The Construction of an Indigenous Emotional Stability Scale

THE CONSTRUCTION OF AN INDIGENOUS EMOTIONAL STABILITY SCALE

Elke Chrystal

DISSERTATION

submitted in fulfilment of the requirements for the degree of

MAGISTER ARTIUM

PSYCHOLOGY

in the

FACULTY OF HUMANITIES

of the

UNIVERSITY OF JOHANNESBURG

Supervisor: Prof. G.P. de Bruin Co-Supervisor: Dr. C. Hill

March 2012

ACKNOWLEDGEMENTS

I would like to whole-heartedly thank the following people, without whom this dissertation would not have been possible:

My husband, Brett, for being there for me every step of the way. Thank you for your continuous support, encouragement, and unwavering belief in me. Words are not enough to express my love and appreciation.

My supervisor, Professor Deon de Bruin, for offering me the opportunity to be part of this exciting project. Thank you for your confidence in my ability, and your guidance and support throughout the whole process.

My co-supervisor, Dr. Carin Hill, for her advice and support.

Dr. Karina de Bruin for her friendship and invaluable assistance along the way.

All collaborators of the SAPI project for their time, ideas and constructive input.

The students for their participation in this study.

UJ for the merit bursary.

The financial assistance of the National Research Foundation (NRF) towards this research is also acknowledged (SUR2009062300001496). The opinions expressed and conclusions arrived at are those of the author and should not be attributed to the National Research Foundation.

ABSTRACT

The present study aimed at the construction and validation of an indigenous Emotional Stability scale. Its development was based on the qualitatively derived Emotional Stability cluster of the SAPI1 (South African Personality Inventory), a project initiated in 2006 to develop a personality instrument, which is locally derived from indigenous conceptions of personality in all 11 official languages. The Emotional Stability cluster consists of six subclusters and 25 facets comprising person-descriptive terms, indicating positive and negative psychological adjustment. These person-descriptive terms were used to create a definition of the meaning of each facet for all languages ensuring coverage of the whole construct. Items were generated to represent these definitions. The final inventory consisted of a single list of 326 items, which was presented to a second year undergraduate psychology student sample, attending a course in personality psychology (N = 610). Participants also completed the Neuroticism scale of the Basic Traits Inventory (BTI, Taylor & De Bruin,

1 “The South African Personality Inventory (SAPI) project aims to develop an indigenous personality measure for all 11 official languages in South Africa. Participants are Byron Adams (University of Johannesburg and Tilburg University, the Netherlands), Deon de Bruin (University of Johannesburg), Karina de Bruin (University of Johannesburg), Carin Hill (University of Johannesburg), Leon Jackson (North-West University), Deon Meiring (University of Pretoria and University of Stellenbosch), Alewyn Nel (North-West University), Ian Rothmann (North-West University), Michael Temane (North-West University), Velichko Valchev (Tilburg University, the Netherlands), and Fons van de Vijver (North-West University, Tilburg University, the Netherlands, and University of Queensland, Australia).”

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2006) and the items of the Positive and Negative Affect Schedule (PANAS, Watson, Clark & Tellegen, 1988) to allow for external validation of the indigenous Emotional Stability scale.

Factor analyses indicated that the positive and negative facets of the Emotional Stability cluster defined separate factors, which led to the exclusion of the positive facets, resulting in the scale measuring only those personality characteristics typically attributed to Neuroticism. To denote the difference, the final scale was renamed “indigenous Neuroticism scale”.

Three comparison groups were formed to evaluate the psychometric properties of the indigenous Neuroticism scale across language groups, namely: Germanic (English and Afrikaans), Nguni (Zulu, Xhosa, Swati and Ndebele), and Sotho (Sepedi, Sesotho and Setswana). The results of the present study revealed a valid and reliable, multifaceted indigenous measure of Neuroticism. The Neuroticism factor consists of five facets, namely Despaired, Anxious, Dependent, Temperamental, and Impulsive.

Factor congruence of the indigenous Neuroticism factor across all language groups assessed was demonstrated, indicating that the dimension Neuroticism has the same psychological meaning across all groups. Tucker’s phi obtained for the factor Neuroticism for each language group was: Germanic (pxy = 1.00), Nguni (pxy = 1.00) and Sotho (pxy = .99).

The results for the five subscales indicated congruence coefficients at or above .90 for all five group facets for the Germanic and the Nguni group, and for three of the facets for the Sotho group. Only two facets of the Sotho Group, Temperamental and Impulsive, showed congruence coefficients of .83 and .87 respectively, indicating that these two constructs are understood somewhat differently in this group.

Good convergent validity of the indigenous Neuroticism scale with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and with the Negative Affect Scales of the PANAS (Watson et al., 1988) was established. Using the Pearson’s correlation coefficient, a strong positive correlation (r = .89) was found with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and a moderate positive correlation (r = .66) was found with the Negative Affect Scale of the PANAS (Watson et al., 1988).

Internal consistency for the indigenous Neuroticism scale and its subscales was determined using Cronbach’s alpha. The total scale showed good internal consistency with an alpha coefficient of α = .96. Subscales that reflect the group factors also demonstrated good internal consistency with the following alpha coefficients: Despaired (α = .91); Anxious (α = .90); Dependent (α = .86); Temperamental (α = .87); and Impulsive (α = .87). The reliability coefficients for both the total indigenous Neuroticism scale and its five subscales were above .80 for all three language groups (Germanic, Nguni and Sotho) indicating good internal consistency.

The present study is possibly the first to assess Neuroticism in South Africa using indigenous conceptions of personality from all 11 official languages. The theoretical construct Neuroticism was found in all 11 languages, and the results of the present study revealed a valid and reliable indigenous scale of Neuroticism across three South African language groups. Its strong positive correlation with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006), whose items were developed specifically for the South African context, is encouraging and highlights the importance of locally developed instruments. The fact that the other eight clusters of the SAPI project (Extraversion, Soft-heartedness, Conscientiousness, Intellect, Openness, Integrity, Relationship Harmony and Facilitating) were developed on the same basis as Neuroticism bodes well for the possibility of developing an indigenous model of personality and a personality instrument to measure it.

TABLE OF CONTENTS

Page Acknowledgements…………………………………..……………………………………….ii Abstract………………………………………………………………………………...... iii Table of contents……………………………………………………………………………..vi List of tables …………………………………………………………………………………ix List of figures…………………………………………………………………………...... x Appendices…………………………………………………………………………………... x

CHAPTER 1: INTRODUCTION 1.1 Introduction………………………………………………………………………………. 1 1.2 Problem statement……………………………………………………………………….. 1 1.3 Aim and objectives ……………………………………………………………………… 5 1.4 Chapter overview………………………………………………………………………… 5

CHAPTER 2: TRAIT MODELS OF PERSONALITY 2.1 Introduction……………………………………………………………………………… 7 2.2 Eysenck’s Big Three (or PEN) model…………………………………………………… 8 2.2.1 The development of Eysenck’s Big Three (or PEN) model...………….……...... 8 2.2.2 Support for the Big Three (or PEN) model………………………………………. 11 2.3 The Big Five/Five Factor model………………………………………………………... 15 2.3.1 The development of the Big Five…………………………………………………. 15 2.3.2 The development of the Five Factor Model (FFM)………………………………. 18 2.3.3 Support for the Five Factor Model………………………………………………... 19 2.4 Evaluation of trait models of personality………………………………………………. 21 2.5 Neuroticism……………………………………………………………………………... 24 2.5.1 Definition and indicators across different models………………………………... 24 2.5.2 Behavioural correlates……………………………………………………………. 28

CHAPTER 3: PERSONALITY AND CULTURE 3.1 Introduction…………………………………………………………………………….. 30 3.2 Various approaches to the study of personality and culture……………………………. 30 3.2.1 The etic perspective ……………………………………………………………… 31

3.2.1.1 Methodological issues………………………………………………………. 32 3.2.2 The emic perspective………………………………………………………………34 3.2.3 Integration of emic and etic perspectives…………………………………………. 37 3.3 Recent studies of personality assessment in South Africa……………………………… 39 3.4 Present study…………………………………………………………………………… 41 3.4.1 Definition of the construct Emotional Stability………………………………….. 41 3.4.1.1 Balance……………………………………………………………………… 41 3.4.1.2 Courage………………………………………………………………………41 3.4.1.3 Emotional Control…………………………………………………………... 42 3.4.1.4 Emotional Sensitivity……………………………………………………….. 42 3.4.1.5 Anxiety……………………………………………………………………… 42 3.4.1.6 Ego Strength………………………………………………………………… 43 3.4.2. Postulates………………………………………………………………………… 44 3.4.2.1 Postulate 1…………………………………………………………………... 44 3.4.2.2 Postulate 2…………………………………………………………………... 44 3.4.2.3 Postulate 3…………………………………………………………………....44 3.4.2.4 Postulate 4……………………………………………………………………45

CHAPTER 4: METHOD 4.1 Introduction……………………………………………………………………………... 46 4.2 Research approach……………………………………………………………………… 46 4.2.1 Analysis process…………………………………………………………………... 46 4.2.2 Item writing………………………………………………………………………. 47 4.3 Procedure……………………………………………………………………………….. 47 4.3.1 Participants………………………………………………………………………... 47 4.3.2 Data collection……………………………………………………………………. 49 4.3.3 Instruments……………………………………………………………………….. 50 4.4. Statistical analyses……………………………………………………………………... 52 4.4.1 Data preparation…………………………………………………………………... 52 4.4.2 Factor Analysis…………………………………………………………………… 52

CHAPTER 5: RESULTS 5.1 Introduction…………………………………………………………………………….. 54 5.2 Data screening………………………………………………………………………….. 54

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5.3 Preliminary data analyses………………………………………………………………. 54 5.4 Reliability………………………………………………………………………………. 67 5.5 Factor analysis………………………………………………………………………….. 69 5.5.1 Neuroticism at facet level………………………………………………………… 72 5.5.2 Neuroticism at item level…………………………………………………………. 75 5.6 Internal consistency…………………………………………………………………….. 88 5.6.1 Total group………………………………………………………………………... 88 5.6.2 Language groups…………………………………………………………………. 88 5.7 Coefficient of congruence……………………………………………………………… 88 5.7.1 Group factors across language groups…………………………………………… 89 5.7.2 Higher order factor Neuroticism across language groups……………...………… 95 5.8 Convergent validity…………………………………………………………………… 101

CHAPTER 6: DISCUSSION 6.1 Introduction……………………………………………………………………………. 102 6.2 Neuroticism in South Africa…………………………………………………………... 102 6.2.1 Hierarchical structure of Neuroticism…………………………………………… 103 6.2.2 Neuroticism across language groups……………………………………………. 106 6.2.3 Convergent validity……………………………………………………………… 108 6.2.4 Reliability across language groups……………………………………………… 110 6.2.5 Facets not included in the Neuroticism factor…………………………………... 111 6.2.6 Split of positive and negative facets…………………………………………….. 112 6.2.7 Postulates………………………………………………………………………... 114 6.2.8 Summary………………………………………………………………………… 115 6.3 Limitations and suggestions for further research……………………………………… 116 6.4 Conclusion…………………………………………………………………………….. 117

REFERENCES…………………………………………………………………………... 118

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TABLES

Table 2.1 Comparison of the Neuroticism facet structures…………………………..…27

Table 4.1 Breakdown of the highest educational qualifications of the sample…………………………………………………………….…...48

Table 4.2 Demographic composition of the sample according to language…………………………………………………………………...48

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster…………………………………………………………….....55

Table 5.2 Alpha coefficients of the 33 facets…………………………………………...67

Table 5.3 Hierarchical Schmid-Leiman Solution for the 33 facets……………………..70

Table 5.4 Pattern matrix for the 21 Neuroticism facets………………………………...73

Table 5.5 Hierarchical Schmid-Leiman Solution for the 21 Neuroticism facets………………………………………………………..74

Table 5.6 Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items……………………………………………………….76

Table 5.7 Hierarchical Schmid-Leiman Solution for the Neuroticism scale………………………………………………………….....83

Table 5.8 Neuroticism scale…………………………………………………………….86

Table 5.9 Target rotated factor pattern matrix of the Germanic group……………...... 89

Table 5.10 Target rotated factor pattern matrix of the Nguni group……………………. 91

Table 5.11 Target rotated factor pattern matrix of the Sotho group ...…………………..93

Table 5.12 Schmid-Leiman solution for the Germanic language group………………...96

Table 5.13 Schmid-Leiman solution for the Nguni language group………………….…98

Table 5.14 Schmid-Leiman solution for the Sotho language group ……………………99

FIGURES

Figure 5.1 Scree plot and parallel analysis of the 33 facets ……………………….…..70

Figure 5.2 Scree plot and parallel analysis of the 21 Neuroticism facets……………………………………………………….….72

Figure 5.3 Scree plot and parallel analysis of the 169 Neuroticism Items………………………………………………………………………...76

Figure 5.4 Scree plot and parallel analysis of the 47 items of the Neuroticism scale ……………………………………………………….….82

Figure 6.1 Hierarchical structure of Neuroticism ………………………………….….103

APPENDICES

Appendix A Emotional Stability Questionnaire………………………………………...139

Appendix B Component matrices and scree plots for seven of the 25 facets indicating multidimensionality………………………………….152

Appendix C Factor pattern matrices of the Neuroticism items per language group …………………………………………………...... …....161

CHAPTER 1 INTRODUCTION

1.1 Introduction

Psychological assessment is in a crisis in South Africa. Many local and imported inventories currently in use have not been tested for bias and have not been cross-culturally validated (Foxcroft, Roodt & Abrahams, 2005). Others show various psychometric problems, such as low reliability and inappropriateness for previously disadvantaged groups (e.g. Meiring, Van de Vijver, Rothmann & Barrick, 2005). One important area of psychological assessment, and the focus of the present study, is personality assessment, which is relevant in educational, organisational and clinical settings. In light of the above challenges, Foxcroft, Paterson, le Roux and Herbst (2004) conducted a survey on test use in South Africa to assess test use patterns and the needs of psychological assessment practitioners. The results indicated the use of many unsuitable instruments due to a lack of appropriate alternatives. For example, practitioners identified the 16 Personality Factor Inventory (16PF, Form SA 92), adapted from Cattell’s 16 Personality Factor Inventory (16PF, Cattell, Eber & Tatsuoka, 1970), as the test most frequently used, although research suggests that it may be culturally biased (Abrahams & Mauer, 1999a). In a multicultural and multilingual country such as South Africa, this practice may have resulted in the inadequate selection of job applicants in organisational settings and improper assessments of clients in the education and healthcare sector, which is clearly an untenable situation.

1.2 Problem statement

For many years the study of personality and culture has been dominated by the cross-cultural trait approach to personality. One of its major goals is the search for universally generalisable traits. Traits can be defined as relatively stable individual difference in thoughts, feelings and behaviour (Church, 2000). In cross-cultural studies culture is treated as quasi-independent variable distinct from personality. Personality inventories based on the trait approach, such as the NEO Personality Inventory (NEO-PI-R, Costa & McCrae, 1992a), have been translated and adapted into different languages across the world. This process is known as the etic perspective, which emphasises commonalities across cultures. This perspective has been criticised for not capturing culture specific personality dimensions (Church, 2001).

In response, the etic perspective has been complemented by the emic perspective, which comprises the cultural and indigenous approaches to psychology. Researchers supporting the emic perspective are concerned with discovering those traits that describe and interpret culture specific behaviour, e.g. the concept of the selfless-self in Taoism, Buddhism and Hinduism (Ho et al., 2001). In cultural and indigenous studies culture and personality are seen as mutually constituted and deeply intertwined (Heine, 2001; Markus & Kitayama, 1991).

An important concept that is especially relevant to the South African context is the individualism-collectivism construct. According to Triandis (1996), individualistic cultures differ from collectivistic culture on four attributes: (a) the meaning of the self (independent versus interdependent); (b) the structure of goals (personal goals versus in-group goals); (c) behaviour (attitudes versus norms), and (d) the focus on the need of in-groups or social exchanges (advantages and costs of relationships versus needs of members of the in-group). South Africa’s population comprises both groups; people of European descent (individualistic worldview) and people of African and Asian descent (collectivist worldview). In relation to personality, it is suggested that individualistic cultures are more “traited” than collectivistic cultures (Church, 2009). In other words, traits as understood within the etic perspective may be of lesser importance for South Africans of African and Asian descent, when describing or predicting behaviour (Markus & Kitayama, 1998).

South Africa is a multilingual, multicultural country, whose individuals differ in regard to their socio-economic status and educational background. According to Census 2001 (Statistics South Africa, 2001) South Africa acknowledges 11 official languages. Of the 44.8 million South Africans, 77.9% speak an indigenous African language as their home language, 13.3% speak Afrikaans as their home language, and only 8.2% of the population speak English as their home language. With respect to cultural diversity the following groups are recognised: Germanic (English, Afrikaans), Nguni (Zulu, Xhosa, Swati and Ndebele) and Sotho (Sesotho, Sepedi and Setswana).

The majority of personality inventories currently in use in South Africa are based on the etic approach and were developed in the Western world. These inventories have been imported and often directly applied to the South African population. Some of these have been adapted or

translated, although most inventories are administered in either English or Afrikaans, potentially disadvantaging those who speak an indigenous language as their home language. For example, research conducted on the 16PF (SA 92) demonstrated that significant score differences between White and Black respondents could be attributed to differences in language ability (Abrahams & Mauer, 1999b). In addition, a replication of Abrahams and Mauer's (1999b) study indicated that the language used in the 16PF (SA 92) caused difficulties even for those participants whose home language was English (Wallis & Birt, 2003).

The first study to comprehensively assess South Africa’s cultural diversity using the 15FQ+, an adapted version of the 15FQ designed to measure Cattell’s 16 personality factors (Tyler, 2003) detected construct bias and poor reliability in various indigenous African groups (Meiring et al., 2005). With the enormous diversity in culture and language indicated by the Census 2001 (Statistics, South Africa, 2001), it would appear that the use of etic inventories alone would be inadequate to assess the South African population.

In multicultural settings such as South Africa, the proper use of personality inventories depends in part on the psychometric equivalence of the inventories across cultures. In other words, before comparisons of the personality characteristics between cultural groups can be made, it needs to be established whether the personality instruments measure the same constructs. This is called construct equivalence (Van de Vijver & Leung, 1997). Local research has demonstrated problems with construct equivalence across race groups (Abrahams & Mauer, 1999a), and language groups (Van Eeden & Mantsha, 2007). Additional problems relate to the low internal consistency of items. For example, even an extensive adaptation of the 15FQ+ (Tyler, 2003), an inventory, which had been adapted from the 16PF (Cattell et al., 1970), demonstrated unacceptably low reliability coefficients, particularly for the Black language groups (Meiring, Van de Vijver & Rothmann, 2006).

According to the Employment Equity Act 55 of 1998 (Section 8) (Government Gazette, 1998), psychological testing is prohibited “unless the test or assessment being used (a) has been scientifically shown to be valid and reliable; (b) can be applied fairly to all employees; and (c) is not biased against any employee or group” (p.16). The promulgation of this act has major implications for psychologists as the onus is on them to prove that their instruments can be fairly applied in a multicultural society. No personality inventory currently in use fulfils these criteria (Meiring et al., 2005), and the above examples indicate that the current approach to the

adaptation of imported instruments is clearly inadequate. The development of inventories that are psychometrically sound and applicable to all cultural groups in South Africa is therefore urgently needed.

Against this background researchers from the University of Johannesburg, North-West University, Stellenbosch University, and Tilburg University (Netherlands) initiated the development of an indigenous model of personality complemented by an indigenous personality inventory (SAPI) in 2006. Their intention is to gain a better theoretical understanding of personality as it manifests in the multicultural context of South Africa rather than relying on imported theories, models and inventories. Their chosen approach to the development of this inventory was to combine etic with emic elements to enable a deeper understanding of the universal and local aspects of personality in South Africa (see Nel (2008) for on in-depth overview).

The first stage of this project encompassed collecting data from 120 persons from each of the 11 official languages by means of interviews. Over 50,000 responses were obtained and transformed into personality descriptive items. A content analysis of these items revealed a 9- cluster model of personality traits (Extraversion, Soft-heartedness, Conscientiousness, Emotional Stability, Intellect, Openness, Integrity, Relationship Harmony and Facilitating) as encoded in lay people’s conceptions of personality (Nel, 2008). The project has now entered its second phase, which is the development of scales to measure these personality traits.

The present study focusses on the dimension Emotional Stability versus Neuroticism. Both names are used interchangeably to emphasize this trait’s positive and negative qualities respectively (De Raad, 2000). Neuroticism is one of the most pervasive traits in the literature, and according to De Raad and Perugini (2002), it has been found to be relevant in the educational field, the organisational and social context and in clinical settings.

The Emotional Stability cluster of the SAPI project comprises six subclusters (Balance, Courage, Emotional Control, Emotional Sensitivity, Anxiety and Ego Strength). Nel (2008) described an emotional stable person as someone who is

emotionally either well or unwell, possesses an inner confidence and respect, is sensitive towards outward events or people, has the ability to control and manage

own emotions or actions, and is emotionally sound, or capable of handling life issues or stimuli. (p. 125)

1.3 Aim and objectives

As part of the second phase of the SAPI project, the present study aims to contribute to a better understanding of Emotional Stability in the multicultural South African context. The principal objective is to develop and validate a scale of Emotional Stability with the intention to contribute to the development of the new SAPI, and ultimately to an indigenous theory of personality.

The specific objectives are:

To use the existing SAPI data base to develop items that reflect the indigenous conceptions of Emotional Stability and how it manifests in peoples’ behaviour To evaluate the items by analysing the responses of a representative sample of the different cultural/linguistic groups in South Africa: o To examine the psychological structure underlying the items by means of factor analysis o To investigate congruence between the factor structures of various language groups o To identify the items that best contribute to measurement precision To investigate concurrent validity of the newly developed indigenous Emotional Stability scale with previously validated existing scales.

1.4 Chapter overview

Chapter 1 presents the purpose and rationale for the present study. The aim and objectives are given.

Chapter 2 introduces the concept of trait models and describes two of the currently most dominant trait models relevant to the present study, namely Eysencks’ Big Three and the Big Five or Five Factor Model. Support for both models is presented followed by an evaluation of

trait models. The trait Emotional Stability/Neuroticism, the focus of the present study, is defined and its effect on behaviour is discussed.

Chapter 3 highlights the importance of culture on personality. Two theoretical perspectives used in research on personality, the etic and emic approaches, are described, and the methodological issues necessary for the development of valid and reliable cross-cultural personality inventories are discussed. A combined etic and emic approach is presented followed by two examples, the Chinese Personality Assessment Inventory (CPAI, Cheung et al., 1996) and the SAPI. Recent studies of personality assessment in South Africa are discussed and the present study including postulates is described.

Chapter 4 describes the process for the development of the Emotional Stability scale, followed by the procedure section, which states the participants, the data collection method, and the instruments used in the data analyses. Finally, the statistical analyses that were performed are presented.

Chapter 5 presents the results of the exploratory factor analysis of the Emotional Stability cluster. Subsequent to the data screening and the preliminary data analyses, initial reliability estimates for all facets are reported. The results of the first and second order factor analyses both at facet and item level are stated and the newly developed indigenous Neuroticism scale is presented. The reliability of the total scale and its subscales is reported followed by the congruence analyses for all comparison groups. Finally, convergent validity with established instruments is stated.

Chapter 6 discusses the major findings presented in the previous chapter. The hierarchical structure of the indigenous Neuroticism scale is presented and compared with the personality models reviewed in Chapter 2. Its psychometric properties are discussed in relation to previous research undertaken in South Africa. Convergent and divergent findings are highlighted and possible reasons for these are offered. The results are related to the relevant postulates, and the performance of the indigenous Neuroticism scale is evaluated. The chapter concludes with the limitations of the study and recommendations for future research.

CHAPTER 2 TRAIT MODELS OF PERSONALITY

2.1 Introduction

This chapter introduces the concept of trait models and describes two of the currently most dominant trait models relevant to the present study, namely Eysencks’ Big Three (or PEN) model and the Big Five or Five Factor Model. Support for both models is presented followed by an evaluation of trait models. The trait Emotional Stability/Neuroticism, the focus of the present study, is defined and its effect on behaviour is discussed.

There are many ways in which personality can be conceptualised. A number of theories such as psychoanalysis, humanistic, and behaviour and learning theories offer much insight into human motives and behaviour. However, these approaches merely “provide a source of hypotheses and content for personality measurement. They do not, however, constitute empirical evidence for or against any particular theory or approach of personality” (Bouchard & Loehlin, 2001, p. 244). In comparison, trait psychology, which has as its aim the comprehensive description of personality, uses an empirical approach to testing its hypotheses, which has resulted in an increased interest in the trait approach. Trait theorists are primarily concerned with the measurement of personality traits, which can be defined as relatively stable, individual differences in thoughts, feelings and behaviour (Church, 2000). These traits are often hierarchically organised, with narrow traits at the bottom and more general broad traits at the top of the hierarchy.

The present study focuses on the broad trait Neuroticism versus Emotional Stability. Both names are used interchangeably, with Emotional Stability being used to emphasize its positive qualities (e.g. in organisational contexts) and Neuroticism being used where neurotic behaviour is considered a problem (e.g. in clinical contexts) (De Raad, 2000). Neuroticism was first measured scientifically in Woodsworth’s (1917) Personal Data Sheet to assess the ability of soldiers to cope with military stress (De Raad & Perugini, 2002). Since then, an impressive amount of research on the trait has been accumulated, and Neuroticism has been found to be relevant in the educational field (e.g. Laidra, Pullmann, & Allik, 2007), the organisational (e.g. Judge & Bono, 2001; Judge, Heller, & Mount, 2002) and social (e.g. Kurdek, 1997) context, and in clinical settings (e.g. Khan, Jacobson, Gardner, Prescott, & Kendler, 2005; Weinstock

& Whisman, 2006). Neuroticism has been shown to be heritable, stable over time, across instruments and observers and replicable across many languages and cultures. These findings will be discussed in more detail later on in the current chapter and in Chapter 3. Neuroticism, which is sometimes also referred to as anxiety (Cattell & Kline, 1977), or Negative Affectivity (Watson & Clark, 1984) has been observed in many trait models of personality and is found in the two currently most prominent models: the Big Three (or PEN) model (Eysenck & Eysenck, 1985), and the Five-Factor Model (FFM, Costa & McCrae, 1992a), which is closely aligned and sometimes seen as synonymous with the Big Five model (Goldberg, 1990). Each of these models will be described in the paragraphs that follow.

2.2 Eysenck’s Big Three (or PEN) model

2.2.1 The development of Eysenck’s Big Three (or PEN) model

In search of a model of individual differences in personality, Eysenck’s development of the Big Three (or PEN) hierarchical trait model was influenced by the thinking of the ancient Greeks, Jung and Wundt (Eysenck, 1978). In contrast with many other personality psychologists, Eysenck was not only interested in describing personality but also in explaining the underlying mechanisms and processes accounting for systematic individual differences between people (O'Connor, 2008). His model therefore consists of a descriptive and causal aspect.

One of the first descriptive and causal theories of personality has been credited to Hippocrates who developed the theory of the four humours or temperaments. His theory originated from an amalgamation of Greek traditional medicine and the philosophical and cosmological worldview of that time, with fire, earth, air and water being the four basic elements of the universe (Stelmack & Stalikas, 1991). It was thought that humours developed from indigestible or surplus material in the body, and that excesses or deficiencies in the humours caused illness. The four primary humours (temperaments) were described as phlegm (phlegmatic), black bile (melancholic), yellow bile (choleric) and blood (sanguine), and they were understood to vary according to the four seasons of the year, the four stages of life and within each individual (Matthews, Deary, & Whitman, 2003; Stelmack & Stalikas, 1991). For example, yellow jaundice would be indicative of an excess of yellow bile, which was a manifestation of fire found predominantly in youth and during summertime; whereas phlegm

was a manifestation of water predominantly found in old age and during winter causing respiratory diseases (Stelmack & Stalikas, 1991).

Hippocrates’ theory was extended and popularised by the physician Galen in the second century AD, who used the four humoral terms to explain individual differences in character linking for example black bile (melancholic) to the symptoms of depression and anxiety (Matthews et al., 2003; Stelmack & Stalikas, 1991). The four humoral terms or temperaments used in Hippocrates’s system, the sanguine, the melancholic, the choleric and the phlegmatic, are still used as descriptive metaphors today (Matthews et al., 2003).

However, in the eighteenth and nineteenth centuries the philosopher Kant and the psychologist Wundt moved away from the explanatory, causal constructs of Hippocrates toward more descriptive, psychological constructs (Stelmack & Stalikas, 1991; Matthews et al., 2003). Whereas Kant divided the four temperaments into four categories that were understood as being determined at birth and to be independent of each other, Wundt challenged the use of the four categories and instead suggested a two-dimensional system with orthogonal axes running from emotional to unemotional, and from changeable to unchangeable (see Stelmack and Stalikas, 1991 for an in-depth overview). A person could occupy any position within the space defined by these axes, which allowed for more flexibility in personality description (Eysenck, 1978).

Today, these two axes or dimensions would be described as Extroversion versus Introversion, terms introduced by Jung (1921), and Emotional Stability versus Neuroticism (Eysenck, 1978). Hippocrates’ sanguine type would be characterised as an emotionally stable extravert according to Wundt, combining traits such as even-tempered and reliable with sociable and outgoing; the choleric type would be characterised as a neurotic/emotionally unstable extravert combining traits such aggressive, and impulsive with carefree and responsive. The phlegmatic type would be described as an emotionally stable introvert linking traits such as peaceful and controlled with quiet and anxious, and the melancholic type would be described as a neurotic/emotionally unstable introvert linking traits such as touchy and restless with reserved and unsociable. Eysenck (1978) used these ideas as a starting point to develop the Big Three (or PEN) model.

The descriptive or taxonomic aspect of the Big Three model is based on factor analysis, and describes personality structure as organised along four hierarchically ordered levels of behaviour (Eysenck & Eysenck, 1985). At the bottom of the hierarchy, the specific response level, one finds single observable behavioural acts. For instance, an individual smiles or tells a joke. The next level is called the habitual response level. A habitual response is the repetition of a specific response across a number of situations. For instance, an individual entertains strangers or smiles at people. The third level is called the trait level. Traits are a collection of significantly inter-correlated different habitual responses. For instance, individuals may display the trait sociability when they enjoy going to parties, like talking to people, and prefer spending time with others rather than being alone. At the highest level of the hierarchy, which is also called the super-factor level; Eysenck identified three broad personality types, or dimensions of personality, namely Extroversion-Introversion (E), Neuroticism-Emotional Stability (N), and Psychoticism (P). The third dimension of Psychoticism was added later to the model (Eysenck, 1992b). According to Eysenck and Eysenck (1985) a personality type is defined by intercorrelated traits, which create a general pattern of behaviour and exert a major influence on a person’s response style. For instance, if a person is described as an extravert type, he or she is likely to display such traits as being sociable, assertive, carefree and exuberant (Carducci, 2009; Eysenck & Eysenck, 1985)

Eysenck (1990) emphasised two important principles of personality research, namely aggregation and the state-trait distinction. Aggregation refers to measures showing increased reliability if they are comprised of many items. For instance, Neuroticism (N) consists of different behaviours, habits and facets, and if all these are taken into account the trait can be measured with good reliability. The state-trait distinction is reflected in the hierarchical structure of the model. States, which are transient and vary widely according to the situation, are found at the lower two levels of the hierarchy. At the top level, the types P, E and N and their traits are seen as stable across time and situation. Whereas states reflect a person’s emotions, behaviours and thoughts over a brief period of time, traits reflect stable patterns of emotions, behaviours and thoughts over long periods of time.

With regard to the causal aspect of his theory, Eysenck (1992a) claimed that the validity of a dimension is dependent on the nomological network or theoretical framework, within which it is embedded (cf. Cronbach & Meehl, 1955). In addition to the specification of psychometric properties, this nomological network includes the influence of people’s genes as well as

environmental factors (Eysenck, 1990). Eysenck argued very strongly that his Big Three traits have a biological basis (for a comprehensive overview see Eysenck & Eysenck, 1985). A distinguishing feature of Eysenck’s work is that he strove to not only psychometrically demonstrate the importance of the traits he studied, but to also experimentally demonstrate the causal effect of the traits.

2.2.2 Support for the Big Three (or PEN) model

Eysenck (2001) provided a number of reasons to support his claim for biological causes of the three super traits or types. First, the three types P, E and N have been found in nearly all investigations into personality, regardless of the instrument or the analytical method used (Eysenck & Eysenck, 1985). Eysenck and Eysenck (1985) reviewed a large number of studies and showed that the three super traits, P, E and N emerged consistently using a variety of instruments such as the Minnesota Multiphasic Inventory (MMPI), the Sixteen Personality Factors Questionnaire (16PF), and the California Psychological Inventory (CPI). Based on these results they argued for a biological foundation of the three types, as it would be unlikely that the positioning of a person on these dimensions could be ascribed to environmental factors alone.

