Self-estimated cognitive ability, cognitive performance and the Rorschach

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Master

Reference

Self-estimated cognitive ability, cognitive performance and the Rorschach

PANAGIOTOPOULOS, Angelos

Abstract

Although there is a large and expanding literature on the relationship between self-estimated intelligence, cognitive ability, personality and gender, most of the studies in the field have focused on introspective self-reports of personality. A behavioural personality test, such as the Rorschach, can potentially reveal personality dimensions not captured by self-reports and thus extent our understanding of these relationships. In the present study, in a sample of 13 males and 22 females between 20 and 36 years of age, we jointly examined four self-estimates of cognitive ability (mathematical, verbal, visual, reasoning) along with a parallel ability test for each (arithmetic, information, paper-folding, R2000) and three personality component scores from the Rorschach. Our main hypothesis was that self-estimates of intelligence would be determined by individual differences in cognitive ability and gender. We also explored the associations of the Rorschach with self-estimated intelligence and cognitive ability. The results indicated that self-estimated intelligence is a multidimensional construct affected by differences in [...]

PANAGIOTOPOULOS, Angelos. Self-estimated cognitive ability, cognitive performance and the Rorschach. Master : Univ. Genève, 2018

Available at:

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Self-estimated cognitive ability, cognitive performance and the Rorschach

MEMOIRE REALISE EN VUE DE L’OBTENTION DE LA MAITRISE UNIVERSITAIRE EN PSYCHOLOGIE

ORIENTATIONS PSYCHOLOGIE CLINIQUE PSYCHOLOGIE COGNITIVE

PAR

Panagiotopoulos Angelos

(angelos.panagiotopoulos@etu.unige.ch)

DIRECTEUR DU MEMOIRE Thierry Lecerf

JURY

Thierry Lecerf Sadegh Nashat Salomé Döll

GENEVE, JUIN 2018

Université de Genève

Faculté de Psychologie et des Sciences de l’éducation Section de psychologie

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Acknowledgements

I am using this opportunity to express my sincere gratitude to Dr. Thierry Lecerf for his assistance throughout the implementation of this dissertation and for his pertinent remarks.

I would also like to thank Sadegh Nashat and Salomé Döll for having accepted to be part of the committee as well as all the people who voluntary participated in this study.

Finally, I am grateful to my family and friends for their support and encouragement.

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Summary

Although there is a large and expanding literature on the relationship between self-estimated intelligence, cognitive ability, personality and gender, most of the studies in the field have focused on introspective self-reports of personality. A behavioural personality test, such as the Rorschach, can potentially reveal personality dimensions not captured by self-reports and thus extent our understanding of these relationships. In the present study, in a sample of 13 males and 22 females between 20 and 36 years of age, we jointly examined four self-estimates of cognitive ability (mathematical, verbal, visual, reasoning) along with a parallel ability test for each (arithmetic, information, paper-folding, R2000) and three personality component scores from the Rorschach. Our main hypothesis was that self-estimates of intelligence would be determined by individual differences in cognitive ability and gender. We also explored the associations of the Rorschach with self-estimated intelligence and cognitive ability. The results indicated that self-estimated intelligence is a multidimensional construct affected by differences in actual intelligence and sociocultural gender stereotypes. Personality dimensions issued from the Rorschach were not associated with self-estimated intelligence nor with cognitive ability.

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1. GENERAL INTRODUCTION

In recent years, differential psychology is more and more concerned with individual differences in self-estimated intelligence (SEI), the ability of individuals to estimate their own intelligence and/or their capacity on different cognitive tests.¹ This area of research is justified on the grounds that SEI has a direct (i.e., independently of actual intelligence and/or personality) impact on performance, self-esteem, goals, confidence and job satisfaction (Chamorro-Premuzic & Furnham, 2006b; Kornilova, Kornilov, & Chumakova, 2009; Ehrlinger

& Dunning, 2003; Camerer & Lovallo, 1999) as well as because self-estimates of intelligence are more and more used in educational and vocational settings (Holling & Preckel, 2005). In this context, some researchers have considered SEI as a proxy measure of intelligence (Paulhus, Lysy, & Yik, 1998) while others as the manifestation of some personality characteristics (Eysenck & Eysenck, 1985). Meanwhile, studies have also demonstrated relatively consistent gender differences,² with men estimating their intellectual abilities higher than women do (Syzmanowicz & Furnham, 2011). Consequently, in an effort to integrate the findings across the literature, it has been proposed that SEI is a multidimensional construct which combines ability (i.e., intelligence) and non-ability (i.e., personality, gender) determinants (Chamorro-Premuzic & Furnham, 2004; Furnham, Chamorro-Premuzic, &

Moutafi, 2005).

At the same time, an intrinsically related area of research concerns the potential function of SEI as an intermediate variable between intelligence and personality. Specifically, it has been argued that although personality and intelligence seem at face value unrelated to one another (due to their weak and inconsistent correlations), they might share distal links through SEI (since SEI is related to both). As a matter of fact, evidence suggest that SEI may act as a mediating (or moderating) variable between the two constructs (Chamorro-Premuzic

& Furnham, 2004; Jacobs, Szer, & Roodenburg, 2012; Kornilova & Novikova, 2013; Chamorro- Premuzic, Moutafi, & Furnham, 2005; Stankov, 1999). In this regard, researchers have recently proposed models aspiring to provide a theoretical framework for the integration of intelligence, personality and SEI (Chamorro-Premuzic & Arteche, 2008; Chamorro-Premuzic & Furnham, 2006a; Chamorro-Premuzic & Furnham, 2004). This is of great theoretical importance given that intelligence and personality, arguably the hallmarks of differential psychology, have been

1 Throughout the paper the term SEI is used interchangeably with the term self-estimates of cognitive ability. Both terms are used to signify self-ratings of one’s own cognitive ability. They represent the same construct which other researchers have termed as self-assessed intelligence (Chamorro-Premuzic &

Furnham, 2006a) or subjectively-assessed intelligence (Chamorro-Premuzic & Furnham, 2004).

2 The term gender refers to both the biological and psychosocial aspects of males and females.

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3 traditionally treated as independent constructs (Chamorro-Premuzic & Furnham, 2006a;

Chamorro-Premuzic & Furnham, 2004).

Despite these theoretical advancements, studies on intelligence, personality, SEI and gender have almost exclusively relied on the use of introspective self-reports and/or hetero- evaluation measures for the assessment of personality variation. Nonetheless, personality can also be measured by behavioural tasks such as the Rorschach. Importantly, the Rorschach could potentially add valuable information in the measurement of personality by revealing dimensions not captured by self-reports and/or hetero-evaluation measures (Meyer, 2017).

Against this background, the present study explored the relationships between intelligence, personality (as measured by the Rorschach), SEI and gender. More precisely, we investigated if the Rorschach along with intelligence and gender can account for individual differences in SEI. Further, we examined whether there is an association between measures of intelligence and the Rorschach and, if so, whether SEI acts as mediator (or moderator) between them.

