Karl-Franzens-University, Graz

Emotional Intelligence, Academic Intelligence and Speed of Mind:
The Case of Emotion Perception

Dissertation
am Institut für Psychologie, Karl-Franzens-Universität Graz,
zur Erlangung des
Doktorgrades der Naturwissenschaften

by

Mag. Arnold Ackerer

Graz, April 2003

Table of contents

CHAPTER ONE1. Intelligence - Introduction ...1

1.1 Introduction ...1
1.2. Sternberg′s Theory Of Successful Intelligence ...1
1.3. Social Intelligence ...2
1.4. Multiple Intelligences ...3

2. Intelligence and Human Abilities ...5
2.1. Intelligence As A Unitary Concept ...6
2.2. Carroll′s Three Stratum Theory of Intelligence ...8
2.3. The Berlin Structural Model Of Intelligence ...10
2.4. Problem Solving Ability And Learning Test Concept ...10

CHAPTER TWO3. Intelligence and Speed of Mind ...12

3.1. Studies On The Connection Between RT And Intelligence ...13
3.1.1. The Hick-Paradigm ...13
3.1.2. The Sternberg-Paradigm ...14
3.1.3. The Posner-Paradigm ...14
3.1.4. Odd Man Out-Paradigm ...15
3.2. Starting Point ...15
3.3. A Developmental Perspective ...17
3.4. Cultural Invariance ...18
3.5. Uniformity Of RT Measures ...18
3.6. Do Different RT Paradigms Yield Different Correlational Patterns With Intelligence? ...19
3.7. Information Psychology And The MS-IQ Correlation ...20
3.8. Predicting Intelligence From RT Measures ...23
3.9. The Issue Of Movement Time ...24
3.10. Specificity Or Singularity Of Mind ...24
3.11. RT-IQ Correlation And Its Dependence On Complexity ...26
3.12. Inspection Time And Intelligence ...28
3.13. Psychophysiological Measures Of Speed And Their Correlation With Intelligence ...29
3.14. The Issue Of Causation ...30

4. Criticism Of Mental Speed Approach ...32

CHAPTER THREE5. Emotions ...35

5.1. Introduction ...35
5.2. Emotions In General ...35
5.3. The Prototypical Model Of Emotions ...36
5.4. The Concept Of Basic Emotions ...37
5.4.1. Criticism of the Basic Emotion Concept ...39
5.5. Vascular Theory of Emotion ...42
5.6. Neural Structures And Emotional Processes - Evidence From Mental Deficit Studies ...43
5.6.1. The Issue of Schizophrenia ...44
5.6.2. The Issue of Autism ...45
5.7. Brain Structures And Emotions ...47
5.7.2. Facial Agnosia ...48
5.8. Withdrawal/ Approach System ...49
5.8.1. The Prefrontal Cortex ...50
5.8.2. The Amygdala ...50
5.8.3. Withdrawal/Approach System in the Context of the Dimensional and Categorical View on Emotions ...51
5.8.4. Handedness and recognition of emotions ...52
5.9. Regularity In Emotional Experience ...52

CHAPTER FOUR6. Concepts Of Emotional Intelligence ...54

6.1 EI Conceptualized According To Salovey And Mayer ...55
6.1.1 Is EI an Intelligence? ...56
6.1.2 Further Criticism on the Ability Concept of EI ...61
6.1.3. The Schutte EI Scale …62
6.1.4. The Arrival of Objective Measures …63
6.2. The Bar-On EQ-I ...65
6.3. EI - Conclusions ...67

7. Recognition Of Emotions In Faces ...70
7.1 Early Investigations ...70
7.2. Beyond The Use Of Only Positive Vs. Negative Emotions ...71
7.3. The Role Of Context And Other Sources Of Information ...73

8. INTEGRATION OF THE RESEARCH REPORTED ...76

9. METHOD9.1. SAMPLE CHARACTERISTICS ...79
9.2. MEASURES ...79
9.2.1. Construction of Tests …79
9.2.1.1. Reaction Time Tests …80
9.2.1.1.1. Emotional reaction time task …80
9.2.1.1.2. Non-emotional reaction time task …81
9.2.1.2. The Posner Paradigm Task …81
9.2.1.2.1. Emotional Posner paradigm test …82
9.2.1.2.2. Non-emotional Posner paradigm test …83
9.2.2. Designation, Derivation and Meaning of the Developed Testscores …85
9.2.3. Intelligence Test …86
9.3. PROCEDURE ...87