Secondly, Eysenck and Eysenck (1985) asserted that the three types P, E and N are found across many different cultures. Research into the three types across different languages and cultures has demonstrated cross-cultural universality (Barrett, Petrides, Eysenck, & Eysenck, 1998). This finding will be discussed in more detail in section 3.1.1.

Thirdly, P, E and N remain stable in individuals over time (Eysenck & Eysenck, 1985). Longitudinal stability of the three Eysenck’s factors across age has been demonstrated by Bouchard and Loehlin (2001). They summarised the results of four large-sample twin studies in three countries measuring Extraversion and Neuroticism. The results indicated that Extraversion and Neuroticism appear to be stable across the adult life span, but are somewhat higher for late adolescents/young adults. Psychoticism, which was only examined in one of those studies, did not vary significantly across age groups.

Finally, Eysenck (1990) strongly argued that traits have a genetic basis. He reported that genetic factors determine at least half the phenotypic variance of the major dimensions of

personality with little evidence for between-family environmental variance. A plethora of twin studies into the heritability of personality traits has been conducted over the last decades, which shows that the data for broad traits have fairly consistently suggested heritabilities in the .40 to .60 range and little or no effect of shared family environment (Bouchard & Loehlin, 2001). In contrast, adoption and family studies of personality have usually yielded lower heritability estimates. For example, Martin et al. (2000) conducted a very large family study (20,415 unique sibling pairs) utilising the Eysenck Personality Questionnaire (EPQ) which displayed correlations of .12 for P, .16 for E, and .17 for N. These salient differences between the correlations observed for twins and siblings suggest a biological basis for personality.

Recently, Johnson, Vernon, and Feiler (2008) reviewed the results of more than 50 years of research of twin and other kinship studies of personality utilising the Big Five, the Big Three and related personality traits. Overall, the results were found to be remarkably consistent, and confirmed the findings of numerous previous studies and reviews, namely: “a pronounced contribution of additive genetic and non-shared or unique environmental factors to individual differences in the Big Five and related traits, and a small to negligible influence of dominant genetic and shared environmental factors” (p.164). These findings support Eysenck's (1990) claim of a genetic basis for personality traits with little effect of between-family environmental variance.

Eysenck (2001) argued that genetic factors are unable to act directly on behaviour and suggested an intervening link in the form of physiological, biochemical and hormonal factors, and neurological structures. His main contribution to the theory of personality is the development of a nervous system-based theory of personality, specifically his theory of arousal (Eysenck, 1967). The key components in Eysenck’s system are the reticulo-cortical and reticulo-limbic circuits (Eysenck & Eysenck, 1985). The reticulo-cortical circuit controls the cortical arousal generated by incoming stimuli and relates specifically to the extraversion dimension. The reticulo-limbic circuit controls the response to emotional stimuli and relates specifically to the Neuroticism dimension. Only the Neuroticism dimension will be discussed below.

Neuroticism is based on activation thresholds in the sympathetic nervous system, or visceral brain (Eysenck, 1967). The visceral brain or limbic system at the base of the brain consists of the hippocampus, amygdala, cingulum, septum and hypothalamus. It coordinates the

activities of the autonomic systems and appears to be mainly concerned with emotion. Activity in the visceral brain produces autonomic arousal. According to Eysenck and Eysenck (1985) individual differences in Neuroticism depend on the activity in this part of the brain. The authors suggested that people who are high in Neuroticism produce activity in the visceral brain more easily than those low in Neuroticism. People high on the N-dimension experience negative effects in the form of physiological and emotional changes. Depending on the severity of the experience, these can range from physiological changes in heart rate, blood pressure, sweating, muscular tensions, cessation of digestion, and dilation of pupils to feelings of apprehension and nervousness or fear and anxiety. People scoring low on the N- dimension have a much higher activation threshold, and experience negative affect only when confronted by major stressors (Furnham, Eysenck, & Saklofske, 2008).

In a comprehensive review of the biological dimensions of personality (Eysenck, 1990) and the biosocial approach to personality (Eysenck, 2001), Eysenck showed meaningful and significant relationships between biology and behaviour in numerous studies related to electroencephalography (EEG), electrodermal responses, salivation, pupillometry and biochemical influences, such as hormones (testosterone) and enzymes (MAO). However, Eysenck (1990) admitted that apart from the arousal theory in relation to Extroversion, research into the physiological theory of Neuroticism has not consistently supported his theory.

Since then evidence from various psychophysiological techniques accumulated over the last decades has largely confirmed Eysenck’s vision of associating traits with neural processes (Boyle, Matthews, & Saklofske, 2008). Stelmack and Rammsayer (2008) recently presented an overview of psychophysiological and neurochemical research encompassing the last four decades focussing on the three major personality dimensions Psychoticism, Extroversion and Neuroticism. Only the findings on Neuroticism will be presented here.

Early EEG studies concerned mainly with stimulus intensity did not show significant effects for Neuroticism (N). The failure of Neuroticism studies to support Eysenck’s (1967) arousal hypothesis is often attributed to insufficient emotional stress during laboratory condition (Matthews, et al., 2003). However, more recent studies, using for example, different imagery (Stenberg, 1992) and arithmetic tasks posing an ego threat (Knyazev, Slobodskaya, & Wilson,

2002) show differences in the brain activity of high and low scoring individuals on N across various areas of the brain.

Biochemical correlates associated with Neuroticism are dopamine, serotonin and cortisol. Preliminary evidence suggests a functional relationship between the dopamine neurotransmitter system and N-related personality traits. Various PET (Positron Emission Tomography) and SPECT (Single Photon Emission Computer Tomography) studies showed a relationship between receptor density and individual detachment scores (Breier et al., 1998; Lee et al., 2005) and scores on the depression facet of the NEO-PI-R (Kestler, Malhotra, Finch, Adler, & Breier, 2000).

Serotonin has been implicated in N, because serotonin specific uptake inhibitors are used successfully to treat depression. In animals, research into the serotonin receptor subtype 5-

HT1A found that anxiety is more pronounced in mice lacking this receptor (Parks, Robinson, Sibille, Shenk, & Toth, 1998; Ramboz et al., 1998). This finding is supported by Tauscher et al.'s (2001) study, which found a negative correlation between the anxiety facet of the NEO-

PI-N scale and the 5-HT1A receptor binding potential in healthy volunteers.

Cortisol is related to the endocrine system, which is responsible for regulating various bodily functions. The hypothalamic-pituitary-adrenal (HPA) axis, a major part of the neuroendocrine system, controls reactions to stress and regulates mood. Dysregulation of HPA is indicated by an excess release of cortisol into the body and has been identified as an indicator of depression (Pariante & Miller, 2001). As high N is a strong predictor for depression, an association between HPA dysregulation and N has been suggested. However, currently this relationship remains unresolved, as studies indicate opposing results. On the one hand, a higher cortisol response has been found in individuals low on N (McCleery & Goodwin, 2001); on the other hand, studies indicate higher cortisol levels for individuals high on N (Portella, Harmer, Flint, Cowen & Goodwin, 2005; Zobel et al., 2004).

The above research indicates that Neuroticism can be conclusively linked to psychobiological and biochemical correlates. Although some of the research findings may still be inconsistent and require further clarification, they nevertheless endorse the idea of a biological basis for personality traits. One important implication of these results is that one should expect to find Neuroticism across cultures, including in South Africa.

2.3 The Big Five/Five Factor model

The most prominent model of personality traits of the last few decades has been the Big Five model or the Five Factor Model. Although these two models originate from separate lines of research (i.e. the Big Five model from the psycholexical approach and the Five Factor model from the questionnaire approach) the names are often used interchangeably (John & Srivastava, 1999).

2.3.1 The development of the Big Five

The Big Five is based on the psycholexical approach to personality, which posits that the most meaningful personality attributes tend to become encoded in the natural language (Goldberg, 1990). The analysis of these terms should then provide a comprehensive taxonomy of personality traits (John, Angleitner, & Ostendorf, 1988). The psycholexical approach is important because it forms the basis of the present study.

The English scientist Francis Galton (1884) identified 1,000 personality descriptors found in a dictionary (John et al., 1988). Subsequently, Baumgarten’s (1933) list of trait descriptive adjectives and nouns based on terms from dictionaries and publications of German characterologists influenced Allport and Odbert, whose work is seen as empirical foundation for most later trait taxonomic research (John et al., 1988).

Allport and Odbert (1936) examined Websters’s New International Dictionary (1925) to construct a list including all personality-relevant terms related to behaviour in the English language. Their final list consisted of 17,953 words listed in four columns classified as personal traits, temporary states, social evaluations and metaphorical or doubtful terms.

Cattell (1943) used Allport and Odbert's (1936) list as the starting point for the development of a model of personality structure. His primary goal was to discover the major dimensions of personality lexicalised in English. Cattell (1943) utilised Allport and Odbert’s personality trait terms in the first column (the personal traits), and added approximately 100 temporary- state terms. He further reduced the number of terms by grouping semantically similar terms as synonyms under a key word. Within each cluster Cattell then added an opposite for each term and by grouping these terms into antonym pairs he eliminated several clusters and

obtained about 4,500 terms classified into 160 mostly bipolar clusters. At this stage, Cattell had removed more than half of the terms listed by Allport and Odbert. As this set was still much too large for factor analytic techniques available in the 1940s (Cattell, 1943; Cattell, 1945a; Cattell, 1945b), Cattell used a clustering approach to condense the 4,500 trait terms to a more manageable set of 35 variables. He subjected this set of 35 variables to a number of factor analyses, and obtained 12 personality factors which he subsequently included in the 16PF (Cattell et al., 1970)2. Later studies, however, mostly failed to replicate the number and nature of Cattell’s factors (e.g. Tupes & Christal, 1961; reprinted in 1992; Howarth, 1976; Digman & Takemoto-Chock, 1981).

Cattell’s work motivated other researchers to investigate the dimensional structure of traits derived from natural language. Fiske (1949, as cited in John et al., 1988) reduced Cattell’s list of 35 trait variables to 22, and obtained five recurrent factors from self- and peer ratings, which would later become known as the Big Five.

To help clarify the personality trait domain, (Tupes & Christal, 1961; reprinted in 1992) used Cattell’s personality traits to isolate independent universal trait factors, which were not sensitive to rating conditions or situations and could be found in a variety of samples. Tupes and Christal (1961; reprinted in 1992) factored and rotated eight intercorrelation matrices. Five fairly strong rotated factors were found in all eight samples, which led the authors to conclude that differences in samples, raters, situations and lengths of acquaintanceship have a minimal effect on the underlying structure of personality. They labelled the five factors (I) Surgency (talkative, assertive, sociable, energetic, cheerful); (II) Agreeableness (good-natured, cooperative, adaptable, kind); (III) Dependability (orderly, responsible, conscientious and persevering); (IV) Emotional Stability (not neurotic, placid, poised, calm, emotionally stable), and (V) Culture (imaginative, socially polished, independent-minded). The fourth factor, Emotional Stability, is of particular relevance for the present study.

Tupes and Christal (1961; reprinted 1992) concluded that there “can be no doubt that the five factors found throughout all eight analyses are recurrent” (p.244). However, they cautioned, that although “reasons are given in support of their fundamental nature and probable invariance” (p. 250), “it is unlikely that the five factors identified are the only fundamental

2 The remaining four personality factors (labeled as Q1, Q2, Q3, and Q4) were derived from analyses of questionnaires and not from the lexical approach. 16

personality factors” (p. 247). The authors pointed out that their results are based on Cattell’s set of 35 factors, which “represent the distillate drawn by Cattell from the interrelationships among some 175 traits which in turn were selected as representative of the Allport-Odbert adjectives” (p.247). They therefore exclude other central concepts likely to be included in the Allport-Odbert list. On the other hand, researchers, such as Norman (1963) and Digman and Takemoto-Chock (1981) have replicated the five-factor structure using Cattell’s 35 variables providing evidence that this set of variables can be summarised by five broad factors.

Despite being able to replicate the five factor structure, Norman (1963; 1967) agreed with Tupes and Christal (1961; reprinted in 1992) on the possibility of additional personality dimensions. He embarked on the development of an exhaustive list of personality descriptive terms, which would be sufficiently precise and well-structured to be useful for scientific communication, assessment and personality theory (John et al., 1988). Norman (1967) returned to Allport and Odberts’ original list of 17,593 items and added terms from the unabridged 1961 Webster’s Third New International Dictionary that had not been included in the original list. Norman (1967) reduced this list to 2,800 terms by omitting evaluative, ambiguous, vague, and obscure terms, as well as terms referring to anatomical and physical dispositions. He presented this list to a sample of 100 undergraduate students who were requested to provide a definition or synonym for each term, rate its social desirability and rate themselves and three peers on each term. A large number of terms were excluded on the basis of level of difficulty, their jargon and extremity of self-rating. A total of 1,556 trait remained, which Norman (1967) later classified into 75 categories containing words with similar meaning. Examining the semantic relations among the terms and combining highly synonymous terms into sets resulted in a further reduction to 1,431 terms.

In an attempt to generalise the Big-Five structure beyond Cattell’s initial set of 35 variables Goldberg (1990) conducted three studies using Norman's (1967) list of 2,800 trait terms. In the first study Goldberg (1990) selected a subset of 1,710 trait terms, (which included the 1,431 terms described above) and requested 187 students to rate themselves on each of these terms. The responses were grouped according to Norman's (1967) 75 categories to obtain 75 scale scores for each student. Reliability estimates for each scale were fairly high, with 95% showing an alpha above .60. Factor rotation across 10 different methods indicated a stable five factor structure with slight differences when six or seven factors were extracted.

In the second study, Goldberg (1990) grouped 479 of the original 1,710 trait terms into 133 synonym clusters, which were treated as personality scales. Two groups of students were asked to provide self-descriptions and two groups of students were asked to provide peer- descriptions for each variable. The five factor structure emerged clearly in all four samples and none of the additional factors extracted were replicated across the four samples.

In the third study, Goldberg (1990) used the 479 trait terms of the second study and asked 192 students to rate themselves on each term. Internal consistency analyses were carried out for the original 133 synonym cluster and the least homogenous clusters were removed. This resulted in a set of 100 clusters based on 339 trait adjectives. Again, factor rotation indicated a clear five factor structure. When analysing this set of 100 clusters using two of the data sets from Study 2, the five factor structure emerged for both groups.

Goldberg, (1990) labelled these factors the Big Five and concluded that an “analysis of any reasonably large sample of English trait adjectives in either self- or peer descriptions will elicit a variant of the Big-Five factor structure, and therefore that virtually all such terms can be represented within this model” (p. 1223).

The development of the Big Five by Goldberg has created large momentum among researchers of the trait approach. Much lexical research has been generated subsequently, and the Big Five have been replicated in many languages and countries. These findings will be discussed in section 2.3.3.

2.3.2 The development of the Five Factor Model (FFM)

While evidence accumulated for a Big Five structure based on the psycholexical approach, researchers studying personality using questionnaires were searching for an integrative framework for the multitude of traits measured by questionnaires (John & Srivastava, 1999). Within the questionnaire approach, Wiggins (1968) had identified the “Big Two”: Extraversion and Neuroticism. In the early 1980’s Costa and McCrae developed the NEO Personality Inventory (NEO-PI, published in 1985) based on cluster analyses of the 16PF (Cattell et al., 1970). This inventory measures Neuroticism (N), Extraversion (E) and an additional factor named Openness (O), both at the level of broad factors and their specific facets. Later, McCrae and Costa (1985) realised that their NEO system related closely to the three factors of the Big Five, but did not include the dimensions Agreeableness (A) and

Conscientiousness (C). They decided to extend their model to include these dimensions, and they developed scales to measure them.

The initial NEO-PI (McCrae & Costa, 1985) did not contain facet scales for the newly added factors Agreeableness (A) and Conscientiousness (C). This limitation was rectified in 1992 by the publication of the Revised NEO Personality Inventory (NEO-PI-R, Costa & McCrae, 1992a), which contains six specific facets for each of the Big Five dimensions. At this point the lexical approach and traditional questionnaire approach converged (John & Srivastava, 1999).

2.3.3 Support for the Five Factor Model

Costa and McCrae (1992b) claimed that the Five-Factor Model (FFM) represents basic dimensions of personality, and they specified four criteria necessary to determine whether a personality dimension is basic or not. The first criterion refers to cross-observer validity and longitudinal stability. McCrae and Costa (1987) assessed the validity of the five factors between peer-ratings and self-reports using adjective rating scale factors and questionnaires. The results showed convergent and discriminant validity for all five factors across instruments and observers, supporting the cross-observer validity of the Five-Factor model. Longitudinal stability for the Five-Factor Model has been assessed in numerous studies with evidence accumulating that personality is stable throughout adulthood (Costa & McCrae, 1988). Recently, additional evidence in support of longitudinal trait stability (Roberts & DelVecchio, 2000; Terracciano, Costa, & McCrae, 2006) and cross-observer validity (McCrae et al., 2004) has been found. However, research indicates that although a person’s rank-order has been demonstrated to be stable, mean levels of traits fluctuate from adolescence to old age (Roberts, Walton, & Viechtbauer, 2006; Terracciano, McCrae, Brant, & Costa, 2005).

The second criterion refers to the pervasiveness of traits. For traits to be basic, they should be found in various personality systems and in the language of laypersons (Costa & McCrae, 1992b). John et al. (1988) reviewed the history of traits within the lexical approach and provided abundant evidence for the emergence of the Big Five. For example, Goldberg's (1990) analysis of various trait descriptions indicated a robust five factor structure across a variety of samples and methods. Lexical studies in countries such as the Netherlands (De Raad, Hendriks, & Hofstee, 1992), Hungary (Szirmák & De Raad, 1994), and Italy (Caprara

& Perugini, 1994) have provided additional evidence in support of the five factor structure. The five factor structure has also been replicated in non-European countries, such as the Philippines (Katigbak, Church, & Guanzon-Lapena, 2002) and Mexico (Ortiz et al., 2007).

The pervasiveness of traits in personality has been demonstrated with instruments developed based on clinical judgments, such as the California Q-Set (CQS, Block, 1961, as cited in McCrae, Costa, & Busch, 1986). McCrae et al. (1986) compared self- and interviewer ratings of the 100-item instrument with self-report and peer- and spouse ratings of the NEO-PI (McCrae & Costa, 1987) and found five factors resembling the Big Five (FFM), albeit with slight differences. Further support has emerged with instruments developed to measure constructs in various classical theories of personality not designed to measure the Big Five. The Meyers Briggs Type Indicator (MBTI, Myers & McCaulley, 1985), which is grounded in Jung’s analytical theory, was assessed with the NEO-PI (McCrae & Costa, 1987) and the CQS, (CQS, Block, 1961, as cited in McCrae et al., 1986) and again, evidence for five factors surfaced (McCrae & Costa, 1989).

The third criterion requires basic dimensions of personality to be universal (Costa & McCrae, 1992b). Cross-culturally, the five factors have been found in numerous cultures, countries and languages (e.g. McCrae, 2002). More recently, McCrae, Terracciano, and 78 members of the Personality Profiles of Cultures Project (2005) administered the Revised NEO-PI-R to a sample of 50 cultures and provided evidence that the five factors are replicable across all cultures assessed. However, the authors cautioned that the results for the African countries were less clear than those found in the European cultures, and suggested possible differences in personality structure or the inappropriate use of a Western questionnaire. These issues will be discussed in more detail in Chapter 3.

The fourth criterion holds that basic dimensions of personality should have a biological basis (Costa & McCrae, 1992b). Costa and McCrae (1992b) maintained that although the five factors have been found in different cultures, supporting the notion of a genetic influence, they do not have to be linked to physiology. They suggested that the “five factors may represent alternative ways in which people in a social environment can respond to their life experience” (Costa & McCrae, 1992b, p. 658).

However, a large number of studies have subsequently demonstrated evidence for the heritability of the five factors. Bouchard and Loehlin (2001) provided a summary of twin studies and found broad heritability across the Big Five factors in the range of .38 to .58. For a more recent, comprehensive overview of the heritability of traits, refer to Johnson, Vernon and Feiler (2008) in section 2.2.2.

2.4 Evaluation of trait models of personality

Unsurprisingly, trait models have not been without criticism. Objections stem from different areas; some question the trait approach in parts or in its entirety (e.g. Mischel, 1968; Block, 1995), others are supportive of the trait approach but propose some alternatives or modifications to the trait models (e.g. McAdams & Pals, 2006). These various criticisms will be discussed below.

One of the most well-known and influential critiques originates from Mischel (1968). His review of personality psychology resulted in a “paradigm crisis” and changed its agenda for many years (Mischel, 2004). Trait psychology is based on the assumption that an individual’s behaviour with regard to a trait is consistent across many different situations (Pervin, 1994). Mischel (1968) maintained that this assumption is untenable. He analysed a variety of studies examining diverse behaviours using different measuring instruments, and found low correlations between a person’s behaviour and rank order position on virtually any psychological dimension (Mischel, 1968; Mischel, 2004). He also demonstrated that the failure to predict behaviour could not be accounted for by deficiencies in measurement techniques or by inadequacies in raters, clinicians, or the particular trait-state personality construct (Mischel, 1968).

Mischel (1973) suggested that personality psychology was searching for consistency in the wrong places. He held that the situational variability seen by trait theorists as an error is in fact an important aspect of behaviour that needs to be understood in order to predict behaviour. Mischel (1968) demonstrated that behaviour can be better predicted by taking into account environmental variables (e.g. a change in life conditions), past behaviour, and different specific stimulus situations, and he suggested a more dynamic view of the person. “Rather than being exclusively intra-psychic”, this view “focuses on the relations between behaviour and the conditions in which the behaviour occurs, and on how an individuals’

behaviour in any one condition is functionally related to what he does on another occasion” (Mischel, 1968, p 298).

Many personality psychologists interpreted Mischel's (1968) review as a rejection of the existence of personality and the “power of the person”. Social psychologists interpreted it as proof of the “power of the situations” with little or no emphasis on individual differences in personality (Mischel, 2009). Mischel's (1968) book initiated the person-versus-situation debate, with social and personality psychologists arguing for many years about which side accounts for more variance and better prediction of behaviour (cf. Epstein, 1979; Eysenck & Eysenck, 1980).

Mischel's, (1968) claim regarding the inability of trait psychology to predict specific behaviour and his call for a more dynamic view of personality has been echoed by a number of other psychologists (Benet & Waller, 1995; McAdams, 1992; Pervin, 1994). Other personality theorists (McAdams & Pals, 2006) have argued that although trait psychology offers an adequate model of personality traits, personality psychology is lacking a comprehensive framework for understanding the whole person. Block (2010) questioned the usefulness of trait models to predict behaviour in children and adolescents. Proponents of the person-centred approach have claimed that personality types, such as resilients, and over- and undercontrollers better characterise the intra-individual organization of experience and behaviour than the trait-centred approach, which focuses on the inter-individual perspective (see Asendorpf, Caspi, & Hofstee, 2002 for a review).

Theoretical and psychometric criticism arises from a number of different researchers. Trait psychology, specifically the Big Five, has been criticised for being arbitrarily derived and therefore being atheoretical (Boyle, 2008; McAdams, 1992). Trait psychology uses factor analysis, which is a data reduction model, designed to simplify a large number of personality descriptors into a comprehensive, psychologically meaningful, yet parsimonious number of factors. A number of shortcomings have been suggested, such as: (a) the discrepancy between the variance explained by a factor compared with its psychological importance (Block, 1995); (b) subjective decision making, possibly leading to a pre-structuring of a set of variables (Block, 1995; McAdams, 1992); and (c) the lack of a nomological network in which the traits are embedded (Eysenck, 1992a).

Another concern for many critics is the fact that trait psychology has been derived from natural language terms based on the lexical hypothesis. Opponents of this approach held that the meaning of these terms is too vaguely defined, ambiguous and context-dependent to function as scientific terminology (John et al., 1988). Block (1995) asserted that single-word descriptors are insufficient to scientifically describe crucial features of personality and its dynamic functioning, and he doubted the ability of laypersons to perceive the full range of psychological characteristics.

Ashton and Lee (2005) published an article in defence of the lexical approach to the study of personality. They addressed many of the above criticisms referring to the theoretical and psychometric basis of the lexical approach and judged them to be invalid.

A more positive review of trait personality can be found in Buss (1989). Mischel (1968) claimed that traits only have an effect on behaviour when an experimental manipulation is weak or absent. However, Buss (1989) reviewed the effects of traits and manipulations on behaviour across a variety of experiments and concluded that contrary to Mischel's (1968) claim, traits impact behaviour even when experimental manipulations significantly influence behaviour. Subsequently, he concluded that traits are important, and after demonstrating that they carry as much variance as experimental manipulation, he suggested that “research that includes both traits and manipulations is closer to the real world, in which individuals who differ (traits) are exposed to environmental influences (manipulations)” (p1382). Buss (1989) further demonstrated that trait variance could be increased by aggregation across responses, situations and time and explained that the breadth of traits can aid in prediction: narrow traits are useful in predicting specific behaviour; broader traits are preferred when searching for a more comprehensive picture of personality.

Other proponents of trait psychology point to the importance of the consequential validity of personality traits (Ozer & Benet-Martinez, 2006). These authors reviewed numerous studies and found increasing evidence of the relevance of personality traits with respect to real-life outcomes in various fields, such as health, interpersonal relationships, work, criminality and community involvement. For example, conscientiousness has been found to predict job performance (Barrick & Mount, 1991), neuroticism predicts an increased risk of mortality from cardiovascular disease (Shipley, Weiss, Der, Taylor, & Deary, 2007), and extraversion

and agreeableness have been linked to volunteerism (Carlo, Okun, Knight, & de Guzman, 2005).

It is evident from the above discourse that trait models have passionate proponents and fervent critics. Their strength lies in the ability to reduce large amounts of personality descriptors to a small number of parsimonious factors, offering a relatively comprehensive framework to account for the co-variation of most personality traits (McCrae, 2009). By providing broad descriptions of individual differences, trait models enable the prediction of a wide range of behaviour in mostly uncontrolled situations. The traits of the three- and five- factor models described above have been found to be heritable, stable over time, across instruments and observers, and they can be recovered in many different languages and cultures, suggesting universality. Traits are therefore real and important for the understanding of personality, and they occupy a unique position in the field of psychology (Buss, 1989).

2.5 Neuroticism

This section defines and compares Neuroticism as conceptualised within the various models described above. Thereafter, an overview of the behavioural correlations with Neuroticism will be presented.

2.5.1 Definition and indicators across different models

Neuroticism has been recognised as one of the oldest and most pervasive personality trait in the study of psychology. It dates back to the ancient Greek physicians Hippocrates and Galen and was described as the melancholic disposition. Contemporary trait theory conceptualises the dimension Neuroticism along the continuum of Emotional Stability at the one end and Emotional Instability or Neuroticism at the other end. At its core Neuroticism is characterised by an enduring tendency to experience negative emotional states.

According to Eysenck (1978) people who are high on Neuroticism, experience strong, long- lasting emotion, which arise in painful fear-producing, conflict situations. Individuals exhibiting this trait can be described as anxious and full of worry. Persons with high standings on N are prone to hypochondria and depression and often lack in self-reliance (Jackson, Furnham, Forde, & Cotter, 2000). Eysenck developed a number of major personality measures during his career (Furnham et al., 2008), some of which are still used in

research and clinical settings today. One of these instruments is Eysenck’s Personality Profiler (EPP, Eysenck & Wilson, 1991), which measures traits at the three super-factor levels (P, E and N) and at the primary factor or facet level. The 420 item questionnaire consists of 21 primary scales with each super factor comprising seven primary scale facets.

For the dimension Neuroticism (N) the seven facets have been conceptualised as: Inferiority, Unhappiness, Anxiety, Dependence, Hypochondria, Guilt and Obsessiveness. High scorers of Inferiority are described as low in self-esteem, have a low opinion of themselves and believe themselves to be failures. High scorers of Unhappiness are described as characteristically pessimistic, gloomy and depressed, disappointed with their existence, and at odds with the world. High scorers of Anxiety are described as being easily upset by things that go wrong, and are inclined to worry unnecessarily about unpleasant things that may or may not happen. High scorers of Dependence are described as lacking in self-reliance, think of themselves as helpless pawns of fate, are pushed around by other people and events, and show a high degree of what has been called “authoritarian submission” – the unquestioning obedience to institutional power. High scorers of Hypochondria are described as being likely to acquire psychosomatic symptoms, and imagine that they are ill. High scorers of Guilt are described as self-blaming and troubled by their conscience, regardless of whether their behaviour is really morally reprehensible. High scorers of Obsessiveness are described as being careful, conscientious, highly disciplined, very particular, and easily irritated by things that are unclean, untidy or out of place.

Watson and Clark (1984) use the term Negative Affectivity in place of Neuroticism and describe it as mood-dispositional dimension. Negative Affectivity is characterised as the subjective experience of distress including a variety of negative emotional states, such as anger, contempt, aversion, guilt, worry, nervousness and fear. Individuals high on Negative Affectivity tend to have a negative view of themselves, and often dwell on their failures and shortcomings. In addition, they appear to focus on the negative side of others and the world in general. Individuals scoring low on Negative Affectivity are seen as relatively content, secure, and satisfied with themselves. Watson and Clark (1984) see Negative Affectivity as unrelated to positive emotions, implying that a person high on Negative Affectivity does not necessarily experience a lack of joy, excitement or enthusiasm. Negative Affectivity is not seen as reactive in nature, but is experienced as a pervasive disposition even in the absence of apparent stress,

suggesting that individuals high on Negative Affectivity are more likely to report distress regardless of the situation.

To measure Negative Affectivity, Watson et al. (1988) developed the PANAS consisting of two 10-item Positive and Negative Affect Scales. The PANAS measure positive and negative affect over a number of different increasing time intervals at state and trait level (moment – today – past few days – week – past few weeks – year – general). When people report their emotions over a brief time span one would most likely refer to states rather than traits. When assessing these two dimensions as long-term traits they are typically referred to as Positive Affectivity and Negative Affectivity respectively (Watson, 2002). Negative Affectivity, is measured by the items (categories): distressed, upset (Distressed), guilty, ashamed (Guilty), jittery, nervous (Jittery), scared, afraid (Fearful) and hostile, irritable (Angry).

Costa and McCrae (1992a) view Neuroticism as a dimension of normal personality, and they contrast adjustment or Emotional Stability with maladjustment or Neuroticism. The core of the domain is the tendency to experience negative effects such as fear, sadness, embarrassment, anger, guilt and disgust. Individuals high in Neuroticism are likely to cope poorly with stress, are prone to irrational ideas, and are less able to control their impulses. In contrast, individuals scoring low on Neuroticism are usually calm, even-tempered, and relaxed, and generally able to face stressful situations without becoming upset or rattled. Costa and McCrae (1992a) developed the NEO-PI-R to measure normal adult personality in detail. It measures five dimensions: Neuroticism, Extraversion, Openness to Experience, Agreeableness, and Conscientiousness. The 240-item questionnaire consists of 30 facet scales with each domain comprising six facets scales.

For the dimension Neuroticism (N) the six facets have been conceptualised as: Anxiety, Angry Hostility, Depression, Self-Consciousness, Impulsiveness and Vulnerability. Anxiety refers to a person’s proneness to fear, worry and nervousness. Angry Hostility measures the tendency to experience anger and related states such as bitterness and frustrations. Depression relates to an individual’s feelings of guilt, sadness, loneliness, and having a generally pessimistic outlook on life. Self-Consciousness indicates the degree to which an individual is easily embarrassed, ashamed and uncomfortable around others. Impulsiveness reflects an individual’s ability to resist temptation, and to control cravings and urges.

Vulnerability refers to the vulnerability to stress; an individual’s feeling of hopelessness, dependency and the inability to cope effectively in stressful situations.

The American-English Big Five structure was developed by Hofstee, De Raad, and Goldberg (1992). Based on this study, ten adjectives were chosen from the 20 highest loading terms to describe Emotional Stability at both ends of the spectrum. Individuals high in Emotional Stability can be described as unenvious, relaxed, unexcitable, patient, undemanding, imperturbable, unselfconscious, uncritical, masculine and optimistic. Individuals low in Emotional Stability can be described as moody, temperamental, jealous, touchy, envious, irritable, fretful, emotional, self-pitying and nervous.

Table 2.1 Comparison of the Neuroticism facet structures Facet Eysenck and Costa and Hofstee, De Raad Watson, Clark Wilson McCrae (1992) and Goldberg and Tellegen (1991) (1992) (1988) Inferiority Unhappiness *1 *5 Anxiety *2 *6 Dependence Hypochondria Guilt *7 Obsessiveness Angry Hostility *3 *8 Depression *4 *9 Self-consciousness Impulsiveness Vulnerability Note. *1: emotional; *2: fretful, nervous, *3: jealous, irritable, moody, touchy, envious, temperamental; *4: self-pitying; *5: distressed, upset, *6: scared, afraid, nervous, jittery,*7: guilty, ashamed; *8: hostile, irritable; *9: distressed, upset

Table 2.1 compares the Neuroticism facet structures of the various models. Eysenck and Wilson’s (1991) Hypochondria and Obsessiveness facets are not represented in any of the other models. Although Neuroticism is seen by Eysenck as a normal personality trait, these

two facets fall within the extreme spectrum of the neurotic personality with high scoring individuals possibly being predisposed to neurotic disorder (Matthews et al., 2003). Costa and McCrae’s (1992) Impulsiveness facet is not portrayed here as it is subsumed under Eysenck and Wilson’s (1991) Psychoticism dimension and under Hofstee et al.’s (1992) Conscientiousness factor. In addition, recent research has demonstrated that Impulsiveness should be assigned to Extroversion (McCrae, 2002).