To our knowledge, this was the first study in this research field to use the Rorschach as a measure of personality, which constituted the nature of our research mainly exploratory.

As a consequence, many relationships were investigated without strong a priori hypotheses.

The aim was to explore new personality dimensions which could potentially broaden the network of SEI’s associations and contribute to the theoretical understanding of the relationship between intelligence and personality. Of course, the study did not intend to provide conclusive answers but gather preliminary data which may open new insights and lead to specific research questions.

Participants were asked to provide self-estimates for four different cognitive abilities³ (i.e., mathematical, verbal, visual, reasoning) by positioning themselves on a normal distribution of standardised IQ scores. For each one of them, they completed a parallel cognitive ability test (i.e., arithmetic, information, paper-folding, R2000). Finally, as already mentioned, personality was evaluated by the Rorschach test.

The current study is structured as follows. The first part includes a theoretical introduction, devised in four main themes. (1) A brief overview of intelligence, personality and SEI followed by (2) an examination of the relationships among them, while also discussing the role of gender on SEI. These two parts are pursued by (3) an integrative overview of the relationships among intelligence, personality, SEI and gender and by (4) the rationale and theoretical hypotheses of the study. The aforementioned theoretical introduction is succeeded by the method, where we detail the procedure, the different tests administered to our sample

3 The terms intelligence, cognitive ability or ability are used interchangeably.

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4 and the hypothesis-driven along with the exploratory analysis performed. Finally, in light of our obtained results, our final conclusions are discussed.

2. THEORETICAL INTRODUCTION

The objective of the theoretical introduction is to answer the question of ‘’what is the relationship between intelligence, personality, SEI and gender’’. However, given that there exist various (often competing) theories regarding the underlying structure of intelligence and personality (Maltby, Day, & Macaskill, 2010) the question can become difficult to answer.Most of the recent literature examining the associations between intelligence, personality, SEI and gender as well as the most prominent theoretical models on their interface have used the Big- Five Model (BFM) and the Gf-Gc model as frameworks for personality and intelligence, respectively⁴ (Chamorro-Premuzic & Arteche, 2008; Chamorro-Premuzic & Furnham, 2006a;

Chamorro-Premuzic & Furnham, 2004). Thus, in order to somewhat refine the question, we focused on these two models as the conceptual basis for understanding, analysing, and interpreting relationships between intelligence, personality, SEI and gender.

As a result, in the first part of the theoretical introduction (section 2.1), we briefly outline personality as conceptualised by the BFM and discuss what could the Rorschach test contribute to the assessment of personality. We then outline the Gf-Gc model and finally define SEI. This first part provides the necessary theoretical background for the understanding and interpretation of the associations between intelligence, personality, SEI and gender, which is the topic of the next part of our introduction (section 2.2). Specifically, we consider the relationship of personality to intelligence, the relationship of SEI to intelligence and this of SEI to personality, in turn. Finally, after examining gender differences in SEI, we propose an integrative view of the above associations (section 2.3). In the final part, we describe the rationale of the study and state our theoretical hypotheses and the relationships that we explored (section 2.4).

2.1 FUNDAMENTAL CONCEPTS

2.1.1 Personality

2.1.1.1 The Big-Five Model

Many different theories have been proposed regarding the structure of personality.

Nevertheless, most researchers accept the BFM as the most reliable and valid taxonomy of personality (Costa & McCrae, 1992; Chamorro-Premuzic & Furnham, 2006a; McCrae et al., 2004). The BFM classifies personality traits into five higher-order factors, namely neuroticism,

4 Although the ‘’Cattell-Horn-Carroll’’ model is the most used theory of intelligence (McGrew, 1997), we only used the ‘’Gf-Gc’’ model.

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5 extraversion, openness to experience, agreeableness, and conscientiousness. Each higher- order factor correlates with six more specific primary factors. Individual differences in these five factors reflect people’s dispositions and should be largely determined by biological mechanisms (Costa & McCrae, 1992).

Neuroticism represents the tendency to experience unpleasant emotions and to be emotionally unstable. It is associated with anxiety, depression, hostility, vulnerability, impulsivity, and self-consciousness. Extraversion is associated to excitement-seeking, warmth, gregariousness, assertiveness, positive emotions, and elevated levels of activity.

Openness to experience reflects the degree of intellectual curiosity and imagination as well as an appreciation for novel ideas/experiences, art, and emotions. Agreeableness describes the tendency towards trust, compliance, altruism, straightforwardness, modesty, and tender- mindedness. Finally, conscientiousness is linked to competence, order, dutifulness, achievement-striving, self-discipline, and deliberation (for a more detailed description see Costa & McCrae, 1992).

The aforementioned personality traits proposed by the BFM are mainly evaluated by self-report inventories such as the NEO Personality Inventory-3 (NEO-PI-3; Costa & McCrae, 2010). Although introspective self-reports are considered valid measures (e.g., Piedmont, McCrae, Riemann, & Angleitner, 2000), information from different classes of tests could add incremental validity to the assessment of personality (Meyer, 2017). In this respect, behavioural tests in which subjects are asked to execute a task, could potentially complement self-reports in the measurement of personality. The most well-known of these tests, which was employed in our study is the Rorschach. At this point it should be stated that the BFM and the Rorschach test operate on different levels. The Big-Five is a theoretical model of personality and its personality dimensions are measured by instruments such as the NEO-PI-3. In contrast, the Rorschach is a behavioural task. It generates scores and scales that are empirically derived from behavioural norms and are to a great extent unrelated to a priori psychological constructs or models. While acknowledging its atheoretical nature, in the present study, the Rorschach is treated in a theoretical manner in order to facilitate interpretation.

2.1.1.2 The Rorschach

Brief Overview and the Comprehensive System

The Rorschach inkblot test, commonly referred as simply the Rorschach, was originally created by the Swiss psychiatrist Hermann Rorschach (1921/1942). The test employs 10 inkblot stimuli, each printed on a white card. Five of the cards contain black and gray ink, two of them contain black and red, while the last three are multicolored. Participants are presented each inkblot card separately and respond to the question “what might this be?”. Their answers

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6 compose the task’s raw data, which are then coded and examined in contrast with established norms, to allow interpretation.

Various Rorschach systems had emerged before the 1970’s, none of which had sound empirical evidence. This perplexing situation was resolved after Exner published the Rorschach Comprehensive System (RCS; Exner, 1974), in which he merged the aspects of the various systems with the most supportive evidence. Coding rules were adjusted to improve interrater reliability and the interpretation was developed based on empirical evidence.

Therefore, he developed the RCS as a valid and reliable tool for personality assessment. In his workbook, he gives explicit guidelines for administration, coding, and interpretation (Exner, 2005; also see section 3.2.3). Among practicing clinicians across the globe, the RCS is the by far the most widely used system, and virtually the only one (Meyer, Hsiao, Viglione, Mihura, &

Abraham, 2013).

What can the Rorschach add to the assessment of personality ?

