Predicting Self-Confident Behaviour with Implicit and Explicit Self-Esteem Measures

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1 European Journal of Personality, Eur. J. Pers. 30: (2016) Published online 5 October 2016 in Wiley Online Library (wileyonlinelibrary.com).2076 Predicting Self-Confident Behaviour with Implicit and Explicit Self-Esteem Measures SASCHA KRAUSE 1 *, MITJA D. BACK 2, BORIS EGLOFF 3 and STEFAN C. SCHMUKLE 1 1 University of Leipzig, Germany 2 University of Münster, Germany 3 Johannes Gutenberg-University Mainz, Germany Abstract: The present research compared the validity of popular direct and indirect measures of self-esteem in predicting self-confident behaviour in different social situations. In line with behavioural dual-process models, both implicit and explicit self-esteem were hypothesized to be related to appearing self-confident to unacquainted others. A total of 127 participants responded to the Rosenberg Self-Esteem Scale, the Multidimensional Self-Esteem Scale, and an adjective scale for measuring explicit self-esteem (ESE). Participants implicit self-esteem (ISE) was assessed with four indirect measures: the Implicit Association Test (IAT), the name-letter task (NLT), and two variants of an affective priming task, the reaction-time affective priming task (RT-APT) and the error-based affective priming task (EB-APT). Self-confident behaviour was observed in four different social situations: (i) self-introduction to a group; (ii) an ostracism experience; (iii) an interview about the ostracism experience; and (iv) an interview about one s personal life. In general, appearing self-confident to unknown others was independently predicted by ESE and ISE. The indirect measures of self-esteem were, as expected, not correlated, and only the self-esteem APTs but not the self-esteem IAT or the NLT predicted self-confident behaviours. It is important to note that in particular the predictive power of the self-esteem EB-APT pertained to all four criteria and was incremental to the ESE measures. Copyright 2016 European Association of Personality Psychology Key words: implicit self-esteem; actual behaviour; predictive validity; Implicit Association Test; name-letter task; affective priming task The idea that automatically activated self-evaluations (i.e. implicit self-esteem, ISE) can have self-relevant behavioural consequences is popular in personality psychology. However, recent research has critically questioned the existence and the relevance of the ISE construct mainly because of low and inconsistent predictive validities across studies and ISE measures (Buhrmester, Blanton, & Swann, 2011; Falk, Heine, Takemura, Zhang, & Hsu, 2015). A conclusive evaluation of the predictive validity of ISE is complicated by the facts that (i) only a few studies have indeed analysed actual behaviours as criterion measures, and (ii) with regard to behavioural prediction, ISE measures have typically been investigated in isolation from each other. In the present study, we aimed to compare the predictive power of the three most prominent classes of ISE measures the Implicit Association Test (IAT; Greenwald & Farnham, 2000), the name-letter task (NLT; Kitayama & Karasawa, 1997), and the affective priming task (APT; Krause, Back, Egloff, & Schmukle, 2011; Spalding & Hardin, 1999) for an outcome that is (i) theoretically associated with self-esteem; (ii) derived from the assumption that ISE measures should mainly predict actual behaviours; (iii) assessed in different situations; and (iv) of high importance in social life: self-confident behaviour in the presence of *Correspondence to: Sascha Krause, Department of Psychology, University of Leipzig, Neumarkt 9-19, Leipzig, Germany. sascha. krause@uni-leipzig.de Copyright 2016 European Association of Personality Psychology unacquainted others. Furthermore, by employing established self-reports of self-esteem (i.e. explicit self-esteem, ESE), we were additionally able to examine the incremental validity of the ISE measures above and beyond the ESE measures. SELF-CONFIDENT BEHAVIOUR AND SELF-ESTEEM Behaving in a self-confident manner in the presence of unacquainted others has many positive consequences for a person s social life. In zero-acquaintance situations, people who exhibit self-confidence receive more positive evaluations from others and are thus more popular (Back, Schmukle, & Egloff, 2011). Moreover, speed-dating studies suggest that the self-confident behaviour of flirting with strangers is particularly advantageous for mate selection: People who flirt more with speed-dating partners are chosen more often as potential partners (Back, Penke et al., 2011). Appearing self-confident to unacquainted others is also an important predictor of job success: Sales performance, for example, is associated with self-confidence (Miner, 1962). Furthermore, in employment interviews, a confident and powerful communication style is an advantage when applying for a job (Imada & Hakel, 1977; Lammers, Dubois, Rucker, & Galinski, 2013; Young & Beier, 1977). A lack of self-confident behaviour (i.e. appearing insecure or shy Received 12 April 2016 Revised 31 August 2016, Accepted 6 September 2016

2 Predicting self-confident behaviour with self-esteem 649 to unacquainted others) can have negative consequences for a person s social life. Insecure or shy people are initially judged as less intelligent (Paulhus & Morgan, 1997). Moreover, shyness is inversely related to positive outcomes such as dating frequency and satisfaction, number of friends, and level of self-disclosure to friends (Jones & Briggs, 1984). Intuitively, in new and unpredictable social situations, appearing self-confident to others should be closely related to self-esteem. Support for this assertion is provided by two complementary perspectives on the dynamics of self-esteem: First, the self-broadcasting perspective implies that an individual acts out his or her self-evaluations in observable social behaviour (Srivastava & Beer, 2005). Thus, when encountering strangers, people high in self-esteem behave confidently, whereas people low in self-esteem behave in an insecure way. Second, the sociometer theory of selfesteem (Leary, Tambor, Terdal, & Downs, 1995) which assumes that self-esteem is developed by social feedback processes comes to the same conclusion: Self-confident behaviour contributes to the experience of more positive evaluations by other people, and this fosters the development of higher self-esteem (e.g. Denissen, Penke, Schmitt, & Van Aken, 2008; Hutteman, Nestler, Wagner, Egloff, & Back, 2015). Both the self-broadcasting and the sociometer perspectives are supported by findings that have shown that people with high self-esteem describe themselves as more sociable, outgoing, and assertive, as well as less shy than people with low self-esteem (MacDonald & Leary, 2012). A DUAL-PROCESS APPROACH TO THE RELATION BETWEEN SELF-ESTEEM AND SELF-CONFIDENT BEHAVIOUR Traditionally, self-esteem researchers have used ESE measures (i.e. by asking participants to self-report how they evaluate themselves) to examine