However, it is clear that the core of Neuroticism versus Emotional Stability refers to individual differences in the extent to which a person experiences the world as threatening and distressing. At the one end of the continuum one finds individuals who are emotionally stable, calm and able to deal successfully with daily life, at the other end one finds individuals who are controlled by their emotions resulting in many perceived and real problems.

2.5.2 Behavioural correlates

Neuroticism has been observed to be relevant as a predictor of behaviour in a number of different fields. De Raad and Schouwenburg (1996) found Neuroticism to be a predictor in academic attainment with highly neurotic students possibly being disadvantaged at university level. A recent cross-sectional study from elementary to secondary school confirmed a negative correlation of Neuroticism with achievement across all grades (Laidra et al., 2007). In the organisational context, a meta-analysis indicated Emotional Stability to be a good predictor of job satisfaction (Judge, Heller, & Mount, 2002), and job performance (Judge & Bono, 2001; Judge et al., 2002). Neuroticism is linked to lower performance on numerical tests in stressful situations (Dobson, 2000), occupational success (Ozer & Benet-Martinez, 2006), and lower status in social groups, particularly in men (Anderson, John, Keltner, & Kring, 2001). In the social context, Neuroticism has a damaging effect on personal commitment in relationships (Kurdek, 1997), the level of marital satisfaction (Kelly & Conley, 1987; Karney & Bradbury, 1997; Watson, Hubbard, & Wiese, 2000), and it is implicated in accelerating divorce (Kelly & Conley, 1987; Rogge, Bradbury, Hahlweg, Engl, & Thurmaier, 2006). In the clinical setting, there is strong evidence of a relationship between Neuroticism and mood, anxiety, (e.g. Griffith et al., 2010; Khan et al., 2005; Weinstock & Whisman, 2006) and personality disorders (Saulsman & Page, 2004). Neuroticism has been found to correlate significantly with various measures of illness (Costa & McCrae, 1987; Friedman & Booth-Kewley, 1987), it is

linked to the use of ineffective coping strategies (Connor-Smith & Flachsbart, 2007; McCrae & Costa, 1986) and to mortality in cardio-vascular disease (Shipley et al., 2007), It is a predictor of positive and negative mood (David, Green, Martin, & Suls, 1997), increased psychological distress (Ormel & Wohlfarth, 1991; Suls & Martin, 2005), and has been found to influence subjective well-being (Ozer & Benet-Martinez, 2006; Steel, Schmidt, & Shultz, 2008) and overall quality of life (Lynn & Steel, 2006).

The above discussion clearly demonstrates that Neuroticism affects all spheres of life. The development of an indigenous Emotional Stability scale within the SAPI project will certainly contribute to a better understanding of this trait for the entire South African population.

CHAPTER 3 PERSONALITY AND CULTURE

3.1 Introduction

This chapter highlights the influence of culture on personality. Two theoretical perspectives used in research on personality, the etic and emic approaches, are described, and the methodological issues necessary for the development of valid and reliable cross-cultural personality inventories are discussed. A combined etic and emic approach is presented followed by two examples, the CPAI, (Cheung et al., 1996) and the SAPI. Recent studies of personality assessment in South Africa are discussed and the present study including postulates is described.

3.2 Various approaches to the study of personality and culture.

South Africa is a diverse country with many different language groups and cultures. The development of a personality instrument that can be fairly administered to and interpreted across these diverse groups requires a major undertaking. One important aspect that should be taken into account when developing such an instrument is the impact of culture on personality.

Culture can be defined in many ways. However, Church and Ortiz (2005) stated that the majority of cross-cultural psychologists would support the following definition provided by Fiske (2002, p.85):

A culture is a socially transmitted or socially constructed constellation consisting of such things as practices, competencies, ideas, schemas, symbols, values, norms, institutions, goals, constitutive rules, artifacts, and modifications of the physical environment.

In other words, culture includes both observable actions and objects outside of the individual, and symbols, values and shared meanings inside the individual (Berry, 2000). This definition of culture is clearly very broad. In the present study culture is represented by ethnicity and language. Historically, ethnicity or race had been the focus of research in South Africa.

However, since the end of apartheid in 1994 and the introduction of 11 official languages in South Africa, the emphasis has shifted, and current research identifies cultural groups by language (Valchev et al., 2011). The present study therefore places secondary importance on ethnicity, and focuses on cultural groups as defined by the 11 official languages of South Africa.

Despite some agreement on what comprises culture, psychologists differ on how they integrate culture with their research (Church & Ortiz, 2005). Two theoretical perspectives currently dominate research on personality and culture: the etic approach (known as cross- cultural trait psychology) and the emic approach comprising cultural- and indigenous- psychology (Church, 2001). Psychologists supporting the etic approach are interested in discovering traits that are universal and therefore seen as relatively culture free. In contrast, psychologists supporting the emic approach are concerned with the study of personality in specific cultures (Church, 2000). Within the emic approach, cultural psychologists are interested in understanding the interconnected nature of culture and personality, whereas indigenous psychologists focus on theories and concepts that represent indigenous cultural contexts (Church & Ortiz, 2005). These different approaches to psychology will be described in the paragraphs that follow.

3.2.1 The etic perspective

One major goal of cross-cultural research is the identification of universally common traits. In cross-cultural studies culture is commonly treated as a quasi-independent variable distinct from personality, which may impact the level, expression and correlates of traits, but not the underlying structure or dimensions of personality (e.g. Barrett et al., 1998; Church, 2001). Cross-cultural psychology is concerned with cross-cultural equivalence of constructs and measures, and typically uses traditional and relatively context-free psychometric scales and questionnaires. Cross-cultural psychologists use trait psychology as their theoretical framework and their main focus is on individual differences (Church, 2001). According to Cheung, Van de Vijver, and Leong (2011), the main strengths of this approach are the large empirical database (personality traits have been found across many countries and cultures, see Chapter 2.3.3), and its comprehensive methodological framework (see Chapter 3.2.1.1 on equivalence testing).

In the last few decades a vast number of cross-cultural personality studies have focused on the comparability of personality traits across cultures. Studies using questionnaires based on the Five-Factor Model or Eysenck’s Big Three represent the cross-cultural trait approach. For example, Barrett et al. (1998) investigated the factorial similarity of Psychoticism, Extroversion and Neuroticism and Social Desirability across 34 countries. They demonstrated an “extraordinary degree of consistency and similarity” (p. 818) across all four scales with modified mean KHB (Kaiser-Hunka-Bianchini) congruence coefficients above .90 for the Extroversion and Neuroticism factors and ranging from .83 to .88 for the Psychoticism and Social Desirability factors. Similarly, McCrae (2002) using the NEO-PI-R demonstrated cross- cultural replicability for the five dimensions Neuroticism, Extroversion, Openness to Experience, Agreeableness and Conscientiousness across 36 cultures. For Neuroticism, the focus of this thesis, the principal component factor loadings ranged from .64 to .86 for all facets except Impulsiveness, which loaded on the Extroversion dimension.

However, despite evidence confirming the replicability of Neuroticism across many countries, languages and cultures (see also Lynn & Martin, 1995; McCrae, Terracciano & 78 members of the Personality Profiles of Cultures Project, 2005; Schmitt, Allik, McCrae, & Benet-Martinez, 2007), De Raad et al. (2010) using the lexical approach, recently found evidence that only three of the five factors are replicable across a set of 12 languages. Neuroticism did not replicate as strongly across the data set as it had done historically, and De Raad et al. (2010) suggested two possible interrelated reasons for this result: (1) the lexical approach is designed to depict everyday attributes of people derived from the natural language. Neuroticism is rooted in psychopathology and its various degrees of emotional experiences used in the clinical context may have not been captured here; (2) Neuroticism generally does not belong to the first two or three factors extracted in the factor analysis. This indicates that the factor is comprised of a smaller number of terms. The use of lexical studies resulted in an even smaller set of items, therefore reducing the ability to capture the various facets of the construct.

3.2.1.1 Methodological issues

Two fundamental concepts that need to be considered when comparing studies across culture are bias and equivalence. Bias can be defined as the presence of a nuisance factor or systematic error in comparison of scores across different cultures. It occurs if score differences on the indicators of a particular construct do not correspond to differences in the

underlying trait, and therefore challenges the validity of cross-cultural comparisons (Van de Vijver & Leung, 1997; Van de Vijver & Tanzer, 2004). Bias can arise from three sources: construct bias, method bias and item bias. Construct bias occurs if the construct measured is not identical across cultural groups. It can occur, for example, due to an incomplete overlap of construct definitions across cultures, poor sampling of all relevant behaviours or differential appropriateness of the test content. An example of construct bias can be found in Cheung et al.'s (2001) study on the universality and sufficiency of the five factor model in the Chinese context. The fifth factor, Openness, did not emerge as a separate dimension when compared with the CPAI, (Cheung et al., 1996) indicating a different conceptualisation of the content across cultures. Method bias arises due to systematic distortions in measurement, such as sample incomparability, instrument characteristics, tester and interviewer effects and the method of administration (Van de Vijver & Leung, 2001). A final source of bias is item bias or differential item functioning (DIF), where items have different meanings across cultures. Item bias occurs from various sources, such as inadequate translation of the item, inadequate item formulation, or inapplicability of an item in a specific culture (Van de Vijver & Leung, 1997; Van de Vijver & Leung, 2001).

Conversely, equivalence is the absence of bias and refers to the level of comparability of constructs in different cultural groups. There are three hierarchically linked types of equivalence (Van de Vijver & Tanzer, 2004). The first type is called construct (or structural) non-equivalence. It is present when an instrument measures different constructs or when concepts of the construct measured overlap only partially across cultures. In this instance, cultures cannot be compared because they measure different attributes of a person. The second type is called measurement unit equivalence. This level of equivalence can be obtained when instruments with identical measurement units but different scale origins are used. This may occur for example, when sources of method bias result in different mean scores in one or more cultures. Comparisons of scores across cultures cannot be made directly, but differences found within each cultural group can be compared across groups. The third and highest level of equivalence, scalar equivalence, allows for direct score comparisons within and across cultural groups. Scalar equivalence assumes bias-free measurement and can be achieved when two metric instruments have the same measurement unit and origin (Van de Vijver & Leung, 1997; Van de Vijver & Leung, 2001; Van de Vijver & Tanzer, 2004).

Cheung et al. (2011) stated that the increased use of equivalence testing in recent years has had a stimulating effect on cross-cultural research. However, they contend that although there has been a vast increase in the availability of relevant software to measure equivalence, there are still more sources of cross-cultural bias than can be identified with the equivalence procedures available at present. This poses problems for the validity of cross-cultural comparisons and can lead to an overly optimistic view of cross-cultural similarities because culture-specific attributes or constructs may have been ignored (Cheung et al., 2011).

In addition to problems with bias and equivalence, Van de Vijver and Rothmann (2004) point to response sets as another factor that that may affect the validity of assessments in multicultural groups. Response sets refer to a person’s tendency to respond to a questionnaire in a certain way regardless of the item content. Examples are acquiescence (the tendency to agree) and social desirability (the tendency to answer in a way that is socially acceptable and desirable). Social desirability, in particular, has been shown to vary substantially across cultures, with less affluent, less educated and less powerful groups showing more social desirability (Van Hemert, Van de Vijver, Poortinga, & Georgas, 2002).

This imposed etic approach, which does not allow for the assessment of culture-specific personality dimensions, has been cited as a major criticism against cross-cultural research (Church, 2001). In response, researchers have developed a more emic approach, which focuses on the understanding of local constructs not captured in the non-western context, and uses native languages, cultural specialists and local literature to identify indigenous personality concepts (Cheung et al., 2011; Church, 2008).

3.2.2 The emic perspective

The emic perspective encompasses both the indigenous and the cultural approach to psychology. These approaches focus less on cultural universals and more on the interpretation of personality within specific cultural contexts. Culture and personality are seen as mutually constituted, and deeply intertwined (Heine, 2001; Markus & Kitayama, 1991).

Cultural psychologists emphasize qualitative, ethnographic and interpretative research methods, and place less importance on individual differences (Church, 2001). The understanding of the self and personality is seen as socially constructed, and therefore varies

across cultures. Within this context, Markus and Kitayama, (1998) have drawn attention to the construct of the independent versus the interdependent view of the self. The Western independent self-view regards an individual as an autonomous, idiocentric, self-contained and individualistic entity with a focus on inner attributes (e.g. traits, abilities, motives, and values), which primarily determine one’s behaviour (Geertz, 1975). Behaviour varies based on these internal attributes, and is understood as consistent across situations and stable over time (Markus & Kitayama, 1998). In contrast, individuals with a non-Western interdependent self-view define themselves as part of interdependent and interconnected social relationships (Markus & Kitayama, 1998). Internal attributes are of secondary importance and are understood as being situation specific. Behaviour is largely determined by being responsive to other people’s thoughts, feelings and actions in the relationship, and varies according to context and situation. These differences in self-definition suggest that for societies characterised by interdependent selves, personality traits may be less useful for describing and predicting behaviour (Markus & Kitayama, 1991).

A related concept particularly relevant for the South African context is the individualism- collectivism construct, which has attracted a vast amount of research among both cross- cultural and cultural psychologists. Triandis (1996) described certain defining characteristics between individualistic and collectivistic cultures including the following: firstly, within the individualistic culture, the sense of self is seen as an autonomous and unique entity (i.e. independent self-construal), whereas within the collectivistic culture it is more connected to in-groups (i.e. interdependent self-construal, Markus & Kitayama, 1991). Secondly, individualistic cultures emphasise personal attributes such as traits, whereas collectivistic cultures emphasize social roles and norms in guiding behaviour (Davidson, Jaccard, Triandis, Morales, & Diaz-Guerrero, 1976).

Cultural psychologists have used these differences to make predictions regarding the “traitedness” of self-concepts and behaviour (Church, 2009). They anticipate self-concepts and descriptions of others to comprise of more internal attributes in individualistic cultures, and of more social and collective aspects in collectivistic cultures. In addition, people in individualistic cultures are expected to focus more on traits or inner processes when explaining or predicting behaviour, whereas people in collectivistic cultures focus more on situational contexts. Finally, regarding behaviour, people in collectivistic cultures are expected to exhibit less cross-situational consistency than people in individualistic cultures,

and behaviour is expected to be more predictable from social roles and expectations in collectivistic cultures and more from traits in individualistic cultures (Church, 2009). Church (2009) highlighted that although cultural psychologists have raised important questions regarding self-concepts and behaviour across cultures, they have tended to ignore evidence from trait psychology (e.g. inter-observer agreement, heritability and predictive validity of traits), which would reduce the effect of these concepts on personality.

In contrast, indigenous psychologists are concerned with devising theories, constructs and methods that reveal indigenous cultural contexts (e.g. Church & Katigbak, 2002). Indigenous psychologists have often focused on the explanation of constructs thought to be especially salient for particular cultural groups (Church & Ortiz, 2005). In the 1970s and 1980s psychologists, particularly in Asia, started the so called “indigenization movement” when they realised that Western models and instruments failed to consider their own distinct cultural values and characteristics (Cheung, Cheung, Wada, & Zhang, 2003; Ho, Peng, Cheng Lai, & Chan, 2001). Many of the indigenous constructs developed subsequently, emphasise the relational nature of human experience, which defines selfhood in a social and interpersonal context (Ho et al., 2001). Examples include the Japanese concept amae (behavioural patterns of dependence and attachment between a mother and child) (Yamaguchi & Ariizumi, 2006), the concept of the selfless-self in Taoism, Buddhism and Hinduism (Ho et al., 2001), and the Chinese concepts of harmony and face (Cheung et al., 2001).

However, Cheung et al. (2011) criticised that by emphasising cultural uniqueness, possible relevant universal aspects may be ignored. For example, Yamaguchi and Ariizumi (2006) found that the Japanese concept amae can also be observed in Americans and Taiwanese. Church (2001) criticised that many indigenous measures identified culture-specific constructs that could also be included under universal personality models. For instance, Katigbak, Church, and Guanzon-Lapena (2002) compared the Big Five model with indigenous Filipino personality scales, and showed evidence that most Philippine dimensions were well covered by the five factor model. The authors highlighted that a few indigenous constructs less well accounted for by the five factor model, were not unknown in Western cultures and that they differed mostly in salience and composition. Church (2001) further argued that for indigenous psychology to be of value, indigenous constructs need to demonstrate incremental validity beyond those provided by imported measures.

It is evident from the above discussion that culture represents an important aspect in the understanding of personality. Research has provided support for both cross-cultural, and cultural and indigenous psychology perspectives. Although the emic and etic approaches appear to be antithetical (Van de Vijver & Leung, 2001), these researchers claim that both approaches are needed for the advancement of knowledge and development of new personality theories, because “without cross-cultural comparisons, psychological theory is confined to its own boundaries; but a blind “exportation” of Western instruments to other cultures without any concern for the appropriateness of the measures is also unlikely to lead to major theoretical advancements” (p.1008).

Triandis (2000) suggested a synthesis between cultural and cross-cultural psychology by using both emic (qualitative) and etic (quantitative) methods with an emphasis on convergent findings. This has been echoed by Berry (2000), who advocated a symbiosis of cultural (emic) and comparative (etic) approaches. His description of the three goals of cross-cultural psychology resembles the three stages discussed above: 1. transport current hypotheses and conclusions about human behaviour to other cultural contexts in order to test their validity (imposed etic approach); 2. explore new cultural systems to discover psychological phenomena not available in the first culture (emic approach); and 3. integrate psychological knowledge gained from these first two activities and generate a psychology that would be valid for all people (derived etic approach). Berry (2000) concluded that “if one takes these three goals as a sequence of activities, cross-cultural psychology thus appears to be evolving in a sensible and understandable way” (p. 198).

Recently, Cheung et al. (2011) suggested an integrated approach to the study of culture and personality. They stated that cross-cultural and cultural concepts are complementary because they address different aspects, and argued that a combined etic-emic approach will “provide a comprehensive framework to understand universal and culturally variable personality dimensions” (p.12).

3.2.3 Integration of the emic and etic perspectives

One of the first studies integrating emic with etic concepts is the CPAI, (Cheung et al., 1996). The researchers selected items from different personality tests including English-language

personality scales, and simultaneously identified indigenous personality constructs by reviewing classical and contemporary literature and recent personality research on the Chinese people. In addition, people’s descriptions of others from a variety of backgrounds and professional sectors were collected. Four factors were identified including a unique factor, Interpersonal Relatedness, which is not covered by the Five Factor Model (Cheung et al., 2001). However, when an English version of the CPAI, (Cheung et al., 1996) was administered to two English-speaking samples, Cheung, Cheung, Leung, Ward and Leong (2003) found factor structures similar to those of the original Chinese version and concluded that the Interpersonal Relatedness factor also has relevance in other cultures. This result demonstrates how an emic and etic approach may be combined to yield a deeper understanding of universal and local aspects of personality structure.

Similarly, the SAPI project, the foundation for the present study, started from an emic approach using interviews to identify culturally and linguistically adequate personality descriptions across all 11 official languages. The existing SAPI database was developed by interviewing participants (N = 1,308) from each of the 11 official languages that differed regarding age, gender and socio economic status. Participants were interviewed in their native language and asked to describe ten target persons: a parent; an older child or sibling; a grandparent; a neighbour; a person they do not like; their best friend of the opposite sex; a colleague or a friend from another ethnic group; their favorite teacher or a person from the village whom they liked very much; their least liked teacher or a person from the village whom they strongly disliked, and their best same-sex friend. The following four questions were used to obtain personality descriptive terms: “Please describe the following people to me by telling me what kind of person he or she is or was”, “Can you describe typical aspects of this person?”, “Can you describe behaviors or habits that are characteristic of this person?”, and “How would you describe this person to someone who does not know him/her?”.

All responses were translated into English by professional translators, and checked by independent multicultural language experts to ensure linguistic and cultural accuracy. More than 50,000 personality descriptive terms were identified and reduced to 193 personality dimensions or facets. These facets were clustered further to create the indigenous personality structure yielding 37 subclusters and 9 clusters (Extraversion, Soft-heartedness,

Conscientiousness, Emotional Stability, Intellect, Openness, Integrity, Relationship Harmony and Facilitating), (see Nel (2008) for a more detailed overview).

The findings of the qualitative stage of the present study indicate that the Five Factor Model is well represented, but that the South African clusters include additional social and relational aspects of personality (Cheung et al., 2011). Currently, the first quantitative analysis is underway to develop and validate scales for all 9 clusters, with the present study focusing on the cluster Emotional Stability. Although the project is still in its early developmental stage, the SAPI project combines the initial emic stages of generating indigenous personality constructs with etic procedures, to identify relevant personality clusters for all 11 official languages in South Africa (Cheung et al., 2011).

3.3. Recent studies of personality assessment in South Africa

Personality assessment is used widely in South Africa. However, most of the personality inventories in common use have been imported from the United States of America or Europe, and directly applied in the South African context. Others, such as the 16PF (SA 92), have been adapted for the South African population, from Cattell et al.’s (1970) 16PF. This etic approach leads to bias and problems with cross-cultural equivalence (Van de Vijver & Leung, 1997; Van de Vijver & Rothmann, 2004), as discussed above. Local research found weak construct equivalence for the 16PF (SA92) between race groups (Abrahams & Mauer, 1999a; but see also Abrahams, 2002; Prinsloo & Ebersöhn, 2002); and language groups (Van Eeden & Mantsha, 2007).

Other studies have focused on investigating the universality of the five-factor structure obtaining mixed results. Heaven and Pretorius (1998) found support for the five-factors in an Afrikaans-speaking student sample but failed to confirm the five-factor structure for the Sotho- speaking student sample. Heuchert, Parker, Stumpf and Myburgh (2000) administered the revised NEO Personality Inventory (NEO-PI-R) to a group of university students, and found a clear five-factor structure across both the total group and the Black and White subgroups suggesting structural equivalence. However, this result needs be interpreted with caution as the Black sample was very small (n = 92). I. Taylor (as cited in Meiring et al., 2005) compared a Black and White employee sample on the NEO-PI-R, and did not find the Openness factor in the Black sample.

More recent studies have centred on comparing race and language groups in personality instruments in the occupational settings. Joseph and Van Lill (2008) compared the nine subscales of the Occupational Personality Profile (OPP) among White and Black race groups, and Afrikaans, English and African language groups and found significant mean differences for the majority of the scales. Here too, the result needs to be interpreted with caution due to the small sample sizes of the White (n = 65) group. Visser and Viviers (2010) compared the 32 scales of the Occupational Personality Questionnaire (OPQ32n) in a Black and White employee sample and demonstrated structural invariance for the two groups. However, it is noteworthy that the personality studies in South Africa have traditionally focussed on comparing Black and White race groups, ignoring the multicultural and multilingual make-up of South Africa.

The first study to comprehensively assess South Africa’s cultural diversity was undertaken by Meiring et al. (2005). The researchers applied the 15FQ+, an adapted version of the 15FQ designed to measure Cattell’s 16 personality factors (Tyler, 2003) to 9 Black language groups and three other race groups, and detected construct bias and poor reliability in various indigenous African groups. In a subsequent study, these problems could not be rectified by an adaptation of the item content (Meiring et al., 2006).

The first locally developed instrument, the BTI, measuring the Big Five was developed by Taylor and de Bruin (2006). Ramsay, Taylor, de Bruin and Meiring (2005) reported strong support for the validity and reliability of scores for the Big Five traits as measured by the BTI (Taylor & de Bruin, 2006) across three indigenous language groups, demonstrating that locally developed measures of personality can yield satisfactory results.

Overall, the available body of research clearly indicates the need for a personality instrument that takes the universal and unique personality factors of all 11 languages and cultures into account. This is the aim of the SAPI project, and the development of an indigenous Emotional Stability scale will contribute towards this goal.

3.4 Present study

The present study is embedded within the framework of the SAPI project, whose ultimate aim is to gain a better theoretical understanding of personality as it manifests in South Africa, by developing a personality instrument that is psychometrically sound and applicable to all 11 official South African languages. As discussed in section 3.2.3 the project has moved from its qualitative stage into a quantitative stage, which is concerned with the development and validation of indigenous scales for all 9 clusters (Extraversion, Soft-heartedness, Conscientiousness, Emotional Stability, Intellect, Openness, Integrity, Relationship Harmony and Facilitating). The present study focuses on the cluster Emotional Stability, which comprises six subclusters (Balance, Courage, Emotional Control, Emotional Sensitivity, Anxiety and Ego Strength) with two to six facets per subcluster. Nel (2008) describes this cluster as encompassing all the personality attributes describing “emotional well-being” or “ill- being” on either side of the Emotional Stability dimension. The definitions for the six subclusters and their 25 facets are presented below.

3.4.1 Definition of the construct Emotional Stability

3.4.1.1 Balance

• Balancing Life: Living a balanced life by dedicating equal amounts of time to family, health and work or studies needs • Even-tempered: Being emotionally stable even in difficult situations, not displaying or controlling one's feelings of anger, not being upset easily, and preferring a peaceful environment • Mature: Acting age appropriately, making insightful decisions, admitting ones' mistakes, and apologising when one has done something wrong • Short-tempered: Getting easily irritated, upset or angry with people, being impatient, aggressive, and wanting to hurt others

3.4.1.2 Courage

• Courageous: Liking challenges and taking risks, not afraid to make changes, speaking up for others and oneself even in the face of negative consequences

• Fearful : Being afraid of people and situations, being worried about one's health and one’s own and other people's safety

3.4.1.3 Emotional Control

• Coping: Way of dealing successfully with diverse complex issues • Impulsive: Talking and acting without thinking or weighing up all options, jumping into a situation without considering the consequences for oneself and others • Obsessive/compulsive: Being fixated on certain routines, and following strict schedules to feel in control • Patient : Listening to and respecting other people, taking time to explain something until it is understood by everyone, preferring to talk things through rather than shouting and showing anger, holding back and not blurting out one's opinion in discussions. • Temperamental: Acting in an unpredictable way, being easily angered and provoked, treating others badly for no reason, and having frequent mood swings

3.4.1.4 Emotional Sensitivity

• Emotional: Showing feelings such as anger, excitement, sadness and happiness through crying, facial expressions and body language • Exaggerating: Being overly dramatic, and displaying behaviour with an intensity inappropriate to the situation • Sensitive: Taking minor things personally, being easily offended and hurt by what other people say, and having difficulties hearing bad news • Ashamed: Being embarrassed about situations, and easily humiliated by others

3.4.1.5 Anxiety

• Complaining: Voicing continuous dissatisfaction, about other people's actions, when things are not going according to plan and about life in general • Content: Being satisfied with life and accepting of one's circumstances • Depressive: Feeling down, based on one's life or work situation, disliking oneself, and lacking direction and interest in life

• Neurotic : Displaying overly fearful and maladjusted behaviour in different situation and interactions with people • Tensed: Being apprehensive about issues, and feeling nervous in certain situations

3.4.1.6 Ego Strength

• Attention-seeking: Desire to be the centre of attention, to be listened to, admired, and liked by others • Demanding: Insisting that others respect, listen and obey him or her, and expecting an immediate reaction and results when giving instructions to others • Needy: Trying to please people to obtain acceptance, recognition, love and praise. Finding it difficult to go somewhere alone • Self-confident: Being sure of oneself, having a good self-image, feeling comfortable in unfamiliar situations. Knowing what one wants, and what's best in life, trusting one's own abilities • Self-respectful: Taking care of oneself by living a healthy lifestyle, being neat and tidy at home, attending to one's appearance, loving and trusting oneself.

The main goal of the present study is the development and preliminary validation of a scale of Emotional Stability for the multicultural South African context based on the above subclusters and facets. Two instruments were chosen to assess convergent validity with the indigenous Emotional Stability scale. The first instrument, the BTI, (Taylor & De Bruin, 2006) is a semi-indigenous instrument, which was developed in South Africa to assess the Big Five factors of personality. Its facets were selected on the basis of previous research in the USA and Europe, but its items were developed and written specifically for the South African context (Taylor, 2004). Neuroticism comprises the facets Affective Instability, Depression, Self-consciousness and Anxiety. As discussed in Chapter 2.3.3, the Big Five factors, including Neuroticism, have been replicated in many countries, languages and across various instruments. Cross-cultural applicability of the BTI (Taylor & De Bruin, 2006) was demonstrated by similar reliability and factor structures across the Black and White samples (Taylor & De Bruin, 2006). Further evidence in support of the reliability and validity of the BTI (Taylor & De Bruin, 2006) across three African language groups was reported by Ramsay et al. (2005). It is therefore anticipated that Neuroticism as found in the natural

language descriptions of various South African groups correlates positively with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006).

The second instrument, the PANAS, (Watson et al., 1998), is an instrument developed in the USA to assess positive and negative affect at state and trait level. Negative Affectivity is characterised as the subjective experience of distress including a variety of negative emotional states. Negative Affectivity is measured by the items (categories): distressed, upset (Distressed), guilty, ashamed (Guilty), jittery, nervous (Jittery), scared, afraid (Fearful) and hostile, irritable (Angry). Considerable overlap between these categories and those describing Neuroticism in the other models discussed in Chapter 2.5.1 (Table 2.1) can be found, and a positive correlation with the indigenous Emotional Stability scale is expected.

3.4.2 Postulates

The following four postulates will be tested:

3.4.2.1 Postulate 1

In an exploratory factor analysis using oblique rotation the facets or first order factors will correspond with the subclusters of the SAPI model.

3.4.2.2 Postulate 2

After performing a second-order factor analysis on the correlations of the first-order factors and a Schmid-Leiman transformation, a hierarchical orthogonal solution will be obtained with the higher-order factor corresponding to the expected Emotional Stability trait.

3.4.2.3 Postulate 3

In a comparison between the Germanic, Nguni and Sotho groups’ factor structure, the congruence coefficients for all groups will be at or above .90 for all factors.

3.4.2.4 Postulate 4

The newly developed indigenous Emotional Stability scale will correlate positively with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the Negative Affect Sales of the PANAS (Watson et al., 1988).

CHAPTER 4 METHOD

4.1 Introduction

In this chapter the process for the development of the indigenous Emotional Stability scale is described, followed by the procedure section, which states the participants, the data collection method, and the instruments used in the data analyses. Finally, the statistical analyses that were performed are presented.

4.2 Research approach

The focus of the present study is the development and preliminary validation of a scale of Emotional Stability for the multicultural South African context. This scale was developed using the existing SAPI database to write items that reflect an indigenous conception of Emotional Stability, and how it manifests in people’s behaviour.

4.2.1 Analysis process

The development of the indigenous Emotional Stability scale is based on one of SAPI’s nine clusters, namely the Emotional Stability cluster, which comprises six subclusters (Balance, Courage, Emotional Control, Emotional Sensitivity, Anxiety, and Ego Strength). Each subcluster consists of two to six facets.

In a first step, all facets belonging to the Emotional Stability cluster were identified, and a spreadsheet was created for each of the subclusters incorporating all responses obtained in all 11 languages. This process is described in Nel et al. (in press) and Valchev et al. (2011). Each spreadsheet contained the responses of the interviewees in their home language, their English translation, a cleaning and categorizing column and the facet to which these responses had been allocated. Thereafter, a second spreadsheet was developed using only three columns from the above spreadsheet, namely language, facet and the English translation of the original responses. These responses were used to create a definition of the meaning of each facet for all languages ensuring coverage of the whole construct. The definitions for the six sub cluster and their 25 facets are presented section 3.4.1.

In a next step, all content-representative responses for the different aspects of the meaning for each facet were extracted. Care was taken to ensure that these responses were derived from the raw data, were implied in the definition and covered all aspects of the definition. This process involved regular quality checks by all members of the SAPI team: cross-cultural specialists, doctoral and master students. These content-representative responses formed the basis for the item construction.

4.2.2 Item writing

The items of the ES scale were developed guided by the following criteria: Items were formulated positively in the direction of the construct. Simple sentences were used to facilitate translatability at a later stage of the project, and negations, idioms and expressions were avoided to ensure comprehension by all respondents. Items were written in the first person, starting with “I” (e.g. “I feel worthless” – measuring the facet Depression). A few additional items from other instruments were added to enhance the trait coverage of the construct. To ensure coverage of the entire content domain, between three and 24 items per facet were created based on the definitions for each facet. Team members of the SAPI project, consisting of experienced cross-cultural psychologists, doctoral and master students, reviewed and evaluated all items for appropriateness and wording.