In answering the question of what the Rorschach could add to the assessment of personality, a brief theoretical foundation of the test is important. Hermann Rorschach’s inkblots were artistically designed, cautiously chosen, pilot-tested and refined in order to accomplish what he probably intended: create stimuli that consisted of various evocative yet incomplete images which were triggering an effect of competitiveness on a person’s visual perception (Meyer, 2017). Thus, on the one hand, the images should yield some rather apparent configurations that are frequently reported by people and on the other hand serve as perceptual ‘’hooks’’ that provoke uncommon images based on each individual’s characteristics (Meyer, 2017). Consequently, a minor number of very frequent responses (e.g., bat) constitute a great percentage of the total responses whereas the majority of responses are seen by few people (Meyer, Viglione, Mihura, Erard, & Erdberg, 2011). This characteristic constitutes the Rorschach a unique personality test which evaluates the conventionality of perception while encouraging personal understanding and expression.

Hence, the Rorschach is a problem-solving task,⁵ which requires the respondents to employ perceptual, cognitive, and affective resources (McGrath, 2008). The task relies on standardised samples to provide a behavioural norm of how people see and interpret things to solve the problem of ‘’what might this be’’. Further, the respondents are free to decide how they are going to perform the task in order to answer to the question.

5 Traditionally, the Rorschach has been classified as a projective test. In contrast, introspective personality self-reports have been termed as ‘’objective’’ personality tests. However, this terminology can be deceptive (Meyer & Kurtz, 2006). The term ‘’objective’’ strongly indicates that introspective personality self-reports are not influenced by one’s response style and biases, an assumption which is certainty false (e.g., Griffin, Hesketh, & Grayson, 2004; Backstrom & Bjorklund, 2013).

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7 The above discussion implies that there are two major differences between the Rorschach and conventional measures of personality (i.e., self-reports or hetero-evaluation measures). First, in the Rorschach, it is the examiner that has to infer the respondent’s characteristics by evaluating his/her responses with reference to established norms. In introspective self-reports, this process is left to the participant who has to think about his/her own qualities, examine them in contrast to others and finally determine what exactly he/she is going to disclose to the examiner. Secondly, in introspective self-reports and hetero-evaluation measures, the stimulus is usually a question or a suggestion that is introduced to the respondent who should then specify how well it represents his/her personality based on a restricted response format (e.g., rating scales). This leaves much less freedom to the participant to express his/her individuality than in the Rorschach.

Therefore, the Rorschach seeks to assess what the person is doing, rather what he/she reports of doing. Accordingly, it is no surprise that the Rorschach exhibits very low correlations with self-report measures, which at face value measure the same constructs (Meyer, Riethmiller, Brooks, Benoit, & Handler, 2000; Mihura, Meyer, Dumitrascu, & Bombel, 2013).

With regards to the BFM in particular, there is some conceptual similarity with certain Rorschach variables (see Petot & Djurić Jočić (2005) for a detailed discussion). Greenwald (1999) suggested a series of variables from the RCS that could be conceptually linked to the scales of the NEO Five-Factor Inventory (NEO-FFI; Costa & McCrae, 1992) in a student sample. For example, she expected WSumC (indicates the amount of emotional reactivity) and Ma (related to higher activity) to be positively correlated with extraversion. Not only she failed to find any of the hypothesised relationships, but she also observed correlations which were conceptually hard to explain. For instance, the sum of shading responses (V + T + Y), which is thought to reflect painful affect, was negatively correlated with neuroticism. Similarly, in a psychiatric population, Petot (2004) found that openness was the only dimension from the BFM that correlated with some variables of the RCS. However, only one of these correlations seemed intuitively comprehensible and generalisable to the general population: the negative relationship between lambda (measure of avoidance to complexity, subtlety, or nuance) and openness.

Perhaps, nothing illustrates better the low convergent validity between the BFM and the Rorschach than the low concordance between extraversion and Rorschach’s extratensiveness. At face value the two constructs are similar, since extratensiveness has been defined as a predisposition to extraversion (Rorschach, 1942). Yet, the results are at best ambiguous. Petot (2004) found a non-significant correlation between the two at r = .12, in line with Meyer’s (1992b) earlier findings. Del Pilar (2005), in a population of 128 students, showed a positive but low (r = .29) relationship between the two. De Carolis and Ferracuti (2005), referring to extraversion as in Eysenck’s model, obtained a stronger relationship (r = .42) in a

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8 non-clinical sample. However, in the two latter studies, the researchers retained unconventional operational definitions of extratensiveness, which transformed it into a continuous quantitative variable, whereas in reality it is categorical.

From the above it can be argued that the Rorschach has little relationship to the BFM, and more general with introspective self-reports. In fact, in the most extensive and recent meta- analytic study of the RCS, Mihura et al. (2013) found a mean validity of .08 between Rorschach variables and parallel introspective self-reports, versus a mean validity of .27 against externally assessed criteria (e.g., observer ratings, psychiatric diagnosis). It follows that the responses on the Rorschach can potentially indicate implicit personality characteristics that are not identified or disclosed by people in self-reports measures. This does not imply by any means that self-reports should be disregarded. It simply suggests that personality data obtained from the Rorschach can potentially add incremental validity over using self-reports alone (for recent evidence see Meyer, 2017).

2.1.2 Intelligence

Moving on from personality, we advance our discussion to intelligence, and focus on the Gf-Gc model. In essence, the majority of intelligence theories are based on hierarchical models derived from Spearman’s (1927) two factor-theory of intelligence. According to Spearman, intelligence has two components: a general (g) factor which has an impact on all ability tasks, and a set of specific (s) factors which influence performance on particular tasks.

Building upon Spearman’s work, Cattell (1971) proposed two distinct factors of general ability:

fluid (Gf) and crystallised (Gc) intelligence (Gf-Gc model; McGrew, 2005). Gf relies on the effective functioning of the central nervous system and reflects the capacity to reason (induction and deduction), to identify relationships (inference), to recognise and form concepts, to generate hypotheses, to transform information and more generally to solve novel problems that cannot be solved by relying exclusively on previous knowledge. On the other hand, Gc indicates the extent and depth of knowledge regarding language, verbal concepts and verbal information, acquired through learning and experience within a culture. In addition, it is associated with verbal comprehension and the ability to communicate information.

Thereafter, Cattell along with Horn, expanded the Gf-Gc model to include 7 additional primary factors (Horn & Noll, 1997).⁶ These factors do not cluster around a general factor. For the purpose of our study it is worth mentioning visual-spatial processing (Gv) and quantitative knowledge (Gq). The former relates to the ability to solve problems through mental imagery.

This is, the ability to mentally perceive, analyse, store, synthesise, retrieve, manipulate, and transform visual stimuli (figurative or geometric). The latter compromises quantitative

6 Despite its expansion the model is still called Gf-Gc.

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9 knowledge and reasoning. It involves the ability to understand and apply mathematical concepts and knowledge (e.g., operations, fractions) to solve quantitative problems in a static (declarative) and dynamic (procedural) way. It is essentially acquired through experience.

Regardless the underlying theory, the assessment of intelligence has traditionally relied on the use of standardised psychometric tests, such as the fourth edition of the Wechsler Adult Intelligence Scale (WAIS-IV; Wechsler, 2011). However, researchers such as Paulhus et al.

