A comparison of self-other agreement in personal values versus the Big Five personality traits

Journal of Research in Personality 50 (2014) 1–10

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A comparison of self-other agreement in personal values versus the Big Five personality traits Henrik Dobewall a,⇑, Toivo Aavik a, Kenn Konstabel b, Shalom H. Schwartz c, Anu Realo a a

University of Tartu, Estonia National Institute for Health Development and University of Tartu, Estonia c The Hebrew University of Jerusalem, Israel and National Research University, Higher School of Economics, Russia b

a r t i c l e

i n f o

Article history: Available online 31 January 2014 Keywords: Self-other agreement Profile similarity Personal values Big Five personality traits Correction for attenuation

a b s t r a c t Can we judge other people’s values accurately, or are values too subjective to assess? We compared selfother agreement in personal values with agreement in the Big Five personality traits. Self-other agreement in four higher-order values (median r = .47) and in six culture-specific value factors (median r = .50) was substantial and similar to that for the Big Five personality traits (median r = .51). When corrected for attenuation due to measurement error self-other agreement was high for all three scales (median rs > .65). The results suggest that people can assess values of others whom they know well with remarkable accuracy. Therefore, other-ratings of personal values can be used to validate and complement self-report value measures. Ó 2014 Elsevier Inc. All rights reserved.

1. Introduction The limits of self-report methodology confront researchers in many areas of psychological science. People’s reports of their behaviour, attitudes, and personality may be affected by various response biases such as socially desirable, neutral, or extreme responding, and acquiescence (e.g., Mõttus et al., 2012; Paulhus, 1991; Schwartz, Verkasalo, Antonovsky, & Sagiv, 1997). Based only on people’s potentially biased self-reports, we cannot be certain whether a person truly endorses benevolence values highly or rejects power values, nor can we be sure a person is actually extraverted or agreeable. To get around self-report biases, it is necessary to collect data with an independent method of measurement. Judgments of other people (e.g., peers, spouses, siblings, parents, etc.) who know the person well can serve this purpose. The degree of agreement between self- and other-ratings—also called convergent validity (Campbell & Fiske, 1959) or consensual validity (McCrae, 1982; McCrae et al., 2004)—can clarify the accuracy of self-reports. Self-other agreement, typically operationalized as a correlation between the two ratings, refers to the extent to which two perceivers (an informant and a target in our case) view the target in the same way (Kenny & West, 2010). Several studies have shown relatively strong self-other agreement in all the Big Five personality ⇑ Corresponding author. Address: Department of Psychology, University of Tartu, Näituse 2, Tartu 50409, Estonia. E-mail address: [email protected] (H. Dobewall). http://dx.doi.org/10.1016/j.jrp.2014.01.004 0092-6566/Ó 2014 Elsevier Inc. All rights reserved.

traits (e.g., Allik, Realo, Mõttus, Esko, et al., 2010; Connolly, Kavanagh, & Viswesvaran, 2007; Hall, Andrzejewski, Murphy, Schmid Mast, & Feinstein, 2008), in affective traits (Watson, Hubbard, & Wiese, 2000), and in subjective well-being (Dobewall, Realo, Allik, Esko, & Metspalu, 2013; Schneider & Schimmack, 2009). Surprisingly few studies, however, have investigated selfother agreement in personal values. How can we explain the relative lack of interest in self-other agreement by value researchers? One reason might be that personal values are considered ‘‘too individually subjective’’ (Hitlin & Piliavin, 2004, p. 359) to be judged by others. McAdams (1995), for instance, distinguished between individual differences in traits, which he described as so easily observable that even a stranger could judge them with some accuracy, and more privately held personal concerns like values, which are less accessible. This view is at odds with the Five Factor Theory (FFT) of personality, according to which, values, are so-called characteristic adaptations which are formed through the interaction of personality traits with the environment (McCrae & Costa, 1999, 2008). As such, values can be assessed better by direct observation than Big Five personality trait domains can (Allik & McCrae, 2002). Resolving these contradictory views requires an empirical assessment of whether selfother agreement is greater in personal values or in personality traits. The current study examines self-other agreement in personal values, both in four higher-order values and in six culture-specific value factors. In order to assess whether values show greater or

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lesser levels of self-other agreement than personality traits, we compared self- and other-ratings of values and of personality domains in the same sample. If the level of self-other agreement in values is comparable to the level in personality traits, it would suggest that other-ratings can also be used successfully in value research. Another way to think about self-other agreement refers to agreement about a person’s profile of values or traits. Does one person accurately perceive another’s hierarchy of values—the relative importance of different values to the other person? How accurate is an observer’s perception of the relative degree to which different traits characterize a person? With this aim in mind, we also assessed self-other agreement regarding individual’s profile of values and traits by computing—raw and distinctive—profile correlations (Furr, 2008). This approach can reveal how well an informant knows, for example, whether a target values self-transcendence highly, openness to change moderately but more than self-enhancement, and does not care at all about conservation.

The strongest evidence for self-other agreement in personal values comes from a study by Lee and colleagues (2009). They examined both actual and assumed similarity of values using the full SVS. They reported self-other agreement correlations for the two major value dimensions of openness to change versus conservation (r = .42) and self-transcendence versus self-enhancement (r = .52). They also reported self-other agreement for the ten broad values, with correlations ranging from r = .18 for achievement to r = .49 for power. However, none of the above-mentioned studies took the examination of self-other agreement in personal values as their focus. 1.2. Comparing values and traits Should we expect different levels of self-other agreement in values as compared to personality traits? If so, why? In order to answer these questions, we must first examine how values and personality traits relate conceptually. Therefore, in the next sections we discuss the similarities and differences between these two constructs.