The items were grouped according to their facets and presented together without demarcating the facets or subclusters resulting in a single list of 326 items (see Appendix A). A five-point Likert scale format (strongly disagree; disagree; somewhat agree/somewhat disagree; agree; strongly agree) was used. Thereafter, a questionnaire was compiled in English and administered to a multicultural student sample, together with the items of the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the items of the PANAS (Watson et al., 1988), to allow for the measurement of convergent validity with the newly developed indigenous Emotional Stability scale.

4.3 Procedure

4.3.1 Participants

The sample consisted of 588 second year undergraduate psychology students attending a course in personality psychology, with a mean age of 20.45 (range 18 to 48) (1 unspecified). There were 122 males (20.7%) and 466 females (79.3%), of which 362 (61.6%) were Black, 161 (27.4%) White, 32 (5.4%) Indian, and 32 (5.4%) Coloured (1 unspecified). Self-rated knowledge of the English language ranged from very poor (0.7%), poor (1.0%), good (42%) to very good (56.3%). Table 4.1 depicts the breakdown of the educational level of the sample. Table 4.2 shows the demographic composition with regard to language.

Table 4.1 Breakdown of the highest educational qualifications of the sample

Educational Level Frequency Percentage

Grade 12 530 90.1 Certificate 19 3.2 Diploma 13 2.2 B degree 19 3.2 Honours or equivalent 1 0.2 Masters 1 0.2 Other 5 0.9 Total 588 100

Table 4.2 Demographic composition of the sample according to language

Language group Language Frequency Percentage

Afrikaans 54 9.2 English 184 31.3 Germanic 238 40.5 Ndebele 9 1.5 Xhosa 31 5.3 Zulu 110 18.7 Swati 32 5.4 Nguni 182 30.9

Table 4.2 Demographic composition of the sample according to language

Language group Language Frequency Percentage

Sepedi 35 6 Sesotho 33 5.6 Setswana 58 9.9 Sotho 126 21.5 Venda 14 2.4 Tsonga 22 3.7 Other 6 1 Total 588 100

4.3.2 Data collection

The Emotional Stability questionnaire including the added items of the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the items of the PANAS (Watson et al., 1988) were administered to a group of second year students attending a course on personality psychology, who received course credits for their participation. The students were informed about the nature of the study and the importance of their participation in this research during class. The questionnaire was made available in an electronic format at the university and students were given three weeks to complete it online. Student numbers were required for the allocation of the course credits, but students were assured of confidentiality. Of the 610 students who attempted the questionnaire, data from 22 questionnaires were not analysed due the questionnaires being incomplete resulting in a total of 588 questionnaires.

At this early stage of the scale construction process only university students were selected as participants. On average, university students can be expected to have a better English reading ability than non-students. In addition, university students may be more familiar with the process of completing surveys and research questionnaires. It is argued that personality items that fail to function appropriately for university students (where language and inexperience

with research questionnaires plays a smaller role) will also be unlikely to function appropriately for non-university students.

4.3.3 Instruments

Demographic questionnaire: The demographic questionnaire contained items referring to the respondents’ age, gender, race, home language, self-rated English reading ability, and highest educational level.

Basic Traits Inventory: The BTI (Taylor & De Bruin, 2006) was developed in South Africa to cross-culturally assess the Big Five factors of personality, namely Extraversion, Agreeableness, Openness to Experience, Neuroticism (vs. Emotional Stability) and Conscientiousness. Each factor is subdivided into four or five facets. Neuroticism (N) comprises four facets (Anxiety, Depression, Self-Consciousness, Affective Instability) and refers to a person’s emotional stability and the general tendency to experience negative affect in response to their environment. The inventory consists of 193 items on a five-point Likert type scale, ranging from strongly agree to strongly disagree with high scores indicating a higher standing on the dimension. Norm groups were created for Black and White students and males and females separately.

The Cronbach’s alpha coefficients across all groups range from .87 to .93 for all five factors indicating satisfactory internal consistency reliability (Taylor & De Bruin, 2006). On the facet level most facets have acceptable reliabilities ranging from .64 to .85, with the exception of Modesty and Openness to Values, which have low reliabilities.

Construct validity was established using factor analysis. All five factors emerged clearly accounting for 59.95% of the variance in the correlation matrix with each of the facets having significant primary loadings on their hypothesized factors. Structural equivalence across all groups was found with congruence coefficients at or above 0.93 for all five factors (Taylor & De Bruin, 2006). Additional evidence for the construct validity was provided by Ramsay et al. (2005) for a group of Nguni, Sotho and Pedi language speakers. For the purpose of the present study only the Neuroticism scale was correlated with the indigenous Emotional Stability scale.

Positive and Negative Affect Schedule: The PANAS (Watson et al., 1988) consists of two 10- item Positive and Negative Affect scales. It measures Positive and Negative Affect over seven increasing time intervals (moment – today – past few days – week – past few weeks – year – general) on a five- point Likert type scale ranging from (1) very slightly or not at all; (2) a little; (3) moderately; (4) quite a bit; to (5) extremely. High scores on the scale indicate a higher standing on the dimension. For the purpose of the present study the time interval “general” was chosen to allow for a comparison with the personality-descriptive trait terms of the indigenous Emotional Stability scale. Positive Affect (PA) indicates the extent to which a person feels enthusiastic, active and alert. High PA is characterised by a state of high energy, full concentration and pleasurable engagement, low PA is characterised by sadness and lethargy (Watson et al., 1988). Negative Affect (NA) indicates the extent of subjective distress and a variety of mood states. High NA is characterised by feelings of anger, guilt, fear, disgust, contempt, and nervousness. Low NA is reflected by a state of calmness and serenity (Watson et al., 1988).

Internal consistency across all time instructions was found to be high with Cronbach’s alpha ranging from .86 to .90 for PA and .84 to .87 for NA (Watson et al., 1988). Inter- correlations between NA and PA ranged from -.12 to -.23 indicating quasi-independence (Watson et al., 1988). Test-retest reliability was found to be stable over an approximate 2 months’ time period with the retest stability increasing as the rated time frames increased in length (Watson et al., 1988). Confirmatory factor analysis provided evidence of the construct validity of the PA and NA scales (Crawford & Henry, 2004, Tuccitto, Giacobbi, & Leite, 2010).

When compared with the set of 60 mood terms reported in Zevon and Tellegen (1982), convergent validity ranged from .89 to .95 for PA and .91 to .93 for NA, with discriminant correlations being relatively low, ranging from -.02 to -.15 for PA and -.10 to -.18 for NA (Watson, et al., 1988). Further evidence for external validity of the PANAS (Watson et al., 1988) was demonstrated when correlated with several other clinical measures. These include (a) high correlations of NA and low negative correlations of PA with the Hopkins Symptom Checklist (HSCL, Derogatis, Lipman, Rickel, Uhlenhuth, & Covi, 1974), which assesses general distress and dysfunction; (b) high correlations of NA and moderate negative correlations of PA with the Beck Depression inventory (BDI, Beck, Ward, Medelson, Mock, & Erbaugh, 1961), a 21-item self- report measure of depressive symptoms; and (c) high correlations of NA and low negative correlations of PA with the State-Trait Anxiety Inventory

State Anxiety Scale (A-State, Spielberger, Gorsuch & Lushene, 1970), a 20-item scale asking subjects to rate their current affect (Watson et al., 1988).

4.4. Statistical analyses

4.4.1 Data preparation

In a first step, the data set was checked for unexpected responses, missing data, outliers and normality of distributions. Thereafter, a principal component analysis on the entire set of items, requesting only one component, was performed to determine if items failed to load on the broad cluster of interest, namely Emotional Stability. Items with a loading < .20, sharing less than 5% of their variance with the total score, were highlighted for further inspection.

In a next step, a principal component analysis requesting only one component was performed for the items in each subcluster. Items, which failed to obtain a loading > .30 within the subcluster, and a loading > .20 when correlated with the total score, were removed from subsequent analyses.

4.4.2 Factor Analysis

The responses to the items were subjected to a hierarchical factor analysis (cf. Gorsuch, 1983; McDonald, 1999; Wolff & Preising, 2005) with the aim of examining the underlying dimensionality of the data. The programme used for the analysis was the Predictive Analysis SoftWare (PASW, version 18). It was hoped that the first-order factors would correspond with the subclusters of the SAPI model, and that the higher-order factor would correspond with the expected Emotional Stability trait. Maximum Likelihood was used as the factor extraction method as recommended by Fabrigar, Wegener, MacCallum and Strahan (1999). The number of factors was decided on the basis of the scree-plot, parallel analysis (Monte Carlo PCA for Parallel Analysis, Watkins, 2000), multiple test runs, and theoretical expectation (cf. Costello & Osborne, 2005, Gorsuch, 1983). Factors were rotated according to the oblique Direct Quartimin criterion (cf. Jennrich & Sampson, 1966). A second-order factor analysis was performed on the correlations of the first-order factors, after which a Schmid-Leiman transformation was applied to obtain a hierarchical orthogonal solution (cf. Wolff & Preising, 2005).

The factors and facets of the indigenous Emotional Stability scale were compared across language groups (Germanic, Nguni and Sotho) by means of a coefficient of congruence (Tucker’s phi coefficient). Values above 0.90 were taken to indicate factorial similarity (Van de Vijver & Leung, 1997).

Items for the indigenous Emotional Stability scale were retained on the following basis:

Items that load on factors in a psychologically meaningful way

Items that function equivalently across groups

Items that contribute to covering the full content domain of the trait

Items that contribute to covering the full range of the trait (include items that are easy to agree with and items that are difficult to agree with)

The reliability of scores obtained with the scale was calculated by means of Cronbach’s coefficient alpha (Cronbach, 1951). The concurrent validity of the indigenous Emotional Stability scale was examined by correlating it with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the PANAS (Watson et al., 1988).

CHAPTER 5 RESULTS

5.1 Introduction

This chapter presents the results of the exploratory factor analysis of the Emotional Stability cluster. Subsequent to the data screening and the preliminary data analyses, initial reliability estimates for all facets are reported. The results of the first and second order factor analyses both at facet and item level are stated, and the newly developed indigenous Neuroticism scale is presented. The reliability of the total scale and its subscales is reported followed by the congruence analyses for all comparison groups. Finally, convergent validity with established instruments is stated.

5.2 Data screening

Prior to the main analyses, the data were checked for accuracy, missing values, normality of distribution and univariate and multivariate outliers. One item (i290EGODrightaway) was miscoded and removed from the questionnaire resulting in a total of 325 items (Appendix A). One item (i111ECCpretend) had to be reverse-scored. Plausibility of the data was checked by means of inspecting minimum and maximum values and means and standard deviations. No unexpected values were found across the scoring range (1 to 5). A total of 22 cases (3.6%) with missing values of more than 10 items were removed from further analyses. For the remaining cases the regression approach was used to replace random missing data. The data were satisfactorily distributed with values for skewness < 2 and kurtosis < 4. No multivariate outliers were detected using Mahalanobis distance statistics, leaving 588 cases for the main analyses. Table 5.1 describes the mean, standard deviation, skewness and kurtosis of the 325 items of the Emotional Stability questionnaire.

5.3 Preliminary data analyses

As a first step, it was checked whether each of the items loaded on the first principal component of the entire data set. This analysis revealed 72 items (22.2%) with loadings < .20 on the component. (Table 5.1) Although the high percentage of low loadings indicated that many of the items did not function as expected, it was decided at this point to retain all items

and to check the correlation of each item with its respective facet. However, it was noteworthy that all items of the facet Balancing life showed loadings < .20 on the component matrix, which suggests that these items measure a separate construct.

As a second step, principal component analyses requesting only one component were conducted for each of the 25 facets. The purpose of this analysis was to establish if each of the items loaded on the first component of the facet to which it belongs, and to check if each facet approximated a uni-dimensional construct. On inspection of the scree plots, seven of the facets indicated multidimensionality, namely: Mature, Fearful, Coping, Temperamental, Emotional, Content and Anxious. The scree plots and respective pattern matrices for the multidimensional facets are presented in the appendix (Appendix B). These facets were split into separate facets, producing a total of 33 facets. Specifically, the fact Mature was split into Mature and Obedient, the facet Fearful was split into Neurotic, Fearful of abstract things and Fearful of concrete things, the facet Coping was split into Coping with the help of others and Coping on your own, the facet Temperamental was split into Temperamental and Moody, the facet Emotional was split into Helpless expression of emotion and Pro-active expression of emotion, the facet Content was split into Content with life and possessions and Accepting self and others, and the facet Neurotic was split into Anxious and Fear of commitment. These facets and the items that comprise them constituted the basic units of analysis.

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix

I1BBLfamily 3.93 0.87 -1.06 1.64 -.17 i2BBLfriend 3.80 0.87 -0.63 0.31 -.03 i3BBLattention 3.84 0.88 -0.76 0.70 -.11 i4BBLworkfam 3.97 0.72 -0.73 1.40 -.20 i5BBLhobby 3.58 0.92 -0.53 0.07 -.11 i6BBLsocialize 3.68 0.88 -0.55 0.03 -.08 i7BBLhours 3.20 1.07 -0.24 -0.60 -.14 i8BBLcombine 3.29 0.88 -0.27 -0.36 -.06 i9BBLhealth 3.45 0.89 -0.49 -0.02 -.15

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N= 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i10BBLquality 3.07 1.04 .013 -0.52 .17 i11BBLequal 3.87 0.91 -0.81 0.55 -.10 i12BBLbalance 3.62 0.85 -.048 0.19 -.20 i13BETemostab 3.71 0.90 -0.73 0.54 -.35 i14BETsitumost 3.71 0.90 -0.72 0.52 -.31 i15BETpredict 3.28 0.90 -0.18 -0.33 .00 i16BETcontr 3.75 0.89 -0.57 0.16 -.40 i17BETpref 4.02 0.80 -0.49 -0.11 -.11 i18BETtalk 3.91 0.72 -0.45 0.61 -.32 i19BETreact 3.63 0.88 -0.58 0.55 -.34 i20BETcalmdow 3.53 0.96 -0.47 -0.18 -.33 i21BETmoodsame 2.83 1.03 0.09 -0.56 -.10 i22BETcalmper 3.78 0.87 -0.67 0.43 -.37 i23BETcheerful 3.36 0.97 -0.31 -0.19 -.27 i24BETsimilar 3.03 0.95 -0.09 -0.54 -.13 i25BETsitudiff 3.38 0.88 -0.30 0.04 -.28 i26BETupset 3.64 0.95 -0.53 -0.02 -.09 i27BETexcited 3.06 0.90 -0.02 -0.16 .00 i28BETexprfeel 3.16 1.01 -0.10 -0.53 -.25 i29BETanger 3.40 1.00 -0.50 -0.15 -.39 i30BETmoodbad 3.46 0.98 -0.57 0.10 -.36 i32BMrespdec 4.01 0.69 -0.26 -0.20 -.26 i33BMemomat 3.99 0.81 -0.83 1.24 -.33 i34BMactage 3.75 0.95 -0.59 0.11 -.07 i35BMrole 4.02 0.75 -0.93 2.26 -.21 i36BMactmat 4.06 0.75 -0.63 0.75 -.26 i37BMlosing 3.53 0.94 -0.51 0.08 -.24 i38BMbehave 4.04 0.65 -0.63 1.81 -.27

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i39BMlisten 3.87 0.70 -0.35 0.36 -.21 i40BMapolog 4.14 0.73 -0.60 0.36 -.22 i41BMdress 4.29 0.72 -1.03 2.09 -.22 i42BMadmit 3.95 0.81 -0.44 -0.01 -.25 i44BSTiritate 3.44 1.05 -0.19 -0.69 .40 i45BSTangry 2.96 1.05 0.19 -0.68 .53 i46BSTagress 2.41 1.01 0.53 -0.18 .50 i47BSThateannoy 3.71 0.84 -0.64 0.86 .27 i48BSTshout 2.91 1.12 0.14 -0.73 .42 i49BSTrespect 3.78 0.91 -0.68 0.50 .23 i50BSTbeat 2.23 1.14 0.75 -0.22 .41 i51BSTrepriothers 2.66 0.92 0.30 -0.24 .42 i52BSTlosetemp 2.67 1.05 0.37 -0.43 .56 i53BSTimpatient 2.91 1.02 0.12 -0.46 .50 i54BSTtold 3.03 0.95 -0.10 -0.22 .43 i55BSTupset 2.63 0.98 0.42 -0.28 .63 i56BSTignore 3.11 1.05 -0.06 -0.61 .39 i57BSTunappr 2.80 1.21 0.20 -0.95 .33 i58BSTinterrupt 3.02 0.98 0.12 -0.39 .32 i59BSTsuffer 2.19 1.01 0.78 0.20 .57 i60BSTquestions 2.91 1.11 0.04 -0.69 .50 i61BSTreprime 2.82 0.94 0.11 -0.20 .51 i62BSTannoy 2.90 1.09 0.16 -0.71 .61 i63BSTshorttemp 2.64 1.12 0.42 -0.64 .59 i64BSTfrustrate 2.93 1.11 0.15 -0.80 .62 i65BSTleave 2.49 1.04 0.47 -0.18 .53 i66BSTbother 2.70 1.06 0.22 -0.53 .53 i67BSTprovoke 3.39 0.97 -0.46 -0.04 .37

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i69CCrisks 3.56 0.92 -0.51 0.17 -.09 i70CCdeal 3.39 0.93 -0.24 -0.27 -.16 i71CCface 3.38 0.90 -0.27 -0.04 -.16 i72CCbraveneed 4.12 0.74 -0.78 1.37 -.17 i73CCsitudang 3.22 0.98 -0.08 -0.27 -.06 i74CCconfront 3.53 0.92 -0.30 -0.29 -.20 i75CChandle 3.52 0.97 -0.69 0.36 -.27 i76CCmajlife 3.81 0.84 -0.62 0.73 -.21 i77CCspeakup 3.64 0.92 -0.39 -0.07 -.09 i78CCprotect 3.43 0.90 -0.15 -0.10 -.02 i79CCbelief 4.23 0.71 -0.69 0.74 -.19 i80CCnegcons 3.62 0.88 -0.28 -0.12 .11 i81CCbraveper 3.81 0.79 -0.39 0.25 -.21 i82CCsitudiff 3.80 0.79 -0.43 0.32 -.28 i84CFjudge 3.15 1.08 -0.00 -0.73 .46 i85CFfailure 3.85 1.03 -0.76 0.04 .29 i86CFsafety 3.83 0.74 -0.38 0.33 -.05 i87CFreject 3.55 1.06 -0.36 -0.61 .39 i88CFsitumany 3.38 0.93 -0.06 -0.46 .51 i89CFintimidate 2.66 1.04 0.55 -0.38 .58 i90CFpressure 3.15 1.08 -0.00 -0.68 .44 i91CFhealthown 3.77 0.97 -0.57 -0.10 .02 i92CFhealthother 3.64 0.92 -0.64 0.39 -.04 i93CFhurtemotion 4.09 0.96 -1.00 0.67 .23 i94CFhurtphysic 3.95 1.10 -0.94 0.13 .14 i95CFbadthing 3.68 0.98 -0.43 -0.32 .37 i96CFnewthing 2.46 0.99 0.56 0.04 .48 i97CFdiffrelax 2.51 1.00 0.64 0.02 .48

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i98CFunfcircum 3.26 0.94 -0.11 -0.25 .46 i99CFscaredquick 2.91 1.04 0.23 -0.68 .49 i100CFanimal 2.72 1.26 0.33 -0.97 .26 i101CFdark 2.58 1.28 0.44 -0.90 .26 i102CFworryself 3.16 1.11 -0.05 -0.84 .52 i103CFworryother 3.71 0.82 -0.51 0.56 .15 i104CFscaredeasi 2.87 1.08 0.29 -0.67 .51 i105CFafraidpeop 3.03 1.06 -0.20 -0.74 .40 i106CFavoidclose 3.02 1.16 0.04 -0.90 .41 i107CFlockdoor 3.54 1.12 -0.37 -0.78 .15 i108ECCdeal 3.81 0.79 -.063 0.92 -.20 i109ECCcope 3.78 0.76 -0.56 0.83 -.27 i110ECCspeakfeel 3.64 1.01 -0.70 0.30 -.16 i111ECCpretend 2.86 1.08 0.12 -0.67 -.18 i112ECCsupport 3.63 0.99 -0.53 -0.02 -.02 i113ECCtalkpeop 3.75 0.92 -0.64 0.38 -.14 i114ECClookgood 3.75 0.86 -0.51 0.25 -.25 i115ECChandle 4.02 0.69 -0.41 0.28 -.26 i116ECCadvice 3.83 0.88 -0.67 0.51 -.09 i117ECCplan 3.89 0.74 -0.54 0.68 -.19 i118ECCbusy 3.56 0.99 -0.37 -0.47 .19 i120ECIspeakthink 2.88 1.13 0.18 -0.66 .33 i121ECIreactimm 3.39 0.82 -0.06 -0.24 .17 i122ECIeffect 2.73 1.03 0.44 -0.39 .53 i123ECIbehavirr 2.20 1.04 0.82 0.23 .45 i124ECIaffectothers 2.42 0.98 0.57 0.08 .51 i125ECInothink 2.60 1.06 0.29 -0.62 .51 i126ECIspontaneous 3.26 0.87 -0.21 0.07 .16

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation Matrix i127ECIinterrupt 2.52 0.95 0.45 -0.09 .40 i128ECIcontremo 2.61 0.99 0.58 -0.10 .62 i129ECItalknot 2.60 1.03 0.47 -0.26 .44 i130ECIreactint 2.98 0.87 0.20 0.09 .42 i131ECIurge 2.70 0.98 0.40 -0.24 .61 i132ECItemptation 2.80 1.03 0.23 -0.42 .47 i133ECInotknow 2.71 1.02 0.33 -0.40 .56 i134ECIregret 2.87 1.02 0.04 -0.35 .53 i135ECIactimpul 2.84 0.92 0.20 -0.03 .47 i137ECOsameorder 2.95 0.99 0.10 -0.57 .29 i138ECOroutine 3.17 1.00 -0.09 -0.65 .27 i139ECOwashhand 3.29 1.07 -0.30 -0.59 .10 i140ECOorderfeel 3.53 1.00 -0.39 -0.43 .23 i141ECOtidy 3.31 1.10 -0.19 -0.74 .19 i142ECOschedule 3.00 1.04 0.08 -0.66 .25 i143ECPexplain 3.71 0.90 -0.52 0.13 -.08 i144ECPdiscuss 3.94 0.81 -0.54 0.04 -.28 i145ECPfrustrate 3.42 0.92 -0.20 -0.31 -.30 i146ECPturn 3.63 0.85 -0.31 -0.06 -.28 i147ECPlisten 4.03 0.74 -0.73 1.04 -.23 i148ECPbear 4.16 0.74 -0.94 1.99 -.20 i149ECPpatient 3.66 0.99 -0.68 0.30 -.29 i150ECPwait 3.73 0.83 -0.50 0.35 -.25 i151ECPchance 3.80 0.84 -0.70 0.86 -.05 i152ECPtease 3.40 0.90 -0.32 -0.08 -.11 i153ECPnotlike 3.39 0.92 -0.42 -0.22 -.10 i154ECPweakness 3.70 0.77 -0.43 0.44 -.18 i155ECPtime 3.77 0.70 -0.72 1.57 -.23

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i156ECPsureunderst 3.98 0.68 -0.59 1.29 -.21 i157ECPfaceprobl 3.62 0.84 -0.35 0.04 -.24 i159ECTmoody 2.82 1.11 0.19 -0.70 .53 i160ECTdowhatever 2.83 0.98 0.33 -0.37 .52 i161ECTcontrolemo 2.80 1.02 0.25 -0.41 .55 i162ECTtreatbad 1.99 1.00 1.12 1.06 .58 i163ECTissueirrit 2.54 1.06 0.43 -0.40 .65 i164ECTissueangr 2.46 1.06 0.61 -0.13 .67 i165ECTactmood 2.76 1.06 0.20 -0.54 .60 i166ECTcannotdo 3.04 0.97 0.00 -0.45 .42 i167ECTsayinappr 2.44 1.00 0.59 0.05 .57 i168ECTloseinterest 2.94 1.04 020 -0.60 .51 i169ECTchangemood 2.78 1.10 0.18 -0.72 .50 i170ECTdrivenmood 2.53 1.04 0.45 -0.35 .64 i171ECTfriendly 2.70 1.10 0.22 -0.76 .58 i172ECTwakeup 3.13 1.08 -0.27 -0.61 .43 i173ECThappysad 3.26 1.04 -0.43 -0.42 .48 i174ECTwalkaway 3.41 0.96 -0.54 -0.01 .18 i175ECTswings 2.75 1.07 0.27 -0.70 .56 i176ESEMgivein 2.81 1.02 0.15 -0.55 .60 i177ESEMfeeldeep 3.52 0.99 -0.53 -0.06 .28 i178ESEMbreak 2.71 1.10 0.38 -0.63 .60 i179ESEMcryeasi 3.11 1.29 -0.03 -1.14 .42 i180ESEMbodylang 3.39 0.94 -0.21 -0.15 .25 i181ESEMopenanger 2.97 0.99 0.18 -0.52 .36 i182ESEMfacial 3.46 0.89 -0.35 0.07 .28 i183ESEMnasty 2.99 0.99 -0.01 -0.45 .48 i184ESEMcryangry 3.22 1.24 -0.25 -0.91 .34

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i185ESEMcrysad 3.56 1.19 -0.66 -0.36 .33 i186ESEMcryhappy 2.60 1.16 0.32 -0.69 .24 i187ESEMshowemo 3.22 1.02 -0.25 -0.48 .32 i188ESEMexprfeel 3.60 0.89 -0.37 -0.03 .04 i189ESEMemotinal 3.33 1.07 -0.19 -0.65 .41 i190ESEMcare 3.61 0.89 -0.43 -0.04 .29 i191ESEMnoreason 2.36 1.16 0.67 -0.30 .53 i192ESEMannoy 3.45 0.85 -0.40 0.25 .32 i194ESEXoverreact 2.80 0.99 0.18 -0.37 .62 i195ESEXgoodthing 3.65 0.96 -0.40 -0.40 .20 i196ESEXbadthing 2.22 0.98 0.80 0.35 .43 i197ESEXexagfeel 2.62 0.93 0.48 0.00 .54 i198ESEXexagthing 2.65 0.97 0.36 -0.16 .52 i199ESEXactexag 2.46 0.97 0.67 0.27 .52 i200ESSEminor 2.85 1.01 0.11 -0.47 .55 i201ESSEtalkbehind 3.46 1.12 -0.32 -0.74 .34 i202ESSEpersonal 3.22 0.92 -0.05 -0.23 .54 i203ESSEhurteasi 3.29 1.10 -0.11 -0.87 .52 i204ESSEbadnews 3.06 1.03 0.24 -0.64 .50 i205ESSEhurtlaugh 3.06 1.03 0.00 -0.62 .49 i206ESSEupset 2.94 1.03 0.29 -0.64 .63 i207ESSEoffend 3.43 0.96 -0.28 -0.31 .42 i208ESSEmovie 3.65 1.02 -0.53 -0.16 .23 i209ESSHembarrass 3.27 1.02 -0.12 -0.52 .53 i210ESSHashamed 2.98 1.06 0.16 -0.69 .55 i211ESSHhumiliate 2.74 1.01 0.37 -0.50 .57 i212NCPcomplevery 2.41 1.00 0.63 -0.02 .62 i213NCPdissat 2.97 0.90 0.00 -0.24 .51

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i214NCPcomplway 3.15 0.96 -0.07 -0.61 .52 i215NCpget 2.43 0.96 0.78 0.57 .47 i216NCPappear 2.79 0.92 0.20 -0.25 .37 i217NCPnag 2.28 0.94 0.84 0.61 .60 i218NCPpoint 2.88 1.00 0.17 -0.48 .45 i219NCPnotlike 3.34 0.92 -0.21 -0.32 .39 i220NCPdifficult 2.96 0.96 0.06 -0.52 .53 i222NCTsatisfilife 3.62 0.93 -0.58 0.26 -.28 i223NCTsatisdo 3.77 0.88 -0.66 0.49 -.27 i224NCTsatiswork 3.75 0.88 -0.62 0.41 -.18 i225NCTpleasehave 3.95 0.83 -0.63 0.40 -.22 i226NCTaccept 3.67 0.87 -0.33 -0.18 -.17 i227NCTsatishome 3.98 0.97 -0.93 0.56 -.09 i228NCTfamily 4.15 0.95 -1.18 1.25 -.21 i229NCTnotwork 3.60 0.83 -0.33 0.20 -.15 i230NCTachieve 3.73 0.94 -0.59 0.11 -.17 i231NCTweakness 3.60 0.87 -0.60 0.32 -.16 i232NCTothers 3.55 0.77 -0.28 0.38 -.11 i233NCTnotperfect 3.62 0.84 -0.63 0.53 -.12 i235NDproblem 3.66 0.77 -0.64 0.88 .16 i236NDaffected 3.79 0.85 -0.47 0.14 .16 i237NDdepressed 2.67 1.12 0.33 -0.56 .55 i238NDnotdoany 3.14 1.00 -0.05 -0.41 .51 i239NDmiserable 2.44 1.06 0.62 -0.14 .63 i240NDdesperate 2.30 1.04 0.65 -0.05 .55 i241NDhelpless 2.32 1.06 0.62 -0.17 .67 i242NDsad 2.82 1.11 0.09 -0.80 .60 i243NDjoy 1.96 1.04 1.16 0.91 .60

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i244NDinterest 1.95 1.09 1.17 0.71 .57 i245NDworthless 1.91 1.05 1.20 0.96 .61 i246NNrelationship 2.49 1.27 0.47 -0.82 .44 i247NNcommitment 2.50 1.27 0.55 -0.75 .43 i248NNtrust 3.00 1.13 0.04 -0.72 .36 i249NNlove 2.55 1.27 0.56 -0.76 .43 i250NNanxious 2.82 0.99 0.25 -0.33 .61 i251NNthreaten 2.79 0.99 0.24 -0.38 .54 i252NNfearworst 2.98 1.06 0.06 -0.66 .49 i253NNnervous 2.95 1.01 0.09 -0.72 .57 i254NNpanic 2.74 1.05 0.39 -0.51 .62 i255NTsmallthing 2.90 1.05 0.22 -0.66 .63 i256NTnervous 2.64 1.06 0.45 -0.46 .59 i257NYstressed 2.98 1.11 0.16 -0.81 .59 i258NTtense 2.65 1.01 0.50 -0.27 .66 i259NTproblems 2.52 0.93 0.64 0.31 .68 i260NTrelax 2.52 1.02 0.61 -0.14 .58 i261EGOAseek 2.66 1.00 0.24 -0.45 .52 i262EGOAnotice 2.98 1.08 -0.05 -0.74 .37 i263EGOAadmire 3.06 1.05 0.05 -0.72 .33 i264EGOArecognition 3.11 1.01 -0.09 -0.49 .39 i265EGOAcentre 2.38 1.02 0.63 -0.02 .45 i266EGOApraise 2.74 1.08 0.28 -0.63 .42 i267EGOAlisten 3.58 0.92 -0.58 0.32 .20 i268EGOAfocus 2.73 1.00 0.36 -0.33 .40 i269EGOAimpress 2.73 1.02 0.30 -0.30 .44 i270EGOAsympathy 2.51 1.03 0.42 -0.39 .46 i271EGOAlike 3.34 0.99 -0.45 -0.16 .32

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i272EGOArespect 4.11 0.81 -1.05 1.77 .03 i273EGOAlook 3.04 1.02 -0.02 -0.41 .37 i275EGODlisten 3.57 0.87 -0.50 0.23 .14 i276EGODobey 2.92 1.01 0.18 -0.45 .32 i277EGODdomore 2.84 1.02 0.27 -0.46 .29 i278EGODdotold 2.85 1.01 0.19 -0.45 .31 i279EGODdevote 2.51 1.00 0.54 -0.05 .44 i280EGODplease 2.66 1.08 0.37 -0.55 .47 i281EGODentertain 2.59 1.03 0.40 -0.25 .48 i282EGODmyway 2.80 0.99 0.14 -0.41 .46 i283EGODapologize 3.86 0.82 -0.79 1.24 .07 i284EGODdothings 2.72 0.94 0.26 -0.21 .54 i285EGODdelay 2.23 1.00 0.90 0.53 .46 i286EGODlistenonly 2.70 1.05 0.22 -0.70 .44 i287EGODtell 2.43 0.94 0.57 0.12 .48 i288EGODexhaust 2.34 0.94 0.57 0.03 .52 i289EGODdrain 2.41 1.24 0.92 -0.09 .29 i292EGONaskopinion 3.30 0.91 -0.21 -0.23 .24 i293EGONaccompany 2.47 0.99 0.43 -0.33 .50 i294EGONlike 2.96 0.97 0.06 -0.46 .46 i295EGONapproval 2.71 1.00 0.29 -0.51 .47 i296EGONplease 2.61 1.00 0.34 -0.41 .46 i297EGONappreciate 3.64 0.92 -0.65 0.33 .23 i298EGONaccept 3.38 0.93 -0.31 -0.22 .28 i299EGONdependopinion 2.55 0.96 0.40 -0.22 .48 i300EGONencourage 2.94 0.97 0.07 -0.54 .45 i301EGONcare 2.56 1.01 0.38 -0.37 .42 i302EGONhelp 2.57 0.96 0.38 -0.22 .46

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i303EGONdependothers 2.41 1.00 0.46 -0.18 .50 i304EGONthink 2.88 1.00 0.09 -0.49 .55 i305EGONknowwell 2.79 1.08 0.15 -0.71 .43 i306EGONaprovedo 2.76 1.03 0.20 -0.57 .47 i308EGOSCsecureability 3.79 0.78 -0.81 1.56 -.22 i309EGOSCtrustability 3.96 0.76 -0.67 1.03 -.27 i310EGOSCsuperior 2.79 1.01 0.39 -0.40 .26 i311EGOSCselfassured 3.73 0.81 -0.46 0.34 -.26 i312EGOSCselfimage 3.82 0.86 -0.70 0.67 -.29 i313EGOSCselfesteem 3.65 0.95 -0.50 -0.06 -.34 i314EGOSCunfamsitu 3.19 0.88 0.01 0.00 -.08 i315EGOSCbelieve 4.08 0.82 -0.82 0.78 -.38 i316EGOSCoverconfident 3.10 1.07 0.12 -0.77 -.04 i317EGOSCaccept 4.14 0.80 -0.80 0.68 -.36 i318EGOSCknowwant 4.16 0.84 -1.07 1.45 -.35 i319EGOSCknowbest 4.07 0.82 -0.72 0.52 -.24 i320EGOSCconfident 3.88 0.86 -0.61 0.40 -.32 i321EGOSCachieve 3.87 0.81 -0.34 -0.07 -.28 i322EGOSCsecureself 3.92 0.83 -0.61 0.29 -.37 i324EGOSRrespect 4.28 0.73 -1.00 1.63 -.39 i325EGOSRmostimport 3.60 1.17 -0.37 -0.86 -.11 i326EGOSRlove 4.22 0.86 -0.97 0.55 -.30 i327EGOSRappearance 4.25 0.71 -0.57 -0.23 -.21 i328EGOSRbodylike 3.77 1.07 -0.62 -0.23 -.24 i329EGOSRcompliment 4.06 0.87 -0.78 0.25 -.25 i330EGOSRtime 4.04 0.86 -0.70 0.22 -.24 i331EGOSRhome 4.05 0.82 -0.66 0.46 -.17 i332EGOSRgoodpers 4.30 0.72 -0.94 1.34 -.25

Table 5.1 Descriptive statistics for the 325 items of the Emotional Stability cluster (N = 588)

Std. Component Item Mean Skewness Kurtosis Deviation matrix i333EGOSRbodycare 4.10 0.86 -0.89 0.77 -.30 i334EGOSRspeak 4.03 0.74 -0.40 -0.01 -.33 i335EGOSRhealth 3.92 0.87 -0.67 0.45 -.27 i336EGOSRlookmyself 4.16 0.74 -0.82 1.36 -.30 i337EGOSRtrust 3.99 0.86 -0.56 0.01 -.26 i338EGOSRrespectbody 4.27 0.75 -0.95 1.15 -.26 i339EGOSRlikemyself 4.27 0.77 -1.06 1.59 -.30 i340EGOSRharmful 3.98 0.85 -0.54 -0.06 -.12 Note. Loadings on the component matrix < .20 are indicated in boldface.