(1998) have proposed that alongside this classical method we could also evaluate intelligence by asking individuals to provide estimates of their own intellectual competence. This leads us to the third main construct of the present study, namely SEI.

2.1.3 Self-Estimated Intelligence

SEI is usually measured by asking individuals to assess their own intelligence, either as a unitary construct or as a function of various specific cognitive abilities (Chamorro- Premuzic & Furnham, 2004). SEI and other related, albeit distinct, self-evaluation constructs which draw on people’s self-concept (e.g., self-efficacy, core self-evaluations) influence a variety of outcomes (e.g., performance, goals, motivation) probably because of their self- fulfilling effects (e.g., Hutchinson, Sherman, Martinovic, & Tenenbaum, 2008; Chamorro- Premuzic & Furnham, 2006b; Bono & Judge, 2003; Judge, Erez, Bono, & Thoresen, 2002).

Nevertheless, SEI can also be conceptualised as a measure of intelligence, particularly a subjective one. Thus, it has been defined as the measure of one’s own insight or awareness into his intellectual ability (Chamorro-Premuzic & Furnham, 2004). Accordingly, Paulhus et al.

(1998) suggested that SEI can be used as a proxy of psychometric intelligence tests. However, as we discuss in greater detail in the next section, SEI might also reflect certain personality characteristics and gender stereotypes.

2.2 INTERFACE OF PERSONALITY – INTELLIGENCE – SELF-ESTIMATED INTELLIGENCE AND THE ROLE OF GENDER

Having considered intelligence, personality and SEI separately, we now proceed to inquire the links among them. As a result, we first consider the relationship of personality to intelligence and then the relationship of SEI to intelligence and to personality. Finally, after investigating gender differences in SEI, we suggest a unifying perspective of the above associations.

2.2.1 Intelligence and Personality

Differential psychologists have traditionally treated personality and intelligence as independent constructs (e.g., Eysenck, 1970; Webb, 1915; Zeidner, 1995; Hofstee, 2001).

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10 Nevertheless, more recent studies suggest modest but significant intelligence-personality associations, even though the results are often inconsistent (Ackerman & Beier, 2003;

Ackerman & Wolman, 2007; Chamorro-Premuzic & Arteche, 2008; Ackerman & Heggestad, 1997; Chamorro-Premuzic & Furnham, 2006c; Reeve, Meyer, & Bonaccio, 2006). At this point it is important to draw a theoretical distinction between actual intelligence and test performance. The former refers to intelligence as a latent construct (i.e., ability as a trait) whereas the latter refers to the output score on psychometrically validated IQ or ability tests.⁷ To further explain this distinction, we could consider the example of Gf. We cannot directly measure an individual’s ‘’true’’ capacity to reason, to identify relationships and to generate hypotheses (actual fluid intelligence). Nevertheless, we assume that this capacity is reflected on test scores which measure Gf (test-based Gf performance). Accordingly, personality traits can relate to actual intelligence and/or to test performance.

Impact of Neuroticism and Extraversion on Test Performance

In their extensive meta-analysis, Ackerman and Heggestad (1997) found that neuroticism was significantly negatively correlated with general intelligence at r = -.15, while extraversion was positively related at r = .08. The magnitude of these relationships was similar across the specific primary factors of Gf, Gc, Gv and Gq. For example, the correlations coefficients between extraversion and the four aforementioned primary abilities ranged from .6 to .11 (all significant). Comparable results have been reported by other studies (Reeve et al., 2006; Chamorro-Premuzic & Furnham, 2006c; Furnham, Moutafi, & Chamorro-Premuzic, 2005; Moutafi, Furnham, & Crump, 2003; Moutafi, Furnham, & Paltiel, 2005) although it is not rare to find conflicting results in the literature (for a discussion see Wolf & Ackerman, 2005).

What both traits have in common is that they probably affect test performance rather than actual intelligence (Zeidner & Matthews, 2000; Chamorro-Premuzic & Furnham, 2004). For example, neuroticism, namely the facet of anxiety, has a negative impact on exam performance while extraversion is linked to higher response speed and assertiveness, which could be advantageous in most types of ability tests (Furnham, Forde, & Cotter, 1998;

Humphreys & Revelle, 1984). Accordingly, neuroticism and extraversion have been termed as performance-related non-ability traits (Chamorro-Premuzic & Arteche, 2008). In other words, they moderate the effect of actual intelligence on ability tests.

Impact of Openness to Experience on Gc

Openness to experience is the personality trait which produces the highest and most consistent correlations with intelligence (Zeidner & Matthews, 2000; Chamorro-Premuzic &

7 Despite the conceptual distinction, it can be assumed that established intelligence tests are valid indicators of actual intelligence (Chamorro-Premuzic & Furnham, 2006a).

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11 Furnham, 2004). In their meta-analysis, Ackerman and Heggestad (1997) found a significant correlation of r = .30 with general intelligence. Studies have reported even higher correlations between .40 and .50 with Gc (Goff & Ackerman, 1992; Schretlen, van der Hulst, Pearlson, &

Gordon, 2010; Brand, 1994). In sharp contrast with neuroticism and extraversion, openness to experience appears to have a direct impact on actual intelligence, namely on Gc, instead of simply affecting performance. Since openness reflects the degree of intellectual curiosity and an appreciation for novel ideas/experiences it likely influences the engagement (or investment) in intellectually stimulating activities, which favors knowledge and skill acquisition (Cattell, 1987; von Stumm & Ackerman, 2013; Rammstedt, Danner, & Martin, 2016; Ashton, Lee, Vernon, & Jang, 2000). In other words, openness may influence the developmental trajectory of Gc through the investment in intellectual activities. As a result, openness has been considered as an investment non-ability trait (Chamorro-Premuzic & Arteche, 2008). Note that openness has also been found to be positively associated with other primary factors of intelligence, although the correlations are often weaker and less consistent than Gc. For instance, there are weak to moderate correlations with Gf (Ashton et al., 2000), Gv (Ackerman

& Heggestad, 1997; Harris, 2004) and Gq (Kyllonen, 1997), which other studies have failed to replicate (e.g., Moutafi et al., 2005).

Impact of Gf on Conscientiousness

With respect to conscientiousness and intelligence, r values are often found to be non- significant and very weak around .02 (Ackerman & Heggestad, 1997; Kyllonen, 1997; Zeidner

& Matthews, 2000). Nevertheless, some studies have reported few significant negative correlations between conscientiousness and fluid aspects of intelligence at approximately r = -.18 (Furnham et al., 2005; Moutafi et al., 2003; Moutafi, Furnham, & Crump, 2006; Moutafi et al., 2005). Considering that Gf is biologically determined and minimally prone to the effect of external factors (Brody, 1992; Belsky, 1990), it is highly unlikely that a personality trait such as conscientiousness could affect its developmental trajectory. Further, there is no intuitive theoretical reason on why higher conscientiousness should lead to inferior intellectual ability or lower conscientiousness to superior intelligence. Thus, most probably Gf has an impact on the development of conscientiousness (Moutafi et al., 2003; Moutafi et al., 2005). In our antagonistic society, it is likely that individuals of lower intelligence would develop a more conscientious personality (i.e., self-discipline, cautiousness, persistence) to compensate for their intellectual disadvantage. Conversely, individuals of high potential may be prone to present a less conscient behaviour as they could count on their high Gf to complete most tasks.