1.1. Self-other agreement in values and other related constructs As noted above, considerable research has examined self-other agreement in such personality constructs as traits, emotional experience, and subjective well-being. For instance, across 36 studies of the Big Five personality traits, the average correlation between self- and other-ratings was r = .36 (Connolly et al., 2007). In other studies, self-other agreement in personality traits has ranged from r = .40 to .70 (Konstabel, Lönnqvist, Walkowitz, Konstabel, & Verkasalo, 2012; McCrae et al., 2004). Agreement correlations for affective traits are only slightly lower than for the personality domains (Watson et al., 2000). For subjective well-being, a recent meta-analysis of 44 studies yielded an average self-other agreement correlation of r = .42 (Schneider & Schimmack, 2009). Substantial cross-observer agreement has also been observed in such constructs as moral character (Cohen, Panter, Turan, Morse, & Kim, 2013), sociopolitical (Beer & Watson, 2008) and ideological attitudes and prejudice (Cohrs, Kämpfe-Hargrave, & Riemann, 2012). As noted, the use of other-ratings in value research is relatively scarce. Rentfrow and Gosling (2006), for example, asked informants who knew only about their target’s top-ten music preferences to describe their values on an abbreviated version of the Rokeach Value Survey (Rokeach, 1973) and their personality traits on a 44-item Big Five Inventory (Benet-Martinez & John, 1998). In this zero-acquaintanceship study, the average agreement correlation across the specific value items was r = .15. Paryente and Orr (2010) reported agreement correlations between children’s perceptions of their parents’ values and their mother’s and father’s self-reports for tradition (r = .41/.39, respectively) and selfenhancement values (r = .56 /.52). Another study of a small student sample, yielded self-peer agreement correlations ranging from r = .33 (conservation) to r = .54 (self-transcendence), using 28 value items of the Schwartz Value Survey (SVS; Bernard, Gebauer, & Maio, 2006; Schwartz, 1992). Murray and colleagues (2002) asked dating and married couples to describe their own and their partners’ traits, feelings, and values, using a list of 18 values adapted from the Schwartz and Bilsky (1990) and Rokeach and Ball-Rokeach (1989) value measures. The similarity (i.e., the intraclass correlation1) between men’s and women’s value profiles was .26 for those who were dating and .29 for married couples (Murray et al., 2002). 1 Pairwise intraclass correlations provide an estimate of similarity that captures whether judges agree on their absolute ratings of their specific values; as opposed to relative similarity of values tapped by Pearson correlations.

1.2.1. Conceptual similarities and differences between traits and values Values. Schwartz’s (1992) theory of basic human values defines values as desirable, trans-situational goals, varying in importance, that serve as guiding principles in people’s lives. Schwartz (2005a) summarized the features that are common to all values as follows: ‘‘(a) Values are beliefs. But they are beliefs tied inextricably to emotion, not objective, cold ideas. (b) Values are a motivational construct. They refer to the desirable goals people strive to attain. (c) Values transcend specific actions and situations. They are abstract goals. The abstract nature of values distinguishes them from concepts like norms and attitudes, which usually refer to specific actions, objects, or situations. (d) Values guide the selection or evaluation of actions, policies, people, and events. That is, values serve as standards or criteria. (e) Values are ordered by importance relative to one another. People’s values form an ordered system of value priorities that characterize them as individuals. This hierarchical feature of values also distinguishes them from norms and attitudes’’ (Chapter 1, Introduction). Values also differ from motives and needs, because ‘‘values are inherently desirable and must be represented cognitively in ways that enable people to communicate about them’’ (Roccas, Sagiv, Schwartz, & Knafo, 2002, p. 789). Recent research (Bilsky & Schwartz, 2008), however, suggests that different indicators of the same motive construct are correlated, independent of the assessment method (i.e., implicit versus explicit). Schwartz (1992) specified ten broad values according to the type of goal or motivational concern that they express: He grounded the ten values in one or more of three universal requirements of human existence: (1) needs of individuals as biological organisms, (2) requisites of coordinated social interaction between individuals, and (3) survival and welfare needs of groups. These motivationally distinct value orientations have been recognized and discriminated by people in over 82 countries studied thus far (Schwartz, 2012). They form a quasi-circumplex structure, presented in Fig. 1, organized by the conflict (the more distant) and congruence (the closer) among the values (cf. Schwartz, 2005a). Personality traits. According to the FFT (McCrae & Costa, 1999, 2008), individual psychological differences can be divided into basic tendencies and characteristic adaptations. Personality traits are basic tendencies that ‘‘refer to more basic, abstract ways of living that are part of the human nature, and thus found in all cultures and at all times’’ (McCrae, 2010, p. 58). More specifically, personality traits are enduring tendencies to behave, think, and feel in consistent ways (McCrae & Costa, 1999, 2008). Cross-observer agreement is often taken as a major indication that personality traits are real, objective psychological attributes

H. Dobewall et al. / Journal of Research in Personality 50 (2014) 1–10

Fig. 1. The value circle of the Schwartz value theory: Ten broad values and four higher-order values. Adapted from Schwartz (1992). Universals in the content and structure of values: Theoretical advances and empirical tests in 20 countries. Advances in Experimental Social Psychology, 25, p. 45. Copyright 1992 by Elsevier. Adapted with permission. Hedonism shares elements of self-enhancement but is most frequently closer to openness to change, where we placed it in this study.

(Funder, 1995). According to McCrae and colleagues (2004), selfother agreement in personality traits ‘‘played a major role in establishing the Five-Factor Model (FFM) of personality as a widely accepted taxonomy of traits’’ (p. 180). Big Five personality traits are latent and therefore not directly observable; they must be inferred on the basis of thoughts, feelings, and behaviours. Furthermore, the FFT postulates that there is little, if any, influence of the environment (e.g., culture or life experiences) on the basic tendencies (Allik, 2002; McCrae & Costa, 2008). The evidence for this comes from studies that show that the five personality factors are universal across cultures (McCrae & Costa, 1997; McCrae, Terracciano, et al., 2005), personality traits change little throughout life (Costa et al., 2000), and that parenting or child-rearing practices have little effect on child’s personality (e.g., Plomin, Corley, Caspi, Fulker, & DeFries, 1998). FFT views values as characteristic adaptations that help the individual to adapt to changes in the social and physical environment. Values are influenced by traits and learned in a particular times and contexts. Thus, the main conceptual difference between traits and values in the FFT is that traits are endogenous latent tendencies, shielded from the direct effects of the environment, whereas values are formed through socialization. As Olver and Mooradian (2003) put it, traits address nature and values address the interaction between nature and nurture. Recent evidence suggests, however, that values are partially heritable (Knafo & Spinath, 2011; Schermer, Feather, Zhu, & Martin, 2008) and that common genetic factors influence values and traits (Schermer, Vernon, Maio, & Jang, 2011). Schwartz (2013) argues that genes and personality interact with the environment ‘‘to generate the substantial variance in value priorities across individuals . . .. [Values] serve as filters that transform the same social experience into different subjective experiences for each individual’’ (p. 5). This literature rejects the FFT view of values as completely lacking a direct genetic base. Moreover, there is an ongoing debate among value researchers about the causal relations between values and traits (see Fischer & Boer, 2013; Nilsson, 2014; Roccas et al., 2002). The extent to which traits and values are stable across time and contexts might contribute to observers’ success in perceiving them accurately. According to FFT theory, traits are relatively stable, and empirical research has supported this claim (Costa et al., 2000). If