5.4 Reliability

A total score was calculated for each of the 33 facets and the internal consistency as reflected by Cronbach’s Alpha was determined. The initial estimates of reliability suggested good internal consistency with Cronbach’s Alpha ranging above .70 for all but one facet, namely Obedient. Detailed results are presented in Table 5.2. In addition to reliability coefficients, this table indicates for each facet items with loadings lower than .30 on the first unrotated factor of that facet. These items were removed from further analyses. The table also shows, which items were removed from the facet to increase reliability and indicates the reliability coefficients after these removals.

Table 5.2 Alpha coefficients of the 33 facets (N = 588) Items Items Original removed removed Facet number of to Cronbach’s α with loading items increase < .30 reliability Balancing Life 12 i10 i11 .81

Table 5.2 Alpha coefficients of the 33 facets (N = 588) Items Items Original removed removed Facet number of to Cronbach’s α with loading items increase < .30 reliability i15, i21, i26, Even-tempered 18 i17 .89 i27 Mature 11 Mature 7 .81 Obedient 4 i37 .66 Short-tempered 24 .92 Courageous 14 .86 Fearful 1 24 i86, i91, i92 Neurotic 8 .82 Fear of abstract things 5 .75 Fear of concrete things 6 i107 .80 Coping 11 i111, i118 Coping with help of others 4 .81 Coping on your own 5 .73 Impulsive 16 i121 .91 Obsessive compulsive 6 .82 Patient 15 .86 Temperamental 17 i174 Temperamental 9 .88 Moody 7 .87 Emotional 17 Helpless expression of emotion 9 .88 Pro-active expression of 8 .77 emotion Exaggerating 6 i195, i196 .85 Sensitive 9 i208 .86 Ashamed 3 .86

Table 5.2 Alpha coefficients of the 33 facets (N = 588) Items Items Original removed removed Facet number of to Cronbach’s α with loading items increase <.30 reliability Complaining 9 .84 Content 12 Content with life and 8 .85 possessions Accepting self and others 4 .72 Depressive 11 i235, i236 .92 Neurotic 9 Anxious 5 .85 Fear of commitment 4 .88 Tensed 6 .88 Attention-seeking 13 i272 .91 i275, i283, Demanding 15 .91 i289 Needy 15 i297 .90 Self-confident 15 i310 314, i316 .92 Self-respectful 17 i325 .94 1 Items i103CFworryother and i106CFavoidclose did not load > .30 in the three-factor solution.

5.5 Factor analysis

Upon removal of unsatisfactory items the 33 facets were subjected to a maximum likelihood factor analysis with oblique (Direct Quartimin) rotation. The aim of this analysis was to check if each of the facets contributed toward the definition of a higher order factor. The inspection of the scree plot suggested that four to six factors should be retained. A parallel analysis showed that four eigenvalues were greater than the eigenvalues of random data, suggesting that four factors should be retained (Figure 5.1). Thus, two-, three-, four-, five-, and six- factor solutions were examined. The four-factor solution seemed to be the psychologically most appropriate. This solution was subjected to a higher order factor analysis with the

Schmid-Leimann transformation to determine if a higher order factor was present among the 33 facets. The results of the Schmid-Leiman transformed solution are presented in Table 5.3.

6 Random eigenvalue Sample eigenvalue

0 0 5 10 15 20 25 30 35

Figure 5.1. Scree plot and parallel analysis of the 33 facets.

Table 5.3 Hierarchical Schmid-Leiman Solution for the 33 facets (N = 588)

Higher Order Factor Facet Factor 1 2 3 4 Even-tempered -.28 -.18 .44 -.03 .43 Self-confident -.21 -.07 .71 -.02 -.13 Self-respectful -.18 .12 .64 -.12 -.10 Mature -.18 .06 .54 -.09 .02 Patient -.17 .09 .57 -.09 .23 Obedient -.16 .08 .41 -.11 .10 Coping on your own -.14 -.12 .70 .07 .08 Content with life and possessions -.14 .00 .55 -.03 -.08 Accepting self and others -.06 .03 .45 .00 -.02

Table 5.3 Hierarchical Schmid-Leiman Solution for the 33 facets (N = 588)

Higher Order Factor Facet Factor 1 2 3 4 Balancing life -.06 -.10 .47 .09 .07 Courageous -.05 -.22 .61 .19 .02 Coping with help of others -.03 .10 .49 -.01 -.12 Obsessive/compulsive .31 .32 .29 .10 .16 Fearful of abstract things .31 .53 .09 -.06 -.10 Fear of commitment .38 .19 -.23 .17 .30 Fearful of concrete things .41 .53 .04 .01 .00 Helpless expression of emotion .45 .45 .10 .08 -.29 Attention-seeking .46 .12 .08 .31 .15 Pro-active expression of emotion .48 .22 .18 .26 -.49 Ashamed .50 .48 -.09 .09 .03 Demanding .54 .06 .11 .42 .19 Needy .54 .26 .00 .29 .21 Sensitive .57 .51 .00 .14 -.15 Neurotic .58 .59 -.15 .08 .00 Exaggerating .58 .11 -.02 .39 -.06 Moody .58 .10 -.16 .36 -.21 Depressive .59 .29 -.26 .27 .20 Impulsive .60 -.03 -.08 .47 -.08 Anxious .60 .58 -.08 .12 .14 Short-tempered .62 .20 -.09 .35 -.26 Tensed .63 .54 -.17 .15 .08 Complaining .63 .23 -.06 .35 .08 Temperamental .68 .01 -.14 .50 -.26 Note. Factors with loadings > .30 are indicated in boldface.

Table 5.3 indicates that several facets did not load on the higher order factor. Each of these facets loaded on group factor 2. This result suggests that, contrary to expectations, the 33

facets do not reflect a single higher order factor, but rather indicate the presence of at least two higher order factors. Group factor 2 consists of 12 facets that indicate good adjustment and psychological health (e.g. patient, courageous, and self-confident). In contrast, group factors 1, 3 and 4 are defined by 21 facets that reflect traits more traditionally associated with Neuroticism. This finding is in line with the theory underlying the PANAS (Watson et al., 1988), which treats PA and NA as two separate constructs. At this point the 12 facets that loaded on group factor 2 were separated from the 21 Neuroticism facets, and the two sets of facets were subsequently analysed separately. The 12 facets loading on group factor 2 were not considered in the remainder of this dissertation as they appear to fall outside the scope of Neuroticism.

5.5.1 Neuroticism at facet level

Next, the 21 Neuroticism facets were subjected to a maximum likelihood factor analysis with oblique (Direct Oblimin) rotation. The purpose of this analysis was to identify facets that possibly do not contribute toward the definition of a higher order Neuroticism factor. Inspection of the scree plot suggested that four factors should be retained. A parallel analysis showed that three eigenvalues were greater than the eigenvalues of random data, suggesting that three factors should be retained (Figure 5.2). Thus, three-, and four-factor solutions were examined. The pattern matrix of the four-factor solution indicated that factor 4 was poorly defined with many facets overlapping with facets of factor 1. The pattern matrix of the three- factor solution produced three clearly defined factors, yielding a psychological interpretable solution (Table 5.4).

Figure 5.2. Scree plot and parallel analysis of the 21 Neuroticism facets.

Table 5.4 Pattern matrix for the 21 Neuroticism facets (N = 588) Factor Facet 1 2 3 Neurotic .76 -.14 .00 Anxious .71 -.02 .21 Tensed .68 -.17 .12 Fearful of concrete things .65 .04 .05 Fearful of abstract things .65 .11 -.02 Sensitive .63 -.21 .03 Ashamed .61 -.11 .06 Helpless expression of emotion .58 -.20 -.11 Depressive .34 -.28 .25 Temperamental -.04 -.92 .06 Moody .10 -.67 .05 Impulsive -.09 -.64 .27 Short-tempered .23 -.60 .05 Pro-active expression of emotion .27 -.49 -.09 Exaggerating .08 -.44 .30 Demanding -.12 -.16 .77 Attention-seeking -.01 -.04 .68 Needy .20 -.07 .57 Complaining .20 -.29 .44 Fear of commitment .18 -.07 .34 Obsessive/ compulsive .30 .14 .33 Note. Factors with loadings > .30 are indicated in boldface.

Based on psychological interpretability, the three-factor solution seemed to be the most appropriate. The correlations between the factors were subjected to a higher order factor analysis and a hierarchical solution was obtained by means of the Schmid-Leiman transformation. The results of this transformed Schmid-Leiman solution are presented in Table 5.5.

Table 5.5 Hierarchical Schmid-Leiman Solution for the 21 Neuroticism facets (N = 588) Higher Factor Facet order factor 1 2 3 Neurotic .66 .51 -.10 .00 Anxious .68 .48 -.01 .15 Tensed .70 .46 -.12 .08 Fearful of concrete things .49 .44 .03 .03 Fearful of abstract things .39 .44 .08 -.01 Sensitive .63 .43 -.15 .02 Ashamed .57 .41 -.08 .04 Helpless expression of emotion .49 .40 -.14 -.08 Depressive .62 .23 -.20 .18 Obsessive/compulsive .36 .21 .10 .24 Pro-active expression of emotion .48 .18 -.35 -.06 Short-tempered .63 .16 -.43 .04 Complaining .66 .14 -.21 .31 Needy .60 .14 -.05 .41 Fear of commitment .42 .12 -.05 .24 Moody .57 .07 -.48 .03 Exaggerating .58 .05 -.32 .21 Attention-seeking .50 -.01 -.03 .48 Temperamental .66 -.03 -.66 .04 Impulsive .57 -.06 -.45 .19 Demanding .57 -.08 -.11 .55 Note. Factors with loadings > .30 are indicated in boldface.

Table 5.5 indicates that the Schmid-Leiman transformation produced a well-defined higher order factor with three clearly defined group factors. Group factor 1 consisting of the facets Neurotic, Anxious, Tensed, Fearful of abstract things, Fearful of concrete things, Sensitive, Ashamed, and Helpless expression of emotion, indicates neurotic characteristics. Group factor 2 consisting of Pro-active expression of emotion, Short-tempered, Moody, Exaggerating, Temperamental and Impulsive, describes mood. Group factor 3 consisting of the facets Complaining, Needy, Attention-seeking, and Demanding characterises immaturity. The facet

Obsessive/compulsive had a factor loading < .40 on the higher order factor and no loadings > .30 on the first-order factors, suggesting that it is not a strong indicator of Neuroticism. The facets Depressive and Fear of commitment did not have first-order factor loadings > .30 on the Schmid-Leiman solution suggesting that their shared variance is mostly explained by the higher order factor. At this point a decision was made to retain all 21 facets in line with theoretical expectation, and to shift the focus from facet dimensionality to item dimensionality.

5.5.2 Neuroticism at item level

In a first step, all items with low loadings on the individual facets, and items whose removal would increase the reliability of the facets as per Table 5.2 were removed. Thereafter, a principal component analysis was conducted on the remaining items, and items with loadings < .30 on the first unrotated component were removed. This resulted in a total of 169 items. These items were subjected to a maximum likelihood factor analysis with oblique (Direct Oblimin) rotation. Inspection of the scree plot suggested that six factors should be retained. A parallel analysis showed that thirteen eigenvalues were greater than the eigenvalues of random data (Figure 5.3). However, it is noteworthy that the differences between the eigenvalues seven to thirteen and the random data ranged from .757 to .040, suggesting that thirteen factors may possibly be too many to be retained. Thus six-, seven-, eight-, nine-, ten-, eleven-, twelve-, and thirteen-factor solutions were examined. Based on psychological interpretability, the six-factor solution appeared to be the most appropriate. The factor correlation matrix for the six factors indicated moderate inter-correlations (.078 to .390), suggesting that the factors are related but distinct. The correlations between the factors were subjected to a higher order factor analysis, which was transformed to a hierarchical solution with the Schmid-Leiman transformation. The results of this transformed Schmid-Leiman solution are presented in table 5.6.

45 40 35 30 25 Random eigenvalue 20 Sample eigenvalue 15 10 5 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17

Figure 5.3. Scree plot and parallel analysis of the 169 Neuroticism items (only the first 17 roots are displayed).

Table 5.6

Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items (N = 588) Higher order Factor Facet Factor 1 2 3 4 5 6 i100CFanimal .25 -.11 .31 -.12 -.10 -.02 .38 i101CFdark .25 -.03 .16 -.10 -.11 -.03 .38 i102CFworryself .44 -.06 -.10 .05 -.22 .12 .37 i104CFscaredeasi .44 -.00 .14 -.06 -.19 .00 .48 i105CFafraidpeop .34 -.01 .04 .06 -.11 .05 .28 i106CFavoidclose .34 -.10 .03 .01 -.27 .15 .07 i120ECIspeakthink .25 .42 -.01 .00 -.01 -.01 .01 i122ECIeffect .42 .50 .00 -.03 -.03 .09 .08 i123ECIbehavirr .35 .53 .06 -.04 -.12 -.04 -.02 i124ECIaffectothers .41 .51 .02 .04 -.04 .04 .02 i125ECInothink .40 .51 .04 .00 -.06 .03 .04 i127ECIinterrupt .33 .47 .15 .09 .04 -.03 .03 i128ECIcontremo .50 .38 -.03 .06 -.11 .10 .15 i129ECItalknot .36 .48 .10 .04 .01 .02 .02 i130ECIreactint .36 .35 .11 .01 .02 .14 .04 i131ECIurge .50 .47 .04 .05 -.03 .15 .08

Table 5.6 Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items (N = 588) Higher order Factor Facet Factor 1 2 3 4 5 6 i132ECItemptation .37 .46 .03 .05 -.01 .05 .02 i133ECInotknow .45 .40 -.03 .07 -.10 .06 .10 i134ECIregret .40 .37 -.13 .09 -.08 .05 .12 i135ECIactimpul .39 .39 .09 -.00 -.02 .11 .06 i137ECOsameorder .27 -.06 .13 .12 -.11 .07 .06 i138ECOroutine .27 -.02 .21 .11 -.08 -.02 .15 i142ECOschedule .28 -.10 .24 .14 -.13 -.04 .15 i159ECTmoody .44 .25 -.15 .07 -.09 .33 -.06 i160ECTdowhatever .43 .31 .03 -.02 -.01 .29 .02 i161ECTcontrolemo .45 .35 -.13 .06 -.05 .23 .07 i162ECTtreatbad .48 .46 .02 .03 -.13 .18 -.10 i163ECTissueirrit .52 .28 -.11 .08 -.05 .36 .03 i164ECTissueangr .56 .29 -.07 .04 -.09 .36 .06 i165ECTactmood .50 .30 -.04 .08 .00 .34 .04 i166ECTcannotdo .34 .15 -.05 .10 .05 .34 -.06 i167ECTsayinappr .46 .49 .01 .03 -.01 .22 -.06 i168ECTloseinterest .42 .18 -.01 .05 -.09 .27 .00 i169ECTchangemood .42 .23 -.04 .16 -.07 .19 -.01 i170ECTdrivenmood .52 .33 -.12 .11 -.06 .29 .02 i171ECTfriendly .47 .23 -.04 .08 -.12 .30 -.07 i172ECTwakeup .36 .09 -.19 .15 -.05 .29 .01 i173ECThappysad .40 .04 -.20 .20 -.06 .27 .08 i175ECTswings .46 .20 -.18 .10 -.08 .30 .06 i176ESEMgivein .49 .27 -.10 .06 .04 .26 .28 i178ESEMbreak .49 .26 -.07 -.03 -.07 .07 .49 i179ESEMcryeasi .35 .12 .03 -.03 .09 -.03 .68 i181ESEMopenanger .33 .09 .21 -.05 .08 .26 .16 i183ESEMnasty .41 .08 .16 .07 .08 .36 .07 i184ESEMcryangry .29 .08 .02 -.04 .07 -.02 .58 i185ESEMcrysad .26 .07 -.07 .02 .13 -.01 .60

Table 5.6 Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items (N = 588) Higher order Factor Facet Factor 1 2 3 4 5 6 i187ESEMshowemo .27 .19 .02 -.03 .17 .04 .49 i189ESEMemotinal .35 .16 -.05 .00 .12 .03 .60 i190ESEMcare .25 .09 -.04 .08 .17 .00 .51 i191ESEMnoreason .45 .28 .07 -.03 -.09 .02 .33 i192ESEMannoy .28 .07 .10 .07 .16 .26 .16 i194ESEXoverreact .51 .28 -.05 .09 -.03 .23 .18 i197ESEXexagfeel .46 .40 .15 .07 -.02 .00 .20 i198ESEXexagthing .44 .35 .09 .08 -.07 .03 .12 i199ESEXactexag .45 .42 .15 .06 -.11 -.01 .06 i200ESSEminor .47 .13 -.07 .13 -.09 .18 .21 i201ESSEtalkbehind .30 -.01 -.19 .28 -.01 .07 .23 i202ESSEpersonal .45 .12 -.21 .24 .00 .17 .27 i203ESSEhurteasi .44 .05 -.11 .12 -.01 .07 .53 i204ESSEbadnews .44 .06 .07 .07 -.09 .06 .37 i205ESSEhurtlaugh .44 -.08 .00 .27 -.13 .03 .30 i206ESSEupset .53 .08 -.07 .12 -.08 .18 .39 i207ESSEoffend .39 -.10 -.13 .37 -.04 .08 .27 i209ESSHembarrass .46 -.06 -.07 .18 -.16 .08 .37 i210ESSHashamed .48 -.03 -.01 .12 -.22 .09 .30 i211ESSHhumiliate .49 .03 -.01 .13 -.26 .08 .22 i212NCPcomplevery .51 .27 .12 .04 -.22 .08 .09 i213NCPdissat .44 .08 .11 .16 -.15 .13 .05 i214NCPcomplway .45 -.04 .25 .13 -.04 .22 .16 i215NCpget .40 .16 .15 -.03 -.33 -.01 .02 i216NCPappear .33 .13 .18 .02 -.07 .11 .06 i217NCPnag .52 .31 .21 .00 -.25 .02 .07 i218NCPpoint .40 .18 .22 .06 -.10 .09 .04 i219NCPnotlike .33 -.03 .08 .20 -.01 .16 .10 i220NCPdifficult .45 .05 .14 .10 -.15 .04 .27 i237NDdepressed .47 .11 -.02 .02 -.42 .03 .07

Table 5.6 Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items (N = 588) Higher order Factor Facet Factor 1 2 3 4 5 6 i238NDnotdoany .43 .07 -.05 .01 -.30 .13 .10 i239NDmiserable .54 .14 .02 -.01 -.48 .09 .00 i240NDdesperate .48 .06 .09 -.01 -.46 .06 .01 i241NDhelpless .57 .13 -.02 .01 -.53 .05 .04 i242NDsad .50 .00 -.09 .05 -.38 .10 .19 i243NDjoy .51 .18 .09 -.05 -.53 .01 -.04 i244NDinterest .48 .23 .07 -.05 -.49 .01 -.09 i245NDworthless .51 .24 .05 -.01 -.51 -.06 .00 i246NNrelationship .37 .02 .02 .10 -.41 .00 -.08 i247NNcommitment .37 .03 .09 .11 -.37 .03 -.12 i248NNtrust .31 -.10 -.01 .03 -.35 .13 -.07 i249NNlove .37 .01 .06 .10 -.40 .00 -.08 i250NNanxious .52 -.03 -.04 .12 -.32 .13 .19 i251NNthreaten .49 -.02 .12 .10 -.32 .01 .23 i252NNfearworst .44 -.08 .14 .08 -.25 .01 .31 i253NNnervous .52 -.13 .02 .11 -.27 .08 .39 i254NNpanic .56 -.04 .06 .04 -.32 .04 .43 i255NTsmallthing .54 -.01 -.05 .05 -.28 .10 .39 i256NTnervous .53 -.05 .03 .03 -.33 .06 .38 i257NYstressed .51 -.10 -.08 .09 -.29 .13 .34 i258NTtense .56 .05 .00 .02 -.40 .12 .18 i259NTproblems .57 .08 -.02 .07 -.43 .10 .09 i260NTrelax .50 .07 .06 -.05 -.43 .08 .10 i261EGOAseek .45 .17 .15 .37 -.10 -.01 -.01 i262EGOAnotice .34 .10 .10 .49 .07 .03 -.08 i263EGOAadmire .34 -.09 .16 .55 .07 .06 -.06 i264EGOArecognition .37 -.04 .14 .54 .04 .06 -.04 i265EGOAcentre .42 .20 .36 .38 .04 -.01 -.04 i266EGOApraise .40 .00 .20 .52 .02 .07 -.09 i268EGOAfocus .38 .08 .34 .44 .11 .05 -.04

Table 5.6 Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items (N = 588) Higher order Factor Facet Factor 1 2 3 4 5 6 i269EGOAimpress .40 .12 .12 .58 .00 -.01 -.14 i270EGOAsympathy .43 .05 .22 .37 -.09 .01 .00 i271EGOAlike .30 -.08 -.06 .60 .06 .05 -.03 i273EGOAlook .34 .06 .21 .43 .07 .01 -.02 i276EGODobey .33 -.10 .56 .17 .05 .15 .01 i277EGODdomore .30 .01 .49 .17 .02 .05 -.03 i278EGODdotold .33 -.14 .55 .11 -.01 .11 .09 i279EGODdevote .42 .09 .54 .18 -.03 .00 .05 i280EGODplease .41 .11 .29 .02 -.18 .17 -.07 i281EGODentertain .44 .20 .41 .13 -.12 .01 -.01 i282EGODmyway .41 .10 .38 .14 .02 .22 -.07 i284EGODdothings .46 .22 .36 .14 -.07 .09 -.02 i285EGODdelay .42 .24 .53 .02 -.13 .00 -.02 i286EGODlistenonly .41 .04 .61 .05 .01 .19 .02 i287EGODtell .44 .15 .57 .09 -.11 .07 -.06 i288EGODexhaust .46 .25 .45 .07 -.13 .06 -.05 i289EGODdrain .27 .18 .37 .04 -.09 -.07 .01 i292EGONaskopinion .25 -.02 -.04 .32 -.03 -.03 .10 i293EGONaccompany .43 .26 .10 .14 -.16 -.06 .13 i294EGONlike .41 .03 .04 .55 .01 -.03 .08 i295EGONapproval .41 .09 -.05 .53 -.05 -.01 -.01 i296EGONplease .40 .21 -.05 .48 -.10 -.09 -.05 i298EGONaccept .28 -.13 .04 .53 -.01 -.05 .04 i299EGONdependopinion .41 .22 -.02 .36 -.17 -.08 -.04 i300EGONencourage .41 .04 .13 .40 -.07 -.03 .09 i301EGONcare .37 .12 .22 .27 -.10 -.11 .11 i302EGONhelp .40 .19 .14 .29 -.13 -.12 .09 i303EGONdependothers .41 .30 .05 .17 -.20 -.10 .06 i304EGONthink .48 .11 -.10 .49 -.09 -.03 .12 i305EGONknowwell .38 .14 .02 .30 -.12 -.06 .07

Table 5.6 Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items (N = 588) Higher order Factor Facet Factor 1 2 3 4 5 6 i306EGONaprovedo .42 .13 .02 .47 -.14 -.09 -.01 i44BSTiritate .34 .03 -.10 -.05 .01 .44 .07 i45BSTangry .45 .06 .01 -.08 -.04 .43 .15 i46BSTagress .42 .20 .06 -.13 -.09 .36 .03 i48BSTshout .34 .10 .05 .01 .04 .30 .10 i50BSTbeat .35 .07 .13 -.09 -.12 .32 -.04 i51BSTrepriothers .37 .09 .17 -.03 .00 .30 .07 i52BSTlosetemp .48 -.04 .17 -.06 -.04 .47 .14 i53BSTimpatient .41 .02 -.01 .00 -.02 .46 .02 i54BSTtold .39 -.10 .22 .04 .04 .46 .01 i55BSTupset .53 .03 .02 -.06 -.12 .52 .05 i56BSTignore .33 -.04 .06 .02 -.07 .36 -.05 i57BSTunappr .28 .03 .03 -.05 -.14 .26 -.07 i58BSTinterrupt .30 -.10 .16 .05 .02 .31 .07 i59BSTsuffer .47 .25 .05 .02 -.11 .34 -.12 i60BSTquestions .43 .02 .06 .06 -.14 .31 .00 i61BSTreprime .43 .11 .05 .03 -.13 .32 -.05 i62BSTannoy .51 .04 -.04 -.02 -.06 .55 .03 i63BSTshorttemp .50 .07 .02 -.04 -.09 .47 .06 i64BSTfrustrate .51 .04 -.10 -.01 -.08 .51 .10 i65BSTleave .45 .02 .03 -.07 -.25 .38 -.04 i66BSTbother .45 -.02 .08 -.02 -.20 .41 -.06 i67BSTprovoke .33 -.16 .04 .06 .02 .47 .03 i84CFjudge .38 .05 -.20 .27 -.13 .06 .14 i87CFreject .33 -.15 -.14 .35 -.05 .12 .16 i88CFsitumany .43 -.05 -.12 .14 -.16 .12 .32 i89CFintimidate .51 .06 -.03 .12 -.25 .05 .28 i90CFpressure .37 -.03 -.09 .07 -.12 .05 .42 i95CFbadthing .33 -.10 .02 .16 -.05 .06 .32 i96CFnewthing .39 .07 .00 .06 -.29 .02 .10

Table 5.6 Hierarchical Schmid-Leiman Solution for the 169 Neuroticism items (N = 588) Higher order Factor Facet Factor 1 2 3 4 5 6 i97CFdiffrelax .41 .05 .03 .00 -.31 .11 .05 i98CFunfcircum .40 -.17 -.05 .10 -.21 .16 .27 i99CFscaredquick .43 -.05 .11 .01 -.14 .04 .47 Note. Factors with loadings > .30 are indicated in boldface.

In a next step, individual items for each factor were selected based on the following criteria: (a) retaining items with loadings on the higher-order factor > .40; (b) retaining items with loadings on the group factor > .30; (c) retaining items with varying means; and (d) retaining items to ensure that as many as possible of the original facets are covered. Group factor 2 mainly consists of items of the facet Demanding. When reviewing the current literature, the facet Demanding was not found in any of the existing Emotional Stability scales but rather belongs to the dimension Agreeableness (De Raad, 2000; Lee & Ashton, 2008). It was therefore decided to remove this facet from further analyses on theoretical grounds. Based on the above criteria, 47 of the 169 items were retained. The only facets not represented by these items were Obsessive/compulsive, and Attention-seeking.

Next, the 47 remaining items were subjected to a maximum likelihood factor analysis with oblique (Direct Quartimin) rotation. The inspection of the scree plot suggested that five or six factors should be retained. A parallel analysis showed that five eigenvalues were greater than the eigenvalues of random data (Figure 5.4).

Figure 5.4. Scree plot and parallel analysis of the 47 items of Neuroticism scale (only the first 15 roots are displayed).

Five- and six-factor solutions were examined and the five-factor solution appeared to be the psychologically most appropriate. The factor correlation matrix for the five factors indicated moderate inter-correlations (.302 to .505) suggesting that a higher order is present but that each factor has distinctiveness. A higher order factor analysis using the Schmid-Leimann solution was conducted. The results are presented in Table 5.7.

Table 5.7

Hierarchical Schmid-Leiman Solution for the Neuroticism scale (N = 588)

Higher order Factor Facet factor 1 2 3 4 5 i244Ndinterest .55 .62 -.06 .00 .00 .03 i245Ndworthless .58 .62 .02 .04 -.05 .03 i243Ndjoy .57 .62 .00 .00 .01 .00 i241Ndhelpless .61 .51 .12 .03 .05 -.01 i239Ndmiserable .58 .48 .06 .01 .11 .00 i260Ntrelax .53 .34 .20 -.01 .12 -.04 i215Ncpget .43 .34 .03 .03 -.01 .08 i259Ntproblems .60 .30 .22 .05 .13 .01 i217NCPnag .56 .25 .03 .11 .07 .16 i253Nnnervous .50 .04 .61 .03 -.01 .00 i254Nnpanic .56 .11 .58 .04 .00 -.01 i255Ntsmallthing .56 .07 .54 .02 .08 .01 i203ESSEhurteasi .44 -.09 .49 .05 .06 .07 i104Cfscaredeasi .45 .07 .44 -.02 .00 .07 i209ESSHembarrass .45 -.01 .42 .12 .04 .02 i102Cfworryself .43 .06 .40 .06 .11 -.07 i206ESSEupset .54 -.03 .39 .06 .19 .06 i250Nnanxious .53 .10 .38 .08 .06 .03 i251Nnthreaten .47 .17 .36 .05 -.04 .04 i178ESEMbreak .54 .02 .34 -.01 .09 .18 i191ESEMnoreason .48 .11 .19 .03 .05 .17 i295EGONapproval .41 -.03 -.06 .69 .07 -.10

Table 5.7 Hierarchical Schmid-Leiman Solution for the Neuroticism scale (N = 588) Higher order Factor Facet factor 1 2 3 4 5 i296EGONplease .42 .04 -.10 .64 -.01 -.01 i299EGONdependopinion .45 .07 -.06 .55 -.03 .04 i294EGONlike .37 -.07 .10 .52 .01 -.03 i304EGONthink .48 -.03 .13 .51 .00 .03 i305EGONknowwell .39 .04 .06 .41 -.04 .04 i300EGONencourage .39 -.02 .10 .40 -.01 .04 i303EGONdependothers .47 .10 .04 .32 -.06 .16 i55BSTupset .54 .08 .08 -.01 .53 -.05 i64BSTfrustrate .52 .00 .15 .02 .48 -.02 i52BSTlosetemp .47 .03 .13 -.03 .44 -.02 i59BSTsuffer .51 .13 -.16 .07 .38 .13 i66BSTbother .45 .12 .02 .02 .38 -.03 i164ECTissueangr .63 .00 .06 .06 .35 .22 i183ESEMnasty .41 -.08 .04 .03 .34 .13 i165ECTactmood .54 .00 .01 .03 .31 .24 i171ECTfriendly .49 .07 -.01 .07 .26 .16 i124ECIaffectothers .49 .04 -.05 .03 -.01 .49 i125ECInothink .48 .05 .02 -.01 -.03 .47 I167ECTsayinappr .54 .00 -.09 .03 .17 .44 i131ECIurge .58 .01 .06 .01 .11 .43 i133ECInotknow .52 .04 .11 .02 -.02 .40 i134ECIregret .47 -.02 .14 .05 -.01 .37 i128ECIcontremo .55 .07 .13 .01 .08 .32 i162ECTtreatbad .57 .15 -.17 .10 .21 .31 i199ESEXactexag .49 .11 .02 .15 .02 .26

% of variance explained 53.2 9.9 12 10 7.2 7.7

Note. Factors with loadings > .30 are indicated in boldface.

