings. Moreover, the correlational nature of the design precludes causal inferences.

Although previous experimental research has provided evidence that thinking about the past can cause a small increase in the awareness of life stories (Hallford & Mellor, 2016), this has not yet been demonstrated in the case of autobiographical coherence and its place in this causal chain. Therefore, future research may seek to include perceived coherence as a mediator in experimental designs.

Tests of indirect effects between variables, such as conducted herein, have inherent limitations regarding directionality, and it can only be ascertained from them that variables are related with one another in some form.

Journal of Individual Differences (2019), 40(1), 45–54

D. J. Hallford et al., Time Perspective and Narrative Identity

Although we specified a particular model in this study, as noted above, further tests are needed to establish the causal relationships. Future studies seeking to replicate or build on these findings might also seek to assess whether cultural background affects the associations between time perspective and perceived narrative coherence. Our sample was predominantly from Australia and the USA, with other country of origin groups too small in number to facilitate reliable comparisons. However, given previous findings showing cross-cultural differences in time perspective (Sircova et al., 2015) and how autobiographical memory is used in forming stories about the self (see Fivush & Nelson, 2004), the moderating factor of cultural heritage might also be examined.

In conclusion, the current study indicated that favoring a past temporal perspective is more strongly associated with a more salient narrative identity and coherency of past experiences, while favoring a future time perspective may marginally decrease the salience of one’s narrative identity.

Acknowledgments Funding: No funding was provided for this research.

Declaration of Conflicting Interest: The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

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00268.x Sircova, A., van de Vijver, F. J., Osin, E., Milfont, T. L., Fieulaine, N., Kislali-Erginbilgic, A., & Zimbardo, P. G. (2015). Time perspective profiles of cultures. In M. Stolarski, N. Fieulaine, & W. van Beek (Eds.), Time perspective theory; review, research and application (pp. 169–187). Cham, Switzerland: Springer.

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Stolarski, M., Matthews, G., Postek, S., Zimbardo, P. G., & Bitner, J. (2014). How we feel is a matter of time: Relationships between time perspectives and mood. Journal of Happiness Studies, 15, 809–827. https://doi.org/10.1007/s10902-0139450-y Syed, M., & McLean, K. C. (2016). Understanding identity integration: Theoretical, methodological, and applied issues. Journal of Adolescence, 47, 109–118. https://doi.org/10.1016/j. adolescence.2015.09.005 Waters, T. E., & Fivush, R. (2015). Relations between narrative coherence, identity, and psychological well-being in emerging adulthood. Journal of Personality, 83, 441–451. https://doi.org/ 10.1111/jopy.12120 Webster, J. D. (2011). A new measure of time perspective: Initial psychometric findings for the Balanced Time Perspective Scale (BTPS). Canadian Journal of Behavioural Science/Revue canadienne des sciences du comportement, 43, 111–118. https:// doi.org/10.1037/a0022801 Williams, J., & MacKinnon, D. P. (2008). Resampling and distribution of the product methods for testing indirect effects in complex models. Structural Equation Modeling, 15, 23–51. https://doi.org/10.1080/10705510701758166 Zhang, J. W., Howell, R. T., & Stolarski, M. (2013). Comparing three methods to measure a balanced time perspective: The relationship between a balanced time perspective and subjective

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well-being. Journal of Happiness Studies, 14, 169–184. https:// doi.org/10.1007/s10902-012-9322-x Zimbardo, P. G., & Boyd, J. N. (1999). Putting time in perspective: A valid, reliable individual-differences metric. Journal of Personality and Social Psychology, 77, 1271–1288.

Zimbardo, P. G., Keough, K. A., & Boyd, J. N. (1997). Present time perspective as a predictor of risky driving. Personality and Individual Differences, 23, 1007–1023. https://doi.org/10.1016/ S0191-8869(97)00113-X Received August 15, 2017 Revision received May 14, 2018 Accepted May 19, 2018 Published online November 16, 2018

D. J. Hallford Deakin University School of Psychology 221 Burwood Highway Burwood 3125 Melbourne, Victoria Australia david.hallford@deakin.edu.au

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Original Article

In Search of the Prosocial Personality Personality Traits as Predictors of Prosociality and Prosocial Behavior Anja Wertag1 and Denis Bratko2 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

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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,

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56

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

Journal of Individual Differences (2019), 40(1), 55–62

A. Wertag & D. Bratko, Personality and Prosociality

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; Mage = 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).

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A. Wertag & D. Bratko, Personality and Prosociality

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. Ó 2018 Hogrefe Publishing

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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 Journal of Individual Differences (2019), 40(1), 55–62

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A. Wertag & D. Bratko, Personality and Prosociality

Table 1. Summary of means, SDs, and Pearson’s correlations among measured variables Gender

Age

PSB

(.78)

H

E

X

A

C

Age

.10**

PSB

.15**

.18**

H

.12**

.03

.40**

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

O

M

N

P

(.77)

(.78)

M

.13**

.03

.45**

.52**

.13**

.15**

.32**

.07

.05

N

.08*

.03

.16**

.40**

.12**

.43**

.19**

.12**

.11**

(.77) .30**

P

.15**

.01

.45**

.38**

.16**

.14**

.42**

.18**

.01

.57**

(.66) .28**

(.73)

M

–

22.04

96.12

3.37

3.36

3.25

3.00

3.47

3.69

2.91

2.70

2.07

SD

–

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 B

SE B

Model 2 β

B

SE B

Model 3 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

2.19

0.63

.14**

N

0.81

0.72

.04

2.74

0.69

.16**

P R2

.06

.37

.41

F

22.51**

49.03**

42.89**

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

1

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 (w2 = 5.21, df = 6, p = .52), while with the Dark Triad, narcissism had a significant contribution in the third step (w2 = 9.24, df = 3, p = .03; Table 3).

Summary of descriptives and correlations among study variables in this subsample is available in Table 1 in the Electronic Supplementary Material, ESM 1.

Journal of Individual Differences (2019), 40(1), 55–62

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A. Wertag & D. Bratko, Personality and Prosociality

59

Table 3. Summary of hierarchical logistic regression analysis for variables predicting prosocial behavior Model 1 B

SE B

Model 2 OR [95% CI]

B

SE B

Model 3 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]

1.00 [0.96, 1.04]

0.00

0.02

M

0.06

0.26

0.94 [0.56, 1.56]

N

0.74**

0.29

0.48 [0.27, 0.84]

P Constant

2.41

0.79

0.09

4.92

1.80

0.01

0.17

0.29

0.84 [0.48, 1.49]

1.59

2.55

0.20

w2

8.12*

13.33

df

2

8

11

Pseudo-R2

.03

.05

.09

%

64.6

64.9

65.5

22.57*

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 fearful2

ness, 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

The facet-level correlation matrix is available from the first author upon request.

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Journal of Individual Differences (2019), 40(1), 55–62

60

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 Journal of Individual Differences (2019), 40(1), 55–62

A. Wertag & D. Bratko, Personality and Prosociality

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 Ó 2018 Hogrefe Publishing

A. Wertag & D. Bratko, Personality and 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.

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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

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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 di-

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verse 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 “The field of cultural clinical psychology takes an important stride forward with this carefully edited volume on the cultural shaping of posttraumatic stress disorder.”

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

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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.”

•H ow culture shapes mental health and recovery

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:

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.

• How to integrate culture and context into PTSD theory •H ow trauma-related distress is experienced and expressed in different cultures, reflecting local values, idioms, and metaphors • How to integrate cultural dimensions into psychological interventions