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stability in values is lower, this would lead us to expect lower self-other agreement in values. However, test–retest correlations of values in student and adult samples, tested from 1 month to 2 years apart, were remarkably high (Schwartz, 2005b). Further, Bardi, Lee, Hofmann-Towfigh, and Soutar (2009) found only small changes in value priorities in four longitudinal studies that varied in life contexts, time gaps, and populations. Moreover, Bardi, Buchanan, Goodwin, Slabu, and Robinson (2013) found substantial stability of values over nine months among police recruits undergoing training, over three years of university among psychology and business students, and over 18 months among Polish immigrants following their immigration to Great Britain. Even among the latter, who went through a major life transition, the mean stability correlation for the 10 Schwartz values was .61 (SD = .07). Thus, traits and values may not differ enough in stability to make it easier to perceive one than the other. Values are goals that motivate behaviour, but they are not behaviours themselves. As values refer to motivation, not to action, observers must infer them indirectly (Bardi & Schwartz, 2003). Rokeach (1973) and Schwartz (1992) both suggested that it is difficult for others to infer a person’s values because a value may be expressed in a variety of relevant behaviours and because any single behaviour may express multiple values. However, Funder (1995, p.659) made the same point about traits: ‘‘. . .many different cues might be diagnostic of the same trait, whereas the same cues might be simultaneously diagnostic of different traits’’ (Funder, 1995, p. 659). Taken together, the theorizing and empirical findings provide no strong arguments for expecting a difference between traits and values in the level of self-other agreement. 1.2.2. Moderating effects of acquaintance and socially desirable responding Personality researchers (Funder, 1995; McCrae & Costa, 2008) assume that people are usually capable of reporting on their own and other people’s characteristics. McAdams (1995; McAdams & Pals, 2006) suggests that the process of getting to know someone starts with personality traits. Additional time is needed before interaction partners exchange information/cues about other psychological attributes such as attitudes or value hierarchies. Therefore, in order to allow for a fair comparison of self-other agreement in traits and values, we used well-acquainted informants in our study. Socially desirable responding may lead to inaccuracy in both self-reports and other-reports (Konstabel, Aavik, & Allik, 2006). This is especially true when reporting on characteristics with an evaluative component such as personal values and such traits as conscientiousness (Funder, 1995; Kenny & West, 2010). Social desirability may affect responses to questionnaires both consciously (impression management) and unconsciously (self-deceptive enhancement; Paulhus, 1991). If informants and targets are close, the motivation to present the target in a more positive light than warranted by the facts may bias other-reports (see Allik, Realo, Mõttus, Borkenau, et al., 2010). Thus, socially desirable responding, by either targets or informants, potentially confounds self-other agreement correlations (Funder, 1995) because it says more about social norms than about the target’s personality (Konstabel et al., 2006). We return to this issue when discussing profile similarity (Section 1.3). 1.2.3. Correction for measurement error Previous research in the field of personality has identified several moderators of self-other agreement in addition to acquaintance and evaluativeness. Visibility, (assumed) similarity, and more technical aspects, such as wording or format of the questions, scale variance, and measurement error may significantly impact the magnitude of self-observer agreement (e.g., Allik, Realo,

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Mõttus, Borkenau, et al., 2010; Allik, Realo, Mõttus, Esko, et al., 2010; Watson et al., 2000). We controlled one of these, random error in measurement, in order to obtain more accurate comparisons between self-other agreement in values and in personality traits. Any observation or response (e.g., a self- or other-rating) may include a large random component. This random error of measurement can be reduced by obtaining multiple responses or observations of the same construct, each with its own random error, and averaging them to generate a score for the construct (Schmidt & Hunter, 1996). Internal consistency coefficients that measure the reliability of test scores (e.g., coefficient alpha; Cronbach, 1951) can be used to estimate the proportion of true score variance in the measurement of a variable. These coefficients are a function of two parameters: (1) the average inter-correlation among the set of items in the scale that measures the construct and (2) the number of items in the scale (Simms & Watson, 2007). The study by Connolly and colleagues (2007) illustrates the impact of random error on self-other agreement in traits. When they adjusted the observed correlations for the (un)reliability of measurement, the weakest self-other agreement (agreeableness) increased from r = .30 to .46 and the strongest (extraversion) from r = .45 to .62. This suggested that the ‘‘true’’ associations between self- and other-ratings were considerably stronger than the observed correlations implied. It is especially important to correct for measurement error2 when comparing self-other agreement in this study because the proportion of error in the measurement of values and of personality traits is likely to differ. Previous research with the value scale we adopted from the European Social Survey (ESS), the PVQ21 (Schwartz, 2007), yielded lower alphas than the scale we use for our personality measure, the Short Five (S5; Konstabel et al., 2012). For example, the internal consistency coefficients of the ten specific values in Schwartz (2007) ranged from .36 to .70, and the Cronbach alphas of the four higher-order values ranged from .69 to .75. In contrast, the Cronbach alphas of the domain scales of the S5 typically range from .74 to .89 (Konstabel et al., 2012). The low reliabilities of the ten PVQ21 values reflects the facts that each scale has only two items (three for universalism) and that these items were constructed to cover the broad conceptual components of each value rather than to express the same narrowly defined content (Schwartz, 2005a). We report both the attenuated correlation coefficients to compare the observed levels of agreement with earlier research and the disattenuated coefficients to provide a fair comparison of traits and values. 1.3. Aim of the study The main aim of the current study is to compare self-other agreement in two aspects of personality—personal values and personality traits—using the same sample of respondents. Our study goes beyond earlier research (e.g., Lee et al., 2009) in several important respects. First, when examining self-other agreement in values and personality, we correct for the biases caused by measurement error in both value and personality scales, as proposed by Schmidt and Hunter (1996). Second, we obtain other-ratings of both values and personality traits from two observers of each target. After estimating the degree of consensus between two judges, we use the mean score of the two other-ratings for each value and personality scale in order to reduce the common method bias due to individual response biases. As Chang, Connelly, and Geeza (2012) point out, ‘‘[w]hen personality ratings are averaged across multiple raters, the 2 It should be noted that the widely used approach to correct for attenuation is not without critics (Traub, 1997, for a review).