the effects of self-esteem on actual self-confident behaviour in the presence of unacquainted others. Although these deliberate evaluations of the self certainly capture important aspects of self-esteem, they are also subject to the well-known limitations of selfreports, including impression management tendencies (Paulhus, 1984) and the limits of self-awareness (Greenwald & Banaji, 1995). Moreover, self-reports of self-esteem are not able to capture automatic self-evaluations (i.e. ISE) that are spontaneously activated in response to self-esteemrelevant stimuli. The distinction between different representations of the self (i.e. ISE and ESE) is in accordance with dual-process models of personality and information processing (e.g. Back & Nestler, in press; Fazio, 1990; Gawronski & Bodenhausen, 2006; Greenwald et al., 2002; Strack & Deutsch, 2004; Wilson, Lindsey, & Schooler, 2000). The distinction between implicit and explicit modes of information processing is important not only for evaluations but also for human behaviour. According to behavioural dual-process models (Back, Schmukle, & Egloff, 2009; Fazio & Olson, 2003; Strack & Deutsch, 2004), people s selfconfident behaviour in social situations is determined by both automatic (i.e. spontaneous) processes that should be triggered by ISE and controlled (i.e. reflective) processes that should be activated by ESE. Accordingly, observations of actual self-confident behaviour in the presence of unacquainted others should be predicted by both ISE and ESE measures. CANDIDATE MEASURES There are a large number of measures that are used to capture self-esteem. Whereas the selection of reliable ESE measures is manifold, there are currently only three prominent domains of ISE measures that have demonstrated both reliability and validity: IATs, NLTs, and variants of the APT. Single studies on each one of the three classes of ISE measures have provided support for their predictive and incremental validities, however, mostly for self-report outcomes (for an overview, see Buhrmester et al., 2011). The self-esteem IAT has been reported to be positively correlated with selfreported criteria such as subjective well-being (Walker & Schimmack, 2008), depression (Haeffel et al., 2007), neuroticism (Robinson & Meier, 2005), the perception of being valued (Back, Krause et al., 2009), performance perceptions, and expectations after failure (Greenwald & Farnham, 2000). The NLT has shown significant correlations with various self-report criteria, including psychological well-being (Kernis, Lakey, & Heppner, 2008), life satisfaction (Kernis et al., 2008), depression (Franck, De Raedt, & De Houwer, 2007), self-concept clarity (DeHart, Pelham, & Tennen, 2006), relationship satisfaction (LeBel & Campbell, 2009), and Internet addiction (Stieger & Burger, 2010). Finally, two variants of self-esteem APTs either based on reaction times or are based on errors made under time pressure have been reported to be significantly associated with self-report outcomes. Whereas the reaction-time APT (RT-APT) predicted differences in the self-evaluations of people with different cultural backgrounds (Hetts, Sakuma, & Pelham, 1999) and the perception of being valued (Back, Krause et al., 2009), the error-based APT (EB-APT) was significantly correlated with self-reported self-esteem (Wentura, Kulfanek, & Greve, 2005) and performance perceptions and expectations before and after failure (Krause, Back, Egloff, & Schmukle, 2012). Although the EB-APT was shown to be more reliable than the RT-APT (Krause et al., 2011), we used both the RT-APT and the EB-APT in the present study, as previous research has suggested that both variants of APTs are able to validly assess ISE. Much less is known about how actual behaviour corresponds with these ISE measures. Table 1 provides an overview of studies that investigated relations between actual behaviours and self-esteem. As can be seen, variants of self-esteem IATs have been shown to correlate with an experimenter rating of self-esteem (Bluemke & Friese, 2012), an interviewer rating of negative affect during a mental health interview (Robinson & Meier, 2005), an observer rating of facial and body adaptors during a public speaking task (Rudolph, Schröder-Abé, Riketta, & Schütz, 2010), and persistence and performance on scrambled letter tasks (Holland, Wennekers, Bijlstra, Jongenelen, & van Knippenberg, 2009). The NLT was significantly associated with defensive verbal

3 650 S. Krause et al. Table 1. Relations between actual behaviours and self-esteem measures Reference Actual behaviours N N observer IAT NLT APT ESE Bluemke and Friese (2012) Experimenter rating of self-esteem **.20* Robinson and Meier (2005) Interviewer rating of negative affect *.23 Rudolph et al. (2010) Facial and body adaptors *.08 Rudolph et al. (2010) Illustrators, control of posture and speech * Holland et al. (2009) Persistence in scrambled letter tasks 42.54* Holland et al. (2009) Performance in scrambled letter tasks 32.80** Kernis et al. (2008) Defensive verbal behaviour **.26** Spalding and Hardin (1999) Interviewer rating of nonverbal anxiety **.14 Vandromme et al. (2011) Gaze avoidance 24.55**.30 Vandromme et al. (2011) Gaze duration 23.42*.01 Note: N = number of participants in the study. N observer = number of observers of behaviour. IAT = Implicit Association Test; NLT = name-letter task; APT = affective priming task; ESE = explicit self-esteem measures. *p < 05. **p <.01. behaviour during an interview (Kernis et al., 2008). Reaction-time based variants of self-esteem APTs have also been shown to correlate with actual behaviours, specifically with an interviewer rating of nonverbal anxiety during an emotional health interview (Spalding & Hardin, 1999), gaze avoidance, and the time spent looking at the experimenter during instructions (Vandromme, Hermans, & Spruyt, 2011). Undoubtedly, the most widely used measure of ESE is the Rosenberg Self-esteem Scale (RSES; Rosenberg, 1965). The RSES assesses global self-esteem by asking participants to respond to five positive and five negative statements about the self. Other ESE measures include, for example, the Self- Rating Scale (Fleming & Courtney, 1984) or adjective scales (e.g. Brown & Kobayashi, 2002). Previous studies have repeatedly confirmed the predictive validity of ESE measures (particularly the RSES) for several consequential outcome variables including subjective well-being (e.g. Schimmack & Diener, 2003), depression (e.g. Murrell, Meeks, & Walker, 1991), physical health (e.g. DeLongis, Folkman, & Lazarus, 1988), and relationship satisfaction (Erol & Orth, 2013). As is common in personality and social psychology, research with ESE measures is mainly focused on self-report outcomes (for criticisms of this practice, see, e.g. Baumeister, Vohs, & Funder, 2007; Furr, 2009). Therefore, actual behavioural studies are rare. In the last column of Table 1, we added the predictive validities of various ESE measures that were used in the above-mentioned ISE research. As can be seen, self-reports of self-esteem have been reported to be significantly associated