Lastly, it appears that there is no association between agreeableness and intelligence, with studies repeatedly reporting almost zero correlation coefficients between the two (Ackerman & Heggestad, 1997; Kyllonen, 1997; Judge, Jackson, Shaw, Scott, & Rich, 2007).

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12 This is no surprise as the facets of agreeableness (e.g., modesty, cooperation, altruism, morality) seem conceptually unrelated to intelligence.

Rorschach and Intelligence

Considering that the Rorschach is used as a measure of personality in our study, it is also important to inquire the links between the Rorschach and intelligence. Based on the most recent extensive meta-analysis of Mihura et al. (2013), the variables that seem to be associated with IQ (mostly Wechsler tests) are the number of responses (R; ability to respond with many ideas), non-form determinants (F%; avoidance vs. attentiveness to complexity), human movement (M; mental abilities such as planning and imagination), complexity ratio (Blends:R; psychological complexity), synthesized response (DQ+; ability to synthesise concepts), organisational frequency (Zf; ability to sustain cognitive effort), experience actual (EA; cognitive and emotional resources) and processing efficiency (Zd; propensity to process information).

It should be highlighted that for many of the above variables, the effect sizes and significance levels are based on the meta-analysis of two or three studies which, additionally, present a great heterogeneity (e.g., clinical vs. non-clinical samples, adolescents vs. adults).

Thus, these results should be interpreted cautiously and cannot be considered conclusive.

Moreover, most of the studies have used general IQ scores and as a result there is little data on the relationship of the Rorschach and more specific cognitive abilities. It is also worth mentioning that out of the aforementioned variables, DQ+, Zf, M, Blends:R and F% appear to compose an underlying factor. This factor has been interpreted as reflecting mental complexity and representational capacity and correlates with Wechsler IQ scale at r = .29 (Wood, Krishnamurthy, & Archer, 2003).

In conclusion, neuroticism and extraversion seem to be related with performance on ability tests, whilst openness and conscientiousness appear to have a direct link to actual intellectual ability. Nevertheless, while the aforementioned studies illustrate a link between intelligence and personality, their relationship is fairly weak and occasionally inconsistent.

Finally, there is weak evidence of a relationship between a few Rorschach scores (mainly variables reflecting mental complexity and representational capacity) and intellectual ability.

Next, we focus on the interplay between SEI and intelligence.

2.2.2 Self-Estimated Intelligence and Intelligence

A notable feature of SEI, which distinguishes it from other self-evaluation constructs, is that it can also be conceptualised as a subjective measure of intelligence. Indeed, the definition of SEI as a measure of one’s own insight into their intellectual ability (Chamorro-Premuzic &

Furnham, 2004), emphasises its nature as an assessment of cognitive ability, namely a

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13 subjective one. To this end, researchers have treated SEI as a proxy measure of IQ tests (Hogan, 1976; Paulhus et al., 1998).

In general, empirical evidence shows positive correlations between SEI and intelligence. That is, individuals who score higher on intelligent tests are more likely to give greater estimates of their own cognitive ability. Three decades ago, Mabe and West (1982) found a correlation of SEI and cognitive tests at r = .34 based on 12 effect sizes. A more recent meta-analysis of 154 effect sizes reported an almost identical overall correlation at r = .33 (Freund & Kasten, 2012). Nevertheless, the directionality of their relationship is still not well understood. When regressed, SEI accounts anywhere from 4% to 11% of the variance in g (Chamorro-Premuzic, 2005; Furnham et al., 2005). This means that SEI may affect intellectual ability through engagement in stimulating intellectual activities (due to higher self-confidence for example). Conversely, when g is regressed onto SEI, it explains about 10% of the variance in SEI (Chamorro-Premuzic & Furnham, 2006c). Hence, it can also be argued that individuals have a limited insight into their intellectual capacity.

Moreover, Freund and Kasten (2012) found that the convergent validity against parallel-test based measures was higher for self-estimates of numerical abilities (corresponding to Gq in the Gf-Gc model) compared to self-estimates of general ability. In contrast, no such effect was observed for spatial and verbal abilities (corresponding to Gv and Gc, respectively), a finding which was also supported by Ackerman and Wolman (2007). The higher validity of self-estimated Gq can be intuitively explained by the fact that unlike general cognitive ability, which has to be conceptually organised into a theoretical combination of various abilities, numerical abilities represent a rather unambiguous construct for participants.

If so, the question raised is why this effect is not also observed for self-estimated Gv and Gc. It is reasonable to speculate that such a discrepancy is somewhat determined by peoples’ experience in the ability that they assess themselves, which consequently leads to more inaccurate self-estimates (Ng & Earl, 2008). That is, the way that numerical abilities are assessed in educational settings and in everyday life provides an accurate source of feedback (a solution to a numerical problem is either correct or false). As a result, people can become relatively aware of their Gq ability. In contrast, the use of verbal and spatial abilities in everyday life is much more indirect, which leaves room for subjective interpretations of one’s Gv and Gc.

Moreover, although people undertake verbal and spatial tasks in school, they rarely resemble to the tasks they confront in validated psychometric tools. Thus, direct assessment of one’s Gv and Gc is often first encountered in psychometric testing. This explanation is in line with evidence showing that participants are more accurate in estimating how well they performed in a task after its completion (von Stumm, 2014; Dunning, Johnson, Ehrlinger, & Kruger, 2003).

As a final remark, it must be noted that all the above mean effect sizes between psychometric intelligence scores and SEI should be treated as a general guideline. Indeed,

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14 this is the case, if one considers that effect sizes were highly heterogeneous across studies and that the relationship is probably moderated by many different variables, such as the methodology of measuring SEI (Holling & Preckel, 2005; von Stumm, 2014). Nevertheless, in general, it can be said that people have limited insight into their intellectual abilities as the relationship can be considered at best as moderate (Cohen, 1988). Based on the above meta- analyses, only 10% of the variation in SEI can be explained by cognitive tests, which leaves 90% of the variability to be accounted by other variables. Hence, in the following subsection we address the question of whether personality could also explain individual differences in SEI.