variance in ratings shared across raters (i.e., trait factors) increases, whereas the variance idiosyncratic to individual raters (i.e., method factors) declines’’ (p. 423). This has been demonstrated in the case of personality traits: Self-other agreement was lower when self-reports were correlated with a single other-report than when they were correlated with the average of two or more otherreports (McCrae et al., 2004). However, we are aware that it is not always possible to obtain ratings from two or more informants. To allow comparisons with the results of other studies and in order to show that the obtained self-other agreement is not ‘‘simply a result of the psychometric benefits of aggregation’’ (Vazire & Mehl, 2008, p. 1209), we also report the self-other agreement correlations between a target and a single informant. Thirdly, the self-other agreement correlations described above reveal how accurately a rater perceives the target’s self-rating of each single value or trait. It does not reveal whether raters accurately perceive a target’s value or trait hierarchy, that is, which values or traits are more and less highly rated by the target. For this purpose, we employ profile correlations (Furr, 2008) that allow us to examine similarity in shape of the two (self-reports versus average of the two other-reports) profiles. First, we calculate correlations between all pairs of raw, unadjusted profiles of self- and other-ratings. This is called overall similarity as measured by the raw profile correlation. Accurate perception of targets’ profiles may yield high overall similarity between self- and other-reports of values and traits, but profile normativeness (Cronbach, 1955) could also cause this. In other words, any two profiles may be similar because they both reflect an average profile. Moreover, social desirability, which is also associated with normativeness, may spuriously enhance accuracy (Furr, 2008). In order to eliminate the effects of the average profile and of social desirability on profile accuracy, we z-standardize the answers of both targets and informants within the sample (means = 0; SDs = 1) and calculate correlations between any pairs of distinctive profiles. This is called distinctive similarity as it ‘‘reflects the similarity between the unique aspects of the two profiles within a pair—the degree to which one distinctive profile matches another distinctive profile’’ (Furr, 2008, pp. 1277–1278). When rating values, individuals differ in the mean rating they give to the set of all values. Based on the validated assumption that the ten broad values in his theory are a reasonably comprehensive representation of the different values people hold, Schwartz (2007) suggested that the true importance individuals attribute to all values on average is similar across people. Consequently, observed differences in individuals’ average value ratings largely reflect differences in response style, including the tendency to respond in a socially desirable manner. Applications of the Schwartz value instruments, comparing individual or group value priorities or relating value priorities to other variables, typically calculate each individual’s mean rating of all value items and use it to control for differences in response style. We adopt this procedure. Mean scores across all value items also have some substantive meaning (Lönnqvist, Verkasalo, & Bezmenova, 2007; Schwartz et al., 1997). However, regardless of the extent to which individuals’ mean value ratings signify style or substance, they too are relatively stable individual characteristics. Can informants assess targets’ mean value ratings with any accuracy? Informants are unlikely to know how targets use a response scale, whether they spread their answers across the scale or concentrate them toward the upper or lower ends (see Schwartz, 2005a). It is plausible, however, that informants might have a sense of the extent to which targets describe themselves as strongly endorsing few or many values, or to which they describe themselves in a socially desirable way (Lönnqvist et al., 2007; Schwartz et al., 1997). It is therefore interesting to assess the correlation between the average self-rating of values and the average other-rating of the target’s values. This is the forth aspect by which we differ from previous research.

H. Dobewall et al. / Journal of Research in Personality 50 (2014) 1–10

2. Method 2.1. Data 2.1.1. Sample 1 One hundred and one participants (21 males and 80 females), with a mean age of 25.7 years (SD = 7.9) completed self-report measures of personal values (PVQ21; Schwartz, 2007) and personality traits (The S5; Konstabel et al., 2012). Two informants (mean age 26.9 years, SD = 9.5 years) who knew the target well provided, upon invitation of the target, other-ratings on the same instruments. Of the informants, 44.1% were friends of the target, 18.3% partners (spouses or co-habitants), and 9.4% were girl- or boyfriends. On average, the informants had known the target for 9.7 years (SD = 8.2). The gender of the informants was quite balanced (44.5% were male; 8.4% of the respondents did not report their gender). 2.1.2. Sample 2 Sample 2 consisted of 100 participants (86 female, 13 male, and 1 person who did not report gender) with a mean age of 21.8 years (SD = 4.3). The participants were asked to complete the self-report form of the Estonian Value Inventory (EVI; Aavik & Allik, 2002) and to find two acquaintances who would agree to rate their values using the same instrument. All the acquaintances were relatives or close friends (mean age 26.7 years, SD = 10.9 years; 74% female). The average time of acquaintance was 3.4 years and most acquaintances met the subjects ‘‘every day (4)’’ (from the options ranging from ‘‘once in a year (1)’’ to ‘‘spend together most of time (5)’’). Participants were students of three universities in Estonia: University of Tartu, the Estonian University of Life Sciences, and the Estonian Entrepreneurship University of Applied Sciences. The questionnaires were completed on a volunteer basis, but some psychology students received extra credit that contributed to the fulfilment of their course requirements. Approximately 75% of the respondents completed all questions. No financial compensation was provided. In Sample 1, we dropped five participants for whom we received no other-reports and used the single other-rating we received for five other participants. For the remaining 91 participants, we averaged the two other-ratings. If respondents had missing values for five or fewer variables, they were replaced with the sample mean for the respective variable. Respondents with more than five missing values were dropped from analyses. In Sample 2, we dropped two participants who did not provide self-ratings and one for whom we received no other-ratings. For nine participants we received only a single other-report. For 88 participants we averaged the two other-ratings. We dropped one participant and six other-ratings because of more than 10 per cent missing data. In all other cases, we replaced missing values with the mean score across all participants. 2.2. Measurement instruments 2.2.1. The PVQ21 The PVQ21 is derived from the 40-item Portrait Values Questionnaire (Schwartz, 2003; Schwartz et al., 2001) for use when space or time limitations require a drastic reduction in the number of items. The PVQ21 includes short verbal portraits of 21 different people in terms of the goals and aspirations important to them (Schwartz, 2007). We used the Estonian version that is used in the ESS. Respondents reported how similar each of the people portrayed is to themselves (self-rating form) or to the target person (other-rating form). Similarity judgments were made on a 6-point numerical scale ranging from 1 (very much like me (him/her)) to 6 (not like me (him/her) at all). For example, the following is an