with an experimenter rating of selfesteem (row 2; Bluemke & Friese, 2012); observer ratings of illustrators, the ability to control posture, and the ability to control speech during a public speaking task (row 5; Rudolph et al., 2010); and defensive verbal behaviour during an interview (row 8; Kernis et al., 2008). Notably, the effect sizes for the interviewer rating of negative affect during a mental health interview (row 3; Robinson & Meier, 2005) and avoiding the gaze of the experimenter during instructions (row 10; Vandromme et al., 2011) were at least as high as those reported above but not significant (probably because of small sample sizes). Altogether, previous research that employed ESE measures has provided evidence that selfreports of self-esteem are as ISE measures are as well able to predict actual behaviours in different social contexts. Taken together, there is little research on the prediction of actual self-esteem-related behaviour with ISE and ESE measures. Moreover, as can be seen in Table 1, there is a lack of knowledge about how different measures of ISE and ESE simultaneously predict identical actual behaviours. In all identified studies, only one measure of ISE and one measure of ESE were applied. Whereas this poses no problem for ESE measures, as they are highly correlated with each other (e.g. Zeigler-Hill, 2010), for ISE measures, researchers have yet to determine the extent to which the different but uncorrelated assessment procedures (see, e.g. Bosson, Swann, & Pennebaker, 2000; Krause et al., 2011; Rudolph, Schröder-Abé, Schütz, Gregg, & Sedikides, 2008) are able to predict the same behavioural outcomes. Previous studies that have applied more than one ISE measure to compare their ability to predict the same criteria have used self-report-based variables as outcomes (e.g. Back, Krause et al., 2009; Bosson et al., 2000; Falk et al., 2015; Verplanken, Friborg, Wang, Trafimow, & Woolf, 2007). Furthermore, Table 1 shows that previous research on ISE and its relation to actual behaviour is further limited by small sample sizes or small numbers of behavioural observers. Specifically, only two studies had more than 100 participants (Bluemke & Friese, 2012; Kernis et al., 2008), and no study had more than one observer who had rated the behaviour of all participants (see the fourth column of Table 1). Notably, the question of incremental validity (i.e. whether ISE measures predict behavioural outcomes above and beyond ESE measures) needs to be addressed because future self-esteem research will benefit only from ISE measures that are able to explain substantial amounts of variance in behavioural outcomes above and beyond standard self-esteem self-reports. Please note that the two previous studies that found both significant ESE and significant ISE correlations with the same behavioural outcomes (see Table 1, Bluemke & Friese, 2012; Kernis et al., 2008) did not explicitly address the question of incremental validity. Last but not least, the question of whether both kinds of self-esteem predict actual behaviours consistently across

4 Predicting self-confident behaviour with self-esteem 651 different social contexts is still unresolved. As can be seen in Table 1, previous research that predicted behaviour with ISE measures focused on only one social situation. Because we aimed to investigate the robustness of ISE-to-behaviour effects, not only did we include multiple measures of ISE, but we also created different social situations in which actual behaviour was obtained. As an outcome measure, we used a criterion that is theoretically associated with self-esteem: self-confident behaviour in the presence of unacquainted others. THE PRESENT RESEARCH For the present study, we designed a real-life context involving first-time meetings; that is, group members did not know each other before the study. To examine whether ISE and ESE would affect self-confident behaviour in different authentic social situations, we designed four realistic contexts: Participants were first asked to introduce themselves to a group of strangers. Second, in order to explore participants levels of self-confidence when experiencing social exclusion by other group members, participants played the ostracism game Cyberball (Williams, Cheung, & Choi, 2000). Third, participants were individually interviewed about their ostracism experiences by an unacquainted experimenter. Fourth, participants had to speak with the interviewer about positive and negative aspects of their personal lives (cf. Spalding & Hardin, 1999). For each of the four different outcomes, we obtained trained observer ratings of actual behaviour, thus allowing us to investigate the degree to which participants behaved self-confidently in the eyes of uninvolved others. Dual-process models of social information processing represent social behaviour as not driven by purely automatic or purely controlled processes but rather as the result of both kinds of processes (cf. Back et al., 2009; Fazio & Olson, 2003; Strack & Deutsch, 2004). On the basis of such models, we expected that observer ratings of self-confident behaviour in the presence of unacquainted others would be affected by both the ISE and ESE of targets. Thus, both types of selfesteem were expected to demonstrate predictive validity for the four different outcomes (see Table 1 for similar results involving other self-esteem-related behaviours). Moreover, because ISE and ESE measures capture different aspects of self-esteem (e.g. Back, Krause et al., 2009; Bosson et al., 2000; Greenwald & Farnham, 2000; Spalding & Hardin, 1999), using both types of measures together was expected to improve the prediction of self-confident behaviour (i.e. incremental validity of ISE above and beyond ESE). METHOD In this section, we provide an overview of the procedures and measures that are relevant to the main aim of the study (i.e. predicting self-confident behaviour with ISE and ESE measures). The supplementary online materials (SOM) provide a complete account of all variables that were assessed in the study, including a more detailed description of the procedure and additional measures. Moreover, the data and analysis scripts of our study can be downloaded from Participants One hundred thirty-one unacquainted 1 students from different fields of study participated in exchange for research participation credit or monetary compensation (20 ). The first group of four participants served as a training group to (i) test the study procedure; (ii) acquaint the experimenter with the study procedure; (iii) obtain video examples of self-confident behaviours for the observer trainings; and (iv) optimize the study procedure after interviewing the four training group members about their experiences in the study. The data from this training group were excluded from the analyses. The average age of the remaining 127 participants (70 women) was 24.1 years (SD = 3.4). Participants belonged to 32 groups, each consisting of four members. 