2.2.3 Self-Estimated Intelligence and Personality

Following Eysenck and Eysenck’s (1985) argument that SEI should be considered the expression of certain personality traits rather than a proxy of intelligence, studies have investigated the extent to which personality could account for a proportion of the unexplained variability in SEI. Links between SEI and the Big Five personality traits have been repeatedly reported although inconsistencies exist in the literature, probably due to the methodological heterogeneity of the studies. Extraversion, openness, and conscientiousness (albeit to a lesser extent) have been positively associated to SEI, while the opposite appears to be the case for neuroticism and agreeableness (Chamorro-Premuzic et al., 2005; Furnham, Kidwai, &

Thomas, 2001; Furnham et al., 2005; Chamorro-Premuzic & Arteche, 2008; Visser, Ashton, &

Vernon, 2008; Jacobs et al., 2012). Usually, the correlation coefficients between each of the five personality traits and SEI range from .20 to .25. Accordingly, when personality traits as a whole are regressed onto SEI, they account for 7 % to 17 % of its variance (Furnham & Dissou, 2007; Furnham & Thomas, 2004; Furnham & Chamorro-Premuzic, 2004; Furnham et al., 2005;

Jacobs et al., 2012).

Theoretically, individuals who score high on neuroticism tend to have a negative self- concept, which could lead to a lower score of SEI (Wells & Matthews, 1994). Similarly, individuals who score high on agreeableness are described as modest, which can explain why they also report lower SEI (Costa & McCrae, 1992; Furnham et al., 2005). Conversely, the higher scores of SEI in extravert individuals can be attributed to over-confidence and assertiveness (Zeidner & Matthews, 2000). Regarding openness to experience, its positive correlation with SEI has been mainly explained by actual intellectual ability (e.g., Chamorro- Premuzic & Furnham, 2004). As already mentioned, openness can be conceptualised as an investment non-ability trait, which promotes intellectual development and knowledge acquisition. Thus, if open individuals have higher Gc, it is reasonable that they also score higher in SEI.

Few studies have examined SEI and personality at the facet level. The primary traits that have been found to be associated with SEI were the neuroticism facets of anxiety, self-

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15 consciousness, and vulnerability (all negatively), the extraversion facet of activity (positively) and the openness facets of ideas and values (both positively) (Chamorro-Premuzic et al., 2005). Moreover, Furnham et al. (2005) found that the neuroticism facet of anxiety and the agreeableness facet of modesty were significant predictors of SEI.

From the above discussion, it can be said that certain aspects of personality are reflected in SEI. However, more research is needed in order to establish the traits of personality that best predict SEI.

2.2.4 The Role of Gender on Self-Estimated Intelligence

Based on the previous two sections, it appears that individual variation in SEI is related to a range of cognitive attributes and personality traits. However, research has also shown the existence of gender-based differences, with males providing higher estimates compared to females. The comprehension of gender differences in SEI seems of high practical relevance in view of SEI’s direct effect on performance (Kornilova et al., 2009) and career choice (Ehrlinger & Dunning, 2003; Camerer & Lovallo, 1999) as well as because SEI is widely used in educational and vocational settings (Holling & Preckel, 2005). For instance, women who underestimate their abilities might avoid professional paths in which they could flourish (Ehrlinger & Dunning, 2003).

With this in mind, we decided to give a particular emphasis to the role of gender in the present study. In what follows, we present the latest data regarding gender differences in SEI and address the question of whether these differences are exclusively determined by personality and/or intelligence differences between males and females. This is important because it would suggest whether or not gender can uniquely contribute to the prediction of SEI over and above intelligence and personality.

As mentioned above, males are more likely to attribute themselves higher SEI compared to females, a phenomon termed as the ‘Hubris-Humility Effect’ (Storek & Furnham, 2012; von Stumm, 2014; Rammstedt & Rammsayer, 2000, 2002; von Stumm, Chamorro- Premuzic, & Furnham, 2009). This consistent gender difference is most strongly reflected on measures of self-estimated general intelligence and on measures of self-estimated Gq, Gv and Gf (Holling & Preckel, 2005; Storek & Furnham, 2012; Storek & Furnham, 2013). In a quite recent meta-analysis, Syzmanowicz and Furnham (2011) reported the largest weighted mean effect size for self-estimated Gq and Gf ability (d = .44), succeeded by self-estimated Gv (d = .43), general (d = .37) and Gc ability (d = .07). Males presented significantly higher self- estimates in all abilities, except from Gc. These gender differences have been replicated cross- culturally with data from Asian, African and Western cultures (e.g., Furnham & Fukumoto, 2008; Yuen & Furnham, 2005; Furnham, 2001).

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16 Gender differences in SEI and intelligence

Regarding actual intelligence, it seems highly unlikely that gender differences in SEI reflect gender differences in objectively measured abilities. Firstly, most researchers would agree that there are not significant differences between males and females in general intelligence (Loehlin, 2000; Hyde, 2005; Halpern & LeMay, 2000; but see Lynn (1999) for a different view) although males consistently report higher self-estimates of g. Secondly, although some researchers argue for a marginal superiority of males in Gq, Gv and Gc (e.g., Brunner, Krauss, & Kunter, 2008; Masters & Sanders, 1993) and of females in Gc (e.g., Halpern, 2004), in most circumstances the moderate gender variance in SEI does not correspond to the low gender variance in the respective actual psychometric ability (Syzmanowicz & Furnham, 2011). For example, in their review Syzmanowicz and Furnham (2011) found a mean effect size of d = 0.44 in self-assessed Gq between males and females, in comparison to a mean effect size of .14 in psychometrically measured Gq intelligence (Else- Quest, Hyde, & Linn, 2010). As a result, gender differences in SEI are unlikely to be driven exclusively by differences in actual ability (if at all).

Gender differences in SEI and personality

Considering personality, studies have demonstrated that females tend to score higher on neuroticism and agreeableness (Feingold, 1994; Costa, Terracciano, & McCrae, 2001).

This is interesting as both traits are negatively associated to SEI. Hence, one can hypothesise that gender differences in SEI are determined by gender differences in these two personality traits. However, evidence does not strongly favor this hypothesis. Specifically, mediator variable analysis has suggested that women’s higher neuroticism partly explains their lower scores in SEI (Stieger et al., 2010; Furnham et al., 2005; Furnham & Buchanan, 2005; Visser et al., 2008). Nevertheless, all the aforementioned studies indicate large direct effects of gender on SEI, which are independent of personality. Ηence, as it was the case for intelligence, personality cannot fully account for gender differences in SEI.

All things considered, the impact of gender on SEI is to a great extent independent of individual differences between males and females in actual intelligence and/or personality. In fact, these differences are more likely driven by social stereotypes and differences in early socialization between males and females (Rammstedt & Rammsayer, 2000; Furnham, 2000;

Beloff, 1992). It has also been argued that males’ significantly higher self-estimates of general intelligence stems from an excessive weight on ‘’male normative abilities’’, in particular Gv and Gf (Furnham & Rawles, 1999). In other words, lay people are more likely to relate general intelligence with these specific facets of intelligence, in which a popular stereotype of male superiority prevails (Rammstedt & Rammsayer, 2000; Petrides, Furnham, & Martin, 2004).

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17 2.3 INTEGRATING FINDINGS

Based on the above discussion, we could draw two main general conclusions. First, it is clear that SEI should be considered as a multidimensional construct, which is determined by individual differences in intelligence, personality, and gender. Second, despite that intelligence and personality appear to be only weakly related (reflected in the low correlations and the many inconsistencies found in the literature), SEI displays stronger and more consistent correlations with both. An extreme illustration of this point can be found in Furnham et al.’s (2005) study, in which about 62% of the correlations of SEI with intelligence and personality variables were significant. In sharp contrast, less than 8% of the correlation coefficients between personality and intelligence variables reached significance levels.