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achievement item: ‘‘It is important to him/her to show his abilities. She/He wants people to admire what he/she does.’’ We computed importance ratings for the four higher-order values by averaging the following relevant items (cf. Fig. 1): the four power and achievement items for self-enhancement, the five universalism and benevolence items for self-transcendence, the six self-direction, stimulation and hedonism items for openness to change, and the six security, conformity and tradition values for conservation. 2.2.2. The Estonian Value Inventory Aavik and Allik (2002) developed an Estonian culture-specific value inventory (i.e., a native language-based set of values). The general structure of the EVI ‘‘refers to the same two-dimensional level of higher-order values described by Schwartz in 1992’’ (Aavik & Allik, 2002, p. 221). The EVI includes 48 value-related words derived through a lexical approach. This set of values consists of nouns (e.g., solidarity, uniqueness, creativity, passion, rationality) and avoids the use of adjectives that may be understood as personality descriptions. The participants were asked to report their own personal values ‘‘as a guiding principle in your life, your aspirations or what you are trying to avoid.’’ A seven-point scale rating from 3 (personally extraordinarily important to aspire) to 3 (personally extraordinarily important to avoid) was used. The informants received standard rating instructions with the subject’s name and used the same rating scale as the targets. To compute the self- and other-ratings of the six value factors, the eight items were averaged for each factor. A factor analysis extracted five factors which moderately correlated with the ten broad values described by Schwartz (1992). Aavik and Allik (2002) labelled the emergent value factors as follows (parallels to the Schwartz values in parentheses): benevolence (benevolence/tradition), self-enhancement (power/achievement), broadmindedness (universalism/self-direction), hedonism (hedonism/stimulation), and conservatism (conformity/security). A sixth factor – self-realization – was unrelated to Schwartz’s values. The Cronbach alphas of the six EVI scales ranged from .78 to .86 (Aavik & Allik, 2002). 2.2.3. Personality traits The Estonian version of the S5 (Konstabel et al., 2012) personality inventory was used in the current study. The S5 consists of 60 items that measure the 30 subscales of the Five-Factor model of personality (Costa & McCrae, 1992). Each subscale is assessed with two relatively long and comprehensive trait items – a negative and a positive item. The subscales are grouped into six facet scales. For example, the openness to actions (O4) subscale items are: ‘‘He/she likes to try different activities, to visit different places, to try out unfamiliar and exotic things from time to time; She/he loves novelty and variety’’ (positive, other-rated form) and ‘‘Changes annoy me. I like to do everything in an accustomed and proven manner’’ (negative item, self-rated form). Responses are provided on a 7-point scale ranging from 3 (completely disagree) to +3 (completely agree). We reverse coded the negative items and summed the two items for each of the 30 personality trait facet scores. We averaged the six facet subscales to obtain scores for each of the five personality domains so that each domain score was based on 12 indicators. 3. Results 3.1. Inter-rater consensus in values and traits First, we examined to what extent the two informants agreed on the characteristics of a target (Table 1). The inter-rater consensus in PVQ21 higher-order values (median r = .37) as well as in the EVI value factors (median r = .23) was not significantly weaker

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Table 1 Inter-rater consensus (Samples 1 and 2) for higher-order values (PVQ21), Big Five personality domains (S5), and specific value factors (EVI). Inter-rater agreement PVQ21 Openness to change Conservation Self-enhancement Self-transcendence

.42 .35 .35 .37

S5 Neuroticism Extraversion Openness Agreeableness Conscientiousness

.41 .54 .43 .49 .31

EVI Self-realization Self-enhancement Benevolence Hedonism Conservatism Broadmindedness

.13 .37 .19 .35 .23 .23

Note. N = 89 in Sample 1 and N = 86 in Sample 2. Correlations with rs < .2 are ns.; rs < .25 are p < .05; rs > .25 are p < .01.

than in Big Five personality traits (median r = .43), Z = and Z = 1.47, p = .14, respectively.

.47, p = .64

3.2. Internal consistency of the value and personality trait measures The top panel of Table 2 presents the internal consistencies of the PVQ21 higher order values and the S5 personality domain scales (self- and other-ratings) from Sample 1. Cronbach alphas for the personality domain scales were similar for self-ratings (median = .83) and other-ratings (median = .85). Cronbach alphas for the higher-order values were slightly lower but also similar for self-ratings (median = .72) and other-ratings (median = .79). The bottom panel of Table 2 presents the internal consistencies of the six Estonian value types from Sample 2. All alphas were above .65, with similar reliabilities for self-ratings (median = .74) and other-ratings (median = .79). The eight-item value indexes of the EVI factors and the four- to six-item indexes of the higher order PVQ21 values showed similar levels of reliability. Not surprisingly, the reliability of the two-item (three for universalism) PVQ21 indexes of the ten broad values items were lower, with median alphas .62 (self-ratings) and .65 (other-ratings). 3.3. Self-other agreement The diagonal of the top panel of Table 2 presents the correlation coefficients for self-other agreement in ratings of the four higherorder values and five personality domains in Sample 1. The observed self-other agreement in all higher-order values (range .43–.50, median r = .47) was smaller than in all personality domains (range .51–.74, median r = .52). However, the medians did not differ significantly (Z = 0.46, p = .65). Self-other agreement was greatest in extraversion (r = .74) and smallest in self-transcendence values (r = .43). All self-other agreement correlations indicated substantial convergence of self-other reports both in values and personality traits. Next, we examined the self-other agreement between a target and a single informant (Table 3). We selected friends because they formed the largest subgroup of informants. In the case of two friend-reports, we chose the one with the longest acquaintanceship (mean = 10.4 years; SD = 6.6). Also the self-friend agreement (N = 63) for higher-order values (median r = .45, ranging from .35