2 Procedure Before group sessions, participants completed three online measures of ESE in a fixed order. After filling out the wellestablished RSES, participants responded to the German version of Fleming and Courtney s (1984) Self-Rating Scale (Multidimensional Self-Esteem Scale; MSES; Schütz & Sellin, 2006) and an adjective scale (AS) containing the target words used in the ISE measures. In addition to these self-report measures, participants had to fill out several other online questionnaires (for more information on these questionnaires, see the SOM). After arriving at the laboratory, participants were photographed in a standardized position with a neutral facial expression to create face photos for relevant tasks. Next, participants were asked to stand in front of the group and briefly introduce themselves. Afterwards, participants were seated in separate cubicles to complete four ISE measures in a fixed order (i.e. the IAT, two APTs (i.e. the RT-APT and the EB-APT), and the NLT, respectively) on a personal computer. Attribute or target adjectives for the different reaction-based ISE measures were selected according to their valences from German norm tables (Hager & Hasselhorn, 1994). All ISE measures were administered on personal computers using Inquisit software (2006). Instead of a standard computer keyboard, participants used external response pads to complete the reaction-time-based ISE measures. This technical detail was applied to reduce error variance in the recorded latencies because key presses on a standard computer keyboard are buffered in the keyboard hardware before they are transmitted to the computer (Voss, Leonhart, & Stahl, 2007). 1 After completing the ISE measures, each participant had to indicate how well she/he was acquainted with each group member before the study (6- point Likert scale; 1 = not a bit, 6=very well; M = 1.05; SD = 0.22). 2 Please note that in one session, an experimenter had to replace a missing participant. Excluding this session s three participants did not change the pattern of results.

5 652 S. Krause et al. Next, participants were separately escorted to individual rooms. Here, participants first played the ostracism game Cyberball (Williams et al., 2000) on a personal computer. Thereafter, the experimenter entered the room and interviewed each participant about the ostracism experience. Then, participants were asked to tell the interviewer about positive and negative aspects of their personality. Finally, participants were debriefed, thanked, and given course credit. To examine whether ISE and ESE would affect selfconfident behaviour, we employed four different realistic social contexts: (i) self-introduction to a group; (ii) the ostracism experience; (iii) the interview about the ostracism experience; and (iv) the interview about participants personal lives. Implicit self-esteem (ISE) measures Implicit association test (IAT) The self-esteem IAT is a computerized categorization task that measures automatic associations of self-relevant and non-self-relevant words by presenting pleasant and unpleasant words. Five self-related stimuli (I, me, my, own, self) and other-related stimuli (other, their, those, you, your) were presented, as well as five attribute stimuli representing positive (beautiful, cheerful, honest, liked, sincere) and negative (arrogant, cowardly, mean, ugly, vicious) categories. The underlying assumption of the IAT is that if two category concepts are highly associated (e.g. self-concept and positivity in the case of a person with high self-esteem), the sorting task will be easier (i.e. faster) when the two associated category concepts share the same response key (i.e. self-positive vs. other-negative) than when they share different response keys (i.e. self-negative vs. other-positive). The IAT procedure followed the five-block structure described by Nosek, Greenwald, and Banaji (2005). In the fourth block, participants had to perform twice as many single-categorization trials (40) as in the first two practice blocks to reduce undesirable order effects from the combined judgement blocks (Nosek et al., 2005). The critical Blocks 3 and 5 consisted of 80 trials each. Stimulus presentation alternated between the target and the attribute dimensions. The critical block order was held constant (i.e. the Self + Pleasant block was followed by the Self + Unpleasant block) to minimize the effect of procedural variations on the measurement of individual differences in self-esteem. The self-esteem IAT scores were computed with an improved scoring algorithm (D 1 measure) described by Greenwald, Nosek, and Banaji (2003). Name-letter task (NLT) The NLT is based on the well-documented finding that people prefer the letters of their own names, especially their initials, over the remaining letters of the alphabet (Nuttin, 1985, 1987). Participants evaluated how much they liked each letter of the alphabet on response scales ranging from 1(I dislike this letter very much) to7(i like this letter very much). To capture reliable name-letter effects, participants had to rate the likeability of each letter twice (duplicate administration; Rudolph et al., 2008; Stieger, Voracek, & Formann, 2012). The likeability ratings of a participant s first initial served as a measure of ISE because a recent meta-analysis found that individuals ratings of their first initial were more closely related to personal self-esteem than individuals ratings of their last initial (Stieger et al., 2012). The first initial preference score was computed by applying the ipsatized double-correction algorithm (Baccus, Baldwin, & Packer, 2004), which is recommended for both theoretical and empirical reasons (LeBel & Gawronski, 2009). Separately for the first and second name-letter rating rounds, the average of a participant s ratings of all non-initial letters was subtracted from the participant s rating of his or her first initial. Next, normative letter baselines which were computed by averaging the ipsatized letter ratings for individuals whose first initial did not include the letter were subtracted from this difference. The mean of the first and second rounds of the first initial preference score served as a measure of ISE. Error based affective priming task (EB-APT) The self-esteem EB-APT is a computerized categorization task that quantifies the degree to which exposure to selfrelated versus other-related primes facilitates the subsequent categorization of words with unambiguous valences into a positive and negative category, respectively. Because they experience positive affect following self-related stimuli, people with high self-esteem are thought to be faster (or show more correct reactions) when a positive stimulus is preceded by a self-related prime and slower (or show more false reactions) when a negative stimulus is preceded by a selfrelated prime, compared with people with low self-esteem. Building on research showing that using pictures of faces as primes in an APT provides a reliable and valid measure of ISE (e.g. Krause et al., 2011, 2012), pictures of participants faces ( pixels) were presented as self-related primes. Pictures of the faces of unacquainted persons served as other-related primes. During