Table 5.7 indicates that the Schmid-Leiman transformation produced a well-defined higher- order factor with five clearly defined group factors. Item i191ESEMnoreason was removed as it did not load on the group factors resulting in a total of 46 items. The higher order factor was labelled Neuroticism and accounts for 53.2% of the variance explained. Table 5.8 presents the five obliquely rotated factors with their respective items, factor loadings, communality estimates (h2), means and standard deviations.

Group factor 1 was labelled Despaired, because the majority of the items related to feeling down, disliking oneself and lacking direction and interest in life. Five items belonged to the facet Depressed, with the remaining four items being split between the facets Tensed and Complaining. The highest loading items were “I have lost interest in life” and “I feel worthless”.

Group factor 2 was labelled Anxious, because the items reflected an overly fearful behaviour in different situations and interactions with people. The items belonged to the facets Neurotic, Tense, Sensitive, Fearful, Ashamed, and Emotional. The highest loading items were “I easily get nervous” and “I panic easily”.

Group factor 3 was labelled Dependent, because all eight items reflected the need to please people and to obtain acceptance, recognition, love and praise. The highest loading items were “I need approval from others” and “I need to please people”.

Group factor 4 was labelled Temperamental, because the majority of the items related to acting in an unpredictable way, treating others badly and having mood swings. Five items belonged to the facet Short-tempered, with the remaining four items belonging to the facets Temperamental and Emotional respectively. The highest loading items were “I get upset with others quickly” and “I get frustrated quickly”.

Group factor 5 was labelled Impulsive, because the majority of the items referred to talking and acting without thinking or weighing up all options, and jumping into a situation without considering the consequences for oneself and others. Six items belonged to the facet Impulsive; the remaining three items belonged to the facets Temperamental and Exaggerating. The highest loading items were “I act without thinking how my actions will affect others” and “I do things without thinking too much in advance”.

Table 5.8 Neuroticism scale (N = 588) Factor loading Item h² M SD 1 2 3 4 5 Factor 1: Despaired i244NDinterest .84 -.07 -.01 .00 .04 .69 1.95 1.09 i245NDworthless .84 .02 .05 -.07 .03 .73 1.91 1.05 i243NDjoy .83 .01 .00 .01 .00 .70 1.96 1.04 i241NDhelpless .68 .15 .03 .07 .00 .65 2.32 1.06 i239NDmiserable .64 .07 .02 .14 .00 .58 2.44 1.06 i260NTrelax .47 .26 -.01 .17 -.06 .46 2.52 1.02 i215NCpget .46 .03 .04 .00 .11 .31 2.43 0.96 i259NTproblems .40 .28 .06 .17 .02 .52 2.52 0.93 i217NCPnag .34 .04 .14 .10 .22 .42 2.28 0.94

Factor 2: Anxious i253NNnervous .05 .76 .03 -.02 .01 .63 2.95 1.01 i254NNpanic .14 .73 .05 -.01 -.01 .67 2.74 1.05 i255NTsmallthing .09 .68 .03 .10 .02 .62 2.90 1.05 i203ESSEhurteasi -.12 .60 .07 .09 .09 .45 3.29 1.10 i104CFscaredeasi .09 .54 -.02 .01 .10 .39 2.87 1.08 i209ESSHembarrass -.01 .52 .14 .05 .03 .40 3.27 1.02 i102CFworryself .08 .51 .07 .15 -.09 .40 3.16 1.11 i206ESSEupset -.04 .49 .08 .25 .09 .49 2.94 1.03 i250NNanxious .14 .48 .10 .08 .05 .45 2.82 0.99 i251NNthreaten .23 .46 .07 -.06 .07 .39 2.79 0.99 i178ESEMbreak .04 .42 .00 .14 .24 .44 2.71 1.10

Factor 3: Dependent i295EGONapproval -.04 -.07 .86 .10 -.14 .63 2.71 1.00 i296EGONplease .06 -.13 .80 -.01 -.01 .59 2.61 1.00 i299EGONdependopinion .10 -.07 .68 -.04 .06 .52 2.55 0.96 i294EGONlike -.09 .12 .64 .01 -.04 .43 2.96 0.97 i304EGONthink -.04 .17 .63 .00 .05 .52 2.88 1.00

Table 5.8 Neuroticism scale (N = 588) Factor loading Item h² M SD 1 2 3 4 5 i305EGONknowwell .05 .08 .51 -.05 .05 .34 2.79 1.08 i300EGONencourage -.03 .13 .50 -.01 .06 .33 2.94 0.97 i303EGONdependothers .13 .05 .40 -.07 .23 .37 2.41 1.00

Factor 4: Temperamental i55BSTupset .10 .10 -.02 .70 -.06 .59 2.63 0.98 i64BSTfrustrate -.01 .18 .02 .64 -.03 .53 2.93 1.11 i52BSTlosetemp .04 .16 -.04 .59 -.04 .45 2.67 1.05 i59BSTsuffer .18 -.21 .09 .51 .17 .46 2.19 1.01 i66BSTbother .16 .03 .03 .50 -.03 .36 2.70 1.06 i164ECTissueangr .01 .08 .08 .48 .31 .58 2.46 1.06 i183ESEMnasty -.11 .06 .04 .46 .18 .32 2.99 0.99 i165ECTactmood .00 .01 .04 .42 .33 .47 2.76 1.06 i171ECTfriendly .10 -.02 .09 .35 .21 .35 2.70 1.10

Factor 5: Impulsive i124ECIaffectothers .06 -.06 .03 -.01 .68 .50 2.42 0.98 i125ECInothink .06 .02 -.02 -.04 .66 .45 2.60 1.06 i167ECTsayinappr .00 -.11 .04 .23 .61 .54 2.44 1.00 i131ECIurge .02 .08 .01 .15 .60 .53 2.70 0.98 i133ECInotknow .06 .14 .02 -.04 .58 .43 2.71 1.02 i134ECIregret -.03 .18 .06 -.02 .52 .36 2.87 1.02 i128ECIcontremo .10 .17 .01 .10 .44 .43 2.61 0.99 i162ECTtreatbad .20 -.21 .13 .28 .42 .54 1.99 1.00 i199ESEXactexag .14 .02 .19 .03 .36 .35 2.46 0.97 Note. Factors with factor loadings > .30 are indicated in boldface.

5.6 Internal consistency

Internal consistency reliability was used to assess the consistency of results across items. Internal consistency coefficients were calculated for both the total group and the three language groups (Germanic, Nguni and Sotho). The results are presented below.

5.6.1 Total group

Internal consistency for the newly developed indigenous Neuroticism scale and its subscales was determined using Cronbach’s alpha. The total scale showed good internal consistency with an alpha coefficient of α = .96. Subscales that reflect the group factors also demonstrated good internal consistency with the following alpha coefficients: Despaired (α = .91); Anxious (α = .90); Dependent (α = .86); Temperamental (α = .87); and Impulsive (α = .87).

5.6.2 Language groups

The total scale showed good internal consistency across language groups with alpha coefficients of α = .95 for the Germanic group, α = .95 for the Nguni group and α = .97 for the Sotho group. Subscales that reflect the group factors also demonstrated good internal consistency with the following alpha coefficients for the Germanic group: Despaired (α = .89); Anxious (α = .90); Dependent (α = .87); Temperamental (α = .88); and Impulsive (α = .86). The alpha coefficients for the Nguni group were: Despaired (α = .90); Anxious (α = .88); Dependent (α = .83); Temperamental (α = .85); and Impulsive (α = .84). The Sotho group had the following alpha reliability coefficients: Despaired (α = .93); Anxious (α = .92); Dependent (α = .88); Temperamental (α = .87); and Impulsive (α = .89).

5.7 Coefficient of congruence

To establish construct equivalence, congruence coefficients were calculated for each of the five factors (Despaired, Anxious, Dependent, Temperamental, and Impulsive) across each of the three language groups (Germanic, Nguni and Sotho). To determine the stability of the Neuroticism factor across the three language groups, the higher order Neuroticism factor of the total group was compared with the higher order Neuroticism factor of each language group. The results are presented below.

5.7.1 Group factors across language groups

To establish construct equivalence across different population groups, postulates 3 specified that within each comparison group, the congruence coefficients would be at or > .90 for all factors. Separate factor analyses were performed for three language groups (i.e. Germanic, Nguni, and Sotho). In each group five factors were retained and obliquely rotated. The factor pattern matrices for the three language groups are presented in Appendix C. The factor pattern matrix of the total group (Appendix C) was used as a target, to which the factor pattern matrices of each of the three language groups were obliquely rotated. The target rotated factor pattern matrices for the Germanic, Nguni and Sotho group will be presented in table 5.9, 5.10 and 5.11 respectively.

Table 5.9 Target rotated factor pattern matrix of the Germanic group (N = 588) Factor Item 1 2 3 4 5 i52BSTlosetemp .14 .23 -.10 .57 .08 i55BSTupset .08 .25 .00 .67 .05 i59BSTsuffer .15 -.08 .02 .44 .24 i64BSTfrustrate -.01 .27 -.05 .56 .09 i66BSTbother .15 .02 .00 .46 .09 i102CFworryself .09 .51 -.02 .24 -.11 i104CFscaredeasi .11 .47 -.03 .06 .11 i124ECIaffectothers .03 -.10 .07 .16 .55 i125ECInothink .10 -.14 -.03 .06 .53 i128ECIcontremo .01 .32 -.07 .07 .51 i131ECIurge .06 .14 -.04 .04 .63 i133ECInotknow .07 .16 .08 -.08 .52 i134ECIregret .06 .05 .11 .08 .40 i162ECTtreatbad .14 -.26 .24 .33 .37 i164ECTissueangr -.05 .06 .11 .61 .32

Table 5.9 Target rotated factor pattern matrix of the Germanic group (N = 588) Factor Item 1 2 3 4 5 i165ECTactmood .02 .02 -.03 .53 .36 i167ECTsayinappr -.01 -.22 .11 .37 .47 i171ECTfriendly .18 -.06 .15 .38 .27 i178ESEMbreak .06 .53 -.02 -.01 .30 i183ESEMnasty -.03 -.07 .08 .69 .11 i199ESEXactexag .09 .03 .29 .08 .22 i203ESSEhurteasi -.16 .65 .10 -.12 .24 i206ESSEupset -.03 .53 .02 .17 .24 i209ESSHembarrass .02 .51 .11 .02 .10 i215NCpget .43 -.11 .10 .07 .09 i217NCPnag .23 .02 .15 .23 .16 i239NDmiserable .69 .13 -.06 -.09 .22 i241NDhelpless .70 .17 -.02 .01 .09 i243NDjoy .86 .00 -.04 .03 .00 i244NDinterest .85 -.03 .02 -.08 .05 i245NDworthless .83 .07 .06 -.11 .04 i250NNanxious .21 .47 .20 .11 -.14 i251NNthreaten .24 .33 .14 .13 -.05 i253NNnervous .15 .65 .13 .06 -.15 i254NNpanic .15 .65 .15 .13 -.17 i255NTsmallthing .01 .65 .09 .28 -.13 i259NTproblems .32 .33 .05 .21 .00 i260NTrelax .31 .31 -.06 .33 -.15 i294EGONlike -.07 .12 .72 -.12 .06 i295EGONapproval -.06 .08 .78 -.03 .02 i296EGONplease -.04 -.07 .80 -.11 .02 i299EGONdependopinion .24 -.07 .68 -.02 .02 i300EGONencourage .04 .05 .55 .15 .06

Table 5.9 Target rotated factor pattern matrix of the Germanic group (N = 588) Factor Item 1 2 3 4 5 i303EGONdependothers .04 .09 .37 .05 .10 i304EGONthink -.04 .25 .58 -.11 .16 i305EGONknowwell .05 .02 .60 -.05 .03

Tucker's phi .98 .97 .98 .92 .92 Note. Factors with factor loadings > .30 are indicated in boldface.

Table 5.10 Target rotated factor pattern matrix of the Nguni group (N = 588) Factor Item 1 2 3 4 5 i52BSTlosetemp .00 .12 -.06 .63 -.01 i55BSTupset .15 .07 -.23 .63 .18 i59BSTsuffer .18 -.11 .05 .46 .36 i64BSTfrustrate .07 .20 -.04 .65 .10 i66BSTbother .17 .13 .05 .48 -.04 i102CFworryself .14 .62 .06 .09 -.12 i104CFscaredeasi .01 .60 .10 -.03 .04 i124ECIaffectothers .10 -.07 .13 -.07 .52 i125ECInothink .09 .14 .05 -.10 .45 i128ECIcontremo .20 -.04 .22 .15 .26 i131ECIurge .09 .01 .18 .28 .36 i133ECInotknow .10 .25 .03 -.14 .47 i134ECIregret .00 .27 .01 -.06 .36 i162ECTtreatbad .24 -.17 .14 .42 .35 i164ECTissueangr .03 .06 .18 .63 .21 i165ECTactmood -.01 -.01 .09 .51 .30 i167ECTsayinappr .00 -.10 .05 .39 .48

Table 5.10 Target rotated factor pattern matrix of the Nguni group (N = 588)

Factor Item 1 2 3 4 5 i171ECTfriendly .10 -.01 .05 .33 .25 i178ESEMbreak -.09 .36 .09 .27 .24 i183ESEMnasty -.27 .16 -.03 .46 .21 i199ESEXactexag .13 -.06 .15 .14 .47 i203ESSEhurteasi -.18 .58 -.08 .09 .26 i206ESSEupset -.10 .53 .03 .18 .23 i209ESSHembarrass -.12 .56 .23 .07 .02 i215NCpget .37 .02 .08 .01 .15 i217NCPnag .34 -.05 .17 .05 .41 i239NDmiserable .66 .09 .09 .25 -.17 i241NDhelpless .79 .18 .07 .06 -.13 i243NDjoy .75 .04 .09 .10 -.04 i244NDinterest .74 -.06 -.10 .05 .11 i245NDworthless .77 .02 -.01 -.09 .14 i250NNanxious .13 .33 .17 .19 .04 i251NNthreaten .27 .33 .05 -.08 .09 i253NNnervous .05 .61 .06 .14 .02 i254NNpanic .22 .66 .13 .15 -.13 i255NTsmallthing .15 .64 .02 .12 -.03 i259NTproblems .52 .34 -.04 .05 .08 i260NTrelax .67 .31 -.12 -.07 .07 i294EGONlike -.09 .12 .46 -.10 .12 i295EGONapproval .01 -.03 .88 .12 -.20 i296EGONplease .16 -.05 .66 -.08 .16 i299EGONdependopinion .08 -.06 .66 -.05 .13 i300EGONencourage -.08 .14 .46 -.18 .18 i303EGONdependothers .17 .01 .44 -.15 .30 i304EGONthink -.13 .17 .70 -.02 -.02

Table 5.10 Target rotated factor pattern matrix of the Nguni group (N = 588) Factor Item 1 2 3 4 5 i305EGONknowwell .00 .12 .37 -.02 .14

Tucker's phi .97 .97 .95 .95 .90 Note. Factors with factor loadings > .30 are indicated in boldface.

Table 5.11 Target rotated factor pattern matrix of the Sotho group (N = 588) Factor Item 1 2 3 4 5 i52BSTlosetemp .01 .23 .08 .43 .07 i55BSTupset .16 .09 .00 .58 .02 i59BSTsuffer .32 -.13 -.01 .36 .22 i64BSTfrustrate -.04 .33 .05 .38 .24 i66BSTbother .13 .11 -.07 .47 .17 i102CFworryself .02 .44 .19 .20 -.16 i104CFscaredeasi .11 .38 .14 .33 -.18 i124ECIaffectothers .17 -.12 -.01 .18 .56 i125ECInothink .06 -.01 .14 .10 .65 i128ECIcontremo .07 .06 .03 .31 .42 i131ECIurge -.08 .08 .05 .22 .70 i133ECInotknow .15 -.14 .08 .27 .45 i134ECIregret -.14 -.03 .28 .34 .38 i162ECTtreatbad .23 -.12 .01 .22 .62 i164ECTissueangr .02 .16 -.01 .39 .49 i165ECTactmood -.01 .26 .00 .25 .37 i167ECTsayinappr .05 -.08 .11 .15 .78 i171ECTfriendly -.04 .16 -.06 .43 .16 i178ESEMbreak .17 .23 -.03 .36 .02

Table 5.11

Target rotated factor pattern matrix of the Sotho group (N = 588)

Factor Item 1 2 3 4 5 i183ESEMnasty -.05 .29 .01 .13 .41 i199ESEXactexag .13 -.04 .20 .09 .47 i203ESSEhurteasi .04 .61 .11 .15 -.23 i206ESSEupset .06 .53 .12 .28 -.19 i209ESSHembarrass .14 .48 .19 .07 -.20 i215NCpget .47 .09 .07 .00 .11 i217NCPnag .37 .08 .16 .10 .27 i239NDmiserable .58 .04 .04 .36 -.18 i241NDhelpless .63 .19 .01 .19 -.07 i243NDjoy .84 -.02 .11 -.03 -.11 i244NDinterest .86 -.02 .00 -.12 .10 i245NDworthless .93 .09 -.03 -.23 .06 i250NNanxious .13 .48 -.08 .18 .19 i251NNthreaten .14 .58 .11 -.12 .19 i253NNnervous .00 .91 -.02 -.11 .07 i254NNpanic .08 .72 .03 -.03 .22 i255NTsmallthing .14 .59 .02 .16 .11 i259NTproblems .41 .27 .05 .19 .15 i260NTrelax .42 .22 -.01 .26 .06 i294EGONlike -.10 .28 .52 .04 -.13 i295EGONapproval -.09 .04 .76 -.02 .05 i296EGONplease .15 -.15 .85 -.07 .03 i299EGONdependopinion .00 -.07 .77 -.08 .04 i300EGONencourage -.11 .09 .65 .06 -.10 i303EGONdependothers .21 .01 .49 -.16 .30 i304EGONthink .05 .16 .56 .08 .09 i305EGONknowwell .06 .10 .55 -.16 .19

Table 5.11

Target rotated factor pattern matrix of the Sotho group (N = 588) Factor Item 1 2 3 4 5

Tucker's phi .97 .94 .95 .83 .87 Note. Factors with factor loadings > .30 are indicated in boldface.

After the target rotation the congruence coefficient between the total group and the Germanic language group (English and Afrikaans) showed good agreement for all factors indicating that the facets measured the same construct. Tucker’s phi obtained for each factor was as follows:

Despaired (pxy = .98), Anxious (pxy = .97), Dependent (pxy = .98), Temperamental (pxy = .92),

and Impulsive (pxy = .92).

After the target rotation the congruence coefficient between the total group and the Nguni language group (Zulu, Xhosa, Swati, and Ndebele) showed good agreement for all factors indicating that the facets measured the same construct. Tucker’s phi obtained for each factor

was as follows: Despaired (pxy = .97), Anxious (pxy = .97), Dependent (pxy = .95),

Temperamental (pxy = .95), and Impulsive (pxy = .90).

After the target rotation the congruence coefficient between the total group and the Sotho language group (Sesotho, Setswana, and Sepedi) showed good agreement for three of the factors indicating that the facets measured the same construct. However, two factors, Temperamental and Impulsive, appeared qualitatively different. Tucker’s phi obtained for

each factor was as follows: Despaired (pxy = .97), Anxious (pxy = .94), Dependent (pxy = .95),

Temperamental (pxy = .83), and Impulsive (pxy = .87).

5.7.2 Higher order factor Neuroticism across language groups

To determine if the general factor Neuroticism is stable across the three different language groups, a higher order factor analysis using the Schmid-Leimann transformation was conducted for each group. The results are presented in Table 5.12, 5.13 and 5.14 respectively. Tucker’s phi was calculated for the higher order factor Neuroticism by comparing the total

group with each language group. Good agreement for all factors was found indicating that the indigenous Neuroticism scale retains its meaning across the three language groups. Tucker’s phi obtained for the factor Neuroticism for each group was: Germanic (pxy = 1.00), Nguni (pxy

= 1.00), Sotho (pxy = .99).

Table 5.12 Schmid-Leiman solution for the Germanic language group (N = 588)

Higher Item Factor order factor 1 2 3 4 5 i52BSTlosetemp .54 .39 -.08 -.08 .01 -.22 i55BSTupset .59 .46 -.01 -.03 -.04 -.24 i59BSTsuffer .47 .33 .01 -.10 .12 .06 i64BSTfrustrate .48 .39 -.04 .03 .02 -.25 i66BSTbother .43 .33 -.01 -.09 .00 -.03 i102CFworryself .39 .14 .01 -.05 -.09 -.45 i104CFscaredeasi .43 .04 .01 -.09 .13 -.41 i124ECIaffectothers .46 .17 .07 -.06 .43 .08 i125ECInothink .37 .09 -.02 -.11 .43 .11 i128ECIcontremo .54 .08 -.02 -.05 .46 -.28 i131ECIurge .55 .08 -.01 -.10 .55 -.13 i133ECInotknow .49 -.01 .10 -.10 .46 -.14 i134ECIregret .44 .09 .11 -.07 .32 -.05 i162ECTtreatbad .51 .28 .19 -.11 .22 .22 i164ECTissueangr .61 .45 .09 .04 .18 -.07 i165ECTactmood .54 .40 -.03 -.02 .23 -.04 i167ECTsayinappr .45 .31 .08 -.01 .32 .17 i171ECTfriendly .55 .29 .12 -.12 .14 .04 i178ESEMbreak .53 .00 .03 -.08 .31 -.46 i183ESEMnasty .44 .49 .05 .05 -.02 .03 i199ESEXactexag .41 .08 .25 -.07 .15 -.02 i203ESSEhurteasi .40 -.08 .14 .08 .28 -.56 i206ESSEupset .54 .12 .05 .00 .22 -.47

Table 5.12 Schmid-Leiman solution for the Germanic language group (N = 588)

Higher Factor Item order factor 1 2 3 4 5 i209ESSHembarrass .43 .01 .13 -.02 .12 -.44 i215NCpget .39 .07 .08 -.30 .03 .10 i217NCPnag .48 .18 .13 -.16 .08 -.02 i239NDmiserable .61 -.04 -.04 -.51 .19 -.10 i241NDhelpless .62 .01 -.01 -.50 .06 -.14 i243NDjoy .57 .02 -.04 -.60 -.04 .02 i244NDinterest .56 -.05 .02 -.61 .02 .04 i245NDworthless .60 -.07 .05 -.59 .02 -.04 i250NNanxious .47 .06 .19 -.13 -.12 -.40 i251NNthreaten .46 .08 .14 -.16 -.05 -.28 i253NNnervous .46 .01 .14 -.09 -.09 -.56 i254NNpanic .49 .06 .16 -.09 -.12 -.56 i255NTsmallthing .48 .16 .11 .01 -.10 -.57 i259NTproblems .54 .14 .06 -.21 -.02 -.29 i260NTrelax .44 .21 -.04 -.19 -.16 -.28 i294EGONlike .36 -.06 .62 .05 .03 -.09 i295EGONapproval .39 .00 .66 .05 -.03 -.06 i296EGONplease .28 -.05 .67 .04 -.03 .08 i299EGONdependopinion .46 .01 .56 -.16 -.05 .07 i300EGONencourage .45 .13 .46 -.02 -.02 -.04 i303EGONdependothers .36 .05 .32 -.03 .05 -.07 i304EGONthink .45 -.05 .51 .02 .13 -.21 i305EGONknowwell .34 -.01 .50 -.03 -.01 -.01

Tucker’s Phi 1.00 Note. Factors with factor loadings > .30 are indicated in boldface.

Table 5.13 Schmid-Leiman solution for the Nguni language group (N = 588)

Higher Item order Factor factor 1 2 3 4 5 i52BSTlosetemp .33 .45 .00 -.06 .10 -.17 i55BSTupset .42 .49 -.12 -.18 .06 .00 i59BSTsuffer .53 .45 -.14 .06 -.10 .16 i64BSTfrustrate .50 .49 -.06 -.04 .17 -.09 i66BSTbother .38 .33 -.15 .04 .10 -.17 i102CFworryself .37 .00 -.15 .03 .52 -.10 i104CFscaredeasi .37 -.04 -.04 .07 .51 .05 i124ECIaffectothers .42 .12 -.08 .13 -.06 .43 i125ECInothink .41 .06 -.08 .06 .13 .39 i128ECIcontremo .46 .20 -.17 .20 -.04 .15 i131ECIurge .53 .32 -.08 .16 .01 .20 i133ECInotknow .46 .03 -.10 .05 .22 .43 i134ECIregret .37 .06 -.01 .02 .23 .32 i162ECTtreatbad .56 .42 -.19 .14 -.15 .14 i164ECTissueangr .59 .52 -.03 .16 .05 -.02 i165ECTactmood .49 .46 .01 .08 -.01 .09 i167ECTsayinappr .50 .44 .01 .06 -.08 .28 i171ECTfriendly .41 .31 -.08 .05 -.01 .11 i178ESEMbreak .48 .25 .06 .08 .31 .13 i183ESEMnasty .28 .38 .23 -.03 .15 .05 i199ESEXactexag .52 .25 -.11 .15 -.05 .33 i203ESSEhurteasi .38 .11 .13 -.07 .51 .22 i206ESSEupset .47 .18 .07 .02 .46 .15 i209ESSHembarrass .38 .04 .07 .18 .47 -.01 i215NCpget .36 .06 -.32 .08 .01 .12 i217NCPnag .56 .17 -.29 .17 -.05 .30 i239NDmiserable .45 .13 -.56 .08 .05 -.21 i241NDhelpless .49 .00 -.68 .07 .12 -.11

Table 5.13 Schmid-Leiman solution for the Nguni language group (N = 588)

Higher Item order Factor factor 1 2 3 4 5 i243NDjoy .49 .06 -.64 .09 .01 -.06 i244NDinterest .42 .07 -.62 -.06 -.07 .09 i245NDworthless .47 -.02 -.65 .02 .00 .14 i250NNanxious .44 .14 -.12 .14 .27 -.03 i251NNthreaten .36 -.04 -.25 .05 .27 .11 i253NNnervous .45 .08 -.07 .04 .52 -.01 i254NNpanic .49 .04 -.21 .09 .55 -.14 i255NTsmallthing .45 .05 -.15 .01 .55 -.03 i259NTproblems .52 .05 -.45 -.03 .28 .08 i260NTrelax .48 -.04 -.58 -.08 .25 .11 i294EGONlike .28 -.02 .06 .38 .10 .08 i295EGONapproval .35 .05 -.03 .72 -.06 -.30 i296EGONplease .47 .01 -.15 .56 -.07 .08 i299EGONdependopinion .42 .03 -.08 .56 -.07 .04 i300EGONencourage .31 -.06 .04 .38 .11 .15 i303EGONdependothers .46 .00 -.16 .38 -.01 .24 i304EGONthink .35 -.01 .09 .58 .13 -.08 i305EGONknowwell .33 .03 -.02 .31 .09 .08

Tucker’s Phi 1.00 Note. Factors with factor loadings > .30 are indicated in boldface.

Table 5.14 Schmid-Leiman solution for the Sotho language group (N = 588)

Higher Item order Factor factor 1 2 3 4 5 i52BSTlosetemp .53 .14 -.03 .08 .15 .34 i55BSTupset .56 .02 -.14 .01 .15 .48

Table 5.14 Schmid-Leiman solution for the Sotho language group (N = 588)

Higher Item order Factor factor 1 2 3 4 5 i59BSTsuffer .47 -.11 -.24 -.01 .24 .25 i64BSTfrustrate .60 .24 .02 .05 .26 .25 i66BSTbother .52 .06 -.11 -.05 .24 .35 i102CFworryself .48 .30 -.04 .17 -.06 .22 i104CFscaredeasi .54 .24 -.11 .13 -.04 .33 i124ECIaffectothers .44 -.05 -.12 -.01 .44 .00 i125ECInothink .52 .04 -.04 .11 .48 -.09 i128ECIcontremo .53 .06 -.05 .03 .37 .15 i131ECIurge .55 .10 .06 .05 .55 -.01 i133ECInotknow .46 -.09 -.11 .07 .39 .11 i134ECIregret .45 -.03 .10 .24 .35 .18 i162ECTtreatbad .55 -.05 -.16 .00 .50 .03 i164ECTissueangr .62 .13 -.02 -.01 .44 .19 i165ECTactmood .53 .21 .00 .01 .32 .11 i167ECTsayinappr .54 .00 -.03 .09 .59 -.08 i171ECTfriendly .41 .10 .02 -.04 .21 .30 i178ESEMbreak .51 .15 -.14 -.02 .11 .30 i183ESEMnasty .48 .25 .03 .01 .33 .00 i199ESEXactexag .49 .00 -.10 .16 .36 -.04 i203ESSEhurteasi .50 .42 -.06 .11 -.12 .20 i206ESSEupset .56 .35 -.07 .12 -.06 .29 i209ESSHembarrass .49 .33 -.13 .17 -.11 .13 i215NCpget .50 .08 -.36 .06 .09 .00 i217NCPnag .62 .08 -.29 .13 .23 .04 i239NDmiserable .60 -.01 -.45 .04 -.02 .37 i241NDhelpless .67 .12 -.49 .01 .01 .21 i243NDjoy .57 -.02 -.64 .09 -.06 .05 i244NDinterest .57 .01 -.65 -.01 .06 -.08 i245NDworthless .59 .10 -.70 -.03 .01 -.16

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Table 5.14 Schmid-Leiman solution for the Sotho language group (N = 588)

Higher Item order Factor factor 1 2 3 4 5 i250NNanxious .61 .36 -.11 -.05 .18 .11 i251NNthreaten .61 .46 -.12 .10 .12 -.13 i253NNnervous .62 .69 -.03 .00 .04 -.10 i254NNpanic .69 .56 -.08 .04 .16 -.07 i255NTsmallthing .70 .44 -.13 .03 .13 .12 i259NTproblems .71 .20 -.32 .05 .16 .14 i260NTrelax .65 .16 -.33 .00 .12 .22 i294EGONlike .38 .18 .05 .45 -.07 .08 i295EGONapproval .41 .01 .05 .64 .05 -.01 i296EGONplease .45 -.13 -.13 .71 .02 -.03 i299EGONdependopinion .36 -.06 -.02 .65 .03 -.05 i300EGONencourage .34 .03 .06 .55 -.04 .09 i303EGONdependothers .49 .04 -.17 .40 .19 -.19 i304EGONthink .58 .11 -.06 .48 .10 .07 305EGONknowwell .42 .09 -.06 .46 .11 -.16

Tucker’s Phi 0.99 Note. Factors with factor loadings > .30 are indicated in boldface.

5.8 Convergent validity

To establish convergent validity of the newly developed indigenous Neuroticism scale, it was correlated with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the Negative Affect scale of the PANAS (Watson et al., 1988) using the Pearson’s correlation coefficient. A strong positive correlation (r = .89) was found with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and a moderate positive correlation (r = .66) was found with the Negative Affect scale of the PANAS (Watson et al., 1988) providing evidence of convergent validity.

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CHAPTER 6 DISCUSSION

6.1 Introduction

This chapter discusses the major findings presented in the previous chapter. The hierarchical structure of the indigenous Neuroticism scale is presented, and compared with the personality models reviewed in Chapter 2. Its psychometric properties are discussed in relation to previous research undertaken in South Africa. Convergent and divergent findings are highlighted, and possible reasons for these are offered. The results are related to the relevant postulates, and the performance of the indigenous Neuroticism scale is evaluated. The chapter concludes with the limitations of the study and recommendations for future research.

To reiterate, the main goal of the present study is the development of an indigenous Emotional Stability scale, which can be used to cross-culturally assess Neuroticism in South Africa, and which will ultimately assist in the theoretical understanding of personality as it manifests in this country. The basis for the development of this scale is the conceptual cluster of Emotional Stability as determined within the context of the SAPI project, which incorporates facets describing positive and negative psychological adjustment.