to .51) was at a comparable level (Z = .57, p = .57) with personality traits (median r = .48, range .43–.78). As expected, the self-other agreement correlations were somewhat weaker for both personality and values scales when using a single informant than the selfother agreement based on the average of two other-reports. The small, non-significant differences in the size of agreement correlations for the value versus personality scales may reflect differences in scale reliabilities. To assess this possibility, we corrected the scales for attenuation due to measurement error. We divided each agreement correlation by the square root of the product of the reliability coefficients of the self- and other-ratings on which it was based (Spearman, 1904). The disattenuated agreement coefficients are presented in brackets. After dissattenuation, the self-other correlations for the higher-order values (median r = .65) and the Big Five personality domains were nearly equal (r = .68).3 Self-other agreement after disattenuation was greatest in extraversion (r = .86) (as in most previous studies), and smallest in conscientiousness (r = .61), another personality domain.4 The diagonal of the bottom panel of Table 2 reports the selfother agreement coefficients for the five EVI value factors for Sample 2. These ranged from r = .37 (benevolence) to .58 (hedonism), with a median of r = .50. Self-realization, which is a value type not assessed in Schwartz inventories, showed the weakest agreement, r = .34. The median of the disattenuated agreement coefficients, r = .68, was similar to those for the higher-order values and the Big Five personality domains in Sample 1.5 This suggests that observers who know the target well can successfully assess culture-specific value factors and not only higher-order values and personality domains. In order to assess self-other agreement regarding the individual’s value hierarchies, we conducted an analysis of profile similarity (Furr, 2008). First, we computed the respective profile correlations for each informant-target pair. Because Pearson’s r is not normally distributed, we secondly converted all correlation coefficients (i.e., rs) using Fisher r-to-z-transformation and averaged those values. Finally, the average z was transformed back to an r. The (average) raw profile correlations were r = .80, .73, and .84 for the PVQ21, the EVI, and the S5, respectively. The (average) distinctive profile similarity, that is, the similarity between the unique aspects of the two profiles within a pair, was (in the same order) r = .66, .49, and .70, respectively. This suggests that also personal value and trait hierarchies can be assessed by close others. The EVI factors showed weaker distinctive profile correlations than the PVQ21 (Z = 1.76, p = .08) and the S5 factors (Z = 2.26, p < .05) but the difference between the profile correlations was statistically significant only in the latter case. Finally, we examined self-other agreement regarding respondents’ tendency to rate values relatively high or low on the response scale regardless of their content. The self-other agreement correlations in the mean rating of all values captured agreement regarding this tendency. These correlations were relatively weak and smaller than agreement in any of the values in both Samples 1 (r = .28, .40 if disattenuated) and 2 (r = .35, .38 if disattenuated).

3 The difference between this pair of median correlation coefficients is apparently non-significant (Z = 0.36; p = .71), but Kenny and West (2010) argue against a Fisher r-to-z transformation when using disattenuated correlations. 4 Agreement coefficients were somewhat smaller based on uncentered value scores, but not substantially so. In the higher-order values, the median self-other agreement was r = .42 (.58, disattenuated). This supports the robustness of the selfother agreement coefficients. By randomly pairing informants with targets, we assessed how much variance was shared by chance. The convergence was extremely small both for values, median r = .05, and for the traits, median r = .05. 5 The median observed self-other agreement in uncentered value scales was r = .39, after correction r = .51.

7

H. Dobewall et al. / Journal of Research in Personality 50 (2014) 1–10 Table 2 Self-other agreement correlations, scale inter-correlations, and internal consistency coefficients for Sample 1 and Sample 2. 0

1

Sample 1 0. Cronbach a

2

3

4

5

6

7

8

.75

.57

.69

.74

.90

.86

.70

.70

.83

.07

.84

.04

.33

.42

.38

.12

.01

.07

.67

.26

.05

.24

.50

.10

.49 (.64) .01

.33

.35

.44

.39

.08

.03

.45 (.58)

.13

.18

.13

.43

.04

.60 (.68) .32

.31

.13

.14

.51

.34

.03

.21

.34

.02

.52 (.69) .06

.05

PVQ21 1. Openness to change

.79

2. Self-transcendence

.79

.50 (.65) .02

3. Conservation

.63

.82

.43 (.74) .16

4. Self-enhancement

.81

.22

.76

S5 5. Neuroticism

.86

.03

.45

.12

.34

6. Extraversion

.86

.55

.13

.57

.10

7. Openness

.79

.51

.39

.55

.36

.17

.74 (.86) .50

8. Agreeableness

.80

.01

.72

.05

.74

.44

.20

.51 (.68) .36

9. Conscientiousness

.85

.17

.09

.10

.02

.44

.15

.04

0

9

1

2

3

4

5

.51 (.61) 6

Sample 2 EVI 0. Cronbach Alpha 1. Self-realization 2. Self-enhancement 3. Benevolence 4. Hedonism 5. Conservatism 6. Broadmindedness

.78 .81 .80 .84 .79 .66

.75 .34 (.44) .30 .02 .51 .09 .21

.73 .18 .50 (65) .73 .40 .33 .43

.80 .06 .65 .37 (.46) .47 .28 .16

.80 .37 .26 .47 .58 (.71) .62 .30

.73 .01 .13 .16 .52 .54 (.71) .24

.69 .01 .50 .14 .19 .41 .50 (.74)

Note. PVQ21 = Human Values Scale used in the European Social Survey (Schwartz, 2003, 2007); S5 = The Short Five personality inventory (Konstabel et al., 2012); EVI = The Estonian Value Inventory (Aavik & Allik, 2002). Upper triangle are self-ratings. Lower triangle are other-ratings (two informants, aggregated). Self-other agreement, disattenuated in brackets, is underlined in the diagonal. p < .01 marked bold; p < .05 marked italic. Sample 1: N = 101 for self-ratings and N = 96 for other-ratings. Sample 2: N = 97 for self-ratings and N = 97 for other-ratings.