the task, participants were asked to identify unambiguously valenced target adjectives as pleasant (beautiful, cheerful, honest, liked, sincere) or unpleasant (arrogant, cowardly, mean, ugly, vicious) as quickly and accurately as possible. On the basis of evidence that the analysis of errors instead of reaction times substantially improves the reliability and validity of self-esteem APT effects (Krause et al., 2011, 2012; Wentura et al., 2005), we used the responsedeadline technique (Degner, Wentura, Gniewosz, & Noack, 2007) to obtain a sufficient number of errors in the priming task. Each judgement trial began with the presentation of a prime, which remained on the screen for 67 ms and was immediately replaced by a blank screen for 33 ms. Then the target word was presented for a maximum of 550 ms. If the participant did not respond within this time span, the target word was replaced by a red exclamation mark. The length of the response deadline was automatically adjusted according to the participant s average accuracy and speed in the preceding critical block (cf. Degner, 2009; Draine & Greenwald, 1998).

6 Predicting self-confident behaviour with self-esteem 653 An initial practice block was followed by five critical blocks of 60 trials each (each target word was paired once with the self-related and once with an other-related prime). Critical trials were presented in a fixed order to optimize the reliability of individual differences (Banse, 2001). Selfesteem priming scores were calculated by excluding the trials in which the response was given after the deadline (Degner et al., 2007). For each participant, a positivity index for the self-related prime was calculated by subtracting the average error rate for pleasant targets from the average error rate for unpleasant targets that followed the same prime. Likewise, a positivity index for other-related primes was computed to control for a preference for positive versus negative target adjectives in the analysis. To yield a single ISE priming effect, the positivity index for the self-related prime was subtracted from the positivity index for other-related primes (cf. Degner et al., 2007). Because of technical problems, one participant did not complete the self-esteem EB-APT (the Inquisit programme crashed at the end of the fourth critical block). This subject s data were discarded. Reaction time affective priming task (RT-APT) Before completing the EB-APT, participants were administered a standard reaction-time-based priming task (RT-APT) as an additional ISE measure. The RT-APT procedure was identical to the above-mentioned EB-APT, but no response-deadline technique was used (for a detailed description of the reaction time priming measure, see Krause et al., 2011). Thus, after the target word was presented, participants reaction times to the unambiguously valenced adjectives were measured and analysed. The examination of self-esteem RT-APT effects followed the improved scoring algorithm presented in Krause et al. (2011); that is, reaction times were trimmed and error penalties were given. After completing the RT-APT, participants had a 5-min break before they started with the above-described EB-APT. Explicit self-esteem (ESE) measures Rosenberg self-esteem scale (RSES) Participants responded to the German adaptation (von Collani & Herzberg, 2003) of the RSES. The RSES was employed as a direct measure of people s conscious feelings of global self-worth. The RSES score was obtained by averaging the 10 RSES items, each measured on a 4-point Likert scale ranging from 1 (strongly disagree) to 4 (strongly agree). Multidimensional self-esteem scale (MSES) After responding to the RSES, participants filled out the MSES. The MSES (Schütz & Sellin, 2006) a German-specific adaption (i.e. not a one-to-one translation) of Fleming and Courtney s (1984) original Self-Rating Scale was applied as an additional direct measure of people s conscious feelings about their self-esteem. The total score was obtained from 32 items, each measured on a 7-point Likert scale ranging from 1 (never) to 7(always). Adjective scale (AS) Next, participants rated the 10 attribute or target adjectives from the IAT and the APT on a scale ranging from 1 (not at all) to 6(very much). The instructions read: Indicate the extent to which the following adjectives apply to you. The AS score was computed as the mean rating for the five adjectives describing the positive pole and the five reverse-scored adjectives describing the negative pole. Social situations Self-introduction Participants were asked to stand in front of the group and briefly introduce themselves by providing information about their first name, age, place of origin, field of study, semester, interests, and leisure-time activities. Ostracism game For each participant, a natural experience of being excluded from a social group was created by using the ball-tossing game Cyberball (Williams et al., 2000). During the game, participants were led to believe that they were playing an interactive ball-tossing game with the other group members, but in fact, the other players were simulated by the computer. Before the game began, participants were explicitly asked to visualize the game situation, themselves, and the other players to make the passing behaviour more realistic. Throughout the game, each participant saw his or her face in the middle of the bottom field on the screen; the other three players faces were depicted in the middle left, middle top, and middle right fields on the screen. When the animated ball was tossed to the participant, she or he had to click on one of the other three pictures to pass the ball to the selected group member. The game was programmed such that each participant experienced the same degree of ostracism. In order to make the ostracism appear natural, we created a successive (rather than abrupt) shift from social inclusion to social exclusion: During the first 16 throws, participants received one fourth of the passes (perfect social inclusion). Over the next 24 throws, participants received one eighth of the passes; that is, each participant was allowed only three throws, whereas each confederate made seven throws (first level of social exclusion). Over the next 33 throws, participants received one eleventh of the passes; that is, each participant was given only three throws, whereas each confederate made 10 throws (second level of social exclusion). During the last 32 throws, participants were never given the ball again by the other group members (perfect social exclusion). To check whether or not participants had experienced social exclusion during the game, we measured participants mood before and after the game with five questions that asked participants to indicate how they felt at that moment (Williams et al., 2000). The anchors for the five items, ranging from 1 (negative mood) to 6 (positive mood), were accepted rejected, bad good, happy sad, tense relaxed, and pleased enraged (α before =.77; α after =.88). Participants actual behaviour during the game was recorded by a web cam that was fixed above the screen.