Accordingly, it has been suggested that intelligence and personality are indirectly associated through SEI. That is, SEI may act as a mediating (or moderating) variable between the two constructs (Chamorro-Premuzic & Furnham, 2004; Jacobs et al., 2012; Kornilova &

Novikova, 2013; Chamorro-Premuzic et al., 2005; Stankov, 1999). In other words, personality may have an impact on how individuals estimate their abilities, which in turn influences their performance on cognitive ability tests. For instance, if extraverts believe that they have high cognitive abilities due to over-confidence, this might lead to better performance on cognitive tests (through an optimal test-taking style for example). The opposite can be hypothesised for neurotics. Lower self-estimates of their abilities due to a negative self-concept, can lead to increased anxiety and thus to lower scores on intelligence tests. Figure 1 recapitulates the interface between intelligence, personality, SEI and gender as discussed so far.

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18 Figure 1. Summary of the principal associations between intelligence, personality, self- estimated intelligence and gender, as discussed in the theoretical introduction.

Note. Gq = quantitative knowledge, Gf = fluid intelligence, Gc = crystallised intelligence, Gv = visual-spatial processing, A = agreeableness, C = conscientiousness, O = openness to experience, N = neuroticism, E = extraversion, SEI = self-estimated intelligence. All correlations are approximative. In bold are negative correlations. The figure is not exhaustive, and it only summarizes the major relationships.

2.4 RATIONALE AND THEORETICAL HYPOTHESES

Considering SEI’s direct impact on job satisfaction, motivation, confidence and performance, much research has been conducted in order to establish its determinants (Chamorro-Premuzic & Furnham, 2006c). At the same time, the importance of examining SEI extends beyond its practical applicability, due to its potential intervening role between intelligence and personality. That is, SEI has received considerable attention as a possible mediating (or moderating) variable between intelligence and personality, despite the long- standing theoretical tradition of differentiating between the two.

Up to date, there is compelling evidence suggesting that interindividual differences in SEI are (at least partly) explained by differences in intelligence, personality and gender while

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19 evidence points towards the mediating effect of SEI on intelligence and personality. Yet, within this research field particular aspects of personality have been neglected so far, namely personality dimensions measured by behavioural tests such as the Rorschach. Importantly, as we argued earlier, the Rorschach has low convergent validity with self-reported personality traits , and thus it could be a useful complement in the measurement of personality.

In this context, the present exploratory study attempted to empirically investigate the relationships between intelligence, Rorschach personality dimensions and SEI, while considering the effect of gender. To the extent that SEI is a multidimensional construct which uniquely reflects ability (i.e., intelligence) and non-ability (i.e., personality, gender) determinants, potential associations with the Rorschach could expand the network of SEI’s relations to individual characteristics not captured by self-reports. At the same time, such an approach might contribute to the better comprehension of how intelligence and personality are conceptually and empirically related.

Following a psychometric approach, self-estimates of Gq, Gv, Gc and Gf ability were compared against parallel objective ability tests. Further, some variables of the RCS were selected and regrouped into linear components, which served as personality dimensions.

Based on our theoretical introduction, we formulated the following general hypotheses:

• Males would tend to give higher scores of SEI on abilities which are considered male normative (i.e., Gq, Gv, Gf) mainly because of gender stereotypes, irrespective of gender differences in actual intelligence and personality.

• SEI would be positively and moderately associated with intelligence.

• SEI would be determined by individual differences in intelligence and gender.

Given the exploratory nature of our study, for the most part we did not have strong a priori hypotheses. Hence, we decided to explore:

• The relationship of SEI with personality dimensions issued from the Rorschach

• The associations between intelligence and personality as measured by the Rorschach

• Whether SEI mediates (or moderates) the relationship between intelligence and personality

3. METHOD

3.1 PARTICIPANTS

A total of 35 participants (13 males and 22 females) took part in the study. Their ages ranged from 20 to 36 with a mean of 24.43 years (SD = 4.44). Sixteen participants were native French speakers while 19 were non-native but fluent in French. In total, 43 % had received (or were receiving) undergraduate education, while 57 % post-graduate education. Participants

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20 were not paid for their participation and were unaware of the measures employed in the study.

It was unfeasible to use random recruiting so most of them were friends or acquaintances of the experimenter.

3.2 MATERIAL

3.2.1 Cognitive Ability Tests Information and Arithmetic

Τhe information and the arithmetic tests are part of the Multidimensional Aptitude Battery-II (MAB-II; Jackson, 1998), a battery of 10 ability tests established on the basis of the Wechsler Adult Intelligence Scales–Revised (WAIS-R; Wechsler, 1981). The items within each of the subtests are multiple-choice questions sorted in order of difficulty and subjects have to select the correct response from five possible alternatives. All tests include a page of instructions and two sample items. The total score for each subtest is computed by simply adding the correct responses. Scores at the subtest level of the MAB have been related to internal consistency reliability estimates above .70 (Jackson, 1998).

Information: The information test is composed of 40 multiple choice items encompassing a wide range of topics of general knowledge (Appendix A; exemplar item : who invented the telephone? possible answers : Leonardo da Vinci, Alexander Pope, Thomas Edison, Benjamin Franklin, Alexander Bell). Participants have a time limit of 5 minutes and the total score ranges from 0 to 40. According to the manual, its score indicates the extent to which an individual has acquired a fund of knowledge about diverse subjects, which ultimately reflects one’s degree of curiosity and incentive to learn new information (Jackson, 1998).

Hence, in our study, the information test was employed as a test-based measure of Gc, in line with Gignac’s (2006) suggestion.

Arithmetic: The arithmetic test consists of 26 multiple choice item-problems that necessitate arithmetic calculations and diverse levels of reasoning and problem-solving abilities (Appendix B; exemplar item : a man earns 25 francs and spends 15 francs. How much money does he have left? possible answers : 10, 40, 15, 5, 30). Participants have a time limit of 7 minutes and the total score ranges from 0 to 26. Its score reflects one’s ability to abstract the elements of a problem that are essential for its solution and one’s ability to rapidly find the answer (Jackson, 1998). Based on the Gf-Gc model, it was used as a test-based measure of Gq.

Paper-Folding

The 3-min version of the paper folding test (i.e., Part 1 of VZ-2) from the Kit of Factor- Referenced Cognitive Tests (Ekstrom, French, & Harman, 1976) was also used (Appendix C).

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21 For each item in the test, 2 to 4 figures are presented at the left of a vertical line while five other figures are presented at the right of the line. The figures at the left illustrate the process of a sheet of paper being folded and the final one of them has one small circle, representing that the paper was punched at that point through all its thickness. The subject has to decide which one of the five figures at the right corresponds to the sheet of paper when it is completely unfolded (Figure 2). The test consists of 10 multiple choice items (5 options per item) and evaluates understanding of concrete spatial relationships. Hence, in the current study, it represented a test-based measure of Gv. Before beginning the task, participants are given a sample item. The total raw score ranges from 0 to 10, calculated by adding 1 point for each correct answer.