Table 3 Self-friend agreement for higher-order values (PVQ21) and the Big Five personality domains (S5) in Sample 1. Self friend agreement PVQ21 Openness to change Conservation Self-enhancement Self-transcendence

.51 .44 .46 .36

S5 Neuroticism Extraversion Openness Agreeableness Conscientiousness

.50 .78 .46 .48 .43

Note. Friends N = 63. All correlations significant at p < .01 level.

4. Discussion The current study examined self-other agreement in personal values and compared it with self-other agreement in Big Five personality domains in the same sample. In the literature, one can find two opposing views: (1) values as too privately held (McAdams, 1995) and subjective (Hitlin & Piliavin, 2004) to be inferred correctly by others, versus, (2) values, as highly contextualized characteristic adaptations (McCrae & Costa, 1999), that are easier to assess by behavioural observation than personality traits. In Sample 1, we assessed four higher-order values with the PVQ21 (Schwartz, 2003, 2007) and the Big Five personality domains with the S5 (Konstabel et al., 2012). The observed self-other agreement was only minimally smaller in the higher-

order values than in the personality domains. For both values and personality domains, the level of agreement indicated substantial convergence. In Sample 2, we assessed self-other agreement in value factors with the indigenous EVI value instrument (Aavik & Allik, 2002). Self-other agreement was only slightly lower for these culture-specific value factors than for the higher-order values in Sample 1. The magnitude of the self-other correlations for ratings of both sets of personal values was similar to that typically found for Big Five personality traits (see Connolly et al., 2007). Furthermore, we found no significant differences between the inter-rater agreement in the PVQ higher-order values, the EVI values, and the S5 personality domains. This finding indicates some validity of other-reports of personal values. We also found a high (r > .70) level of raw profile similarity between the self- and other rated value and trait hierarchies of individuals. The distinctive profiles correlated at a reasonably high (r > .65) level for the PVQ21 higher-order values and the S5 personality domains, but were somewhat weaker (r = .49) for the EVI value factors. By removing the normativeness (i.e., the average profile) from the responses of the informants and targets, we controlled for the effects of socially desirable responding, at least partially. We interpret the results as indicating that the self-other agreement in value profiles (hierarchies) reflects accurate perception of individuals’ distinctive features and not merely shared response biases. The internal reliability of the scales was consistently lower for the values, which included fewer items, than for the personality domains. When we corrected for measurement error in the observed correlations between self- and other-ratings, self-other agreement was similar for the four Schwartz higher-order values and the Big Five personality domains. The Estonian value

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H. Dobewall et al. / Journal of Research in Personality 50 (2014) 1–10

factors also showed substantial self-other agreement when disattenuated.6 Finally, we found self-other agreement to be relatively low in the mean ratings given to all values. Nonetheless, the correlation for the mean rating of the higher order values was significant. Thus, people do have some sense of the tendency of their acquaintances to consider values more or less important. Our findings suggest that well-acquainted informants do not find it any more difficult to describe targets’ values accurately than their personality traits. Compared with traits, personal values are apparently neither too privately held (McAdams, 1995) nor too individually subjective (Hitlin & Piliavin, 2004) to be accurately judged by others. People are able to infer how important values are to close others from the cues they observe. Thus, our results provide evidence that other-ratings of personal values can be used to validate self-report value measures. Vazire (2010) suggested that others know some aspects of one’s personality better than people know themselves. If so, others can provide information about a person’s values not available from self-reports alone. Informant reports of personality traits (Vazire & Mehl, 2008; Wagerman & Funder, 2007) and of subjective well-being (Fogarty, Davies, MacCann, & Roberts, 2013) explained unique variance in objective criterion variables. For example, Wagerman and Funder (2007) found that other-rated conscientiousness predicted later academic achievement better than self-reported conscientiousness did in a sample of college students. Given a level of self-other agreement in values comparable to that in personality traits, it seems at least plausible that ratings of well-acquainted others can also be used in value research to complement existing self-report measures. No studies have tested this possibility yet.

4.1. Exemplary applications of other-report measures of values Sending value messages to others and inferring others’ values is a common activity not only in families (e.g., Murray et al., 2002) but in organizations (e.g., Graf, Van Quaquebeke, & Van Dick, 2011), among friends (e.g., Boer et al., 2011), and in many daily interactions. Transmission of values from one generation to another depends upon children’s perceptions of their parents’ values (Grusec & Goodnow, 1994; Knafo & Schwartz, 2003). Children’ must perceive their parents’ values accurately if they are to accept the values their parents want for them. Knafo and Schwartz (2001, 2003) found an average profile correlation of r = .48 between parents’ self-reported preferences among 11 values they wanted their children to have and children’s perceptions (i.e., other-reports) of these value preferences. Interest in assessing children’s values has risen during the last decade (Boehnke & Welzel, 2006; Bubeck & Bilsky, 2004; Döring, Blauensteiner, Aryus, Drögekamp, & Bilsky, 2010). But young children have limited vocabularies and reading ability and cope poorly with the demands for abstract thinking in most value assessment instruments (Döring et al., 2010). Other-reports of caretakers (parents, day-care personnel, teachers) have successfully assessed characteristics of children under seven years old in other fields (e.g., Sevón, Rönkä, & Hintikka, 2013). Our findings suggest that other-reports could also be used to study the values of younger children but this needs to be ascertained by further studies. Value stereotypes are another example of the application of other-ratings of values. Other-ratings of the typical member of a nation have been used in a number of studies (Dobewall & Strack, 2011; Eicher, Pratto, & Wilhelm, 2013; Lönnqvist, Yijälä, 6 Note that without correction, self- and other-ratings of values shared only 22– 25% of their variance, suggesting a more modest reading of the findings.