7 654 S. Krause et al. Ostracism interview After the Cyberball game ended, the experimenter entered the room and interviewed the participant about the ostracism experience. The interview contained six questions (e.g. Do you think you were ostracized? ) and was standardized; that is, each interviewer had to ask the questions in the specified order (the complete list of questions is included in the Appendix of the SOM). Personal interview After the participant had answered the last question from the ostracism interview, the experimenter changed the focus of the conversation toward positive and negative aspects of the participant s personal life ( Now that we have talked about your ostracism experience, I want to ask you about personal aspects of your life ). This part of the interview was comprised of eight questions (e.g. If you look back on your life, do successes or failures predominate? ) that had to be asked in a specified order. At the end of the conversation, the experimenter confronted participants with five self-threatening situations. Participants were asked to imagine the situation and then indicate how they would cope with it (the complete list of questions is included in the Appendix of the SOM). Ratings of self-confident behaviours In each of the four social situations, participants behaviour was recorded by a video camera that was positioned in front of them. After the end of the study, independent groups of three observers evaluated the degree to which each participant appeared to be self-confident in each situation. In contrast to previous research in which behaviour was predicted with ISE (see Table 1), we aimed to reduce observer bias in the self-confidence ratings by using more than one observer for each situation. Moreover, to avoid dependency in the observer ratings, we aimed to recruit different observers for each social outcome. 3 An observer rating of self-confident behaviour was made on a 6-point Likert scale ranging from 1 (not at all)to6(very much). In order to ensure that the observers had a common understanding of what is meant by self-confident behaviour, each rating sheet contained written definitions of behavioural anchors of self-confident versus insecure behaviour. The following anchors were used: insecure appearance versus self-confident appearance, insecure/low voice versus clear/strong voice, excitement versus calmness, tense posture versus straight posture. Although an observer was asked to consider the behavioural anchors for a rating, she or he was explicitly instructed to make a global judgement on the basis of her or his holistic impression of how self-confidently a person acted (for a similar approach, see Spalding & Hardin, 1999). 3 In sum, 10 psychology students (seven women) participated in the study as observers of self-confident behaviors. Eight of these students rated one situation, and two of these students rated two situations. Accordingly, each of the four situations was evaluated by a different team of observers. We used this molar-level behavioural approach rather than observing microlevel behaviours (e.g. smiling, gesturing, eyebrow flashes, etc.) because macrolevel behavioural measures are better suited to capture the psychological meaning behind specific acts (Sherman, Nave, & Funder, 2009). A smile, for example, can be caused by different motives (e.g. amusement, sarcasm, irritation), and thus, observers are only able to judge whether a smile is an indicator of self-confident behaviour when they include the context of the specific act. Furthermore, some people with high self-confidence might smile when meeting strangers, whereas others may speak with a loud voice. Thus, a self-confident behaviour cannot be reduced to specific microlevel behaviours. Accordingly, microlevel behaviours show less cross-situational consistency than molar-level behaviours (Funder & Colvin, 1991). To ensure that the behavioural assessments of participants self-confidence were reliable and valid, each observer had previously completed an observer training along with the other two observers in the specific rating group. As mentioned previously in the Participants section, the first four study participants served as a training group that provided video examples for this observer training. At the beginning of the training, each of the three observers in a rating group independently evaluated the self-confidence of one traininggroup participant. Thereafter, the three group members discussed their individual ratings (i.e. each of them explained her/his observer rating). After exchanging their ideas, the three observers collectively evaluated (i.e. by discussing their thoughts) the self-confident behaviours of two additional training-group participants. The aim of this procedure was to ensure that the observers would arrive at similar evaluation criteria. Finally, each observer independently evaluated the self-confidence of the last training-group participant. The observer training was successful because group members reported no disagreements in their evaluations of this last participant. After the end of the training session, each observer was given a rating sheet on which all of the participants were presented in different random orders. Essentially, the observers were asked to independently rate each participant s behaviour on the extent to which it showed self-confidence. After finishing the behavioural assessments, the ratings of the three observers in a group were averaged into a self-confident behaviour score for each individual participant in each of the four social situations. Power analysis Two analyses were computed to determine the statistical power of our analyses. According to a meta-analysis of the results of Table 1, the ISE measures predicted actual behaviours with an average effect size of r =.42. With an alpha level of.05 and a sample size of 127, the power to detect this effect with a two-sided significance test was.999. A comprehensive meta-analysis of the predictive validity of the IAT found an average criterion correlation of.274 (Greenwald, Poehlman, Uhlmann, & Banaji, 2009). Similarly, in a comprehensive meta-analysis, Cameron, Brown-Iannuzzi, and Payne (2012) found that priming tasks showed an average