An additional objective of the present study is the comparison of the indigenous Neuroticism scale with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the Negative Affect scale of the PANAS (Watson et al., 1988), to assess convergent validity. The BTI (Taylor & De Bruin, 2006) is a semi-indigenous instrument developed in South Africa to assess the Big Five factors of personality. Its facets were selected on the basis of previous research in the USA and Europe, but its items were developed and written specifically for the South African context (Taylor, 2004). The PANAS (Watson et al., 1988) is an instrument developed in the USA to assess positive and negative affect.

6.2 Neuroticism in South Africa

Using the Emotional Stability cluster of the SAPI project as a starting point, Neuroticism was found in the natural language descriptions of all 11 official South African languages. Exploratory factor analyses indicated that the positive and negative facets of the Emotional

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Stability cluster defined separate factors. This split has psychological implications, which will be discussed in section 6.2.6. The focus of this discussion centres on the negative facets, reflecting traits more traditionally associated with Neuroticism. The results of the present study revealed a valid and reliable, multifaceted indigenous measure of Neuroticism.

6.2.1 Hierarchical structure of Neuroticism

The Neuroticism factor consists of five group factors. Except for the group factor Dependent, comprising items from the Needy facet only, all other group factors contain items from a variety of facets derived from the Emotional Stability cluster. The higher order factor Neuroticism accounted for 53.2% of the total variance explained, indicating good explanatory power (Gorsuch, 1983). The hierarchical structure of the indigenous Neuroticism scale is presented below.

Neuroticism

Despaired Anxious Dependent Temperamental Impulsive

Depressive Neurotic Needy Temperamental Impulsive Tensed Sensitive Short-tempered Temperamental Complaining Tensed Emotional Exaggerate Fearful Ashamed Emotional

Figure 6.1. Hierarchical structure of Neuroticism.

When comparing the indigenous Neuroticism scale with the instruments discussed in Chapter 2, it becomes evident that its structure is most closely aligned with that of the NEO-PI-R, which comprises the facets Anxiety, Angry Hostility, Depression, Self-Consciousness, Impulsiveness and Vulnerability. The facet Anxiety, which refers to a person’s proneness to fear, worry and nervousness, correlates with the facet Anxious of the indigenous Neuroticism scale. The facet Angry Hostility, which measures the tendency to experience anger, and related states such as bitterness and frustrations, can be compared with the facet

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Temperamental of the indigenous Neuroticism scale. The facet Depression, which relates to an individual’s feeling of guilt, sadness and loneliness, and the facet Vulnerability, which refers to the vulnerability to stress; an individual’s feelings of hopelessness, dependency and the inability to cope effectively in stressful situations, are represented in the facets Despaired and Dependent of the indigenous Neuroticism scale. Finally, the facet Impulsiveness, which reflects an individual’s ability to resist temptation and to control cravings and urges, can be related to the facet Impulsive of the indigenous Neuroticism scale.

However, the facet Self-consciousness of the NEO-PI-R was absent in the language descriptions of all 11 languages. Only two items (“I am easily embarrassed”, and “I am concerned about what others think about me”), which loaded on the Anxious and Dependent scales of the indigenous Neuroticism scale respectively, can be related to the NEO-PI-R facet Self-consciousness. This facet refers to the degree to which an individual is easily embarrassed, ashamed and uncomfortable around others. A possible explanation could be the fact that Self-consciousness is an inward focussed activity describing internal emotional states, which lends itself to self-description rather than to describing others, as it was required by the semi-structured interviews. Taylor and de Bruin (2006), found Self-consciousness for both the Black and White group on the BTI, with a congruence coefficient of .95, which suggests that its absence from the indigenous Neuroticism scale is likely due to methodological factors (semi-structured interviews) rather than a to a difference in personality structure.

Generally, there is good agreement between the facet structures of the NEO-PI-R and the indigenous Neuroticism scale. The development of an instrument combining emic and etic elements resulted in an indigenous measure of Neuroticism, which is structurally similar to that of the NEO-PI-R. The results of the present study support and extend the findings of previous research (McCrae et al., 2005) providing evidence in support of the universality of the trait Neuroticism.

Far less agreement is found between the indigenous Neuroticism scale and the EPP (Eysenck & Wilson, 1991), which comprises the facets Inferiority, Unhappiness, Anxiety, Dependence, Hypochondria, Guilt and Obsessiveness. The facet Unhappiness, which refers to high scoring individuals as characteristically pessimistic, gloomy and depressed, disappointed with their existence and at odds with the world, can be related to the facet Despaired of the Neuroticism

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scale. The facet Anxiety, which refers to high scoring individuals as being easily upset by things that go wrong, and who are inclined to worry unnecessarily about unpleasant things that may or may not happen, is represented by the facet Anxious of the indigenous Neuroticism scale. The facet Dependency, which refers to high scoring individuals as lacking in self-reliance, who think of themselves as helpless pawns of fate, are pushed around by other people and events, and show a high degree of what has been called “authoritarian submission”, shows some similarity with the facet Dependent of the indigenous Neuroticism scale.

However, four facets of the EPP are not directly represented in the indigenous Neuroticism scale. These are Inferiority, Hypochondria, Guilt, and Obsessiveness. The facet Inferiority refers to high scoring individuals as being low in self-esteem, having a low opinion of themselves and believing themselves to be failures. The facet Hypochondria refers to high scoring individuals as being likely to acquire psychosomatic symptoms and imagining that they are ill. The facet Guilt refers to high scoring individuals as self-blaming and troubled by their conscience regardless of whether their behaviour is really morally reprehensible. The facet Obsessiveness refers to high scoring individuals as being careful, conscientious, highly disciplined, very particular and easily irritated by things that are unclean, untidy or out of place.

Table 2.1 indicates that except for the facet Guilt, which is also represented in the PANAS (Watson et al., 1988), none of the other three facets above are found in any of the other models. Similarly to the facet Self-consciousness of the NEO-PI-R, a possible reason for the absence of the facet Inferiority could be that it is also an inward focused activity, describing internal emotional states lending itself to self-description rather than to describing others. A possible reason for the absence of Hypochondria and Obsessiveness could be that these concepts developed in the Western world, are rooted in psychopathology, which, at the high end of the Neuroticism dimensions, point to abnormal personality. In contrast, the indigenous Neuroticism scale was developed using natural language descriptions as conceived by “laypersons” portraying essentially normal personality characteristics. Another possible reason may be that Hypochondria and Obsessiveness are absent or occupy a less important role in the personality of South Africans.

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6.2.2 Neuroticism across language groups

Structural equivalence of the indigenous Neuroticism factor and its five subscales was established using Tucker’s phi. A value above .90 is seen as evidence for factorial similarity (Van de Vijver & Leung, 1997). Tucker’s phi was calculated for the higher order factor Neuroticism by comparing the total group with each language group. The results of the present study demonstrated factor equivalence of the indigenous Neuroticism factor across the three language groups assessed, indicating that the higher order dimension Neuroticism has the same psychological meaning across all groups. Tucker’s phi obtained for the factor

Neuroticism for each language group was: Germanic (pxy = 1.00), Nguni (pxy = 1.00), Sotho

(pxy = .99).

The results for the five group factors (Despaired, Anxious, Dependent, Temperamental and Impulsive) indicated congruence coefficients at or above .90 for all five group factors for the Germanic and the Nguni group, and for three of the group factors for the Sotho group. However, two group factors of the Sotho Group, Temperamental and Impulsive, showed congruence coefficients of .83 and .87 respectively, indicating that these two constructs are understood somewhat differently in this group.

These results are in stark contrast with those found in studies conducted in South Africa using instruments based on the 16PF. For example, Meiring et al. (2005) examined construct bias in the 15FQ+, an adapted version of the 15FQ designed to measure Cattell’s 16 personality factors (Tyler, 2003). Research on the 16PF has found second order factors highly similar to those known as the Big Five (Hofer & Eber, 2002). These secondary factors are Extraversion, Anxiety, Tough-Mindedness, Independence and Self-Control. Anxiety, which has been demonstrated to be highly congruent with the Neuroticism scale of the NEO-PI-R (Hofer & Eber, 2002), consists of the scales Emotional Stability, Vigilance, Apprehension and Tension.

Of the four scales comprising the Anxiety factor, only the Emotional Stability scale showed structural equivalence across all 12 groups in Meiring et al.’s (2005) study. A subsequent adaptation of the 15FQ+ (Meiring et al., 2006), primarily in item question design and wording modifications resulted in higher overall structural equivalence for Anxiety. The Emotional Stability and Vigilance factors showed structural equivalence across all groups,

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the factor Apprehension showed structural equivalence for all except the White group. However, the factor Tension still showed unsatisfactory equivalence across 50% of the groups, with Tucker’s phi below .90. In addition, the values of the factor Tension indicated that the improvements in test design did not function equally well for all language groups. Specifically, the Xhosa, Pedi and Tsonga groups, who had shown structural equivalence on this scale before the adaptation, now fell below the acceptable level of .90. These results demonstrate that although the adaptation of this instrument led to a higher overall equivalence, it posed new problems for other language groups, and is therefore still insufficient to enable unbiased measurement across the various South African language and race groups.

Van Eeden and Prinsloo (1997) compared African and Afrikaans/English language speakers using the SA version of the 16PF. They found the five second-order factor structure for the Afrikaans/English sample but only four factors for the African language speakers. For this group Emotional Sensitivity and Anxiety essentially measured the same trait. A comparison between African language and Afrikaans/English speakers for the second order factor Anxiety found a coefficient of congruence of .75, indicating construct non-equivalence for the two groups.

On the other hand, comparisons of studies based on the Big Five are more favourable. Heuchert, Parker, Stumpf, and Myburgh (2000) using the NEO-PI-R compared a sample of Black and White students and found the five-factor structure with a congruence coefficient for the total sample of .97 for Neuroticism when compared with the normative sample. Highly similar results were found for the White subgroup. The five factors were less clear for the Black subgroup. However, after target rotation of the Black subgroup against the normative sample, the congruence coefficient for Neuroticism was .90. Target rotation of the Black sample against the White sample indicated a similar basic personality structure and a congruence coefficient of .88 for Neuroticism. Only one facet, N5: Impulsiveness, yielded significant statistical differences between Black and White groups. Taken the findings of the present study into account, the facet Impulsiveness/Impulsive appears to be problematic. Disagreement also exists among researchers as to where to locate this facet. As discussed in Chapter 2.5.1, Impulsiveness is included in Eysenck and Wilson’s (1991) Psychoticism dimension and Hofstee et al.’s (1992) Conscientiousness factor. In addition, recent research has demonstrated that Impulsiveness should be assigned to Extroversion (McCrae, 2002).

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In contrast to Heuchert et al.'s (2000) findings Heaven and Pretorius (1998) comparing a sample of Sotho and Afrikaans speaking students using John's (1990) natural language descriptors, were unable to recover the five factor structure for the Sotho group. Nonetheless, a clear Neuroticism factor was found for both, the Afrikaans and the Sotho language groups.

Congruence coefficients on the BTI (Taylor & De Bruin, 2006) comparing White and Black groups also compare favourably with the results of the indigenous Neuroticism scale. The congruence coefficient for the factor Neuroticism was .96. Its subscales Affective Instability, Depression, Self-Consciousness and Anxiety measured .98, .98, .95, and .99 respectively. Further support for measurement invariance across language groups (Nguni, Sotho and Pedi) on the BTI (Taylor & De Bruin, 2006) was demonstrated by Ramsay et al. (2005).

6.2.3 Convergent validity

Convergent validity was demonstrated by comparing the indigenous Neuroticism scale with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the Negative Affect Sales of the PANAS (Watson et al., 1988). Using the Pearson’s correlation coefficient, a strong positive correlation (r = .89) was found with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006), and a moderate positive correlation (r = .66) was found with the Negative Affect scale of the PANAS (Watson et al., 1988), providing evidence of good convergent validity.

When comparing the items of the BTI (Taylor & De Bruin, 2006) with those of the indigenous measure of Neuroticism, it becomes apparent that both instruments measure very similar constructs. The BTI (Taylor & De Bruin, 2006) divides Neuroticism into four factors: Affective Instability, Depression, Self-consciousness and Anxiety. Affective Instability refers to the tendency to be easily upset, have feelings of anger and bitterness and be emotionally volatile. This factor is comparable with the factors Temperamental and Impulsive of the indigenous Neuroticism scale, which include items such as “I get upset with others quickly”, and “I find it difficult to keep my emotions under control”. Depression refers to the tendency to experience guilt, sadness, and hopelessness, and to feel discouraged and dejected. This factor is comparable with the factor Despaired of the indigenous Neuroticism scale, which includes items such as “I have no joy in life”, “I feel worthless”, and “I have lost interest in

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life”. Anxiety refers to the tendency to experience worry, nervousness, apprehensiveness, and tension. This factor is comparable with the factor Anxious of the indigenous Neuroticism scale, which includes items such as “I worry a lot”, and “I easily get scared”. Self- consciousness refers to the degree to which a person is sensitive to criticism, and has frequent feelings of shame and embarrassment. This factor shows a slight similarity with the factors Dependent and Anxious of the indigenous Neuroticism scale, which includes items such as “I am concerned about what others think about me”, and “I am easily embarrassed”. As already discussed above, a possible reason for the absence of a clear Self-consciousness facet may be due to methodological issues.

The moderate correlation of the indigenous Neuroticism scale with the Negative Affect scale of the PANAS (Watson et al., 1988) could be due to the format of the PANAS (Watson et al., 1988) scale and the small number of items. The Negative Affect scale of the PANAS (Watson et al., 1988) comprises 5 categories (Distressed, Guilty, Jittery, Fearful, and Angry). Each of these categories consists of two adjectives. These 10 adjectives are interspersed with the 10 adjectives of the Positive Affect scale and presented as a single list of items. In contrast to the indigenous Neuroticism scale, no context is provided, which could lead to misinterpretation. For example, the item “upset” (belonging to the category Distressed of the PANAS (Watson et. al, 1988) is used in the indigenous Neuroticism scale to describe the factors Anxious (“I get upset easily.”) and Temperamental (“I get upset with others easily.”). Another possible reason for its lower correlation with the indigenous Neuroticism scale could perhaps be the fact that the items were developed in the Western context. For example, the item “jittery” may be difficult to understand among African indigenous language speakers.

When comparing the items of the PANAS (Watson et al., 1988) with those of the new indigenous measure of Neuroticism, it becomes apparent that both instruments measure partially different constructs. The category Distressed (distressed, upset) can be related to the factors Despaired and Anxious of the indigenous Neuroticism scale, which include items such as “I feel miserable”, and “I get upset easily”. The categories Fearful (scared and afraid) and Jittery (jittery, nervous) can be related to the factor Anxious of the indigenous Neuroticism scale, which includes items such as, “I easily get scared”, and “I easily get nervous”. The category Angry (irritable, hostile) can be related to the factor Temperamental of the indigenous Neuroticism scale, which includes items such as “I get frustrated quickly” and “I easily lose my temper when things don’t go my way”. None of the items of the

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indigenous Neuroticism scale relate to the category Guilty (guilty, ashamed) of the PANAS (Watson et al., 1988), as the only item of the facet Ashamed (“I am easily embarrassed”) loaded on the Anxious factor of the indigenous Neuroticism scale. The items of the two factors, Dependent and Impulsive of the indigenous Neuroticism scales are not represented by the terms of the PANAS (Watson et al., 1988). To summarise, only three of the five factors of the indigenous Neuroticism scale are represented by the items of the PANAS (Watson et al., 1988), which results in the moderate correlation between these two instruments.

6.2.4 Reliability across language groups

Internal consistency for the indigenous Neuroticism scale and its subscales was determined using Cronbach’s alpha. As discussed in section 5.6 the total scale showed good internal consistency with an alpha coefficient of α = .96. Subscales that reflect the group factors also demonstrated good internal consistency with the following alpha coefficients: Despaired (α = .91); Anxious (α = .90); Dependent (α = .86); Temperamental (α = .87); and Impulsive (α = .87). The reliability coefficients for both the total indigenous Neuroticism scale and its five subscales were above .80 for all three language groups (Germanic, Nguni and Sotho) indicating good internal consistency.

These results differ from the findings of various studies conducted in South Africa using instruments based on the 16PF. Internal consistency in Meiring et al.'s ( 2005) study of the 15FQ+ was very low for some of the factors, specifically for the Black language groups. The four scales Emotional Stability, Vigilance, Apprehension, and Tension showed mean alphas across all groups of .64, .44, .40, and .51 respectively, which is well below the often referenced level of .70 (Nunnally & Bernstein, 1994). A subsequent adaptation of the instrument (Meiring et al., 2006) led to slight improvements for different groups. However, the mean alphas for all four Anxiety factors remained below .70, making “the instrument unsuitable for the South African context” (p. 350).

Similar results were found for the 16PF (SA92). Abrahams and Mauer (1999a) investigated the cross-cultural comparability of the 16PF (SA92) across four race groups and reported extremely low internal consistency coefficients with alphas of below .50 for 13 of the 16 primary factors for the Black group. The four factors comprising the Anxiety scales showed

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alphas of .26, .32, .25, and .46 for the Emotional Stability, Vigilance, Apprehension and Tension scales respectively.

Van Eeden and Mantsha (2007), who translated the 16PF5 into an African language (Venda) and administered it to a Venda speaking student sample, reported reliability coefficients of above .60 for only four of the 16 factors even after excluding items to increase reliability. They cited problems with equivalent concepts in the target language and cultural differences in the manifestation of the constructs and concluded that further validity and equivalence studies were not feasible.

In contrast, the BTI (Taylor & De Bruin, 2006) is the only instrument, which showed similar reliability coefficients to that of the indigenous Neuroticism scale. Its Neuroticism factor had an alpha coefficient of α = .93. Comparisons between White and Black groups were made, and all four subscales (Affective Instability, Depression, Self-Consciousness and Anxiety) yielded alphas of above .80 across both race groups. A subsequent study by Ramsay et al. (2005) using the BTI to measure Neuroticism across the Nguni, Sotho and Pedi language groups revealed reliability coefficients of .90, .91, and .92 respectively.

6.2.5 Facets not included in the Neuroticism factor

Some negative facets of the Emotional Stability cluster did not load on the Neuroticism factor as expected. These facets were: Demanding, Obsessive/compulsive and Attention-seeking. The facet Demanding was removed on theoretical grounds after reviewing current literature, which indicated that it belongs to the dimension Agreeableness (De Raad, 2000; Lee & Ashton, 2008).

The facets Obsessive/compulsive and Attention-seeking were removed for psychometric reasons. Considerable overlap of item content existed between the facet Needy and Attention- seeking, and the items loaded on one factor during the initial item analysis. After removal of items with low loadings this factor split into two, Needy and Attention-seeking. However, the facet Attention-seeking had insufficient items to retain it as a factor and was therefore removed.

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At facet level analysis, the facet Obsessive/compulsive had a factor loading < .40 on the higher order factor and no loadings > .30 on the first-order factors, suggesting that it is not a strong indicator of Neuroticism. During item analysis it became apparent that none of the items fulfilled the required psychometric criteria set for the retention of these items. A possible reason for this finding could be that the facet Obsessive/compulsive falls outside the range of normal personality. Costa and McCrae (1992a) view Neuroticism as a dimension of normal personality and they contrast adjustment or Emotional Stability with maladjustment or Neuroticism. When comparing the facet structures of the various models describing Neuroticism (Table 2.1) only Eysenck and Wilson’s (1991) model includes Obsessiveness, which refers to behaviour such as being careful, conscientious, highly disciplined, very particular and easily irritated by things that are unclean, untidy or out of place. Although the facet Obsessive/compulsive includes items referring to obsessive behaviour such as “I need to tidy up continually”, and “I wash my hands repeatedly”, it also includes items describing compulsiveness such as “I need to keep my daily routines”, and ”I need to do certain things in the exact same order every time”, indicating abnormal personality.

6.2.6 Split of positive and negative facets

Some facets of the Emotional Stability cluster did not load on the higher order Neuroticism factor. These facets were Balancing life, Even-tempered, Mature, Obedient, Courageous, Coping on your own, Coping with the help of others, Patient, Content with life and possessions, Accepting self and others, Self-confident and Self-respectful. Instead, they formed a factor on their own (Table 5.3), indicating good adjustment and psychological health.

When compared with the instruments discussed previously (Costa & McCrae, 1992a; Eysenck & Wilson, 1991; Hofstee et al., 1992) this finding is surprising and contrary to the a priori theoretical expectations. Within these models Emotional Stability is understood as a bipolar construct comprising of a positive pole at one end of the dimension (Emotional Stability) and a negative pole at the other end (Neuroticism). For example, in the present study the facets Patient and Even-tempered of the indigenous Neuroticism scale are comparable with Hofstee et al.'s, (1992) terms Patient and Unexcitable, which load on the positive pole of Emotional Stability. The facets Coping on your own, and Coping with the help of others, are comparable with the NEO-PI-R’s (Costa & McCrae, 1992a) positive pole

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of Vulnerability, which refers to the ability to cope effectively in stressful situation. The facet Even-tempered can be compared with the NEO-PI-R’s (Costa & McCrae, 1992a) positive pole of Angry Hostility. Individuals scoring low on this scale are likely to be seen as even- tempered. In addition, the facet Mature is comparable with Mature, which is a descriptor on the positive pole of the Emotional Stability scale on the 16PF (Hofer & Eber, 2002).

A possible explanation for these results may be found in the theory underlying the PANAS (Watson et al., 1988), which treats PA and NA as two separate “truly uni-polar constructs that essentially are defined by their high poles” (Watson, Wiese, Vaidya, & Tellegen, 1999). According to Watson et al. (1999) these two dimensions are related to bio-behavioural systems that have developed to deal with different evolutionary tasks. Negative Affect is a component of the withdrawal-oriented behavioural inhibition system (BIS), whose main purpose is to prevent problems to the organism by inhibiting behaviour that might lead to pain, punishment, or some other negative consequence. Negative feelings related to NA assist in the identification of possible threats. For example, feelings of nervousness and fear prompt an organism to escape from potentially dangerous situations (Watson et al., 1999).

In contrast, Watson et al. (1999) describe Positive Affect as a component of the approach- oriented behavioural facilitation system (BFS), which guides organisms toward situations and experiences that may potentially lead to pleasure and reward. Its main function is to ensure the procuring of resources (e.g. food and water, warmth and shelter, the cooperation of others, sexual partners) that are essential to the survival of both the individual and the species. Positive feelings related to PA act as motivator and reward for goal-directed behaviours. For example, enthusiasm and confidence increase the expectation that goal- initated behaviour will be rewarded and therefore increase the likelihood of performing the activities required to attain a set goal. Once that goal has been successfully achieved, the organism is rewarded with feelings of joy and pleasure (Watson et al., 1999). In other words, Negative and Positive Affect fulfil two completely different functions and are therefore seen as two highly distinctive dimensions (Watson et al., 1999). With regard to the present study this theory implies that individuals scoring low on Neuroticism are not necessarily likely to experience positive emotions, but rather the absence of negative emotions.

Watson et al. (1999) demonstrated very strong correlations between Negative Affect and Neuroticism and strong correlations between Positive Affect to Extraversion. In the present

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study the two facets Courageous and Self-confident of the Emotional Stability cluster did not load on the higher order factor representing Neuroticism. These facets are comparable with (Hofstee et al., 1992)’s terms Bold and Confident, which have been attributed to Extraversion.

Overall, these findings suggest that the dimension Neuroticism as measured in South Africa, appears to be understood in line with the theory underlying the PANAS (Watson et al., 1988), which treats PA and NA as two separate constructs (Watson et al., 1999). In contrast with other existing Western measures discussed above (Costa & McCrae, 1992a; Eysenck & Wilson, 1991; Hofstee et al., 1992) the indigenous Neuroticism scale is uni-polar, assessing Neuroticism only. The facets referring to positive adjustment and psychological health typically assigned to Emotional Stability and Extraversion load on a separate factor. These findings have major implications for the understanding and the assessment of the construct Neuroticism in the South African context, as low scores on the indigenous Neuroticism scale cannot be equated with the presence of Emotional Stability.

6.2.7 Postulates

In the present study four postulates were tested. Postulate 1 stated that in an exploratory factor analysis using oblique rotation the facets or first order factors would correspond with the a-priori subclusters of the SAPI model. Postulate 2 stated that after performing a second- order factor analysis on the correlations of the first-order factors and a Schmid-Leiman transformation, a hierarchical orthogonal solution would be obtained with the higher-order factor corresponding to the expected Emotional Stability trait. On the whole, these two postulates were clearly not supported by the data due to the multidimensionality of several facets, and failure of some facets and items to define a higher order Neuroticism factor as discussed above. However, despite the failure to meet the a priori expectations, the present study revealed a cross-culturally valid and reliable indigenous Neuroticism scale, which measures facets and items traditionally associated with Neuroticism, but excludes those facets and items traditionally associated with Emotional Stability and Extroversion.

Postulate 3 stated that in a comparison between the Gemanic, Nguni and Sotho groups’ factor structure, the congruence coefficients for all groups would be at or above .90 for all factors. This postulate was well supported for the Neuroticism factor and for the majority of the five

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group factors across all language groups. Only two group factors, Temperamental and Impulsive, showed congruence coefficients of .83 and .87 respectively, indicating that these two constructs are understood somewhat differently in this group.

Postulate 4 stated that the newly developed indigenous Emotional Stability scale would correlate positively with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and the Negative Affect scales of the PANAS (Watson et al., 1988). This postulate was well supported. A strong positive correlation (r = .89) was found with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006) and a moderate positive correlation (r = .66) was found with the Negative Affect scale of the PANAS (Watson et al., 1988).

6.2.8 Summary

On the whole, the findings of the present study are very promising. The present study is possibly the first to assess Neuroticism in South Africa as conceived in natural language descriptions of individuals from all 11 official languages. It revealed a valid and reliable indigenous measure of Neuroticism with good psychometric properties at the higher order factor level. Neuroticism was found in all 11 languages, and the Neuroticism factor replicated across three South African language groups endorsing the idea of a biological basis for the trait Neuroticism, as discussed in Chapter 2.2.2.

Good construct validity of the indigenous Neuroticism scale was established across three language groups and further validated by the high correlation with the Neuroticism scale of the BTI (Taylor & De Bruin, 2006; Ramsay et al., 2005), which is based on the NEO-PI-R. These findings support the notion of Neuroticism as a universal trait.

The Emotional Stability cluster as defined within the SAPI context was separated into facets describing positive (Emotional Stability) and negative (Neuroticism) psychological adjustment during data analysis. Although contrary to expectations, this finding is in line with the theory underlying the PANAS (Watson et al., 1988), which treats PA and NA as two separate constructs (Watson et al., 1999). The final uni-dimensional indigenous Neuroticism scale contains 46 items and measures negative adjustment only. This is an important finding as it affects construct equivalence when compared with the other scales discussed above, (Costa & McCrae, 1992a; Eysenck & Wilson, 1991; Hofstee et al., 1992), which assess both

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Neuroticism and Emotional Stability. Therefore, no direct comparisons with other cultures can be made (Van de Vijver & Tanzer, 2004).

Nonetheless, the present study has demonstrated that the indigenous Neuroticism scale is a viable tool to accurately assess the dimension Neuroticism in South Africa’s multicultural society. The fact that the other eight clusters of the SAPI project (Extraversion, Soft- heartedness, Conscientiousness, Intellect, Openness, Integrity, Relationship Harmony and Facilitating) were developed on the same basis as Neuroticism, using natural language descriptions and semi-structured interviews, bodes well for the possibility of developing an indigenous model of personality and a personality instrument to measure it.

6.3 Limitations and suggestions for further research

As with all research, the present study has several limitations. Although it was decided at this early stage of the scale construction process to only select university students, this presents a limitation with regard to the generalisability of the study. In addition, only nine of the 11 languages were assessed. Therefore, the present study should be replicated with a larger, more representative sample of the South African population.

Another limitation refers to the construct validity of the facet scales. The newly developed indigenous Neuroticism scale demonstrates good construct validity across the three language groups at the dimension level, and across the majority of its group factors. However, two of the group factors, Temperamental and Impulsive, indicated congruence coefficients below the traditionally accepted level of .90 (Van de Vijver & Leung, 1997) for the Sotho group. Further research on the facets Temperamental and Impulsive would be necessary to enable measurement of Neuroticism at facet level.

In addition, the item properties of the indigenous Neuroticism scale should be investigated using a method such as the Rasch model to identify possible differential item functioning. Furthermore, personality inventories are prone to response sets such as acquiescence and social desirability (e.g. Van de Vijver and Rothmann 2004). The questionnaire used in the present study includes a set of social desirability items, and future research should investigate the indigenous Neuroticism scale for response bias. Finally, the 12 facets that appeared to fall outside the scope of Neuroticism describing positive psychological adjustment should be

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investigated and analysed separately to ensure coverage of all items of the original SAPI database.

6.4 Conclusion

The ultimate goal of the SAPI project is to gain a better theoretical understanding of personality as it manifests in South Africa, and to develop a personality instrument that is psychometrically sound and applicable to all cultural groups in South Africa. The present study has contributed to this goal through the development of a valid and reliable scale of Neuroticism across various South African language groups using the combined emic (locally developed instrument) and etic (quantitative statistical analyses) approach. This result is encouraging, and the present study can be seen as a first step in the process towards fulfilling the demands of the Employment Equity Act 55 of 1998 (Section 8) (Government Gazette, 1998), which requires for tests to be (a) scientifically valid and reliable; (b) fair to all employees; and (c) not biased against any employee or group.