Jasinskaja-Lahti, & Verkasalo, 2012; Soutar, Grainger, & Hedges, 1999). These national character stereotypes are widely shared but often inaccurate. Peng, Nisbett, and Wong (1997) found that even cultural experts need more contextual information (i.e., a hypothetical social situation with various behavioural options) to attain consensual value ratings about a national prototype. Our results indicate that people have the potential to make accurate judgments of others’ values when they are well acquainted. It is not surprising that people do less well when judging the values of whole groups with which they have little familiarity and which are actually quite heterogeneous. 4.2. Limitations and future research Thus far, we have attributed self-other convergence in the rating of values to accurate information about the targets’ values and convergence in the rating of traits to accurate information about the targets’ personality traits. It is possible, however, that informants also infer a target’s values from their perceptions of the target’s personality traits and not only from knowledge of the target’s values. For instance, Dobewall and colleagues (2013) found that informants, when making judgments about someone’ happiness or life satisfaction, seem to rely on the personality traits of this person. Moreover, Daugherty, Kurtz, and Phebus (2009) showed that even implicitly held motives can be predicted by observer-ratings of personality traits. It is equally possible that informants infer a target’s personality from their perceptions of the target’s values and not only from knowledge of his or her traits. Lee and colleagues (2009), for example, found that people tend to assume they are similar to close others, especially in personality traits that are related to values. The strongest self-other correlations we observed were for extraversion (in Sample 1) and hedonism, including stimulation items (in Sample 2). These are precisely the personality trait and the values that correlated most highly with one another in previous research (e.g., Fischer & Boer, 2013; Olver & Mooradian, 2003; Roccas et al., 2002). This reinforces the possibility that informants partially base their personality ratings on the target’s values and vice versa. Teasing apart possible influences of perceived values on people’s inferences about others’ traits and perceived traits on inferences about others’ values is an interesting task for future research because both causal directions seem plausible (see Dobewall et al., 2013). Another question worth addressing is the extent to which, if at all, observed levels of self-other agreement are due to actual rather than assumed value similarity between informants and targets (i.e., between self-ratings of informants and of targets). Assumed similarity is the case if informants project their own characteristics on the target (Cronbach, 1955; Kenny & West, 2010). Recently, Paunonen and Hong (2013) pointed out that assumed similarity may increase or diminish self-other agreement or have no effect, depending on its interplay with actual similarity: (1) Accuracy increases if there is actual similarity (cf. Paunonen & Hong, 2013). (2) Accuracy diminishes if assumed similarity and actual similarity do not match (e.g., Beer & Watson, 2008; Watson et al., 2000). (3) There is no effect on accuracy if both actual similarity and assumed similarity are low. Our well-acquainted informants may have shared values with their targets (cf. Boer et al., 2011; Lee et al., 2009). Hence, projection of their own values by informants may have contributed to self-other agreement. We could not examine this possibility in the current study because we had no information about informants’ own values. Lee and colleagues (2009) did find evidence both for actual similarity on the major value dimensions in the Schwartz theory (r P .20) and for assumed similarity (r P .30) (see also Murray et al., 2002). It is likely that knowing that the targets they rated were actually similar to self, rather than merely

H. Dobewall et al. / Journal of Research in Personality 50 (2014) 1–10

assuming it, helped our well-acquainted informants to rate their targets accurately. Research on personality traits has revealed numerous moderators of the correlation between self- and other-ratings (e.g., Allik, Realo, Mõttus, Borkenau, et al., 2010; Allik, Realo, Mõttus, Esko, et al., 2010; Watson et al., 2000). To test for moderators of selfother agreement in values is a task for the future. For instance the level of closeness (the length of acquaintance) between self and informant is especially important for availability of information (Kenny & West, 2010). A test of the moderation effects of acquaintance was not significant here. However, this is inconclusive because the test lacked power due to the small size of our samples and the relatively high levels of acquaintance for most participants; whilst moderation effects are usually weak (see Chaplin, 1991). There is evidence that some traits can be perceived accurately at lower levels of acquaintance (Borkenau, Brecke, Möttig, & Paelecke, 2009; Carney, Colvin, & Hall, 2007). There is also evidence that it is easier to form first impressions of some values (namely, benevolence and universalism) than of others (Rentfrow & Gosling, 2006). Our findings, still, do not allow us to say how easy or difficult it would be for observers to judge the values of strangers. Future research is needed to assess the effects of acquaintance on accurate perception of traits versus values. Most participants in the current studies were well-acquainted, so we doubt that differences in acquaintance had much effect on levels of self-other agreement. 4.3. Conclusion We conclude that other-ratings of personal values yield useful and meaningful information. Well-acquainted informants judge targets’ values at levels of accuracy similar to their accuracy as judges of targets’ well-being, personality traits, emotions, and other individual attributes. We therefore recommend that researchers draw more often on other-report measures of values to complement self-report measures. However, research on other-reports of values is still at an early stage and there remain many open questions, especially under low acquaintance conditions. Conflict of interest No conflict of interest is declared. Acknowledgments This research was supported by grants from the Estonian Ministry of Science and Education (IUT2-13) and the Estonian Research Council (PUT78). The work of the fourth author was partially supported by the Higher School of Economics, Moscow, Basic Research Program (International Laboratory of Socio-Cultural Research). We thank Diana Boer, Jan-Erik Lönnqvist, and Delaney Michael Skerrett for their helpful comments on earlier drafts of this article. References Aavik, T., & Allik, J. (2002). The structure of Estonian personal values: A lexical approach. European Journal of Personality, 16, 221–235. Allik, J., & McCrae, R. R. (2002). A Five-Factor Theory perspective. In R. R. McCrae & J. Allik (Eds.), The Five-Factor Model of personality across cultures (pp. 303–321). New York: Kluwer Academic/Plenum Publishers. Allik, J., Realo, A., Mõttus, R., Borkenau, P., Kuppens, P., & Hrˇebícˇková, M. (2010). How people see others is different from how people see themselves: A replicable pattern across cultures. Journal of Personality and Social Psychology, 99, 870–882.

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