8 Predicting self-confident behaviour with self-esteem 655 correlation with behavioural measures of.28. Under the assumption that the ISE measures in our study would be correlated with the behavioural outcomes with an effect size of r =.28, the power to detect this effect was.90 in our study. RESULTS Descriptive statistics Self-esteem measures The descriptive statistics and intercorrelations for the selfesteem measures can be found in Table 2. As can be seen in column 4, all seven self-esteem measures exhibited a statistically significant positivity bias. People s general tendency to have a positive self-view (Bosson et al., 2000) was thus reflected by each self-esteem measure. With the exception of the RT-APT, the reliabilities of the self-esteem measures were higher than.70 and thus satisfactory. This is particularly remarkable for the NLT and the EB-APT because, with the exception of the IAT, implicit measures tend to be chronically unreliable (e.g. Bosson et al., 2000; LeBel & Paunonen, 2011). As expected, all three ESE measures were significantly correlated (mean r =.60). The different types of ISE measures (i.e. IAT, NLT, APT), by contrast, were not significantly correlated (mean r =.08) and thus demonstrated their independence from each other a typical finding in ISE research (e.g. Bosson et al., 2000; Krause et al., 2011; Rudolph et al., 2008). The average r of.12 between the direct and indirect self-esteem measures replicated the finding that the two kinds of measures do not share a substantial amount of variance (for meta-analyses on the APT, IAT, and NLT, see Cameron et al., 2012; Greenwald et al., 2009; Krizan & Suls, 2008). However, regarding the convergence between ISE and ESE measures, a closer look on the intercorrelations reveals that the self-esteem EB-APT was significantly correlated with two of three ESE measures (r RSES =.24, p <.01; r MSES =.30, p <.01). Given the fact that ISE and ESE measures usually do not significantly correlate at all, this finding provides first evidence for the ability of the EB-APT to validly assess self-esteem. Criterion measures The results of the Cyberball game suggest that, on average, participants experienced social exclusion: Compared with their pregame mood (M = 4.24, SD = 0.79), participants reported a significantly less positive mood after completing the Cyberball game (M = 3.13, SD = 0.99), t(126) = 8.20, p <.01, d = The difference score computed between pre- and postgame mood was significantly correlated with ESE (r RSES =.38, p <.01; r MSES =.51, p <.01; r AS =.35, p <.01), indicating that participants who self-reported high levels of pregame self-esteem reported a smaller decrease in mood after social exclusion than people who self-reported low levels of pregame self-esteem. The mood difference score was not correlated with any of the ISE measures (r IAT =.07, p =.44; r NLT =.04, p =.65; r RT-APT =.03, p =.73; r EB-APT =.07, p =.41). The descriptive statistics and intercorrelations for the four self-confident behaviours are shown in Table 3. To estimate observer agreement for each behavioural measure, we calculated intraclass correlation coefficients (ICCs [2,k]). The reliabilities of the observer ratings varied across situations: Whereas each observer showed a good level of agreement between the two interview situations (with ICCs >.70), the interobserver reliability was relatively low albeit satisfactory (with ICCs of around.60) in the self-introduction and game situations. All four behavioural criterion measures were positively related, indicating some consistency in individual differences in self-confident behaviour across situations (α =.76). Therefore, we additionally created a composite score by averaging across the four criterion measures (see last line and last column of Table 3). Table 2. Descriptive statistics and intercorrelations for self-esteem measures Self-esteem measures Explicit self-esteem Descriptives Intercorrelations M SD d Rel MSES AS IAT NLT RT-APT EB-APT RSES **.88.70**.52** ** MSES **.93.59** ** AS ** Implicit self-esteem IAT ** NLT ** RT-APT **.64.50** EB-APT **.73 Note: N = 127. RSES = Rosenberg Self-Esteem Scale; MSES = Multidimensional Self-Esteem Scale; AS = adjective scale; IAT = self-esteem Implicit Association Test; NLT = name-letter task; RT-APT = reaction-time affective priming task; EB-APT = error-based affective priming task. M = mean; SD = standard deviation; d = Cohen s d represents the effect size of the positivity bias tested against the neutral value for each measure (2.5, 4.0, and 3.5 indicate neutral self-esteem on the RSES, MSES, and AS; 0 indicates neutral self-esteem on the IAT, NLT, RT-APT, and the EB-APT); Rel = Cronbach s alpha based on the items from the RSES, MSES, and AS; test retest reliability for the first initial from the NLT; Spearman Brown corrected split-half reliability estimated by separately applying the scoring algorithm to two mutually exclusive subsets of critical task trials for the IAT, the RT-APT, and the EB-APT. *p < 05. **p <.01.