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Appendix A

Emotional Stability Questionnaire (326 items and 15 Social Desirability items )

Item Item coding Item description

1 i1BBLfamily I balance my family life with the other things that I do 2 i2BBLfriend I make time for my friends regularly 3 i3BBLattention I give enough attention to both my work or studies and other areas in my life 4 i4BBLworkfam I balance my work and family responsibilities 5 i5BBLhobby I have time for hobbies 6 i6BBLsocialize I have enough time to socialise with my friends 7 i7BBLhours I find that there are enough hours in the day to get my work done 8 i8BBLcombine I find that my work or study load can be combined with my family needs 9 i9BBLhealth I have a healthy workload 10 i10BBLquality I think that quality of life is more important than my work or studies 11 i11BBLequal I find my work or studies and personal life equally important 12 i12BBLbalance I live a balanced life 13 i13BETemostab I am emotionally stable 14 i14BETsitumost I am calm in most situations 15 i15BETpredict I behave in a predictable way with others 16 i16BETcontr I control my emotions 17 i17BETpref I prefer calm places 18 i18BETtalk I talk to others calmly 19 i19BETreact I react to problems in a calm manner 20 i20BETcalmdow I calm down quickly 21 i21BETmoodsame I stay in the same mood from one day to the other 22 i22BETcalmper I am a calm person

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Item Item coding Item description

23 i23BETcheerful I remain cheerful even when there are problems 24 i24BETsimilar I behave in a similar way from one situation to the other 25 i25BETsitudiff I remain calm in difficult situations 26 i26BETupset I only get upset when others do something with very serious bad consequences 27 i27BETexcited I remain calm even when others are excited 28 i28BETexprfeel I express my feelings in a calm manner even if I am upset 29 i29BETanger I am able to hold back my anger 30 i30BETmoodbad I get over bad moods easily 31 i31BETSD I never hesitate to go out of my way to help someone in trouble 32 i32BMrespdec I make responsible decisions 33 i33BMemomat I am emotionally mature 34 i34BMactage I act according to my age 35 i35BMrole I act in a way that suits my role 36 i36BMactmat I act in a mature manner 37 i37BMlosing I can accept losing 38 i38BMbehave I behave appropriately in most situations 39 i39BMlisten I listen when I get reprimanded 40 i40BMapolog I apologise when I act inappropriately 41 i41BMdress I dress appropriately 42 i42BMadmit I admit when I am wrong 43 i43BMSD I always forgive others for their wrongdoings 44 i44BSTiritate I get irritated easily 45 i45BSTangry I get angry easily 46 i46BSTagress I become aggressive quickly 47 i47BSThateannoy I hate it when others annoy me 48 i48BSTshout I shout when I am angry 49 i49BSTrespect I get angry when people do not respect me 50 i50BSTbeat I feel like beating up others when I am angry

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Item Item coding Item description

51 i51BSTrepriothers I reprimand others over minor issues 52 i52BSTlosetemp I easily lose my temper when things do not go my way 53 i53BSTimpatient I get impatient with others 54 i54BSTtold I get angry when people do not do what I told them to 55 i55BSTupset I get upset with others quickly 56 i56BSTignore I ignore others when I get angry 57 i57BSTunappr I appear to be unapproachable to others 58 i58BSTinterrupt I get angry when people interrupt me while I talk 59 i59BSTsuffer I make others suffer when I am in a bad mood 60 i60BSTquestions I get irritated when someone asks too many questions 61 i61BSTreprime I get angry when others reprimand me 62 i62BSTannoy I get annoyed quickly 63 i63BSTshorttemp I have a short temper 64 i64BSTfrustrate I get frustrated quickly 65 i65BSTleave I want people to leave me alone 66 i66BSTbother I want others to stop bothering me 67 i67BSTprovoke I get angry when people provoke me 68 i68BSTSD I sometimes feel like breaking things 69 i69CCrisks I take risks 70 i70CCdeal I deal with uncomfortable emotions immediately 71 i71CCface I face difficult problems immediately 72 i72CCbraveneed I am brave when I need to be 73 i73CCsitudang I enter dangerous situations without showing fear 74 i74CCconfront I confront my fears 75 i75CChandle I can handle bad news 76 i76CCmajlife I have the courage to make major life changes

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Item Item coding Item description

77 i77CCspeakup I speak up for others when I hear someone saying mean things about them 78 i78CCprotect I take risks to protect others 79 i79CCbelief I stand up for my beliefs 80 i80CCnegcons I speak my mind even if this has negative consequences 81 i81CCbraveper I am a brave person 82 i82CCsitudiff I can handle difficult situations 83 i83CCSD I always admit when I do not know something 84 i84CFjudge I am afraid of people judging me 85 i85CFfailure I am afraid of failure 86 i86CFsafety I am worried about the safety of others 87 i87CFreject I am afraid of being rejected 88 i88CFsitumany I get worried in many situations 89 i89CFintimidate I am intimidated by small things 90 i90CFpressure I panic when I am under pressure 91 i91CFhealthown I worry about my health 92 i92CFhealthother I worry about other peoples' health 93 i93CFhurtemotion I am afraid of being hurt emotionally 94 i94CFhurtphysic I am afraid of being hurt physically 95 i95CFbadthing I am afraid that bad things may happen 96 i96CFnewthing I am afraid of doing new things 97 i97CFdiffrelax I find it difficult to relax 98 i98CFunfcircum I get anxious in unfamiliar circumstances 99 i99CFscaredquick I get scared quickly 100 i100CFanimal I am afraid of many animals 101 i101CFdark I am afraid of the dark 102 i102CFworryself I worry a lot 103 i103CFworryother I worry about others 104 i104CFscaredeasi I easily get scared 105 i105CFafraidpeop I am afraid of some people

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Item Item coding Item description

106 i106CFavoidclose I avoid getting close to others so as not to get hurt 107 i107CFlockdoor I lock all doors at home 108 i108ECCdeal I can deal with difficulties in my life 109 i109ECCcope I cope well in my life 110 i110ECCspeakfeel I speak to others about my feelings when I have a problem 111 i111ECCpretend I pretend that nothing bad has happened even if it actually has 112 i112ECCsupport I seek emotional support from friends and relatives when I have a problem 113 i113ECCtalkpeop I talk to people who can help me with a problem 114 i114ECClookgood I look for something good even in the bad things that happen 115 i115ECChandle I think about how to best handle a problem 116 i116ECCadvice I ask for advice from people who have experienced similar problems 117 i117ECCplan I make a plan of action when something goes wrong 118 i118ECCbusy I keep busy to avoid thinking of bad things 119 i119ECCSD I have "played sick" to get out of something 120 i120ECIspeakthink I speak before I think 121 i121ECIreactimm I react to situations immediately 122 i122ECIeffect I act without considering the effects that my actions will have on me 123 i123ECIbehavirr I behave irresponsibly 124 i124ECIaffectothers I act without thinking how my actions will affects others 125 i125ECInothink I do things without thinking too much in advance 126 i126ECIspontaneous I do things spontaneously 127 i127ECIinterrupt I interrupt people to say what I think

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Item Item coding Item description

128 i128ECIcontremo I find it difficult to keep my emotions under control 129 i129ECItalknot I talk even when I know I should not 130 i130ECIreactint I react intensely 131 i131ECIurge I find it difficult to control my urges 132 i132ECItemptation I find it difficult to resist temptations 133 i133ECInotknow I do things without knowing why 134 i134ECIregret I do things that I later regret 135 i135ECIactimpul I act impulsively 136 i136ECISD I am sometimes irritated by people who ask favours of me 137 i137ECOsameorder I need to do certain things in the exact same order every time 138 i138ECOroutine I need to keep my daily routines 139 i139ECOwashhand I wash my hands repeatedly 140 i140ECOorderfeel I need everything to be in order to feel all right 141 i141ECOtidy I need to tidy up continually 142 i142ECOschedule I need to follow a strict schedule to feel in control 143 i143ECPexplain I explain things until people understand what I mean 144 i144ECPdiscuss I prefer to discuss things calmly rather than argue 145 i145ECPfrustrate I remain calm even when I am frustrated 146 i146ECPturn I calmly wait for my turn to speak 147 i147ECPlisten I make time to listen to other peoples' problems 148 i148ECPbear I bear with others when they are going through hard times 149 i149ECPpatient I am patient 150 i150ECPwait If there is something I want to say, I can wait until I get the chance to say it

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Item Item coding Item description

151 i151ECPchance I give people who have disappointed me a second chance 152 i152ECPtease I remain patient when others tease me 153 i153ECPnotlike I am patient even with people I do not like 154 i154ECPweakness I bear with the weaknesses of others 155 i155ECPtime I give others time to do what I have asked them to 156 i156ECPsureunderst I make sure others understand what I explain to them 157 i157ECPfaceprobl I face problems with patience 158 i158ECPSD I am always a good listener, no matter whom I am talking to 159 i159ECTmoody I am moody 160 i160ECTdowhatever I do whatever comes to my mind when I am irritated 161 i161ECTcontrolemo I am controlled by my emotions 162 i162ECTtreatbad I treat others badly for no reason 163 i163ECTissueirrit I get irritated by minor issues 164 i164ECTissueangr I get angry over minor issues 165 i165ECTactmood I act on my moods 166 i166ECTcannotdo I get irritated if people cannot do things for themselves 167 i167ECTsayinappr I say inappropriate things 168 i168ECTloseinterest I lose interest in things suddenly 169 i169ECTchangemood I quickly change between a good and a bad mood 170 i170ECTdrivenmood I am driven by my mood 171 i171ECTfriendly I am friendly on some days and harsh on other days 172 i172ECTwakeup I sometimes wake up in a good mood and other times in a bad mood 173 i173ECThappysad I can be happy one day and sad the next day

145

Item Item coding Item description

174 i174ECTwalkaway I walk away if I am irritated 175 i175ECTswings I often have mood swings 176 i176ESEMgivein I give in to my emotions easily 177 i177ESEMfeeldeep I feel emotions deeply 178 i178ESEMbreak I break down easily 179 i179ESEMcryeasi I cry easily 180 i180ESEMbodylang I express my feelings through body language 181 i181ESEMopenanger I show my anger openly 182 i182ESEMfacial I show strong emotions through facial expressions 183 i183ESEMnasty I am nasty to people when they have upset me 184 i184ESEMcryangry I cry when I am angry 185 i185ESEMcrysad I cry when I am sad 186 i186ESEMcryhappy I cry when I am happy 187 i187ESEMshowemo I show my emotions easily 188 i188ESEMexprfeel I express my feelings 189 i189ESEMemotinal I am emotional 190 i190ESEMcare I care a lot about emotions 191 i191ESEMnoreason I cry for no apparent reason 192 i192ESEMannoy I show it if something annoys me 193 i193ESEMSD I sometimes try to get even, rather than forgive and forget 194 i194ESEXoverreact I overreact to situations 195 i195ESEXgoodthing I become overly excited when good things happen 196 i196ESEXbadthing I become overly excited when bad things happen 197 i197ESEXexagfeel I exaggerate my feelings 198 i198ESEXexagthing I exaggerate things 199 i199ESEXactexag I act in an exaggerated way 200 i200ESSEminor I take minor things seriously

146

Item Item coding Item description

201 i201ESSEtalkbehind I am bothered by people who talk behind my back 202 i202ESSEpersonal I take things personally 203 i203ESSEhurteasi I am easily hurt 204 i204ESSEbadnews I have difficulty hearing bad news 205 i205ESSEhurtlaugh I get hurt when people laugh at me 206 i206ESSEupset I get upset easily 207 i207ESSEoffend I get offended if people say something bad about me 208 i208ESSEmovie I am easily touched by movies I see 209 i209ESSHembarrass I am easily embarrassed 210 i210ESSHashamed I am easily ashamed 211 i211ESSHhumiliate I am easily humiliated by others 212 i212NCPcomplevery I complain about everything 213 i213NCPdissat I tend to be dissatisfied with different situations 214 i214NCPcomplway I complain if things do not go my way 215 i215NCpget I never get what I want 216 i216NCPappear I express problems with other peoples' appearance 217 i217NCPnag I nag about everything I see 218 i218NCPpoint I point out problems in many things 219 i219NCPnotlike I complain when I have to do work that I do not like 220 i220NCPdifficult I complain about the difficulties in my life 221 i221NCPSD I sometimes feel resentful, when I do not get my way 222 i222NCTsatisflife I am satisfied with my life 223 i223NCTsatisdo I am satisfied with what I do in my life 224 i224NCTsatiswork I am satisfied with my work or studies 225 i225NCTpleasehave I am pleased with what I have 226 i226NCTaccept I accept things as they are 227 i227NCTsatishome I am satisfied with the home I have

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Item Item coding Item description

228 i228NCTfamily I am happy with my family 229 i229NCTnotwork I accept it when things do not work out as planned 230 i230NCTachieve I am satisfied with my achievements 231 i231NCTweakness I accept my weaknesses 232 i232NCTothers I am satisfied with the way others do what they do 233 i233NCTnotperfect I accept it if things are not perfect 234 i234NCTSD I always admit it when I have made a mistake 235 i235NDproblem I feel down when I cannot solve a problem 236 i236NDaffected I am affected deeply by what happens in my life 237 i237NDdepressed I feel depressed 238 i238NDnotdoany I often feel that I do not want to do anything 239 i239NDmiserable I feel miserable 240 i240NDdesperate I feel desperate 241 i241NDhelpless I feel helpless 242 i242NDsad I tend to feel sad 243 i243NDjoy I have no joy in life 244 i244NDinterest I have lost interest in life 245 i245NDworthless I feel worthless 246 i246NNrelationship I am afraid of being in a relationship 247 i247NNcommitment I am afraid of commitment 248 i248NNtrust I find it difficult to trust others 249 i249NNlove I am afraid to love someone 250 i250NNanxious I get anxious in many situations 251 i251NNthreaten I am afraid of things that other people do not find threatening 252 i252NNfearworst I fear the worst 253 i253NNnervous I easily get nervous 254 i254panic I panic easily 255 i255NTsmallthing I worry about small things 256 i256NTnervous I am a nervous person

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Item Item coding Item description

257 i257NYstressed I get stressed about many things 258 i258NTtense I am a tense person 259 i259NTproblems I find it difficult to deal with problems 260 i260NTrelax I find it difficult to relax 261 i261EGOAseek I seek attention from others 262 i262EGOAnotice I want to be noticed 263 i263EGOAadmire I need to be admired by others 264 i264EGOArecognition I need recognition from others 265 i265EGOAcentre I need to be the centre of attention 266 i266EGOApraise I need others' praise 267 i267EGOAlisten I want people to listen to me 268 i268EGOAfocus I want people to focus on me 269 i269EGOAimpress I need to impress people 270 i270EGOAsympathy I want sympathy from others 271 i271EGOAlike I want to be liked by others 272 i272EGOArespect I want to be respected 273 i273EGOAlook I want people to look at me 274 i274EGOASD I like to gossip at times 275 i275EGODlisten I expect others to listen to me 276 i276EGODobey I expect others to obey me 277 i277EGODdomore I expect others to do more than they can 278 i278EGODdotold I expect others to do as they are told immediately 279 i279EGODdevote I want others to devote their time to me 280 i280EGODplease I am difficult to please 281 i281EGODentertain I need to be entertained all the time 282 i282EGODmyway I want things to be done my way 283 i283EGODapologize I expect people to apologise for their mistakes 284 i284EGODdothings I want others to do things for me 285 i285EGODdelay I expect others to listen only to me 286 i286EGODlistenonly I want things to be done for me without delay 287 i287EGODtell I need to tell people what to do

149

Item Item coding Item description

288 i288EGODexhaust I exhaust people with my expectations 289 i289EGODdrain I drain other peoples' energy 290 i290EGODrightaway When I want something, I want it right away 291 i291EGODSD I have taken advantage of someone on occasions 292 i292EGONaskopinion I constantly ask other peoples' opinions before I make decisions 293 i293EGONaccompany I need someone to accompany me everywhere 294 i294EGONlike I need to know that people like me 295 i295EGONapproval I need approval from others 296 i296EGONplease I need to please other people 297 i297EGONappreciate I need to be appreciated 298 i298EGONaccept I need to be accepted by others 299 i299EGONdependopinion I depend on other peoples' opinions 300 i300EGONencourage I need others to encourage me constantly 301 i301EGONcare I need others to take care of me 302 i302EGONhelp I need help from others for many things 303 i303EGONdependothers I depend on others 304 i304EGONthink I am concerned about what others think about me 305 i305EGONknowwell I ask for others' opinions even on things that I know well 306 i306EGONaprovedo I need people to approve of what I do 307 i307EGONSD I am sometimes jealous of others with good fortune 308 i308EGOSCsecureability I am secure in my own ability 309 i309EGOSCtrustability I trust my own abilities 310 i310EGOSCsuperior I feel superior to other people 311 i311EGOSCself-assured I am self-assured 312 i312EGOSCself-image I have a good self-image 313 i313EGOSCself-esteem I have high self esteem 314 i314EGOSCunfamsitu I feel comfortable in unfamiliar situations 315 i315EGOSCbelieve I believe in myself

150

Item Item coding Item description

316 i316EGOSCover-confident I am over-confident in my own abilities 317 i317EGOSCaccept I accept myself 318 i318EGOSCknowwant I know what I want from life 319 i319EGOSCknowbest I know what is best for me in my life 320 i320EGOSCconfident I am a confident person 321 i321EGOSCachieve I know how to achieve what I want 322 i322EGOSCsecureself I feel secure in myself 323 i323EGOSCSD I sometimes have doubts about my ability to succeed in life 324 i324EGOSRrespect I respect myself 325 i325EGOSRmostimport I am the most important person in my life 326 i326EGOSRlove I love myself 327 i327EGOSRappearance I take care of my appearance 328 i328EGOSRbodylike I like my body 329 i329EGOSRcompliment I compliment myself on things well done 330 i330EGOSRtime I make time for myself 331 i331EGOSRhome I take pride in keeping my home clean 332 i332EGOSRgoodpers I think of myself as a good person 333 i333EGOSRbodycare I take care of my body 334 i334EGOSRspeak I speak in a calm, respectable way 335 i335EGOSRhealth I look after my health 336 i336EGOSRlookmyself I look after myself 337 i337EGOSRtrust I trust myself completely 338 i338EGOSRrespectbody I respect my body 339 i339EGOSRlikemyself I like myself 340 i340EGOSRharmful I keep myself away from harmful things 341 i341EGOSRSD I always practice what I preach Note. The social desirability items indicated by SD in the item coding of the questionnaire were excluded from this thesis.

151

Appendix B Component matrices and scree plots for seven of the 25 original facets indicating multidimensionality

1. Mature

Figure B1. Scree plot: Mature

Table B1 Pattern Matrix: Mature Component Item 1 2 i32BMrespdec .62 .15 i33BMemomat .59 .15 i34BMactage .76 -.21 i35BMrole .85 -.14 i36BMactmat .81 .05 i37BMlosing -.07 .62 i38BMbehave .45 .35 i39BMlisten .09 .63 i40BMapolog .01 .76 i41BMdress .45 .23 i42BMadmit .04 .72 Note. Component loadings > .30 are in boldface.

152

2. Fearful

Figure B2. Scree plot: Fearful

Table B2 Pattern Matrix: Fearful Component Item 1 2 3 i84CFjudge .52 .35 -.18 i85CFfailure .17 .61 -.11 i87CFreject .25 .66 -.12 i88CFsitumany .52 .30 .07 i89CFintimidate .63 .13 .10 i90CFpressure .37 .23 .23 i93CFhurtemotion -.12 .82 .03 i94CFhurtphysic -.28 .59 .42 i95CFbadthing .09 .57 .25 i96CFnewthing .66 -.10 .12 i97CFdiffrelax .78 -.20 -.02 i98CFunfcircum .49 .17 .20 i99CFscaredquick .36 .05 .60 i100CFanimal -.03 -.05 .75

153

Table B2 Pattern Matrix: Fearful Component Item 1 2 3 i101CFdark .07 -.15 .71 i102CFworryself .54 .12 .23 i104CFscaredeasi .26 -.03 .74 i105CFafraidpeop .18 .07 .52 i106CFavoidclose .29 .13 .22 i107CFlockdoor -.07 .17 .36 Note. Component loadings > .30 are in boldface. Items i86, i91, and i92 were removed as they loaded < .30 on the component matrix. Item i103 did not load on the component matrix.

3. Coping

Figure B3. Scree plot: Coping

154

Table B3 Pattern Matrix: Coping Component Item 1 2 i108ECCdeal -.09 .74 i109ECCcope .06 .66 i110ECCspeakfeel .75 .08 i112ECCsupport .92 -.20 i113ECCtalkpeop .85 .05 i114ECClookgood .29 .50 i115ECChandle -.02 .77 i116ECCadvice .61 .22 i117ECCplan .00 .69 Note. Component loadings > .30 are in boldface. Items i111 and i118 were removed as they loaded < .30 on the component matrix.

4. Temperamental

Figure B4. Scree plot: Temperamental

155

Table B4 Pattern Matrix: Temperamental Component Item 1 2 i159ECTmoody .31 .50 i160ECTdowhatever .55 .13 i161ECTcontrolemo .63 .10 i162ECTtreatbad .79 -.07 i163ECTissueirrit .81 -.02 i164ECTissueangr .82 .02 i165ECTactmood .65 .19 i166ECTcannotdo .61 -.07 i167ECTsayinappr .81 -.10 i168ECTloseinterest .52 .12 i169ECTchangemood .25 .51 i170ECTdrivenmood .41 .48 i171ECTfriendly .25 .60 i172ECTwakeup -.13 .90 i173ECThappysad -.14 .89 i175ECTswings .18 .67 Note. Component loadings > .30 are in boldface. Item i174 was removed as it loaded < .30 on the component matrix.

156

5. Emotional

Figure B5. Scree plot: Emotional

Table B5 Pattern Matrix: Emotional Component Item 1 2 i176ESEMgivein .36 .42 i177ESEMfeeldeep .27 .43 i178ESEMbreak .67 .15 i179ESEMcryeasi .85 -.01 i180ESEMbodylang .11 .50 i181ESEMopenanger -.04 .70 i182ESEMfacial -.08 .74 i183ESEMnasty -.07 .62 i184ESEMcryangry .82 -.07 i185ESEMcrysad .81 -.08 i186ESEMcryhappy .63 -.12 i187ESEMshowemo .46 .38 i188ESEMexprfeel .20 .41 i189ESEMemotinal .69 .19

157

Table B5 Pattern Matrix: Emotional Component Item 1 2 i190ESEMcare .52 .22 i191ESEMnoreason .66 -.04 i192ESEMannoy -.09 .74 Note. Component loadings > .30 are in boldface.

6. Content

Figure B6. Scree plot: Content

Table B6 Pattern Matrix: Content Component Item 1 2 i222NCTsatisfilife .80 -.08 i223NCTsatisdo .84 -.07 i224NCTsatiswork .74 -.04 i225NCTpleasehave .78 .01 i226NCTaccept .50 .28

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Table B6 Pattern Matrix: Content Component Item 1 2 i227NCTsatishome .63 -.01 i228NCTfamily .64 .00 i229NCTnotwork .12 .68 i230NCTachieve .56 .19 i231NCTweakness .05 .71 i232NCTothers -.02 .71 i233NCTnotperfect -.09 .82 Note. Component loadings > .30 are in boldface.

7. Neurotic

Figure B7. Scree plot: Neurotic

Table B7 Pattern Matrix: Neurotic Component Item 1 2 i246NNrelationship -.02 -.90

159

Table B7 Pattern Matrix: Neurotic Component Item 1 2 i247NNcommitment -.03 -.90 i248NNtrust .08 -.71 i249NNlove .00 -.89 i250NNanxious .67 -.17 i251NNthreaten .68 -.12 i252NNfearworst .78 .07 i253NNnervous .88 .04 i254NNpanic .88 .06 Note. Component loadings > .30 are in boldface.

160

Appendix C Factor pattern matrices of Neuroticism items per language group

Table C1 Factor pattern matrix of the Neuroticism scale for the total group Factor Item 1 2 3 4 5 i52BSTlosetemp .04 .16 -.04 .59 -.04 i55BSTupset .10 .10 -.02 .70 -.06 i59BSTsuffer .18 -.21 .09 .51 .17 i64BSTfrustrate -.01 .18 .02 .64 -.03 i66BSTbother .16 .03 .03 .50 -.03 i102CFworryself .08 .51 .07 .15 -.09 i104CFscaredeasi .09 .54 -.02 .01 .10 i124ECIaffectothers .06 -.06 .03 -.01 .68 i125ECInothink .06 .02 -.02 -.04 .66 i128ECIcontremo .10 .17 .01 .10 .44 i131ECIurge .02 .08 .01 .15 .60 i133ECInotknow .06 .14 .02 -.04 .58 i134ECIregret -.03 .18 .06 -.02 .52 i162ECTtreatbad .20 -.21 .13 .28 .42 i164ECTissueangr .01 .08 .08 .48 .31 i165ECTactmood .00 .01 .04 .42 .33 i167ECTsayinappr .00 -.11 .04 .23 .61 i171ECTfriendly .10 -.02 .09 .35 .21 i178ESEMbreak .04 .42 .00 .14 .24 i183ESEMnasty -.11 .06 .04 .46 .18 i199ESEXactexag .14 .02 .19 .03 .36 i203ESSEhurteasi -.12 .60 .07 .09 .09 i206ESSEupset -.04 .49 .08 .25 .09 i209ESSHembarrass -.01 .52 .14 .05 .03 i215NCpget .46 .03 .04 -.01 .11 i217NCPnag .34 .04 .14 .10 .22

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Table C1 Factor pattern matrix of the Neuroticism scale for the total group Factor Item 1 2 3 4 5 i239NDmiserable .65 .07 .02 .14 .00 i241NDhelpless .68 .16 .03 .07 .00 i243NDjoy .83 .01 -.01 .01 .01 i244NDinterest .84 -.07 -.01 .00 .04 i245NDworthless .84 .03 .05 -.07 .03 i250NNanxious .14 .48 .10 .08 .05 i251NNthreaten .23 .46 .07 -.06 .07 i253NNnervous .05 .76 .03 -.02 .01 i254NNpanic .14 .73 .05 -.01 -.01 i255NTsmallthing .09 .68 .03 .10 .02 i259NTproblems .40 .28 .06 .17 .02 i260NTrelax .47 .26 -.01 .17 -.06 i294EGONlike -.09 .12 .64 .01 -.04 i295EGONapproval -.04 -.07 .86 .10 -.14 i296EGONplease .06 -.13 .80 -.01 -.01 i299EGONdependopinion .10 -.07 .68 -.04 .06 i300EGONencourage -.03 .13 .50 -.01 .06 i303EGONdependothers .13 .05 .40 -.07 .23 i304EGONthink -.04 .17 .63 .00 .05 i305EGONknowwell .05 .08 .51 -.05 .05 Note. Factors with factor loadings > .30 are indicated in boldface.

Table C2 Factor pattern matrix of the Neuroticism scale for the Germanic group Factor Item 1 2 3 4 5 i52BSTlosetemp .55 -.10 -.11 .01 -.25 i55BSTupset .65 -.01 -.04 -.05 -.27 i59BSTsuffer .47 .01 -.14 .14 .06

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Table C2 Factor pattern matrix of the Neuroticism scale for the Germanic group Factor Item 1 2 3 4 5 i64BSTfrustrate .54 -.05 .04 .02 -.29 i66BSTbother .47 -.01 -.13 .00 -.04 i102CFworryself .20 .01 -.07 -.10 -.52 i104CFscaredeasi .06 .01 -.12 .14 -.47 i124ECIaffectothers .24 .08 -.08 .49 .09 i125ECInothink .13 -.02 -.16 .50 .13 i128ECIcontremo .12 -.03 -.08 .53 -.33 i131ECIurge .11 -.01 -.14 .63 -.15 i133ECInotknow -.01 .12 -.14 .53 -.16 i134ECIregret .13 .13 -.10 .37 -.06 i162ECTtreatbad .40 .22 -.15 .25 .25 i164ECTissueangr .64 .11 .06 .20 -.09 i165ECTactmood .56 -.03 -.02 .26 -.04 i167ECTsayinappr .44 .10 -.01 .36 .20 i171ECTfriendly .41 .14 -.18 .17 .05 i178ESEMbreak .00 .03 -.11 .35 -.53 i183ESEMnasty .69 .06 .07 -.03 .04 i199ESEXactexag .12 .30 -.11 .17 -.03 i203ESSEhurteasi -.12 .16 .11 .33 -.64 i206ESSEupset .18 .06 .00 .26 -.53 i209ESSHembarrass .02 .16 -.03 .13 -.50 i215NCpget .10 .09 -.43 .04 .12 i217NCPnag .26 .15 -.22 .09 -.02 i239NDmiserable -.06 -.04 -.73 .22 -.11 i241NDhelpless .02 -.01 -.71 .07 -.16 i243NDjoy .03 -.05 -.86 -.05 .02 i244NDinterest -.06 .02 -.86 .02 .05 i245NDworthless -.10 .06 -.84 .03 -.05 i250NNanxious .08 .22 -.19 -.13 -.46

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Table C2 Factor pattern matrix of the Neuroticism scale for the Germanic group Factor Item 1 2 3 4 5 i251NNthreaten .12 .16 -.22 -.06 -.32 i253NNnervous .02 .17 -.13 -.11 -.64 i254NNpanic .08 .19 -.12 -.14 -.64 i255NTsmallthing .23 .13 .02 -.12 -.65 i259NTproblems .20 .07 -.30 -.03 -.33 i260NTrelax .29 -.05 -.28 -.18 -.32 i294EGONlike -.08 .74 .07 .03 -.11 i295EGONapproval .00 .78 .07 -.04 -.07 i296EGONplease -.07 .80 .05 -.04 .09 i299EGONdependopinion .02 .67 -.22 -.06 .08 i300EGONencourage .18 .55 -.03 -.02 -.05 i303EGONdependothers .08 .38 -.04 .06 -.08 i304EGONthink -.08 .61 .02 .15 -.24 i305EGONknowwell -.02 .60 -.04 -.02 -.01 Note. Factors with factor loadings > .30 are indicated in boldface.

Table C3 Factor pattern matrix of the Neuroticism scale for the Nguni group Factor Item 1 2 3 4 5 i52BSTlosetemp .59 .00 -.07 .12 -.19 i55BSTupset .66 -.14 -.22 .07 .00 i59BSTsuffer .59 -.17 .07 -.12 .17 i64BSTfrustrate .65 -.07 -.04 .20 -.10 i66BSTbother .44 -.18 .04 .12 -.19 i102CFworryself .00 -.18 .04 .61 -.11 i104CFscaredeasi -.05 -.05 .08 .60 .06

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Table C3 Factor pattern matrix of the Neuroticism scale for the Nguni group Factor Item 1 2 3 4 5 i124ECIaffectothers .16 -.10 .16 -.07 .47 i125ECInothink .08 -.10 .07 .15 .44 i128ECIcontremo .26 -.20 .24 -.05 .16 i131ECIurge .42 -.10 .19 .01 .22 i133ECInotknow .04 -.12 .05 .25 .48 i134ECIregret .08 -.01 .03 .27 .36 i162ECTtreatbad .56 -.23 .17 -.18 .16 i164ECTissueangr .69 -.03 .19 .06 -.02 i165ECTactmood .61 .02 .10 -.01 .10 i167ECTsayinappr .58 .01 .07 -.09 .31 i171ECTfriendly .42 -.10 .06 -.01 .12 i178ESEMbreak .34 .07 .09 .36 .14 i183ESEMnasty .51 .27 -.04 .17 .06 i199ESEXactexag .34 -.13 .18 -.06 .37 i203ESSEhurteasi .15 .15 -.09 .59 .24 i206ESSEupset .23 .08 .03 .53 .17 i209ESSHembarrass .05 .08 .21 .55 -.01 i215NCpget .08 -.37 .09 .01 .13 i217NCPnag .23 -.34 .20 -.06 .34 i239NDmiserable .17 -.67 .10 .06 -.23 i241NDhelpless .01 -.80 .08 .14 -.13 i243NDjoy .09 -.75 .10 .01 -.07 i244NDinterest .10 -.74 -.08 -.08 .10 i245NDworthless -.02 -.77 .02 .00 .16 i250NNanxious .19 -.15 .16 .32 -.03 i251NNthreaten -.06 -.29 .06 .32 .12 i253NNnervous .11 -.08 .05 .61 -.01 i254NNpanic .06 -.25 .11 .64 -.15 i255NTsmallthing .07 -.18 .01 .64 -.03

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Table C3 Factor pattern matrix of the Neuroticism scale for the Nguni group Factor Item 1 2 3 4 5 i259NTproblems .06 -.54 -.03 .33 .09 i260NTrelax -.06 -.69 -.10 .29 .12 i294EGONlike -.03 .07 .46 .11 .09 i295EGONapproval .07 -.03 .86 -.07 -.33 i296EGONplease .02 -.18 .67 -.08 .09 i299EGONdependopinion .04 -.10 .67 -.09 .05 i300EGONencourage -.08 .05 .46 .13 .17 i303EGONdependothers -.01 -.19 .46 -.01 .26 i304EGONthink -.01 .10 .69 .15 -.09 i305EGONknowwell .04 -.02 .37 .11 .09 Note. Factors with factor loadings > .30 are indicated in boldface.

Table C4 Factor pattern matrix of the Neuroticism scale for the Sotho group Factor Item 1 2 3 4 5 i52BSTlosetemp .19 -.03 .09 .20 .40 i55BSTupset .03 -.18 .01 .21 .56 i59BSTsuffer -.14 -.32 -.01 .33 .29 i64BSTfrustrate .32 .02 .06 .35 .29 i66BSTbother .08 -.14 -.06 .31 .40 i102CFworryself .39 -.05 .21 -.08 .25 i104CFscaredeasi .32 -.14 .16 -.05 .38 i124ECIaffectothers -.07 -.16 -.02 .58 .00 i125ECInothink .06 -.06 .13 .65 -.10 i128ECIcontremo .08 -.07 .04 .50 .17 i131ECIurge .14 .08 .05 .73 -.01 i133ECInotknow -.12 -.15 .08 .51 .12

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Table C4 Factor pattern matrix of the Neuroticism scale for the Sotho group Factor Item 1 2 3 4 5 i134ECIregret -.04 .13 .29 .46 .20 i162ECTtreatbad -.06 -.22 .00 .66 .03 i164ECTissueangr .18 -.03 -.01 .58 .22 i165ECTactmood .28 .00 .01 .43 .12 i167ECTsayinappr -.01 -.04 .10 .78 -.10 i171ECTfriendly .13 .03 -.05 .28 .35 i178ESEMbreak .20 -.19 -.02 .14 .34 i183ESEMnasty .33 .04 .02 .43 .00 i199ESEXactexag .01 -.13 .19 .48 -.04 i203ESSEhurteasi .56 -.08 .13 -.16 .23 i206ESSEupset .47 -.09 .14 -.08 .34 i209ESSHembarrass .45 -.18 .20 -.15 .15 i215NCpget .11 -.48 .07 .12 .00 i217NCPnag .10 -.38 .16 .30 .05 i239NDmiserable -.02 -.59 .05 -.03 .43 i241NDhelpless .17 -.64 .02 .02 .24 i243NDjoy -.02 -.85 .10 -.08 .06 i244NDinterest .02 -.85 -.01 .09 -.10 i245NDworthless .13 -.92 -.04 .02 -.18 i250NNanxious .49 -.15 -.06 .24 .13 i251NNthreaten .61 -.16 .12 .16 -.15 i253NNnervous .93 -.04 .00 .05 -.11 i254NNpanic .75 -.11 .04 .21 -.08 i255NTsmallthing .59 -.17 .04 .17 .14 i259NTproblems .27 -.42 .06 .22 .17 i260NTrelax .21 -.44 .00 .16 .25 i294EGONlike .24 .07 .53 -.09 .09 i295EGONapproval .02 .06 .75 .07 -.02 i296EGONplease -.17 -.17 .85 .03 -.04

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Table C4 Factor pattern matrix of the Neuroticism scale for the Sotho group Factor Item 1 2 3 4 5 i299EGONdependopinion -.09 -.02 .77 .03 -.06 i300EGONencourage .04 .08 .65 -.06 .11 i303EGONdependothers .05 -.22 .48 .26 -.21 i304EGONthink .14 -.08 .57 .13 .08 i305EGONknowwell .12 -.07 .54 .15 -.19 Note. Factors with factor loadings > .30 are indicated in boldface.

168