Figure 2. Exemplar items from the paper-folding test

R2000

The R2000 test (Reasoning Test, 2000 version; Appendix D) was used as a test-based measure of Gf (ECPA, 2000). The 40 items of the test are fairly variable (15 verbal items, 10 mixed items and 15 numerical items; Figure 3) and thus the test also evaluates one’s flexibility of reasoning, defined here as the ability to switch from a type of reasoning to another (ECPA, 2000, p. 1). After 6 sample items, participants have a time limit of 20 minutes to complete the test. The raw score can vary from 0 to 40 points (one point per correct answer). According to the manual, the test has a satisfactory internal consistency of α = .89 and correlates at r = .67 with R85, the previous version of the test (ECPA, 2000, p. 26). In our study the time limit was set to 15 minutes.

Figure 3. Exemplar items from the R2000

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22 3.2.2 Self-Estimated Intelligence

SEI was assessed by a standardised procedure that has been previously employed in other studies (Furnham, 2001). A normal distribution of standardised IQ scores, extending from -3 to +3 standard deviations around the mean, along with short descriptions of each of the six score bands was used (Appendix E). The score ranges and their respective labels were the following: IQ scores from 40 to 70 were labelled as mental retardation (2.5 % of the population), IQ scores from 70 to 85 were descripted as low intelligence (13.5 % of the population), scores from 85 to 100 and from 100 to 115 were labelled as low average and high average intelligence (in total they encompassed 68 % of the population), scores from 115 to 130 were indicative of high intelligence (13.5 % of the population) and scores from 130 to 160 signified intellectual giftedness (2.5% of the population). Four separate images (see Figure 4 for an example) of the above distribution were employed: one for Gq, one for Gv, one for Gc and one for Gf ability along with a brief definition of each. Participants were asked to self-assess themselves by marking a point along a horizontal line underneath the bell curve, corresponding to an IQ score.

No time limit was imposed. To compute SEI scores, for each self-estimated ability we measured the distance (in centimeters) between the starting point of the bell curve and participants’ mark with a ruler. These distances were transformed into raw IQ-like scores according to the following equation: SEI score = 40 + (5.195 x distance in centimeters).⁸ The resulting SEI scores were then rounded to the nearest whole number.

Figure 4. Normal distribution of standardised IQ scores used to measure SEI (i.e., self- estimated Gq). Participants had to estimate their ability by marking a point along the horizontal line underneath the distribution.

8 The equation was derived as follows. One centimeter in the normal distribution curve corresponded to 5.195 IQ units. Moreover, the starting point of the curve was 40 and thus it was added as a constant in the equation.

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23 3.2.3 The Rorschach

Personality was measured by the Rorschach. What follows is a concise presentation of the standardised procedures for administrating, coding, and interpreting the Rorschach, under the comprehensive system. An exhaustive description can be found in Exner’s (2003) test manual.

A) Administration:

Regarding administration, it is vital that the examiner follows the standardised procedure as even slight deviations can have a dramatic influence on participants’ responses (Hersen & Greavesm, 1971). Prior to the actual administration, the examiner should ensure that the participant is rather comfortable with the task. To this end, the examiner could explain the procedure and answer to potential inquires without however providing details that could potentially influence participant’s responses (e.g., the examiner should not provide examples on how to respond). Following a standardised introduction by the examiner, the task unravels in two consecutive phases: the response and the inquiry phase. During both phases the examiner writes down, verbatim, everything the subject says. Commentary on the test, the cards, or the responses (including nonverbal behaviour) should be strictly avoided to ensure minimal influence on the respondent. For this purpose, side-by-side seating is recommended in order to diminish the effects of nonverbal behaviour.

Response Phase: In the response phase, the subject sees each inkblot card separately and responds to the question “what might this be?” (for an exemplar inkblot see Appendix F). The inkblots are administered in order, starting from the first inkblot and finishing with the tenth. The participant can give one or more responses per inkblot. Nevertheless, the RCS necessitates at least two and a maximum of 5 responses on the first card, one response per card, and a minimum of 14 responses across the entire set. In case the participant gives only one or more than 5 responses on the first card, the examiner either prompts him to give more or moves to the next inkblot, respectively. Further, if the participant cannot provide a response for a specific inkblot the examiner encourages him to do so. Finally, if the total responses are less than 14, a clear request for more responses is made and the test should be re-administered. If the participant demands elements on how to answer or seeks feedback for his response (e.g., ‘’do others see it as well? ‘’), the examiner should typically respond that he/she can reply however he/she wishes. The fact that there are no correct responses may sometimes be marked.

Inquiry phase: The completion of all inkblots is followed by the inquiry phase. The goal is to gather supplementary information on the responses given at the response phase, which is necessary for appropriate coding. Thus, the examiner re-presents the stimuli one at a time,

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24 in the order that they were administered, and repeats verbatim each response. The subject should clarify the location of what he/she saw and what made it look like that. Often, the examiner is required to interfere with nondirective questions in order to acquire all the information needed (e.g., ‘’what about it made it look like a [response] ?’’)

B) Coding:

Following the administration of the test, various variables need to be coded. The variables of the RCS can be classified into 4 types: (a) the total number of responses (R), (b) the ‘’primary’’ variables that are codes on a number of categories, (c) the ‘’secondary’’

variables that are derived from different combinations of ‘’primary’’ variables, and (d) 6 special indices.

Primary variables: The ‘primary’’ variables constitute the fundamental information of the RCS and are derived from the coding of the following categories: location, developmental quality, determinants, form quality, contents, popularity, organizational activity and special scores.

Location is merely the part of the inkblot on which the response was based. Participants can use the whole inkblot or specific parts of it, including the white space (Table 1).

Table 1

Symbols, definitions, and criterions for coding the location of responses based on the RCS

Symbol Definition Criterion

W Whole response The entire area of the blot is used

D Common detail reponse A frequently identified area of the blot is used Dd Unusual detail response An infrequently identified area of the blot is used

S White space response A white-space area of the card is used (always coded with another location symbol; WS, DS, DdS)

Note. Adapted from The Rorschach: A Comprehensive System, Volume 1: Basic Foundations and Principles of Interpretation (4th ed.), by J. E. Exner Jr., 2003, Hoboken, NJ: John Wiley &

Developmental quality (DQ) indicates the quality of processing that has been involved while forming the answer. For example, a participant may relate separate objects with specific forms or report a single object without any form (Table 2).

Self-estimated cognitive ability, cognitive performance and the Rorschach

Master

Reference

Self-estimated cognitive ability, cognitive performance and the Rorschach

Self-estimated cognitive ability, cognitive performance and the Rorschach

Acknowledgements

TABLE OF CONTENTS

Summary

1. GENERAL INTRODUCTION

2. THEORETICAL INTRODUCTION

3. METHOD