9 656 S. Krause et al. Table 3. Descriptive statistics and intercorrelations for self-confident behaviours Self-confident behaviours Descriptives Intercorrelations M SD ICC Ostracism game Ostracism interview Personal interview Composite score Self-introduction **.53**.40**.73** Ostracism game **.28**.71** Ostracism interview **.85** Personal interview ** Composite score Note: N = 127. M = mean; SD = standard deviation; ICC = intraclass correlation (2,k). **p <.01. Predictive validities Table 4 shows the correlations between the self-esteem measures and the observer ratings of self-confident behaviours. As can be seen in the first three columns, the ESE measures (at least marginally) significantly predicted each of the criterion variables. There was only one nonsignificant but positive correlation between self-confident behaviour during the self-introduction and the RSES (r =.14, p =.11). Remarkably, the MSES showed substantially higher predictive validities than the established RSES. For the ISE measures, a similar pattern of significant predictive validities was obtained only for the error-based priming procedure. That is, whereas the self-esteem EB-APT significantly predicted each outcome variable, 4 the selfesteem IAT and the NLT were not significantly correlated with any of the self-confident behaviours. Only two predictions using the NLT almost reached significance, one for observer-rated self-confident behaviour during the ostracism game (r =.17, p =.06) and one for the composite behaviour score (r =.15, p =.097). Notably, although both kinds of self-esteem priming measures were substantially correlated (r =.50, p <.01; see Table 2), the predictive validities were substantially higher for the EB-APT than for the RT-APT, and were consistently significant only for the EB-APT (see the last column of Table 4). As can be seen in Table 4, a comparison of the sizes of the correlation coefficients between the seven self-esteem measures and the five behavioural criteria showed that the EB-APT demonstrated predictive validities that were descriptively stronger than for five of the other single measures (including two established ESE measures, the RSES and the AS). Only the MSES demonstrated stronger predictive validities than the error-based priming measure, but the differences were not significant (Z 1.74, p.08). 5 4 A reviewer correctly pointed out that this phrase was incorrect for one of the outcomes. Self-confident behavior in the self-introduction situation was assessed before participants completed the self-esteem EB-APT. Thus, carefully worded, the priming measure showed retrodictive validity in this case. In the remainder of the manuscript, we use the term predictive validity of the self-esteem EB-APT for readability reasons and because the priming measure indeed significantly predicted the remaining three behavioral outcomes. 5 We found only two significant sex differences in the prediction of observer ratings of self-confident behaviors with the ESE and ISE measures (see Table S1 in the SOM). Regarding the predictive validities of the interactions between ESE and ISE measures for the outcome variables, there was no consistent pattern of significant effects (see Table S2 in the SOM). In order to examine the ability of the self-esteem EB-APT to incrementally predict each of the behavioural outcomes above and beyond ESE, we computed hierarchical regressions with the observer ratings of the selfintroduction, ostracism game, ostracism interview, personal interview, and the composite score as separate criteria. 6 In each of the five regressions, the RSES, the MSES, and the AS were entered as separate predictors in Step 1, and the self-esteem priming score was entered in Step 2. As can be seen in Table 5, the self-esteem EB-APT at least marginally significantly predicted each of the five validity criteria above and beyond ESE, even when all three direct self-esteem measures are included in the analysis. The highest amounts of variance that were additionally explained by the self-esteem EB-APT were found for the personal interview situation and the composite score of observed self-confident behaviour (see the last two rows of Table 5). The last column of Table 5 shows the amount of variance explained by both types of self-esteem for each validity criterion. Thus, using the EB-APT in addition to standard self-reports of self-esteem provided a better explanation of self-confident behaviour in social settings. In addition to the incremental validation strategy, we used commonality analyses (Nimon, Lewis, Kane, & Haynes, 2008) to disentangle the amount of criterion variance attributable to both kinds of self-esteem measures (common variance) from explained variance unique to ESE measures and explained variance unique to the self-esteem EB-APT. To create a single index of ESE, we first standardized and then averaged the scores on the RSES, the MSES, and the AS (α =.82). As can be seen in Figure ure 1, consistently across all four situations, about one quarter of the variance was shared between the composite of ESE and the priming measure (25.7% for the composite behaviour score), but both kinds of measures also had unique variance. The amount of unique variance for the self-esteem EB-APT was about one 6 We additionally computed multilevel mixed effects regression analyses reported in Table 5 with the group as a random factor to account for possible effects of grouping. However, in all five mixed effects regression analyses, the random group factor was not significant as shown by a likelihood ratio test comparing the mixed effects regression model with the standard linear regression model (LR test statistics <.53, ps >.23). In addition, the ICCs were smaller than.06 for all five analyses, also indicating that group effects were negligible for all five dependent variables. Accordingly, the fixed effects in the mixed effects analyses did not differ substantially from the effects obtained from the ordinary least squares regressions.

10 Table 4. Predictive validities of the explicit and implicit self-esteem measures Predicting self-confident behaviour with self-esteem 657 Self-confident behaviours Explicit self-esteem Implicit self-esteem RSES MSES AS IAT NLT RT-APT EB-APT Self-introduction.14.29**.25** * Ostracism game.17.24** *.24** Ostracism interview.22*.46**.26** ** Personal interview.36**.48**.31** ** Composite score.30**.49**.33** ** Note: N = 127. RSES = Rosenberg Self-Esteem Scale; MSES = Multidimensional Self-Esteem Scale; AS = adjective scale; IAT = Implicit Association Test; NLT = name-letter task; RT-APT = reaction-time affective priming task; EB-APT = error-based affective priming task. p <.10. *p <.05. **p <.01. Table 5. Incremental validity of the self-esteem EB-APT above and beyond the ESE measures Hierarchical regression Self-confident behaviours Step 1 Step 2 EB-APT ESEM ESEM + EB-APT R 2 β ΔR 2 R 2 Self-introduction.11** ** Ostracism game.07* * Ostracism interview.25** ** Personal interview.23**.24.05**.29** Composite score.26**.23.05**.31** Note: N = 127. ESEM = Explicit self-esteem measures; EB-APT = error-based affective priming task. p <.10. *p <.05. **p <.01. Figure 1. Commonality analyses for the self-esteem EB-APT and the composite score of the three explicit self-esteem measures (ESEM). 100% refers to the mean total amount of explained variance in a behavioural outcome. Unique EB-APT variance refers to variance uniquely explained by the error-based priming measure. Unique ESEM variance refers to variance uniquely explained by the composite of the three ESE measures (i.e. RSES, MSES, and AS). Common EB- APT + ESEM variance refers to explained variance that is common to the priming and composite of ESE scores. quarter (23.4% for the composite behaviour score), about one half of the variance in the composite behaviour score was uniquely explained by ESE measures (50.9 %). It is important to note that both analytic strategies (i.e. incremental validity and commonality analyses) showed that the self-esteem EB- APT substantially added to the prediction of self-confident behaviour above and beyond ESE measures. Additional results In the SOM, we provide a detailed overview of additional variables and results that were obtained in our self-esteem study. Some of the presented findings should be highlighted because they might be important for future research on behaviour prediction and self-confidence. First, for the