10. RESULTS
10.1. TEST CHARACTERISTICS ...88
10.1.1. IQ Testscore …88
10.1.2. Mental Speed Testscores …88
10.1.2.1. Data Cleaning …88
10.1.2.1.1. Ambiguous items …88
10.1.2.1.2. Outliers …89
10.1.2.2. Distribution of MS testscores …89
10.1.2.3. Reliability …90
10.1.3. Dependence of Testscores on Situational and Personal Variables …91
10.1.3.1. Age of subjects …91
10.1.3.1.1. Age and IQ …91
10.1.3.1.2. Age and MS …91
10.1.3.2. Gender of subjects …92
10.1.3.2.1. Gender and IQ …92
10.1.3.2.2. Gender and MS …92
10.1.3.3. Testorder …92
10.1.3.3.1. Testorder and IQ …92
10.1.3.3.2. Testorder and MS …93
10.1.3.4. Button control …93
10.2. RELATIONSHIP AMONG MS TESTS ...94
10.2.1. Considerations …94
10.2.2. Relationship Between the Emotional and Non- Emotional MS Tests …94
10.2.2.1. Emotional and non-emotional RT tests …94
10.2.2.2. Emotional and non-emotional PP tests …95
10.2.2.3. Comparing RT and PP tests …95
10.3. RELATIONSHIP BETWEEN IQ AND MS TESTSCORES ...98
10.3.1. IQ and RT Testscores …99
10.3.2. IQ and PP Testscores …98
10.3.3. Factor Analysis Including IQ, RT, and PP Testscores …99
10.3.4. Regression Analysis …100
10.3.5. AMOS Model Building …101
10.4. RESULTS SEPARATED FOR CULTURAL GROUPS ...103
10.4.1. Relationship between emotional and non-emotional MS testscores …104
10.4.1.1. Emotional and Non-emotional RT Tests …104
10.4.1.2. Emotional and Non-emotional PP Tests …104
10.4.1.3. Comparing RT Tests with PP Tests …105
10.4.2. Relationship between IQ and MS Testscores …106
10.4.2.1. IQ and MS Tests …106
10.4.2.2. Factor Analysis Including IQ, RT, and PP Testscores …107
10.4.3. The AMOS Model - One Model for All? …108

11. DISCUSSION
11.1. The Use Of Mental Speed Measures ...110
11.2. Relationship Among Emotional And Non-emotional MS Tests ...112
11.3. Relationship Between IQ And MS Testscores ...114
11.4. Group Differences ...117

12. FOLLOW-UP STUDY
12.1. OVERVIEW ...120
12.2. METHOD ...120
12.2.1. Sample Characteristics ...120
12.2.2. Measures ...120
12.2.3. Procedure ...121
12.3. RESULTS ...122
12.3.1. Testcharacteristics ...122
12.3.1.1. Data Cleaning ...122
12.3.1.2. Distribution of Testscores ...122
12.3.1.3. Reliability - Internal Consistency ...122
12.3.1.4. Correlation to Personal Variables ...123
12.3.1.4.1. Age of subjects …123
12.3.1.4.2. Gender of subjects …123
12.3.2. Relationship among MS Tests ...123
12.3.2.1. Relationship in the Follow-up Study ...123
12.3.2.1.1. Emotional and non-emotional RT tests …124
12.3.2.1.2. Emotional and non-emotional PP tests …124
12.3.2.1.3. Comparing all MS scores …124
12.3.2.2. Relationship between Main and Follow-up Study ...126
12.3.2.2.1. Stability in MS scores …126
12.3.2.2.2. Stability in correlation to IQ …126
12.3.2.2.3. Stability in the AMOS model …128
12.4. DISCUSSION ...130
12.4.1. The Level Of Testscores ...130
12.4.2. The Level Of Relationship Pattern ...131
12.4.3. Stability In The AMOS Model ...132

13. GENERAL DISCUSSION …133

14. REFERENCES …135

APPENDIX
(A.) List of Subjects′ Countries of Origin …148
(B.) Instruction for Emotional RT …149
(C.) Instruction for Non-emotional RT …151
(D.) Instruction for Emotional Posner Paradigm Test …153
(E.) Instruction for Non-emotional Posner Paradigm Test …156
(F.) FA with all MS testscores and the APM score …159
(G.) FA for RT and LTM scores separated for cultural groups …160
(H.) FA for RT, LTM and APM scores separated for cultural groups …161
(F.) FA for the Japanese Sample Employing all Testscores …162
(G.) FA for the International Student Sample Employing All Testscores …163
(K.) Intelligence Differences according to Cultural Background …164
(L.) Absolute Values for the MS Testscores in Milliseconds …165

Tables
Table 1: Dependence of correlations between RT measures and intelligence on the complexity of RT tasks …27
Table 2: The pattern of possible conditions in the Posner paradigm …81
Table 3: List of all MS testscores …85
Table 4: MS testscores and normal distribution …90
Table 5: MS tests and their reliability …91
Table 6: MS tests and their correlation with age …92
Table 7: Correlations among emotional and non-emotional RT tests …94
Table 8: Correlation among LTM scores …95
Table 9: Correlations among RT and LTM scores …96
Table 10: Factor analysis of RT and LTM scores - rotated matrix …97
Table 11: Relationship between IQ and RT testscores …98
Table 12: Relationship between IQ and LTM scores …99
Table 13: Eigenvalues and explained variance for the three extracted factors …99
Table 14: Rotated factor matrix for RT, LTM and the IQ Score …100
Table 15: Correlations among emotional and non-emotional RT tests for the Japanese and the international sample …104
Table 16: Correlation among LTM scores for the Japanese and international sample …105
Table 17: Correlations among RT and LTM scores for the Japanese and the international sample …105
Table 18: Relationship between IQ and RT testscores for the Japanese and the international sample …106
Table 19: Relationship between IQ and LTM scores for the Japanese and the international sample …107
Table 20: Factor composition separated for the Japanese group, the international student group and the total sample …108
Table 21: Comparing the fit indices for the Japanese and the international student sample …109
Table 22: Internal consistency for the MS testscores in the follow-up study …123
Table 23: Correlations among emotional and non-emotional RT tests in the follow-up data …124
Table 24: Correlations among LTM scores in the follow-up data …124
Table 25: Correlations among RT and LTM scores in the follow-up data …125
Table 26: Factor analysis of RT and LTM scores for the follow-up study …125
Table 27: Test-retest reliability for the MS testsscores …126
Table 28: Correlation between the MS tests from the follow-up study and Raven′s APM scores …127
Table 29: Factor analysis of MS testscores and intelligence for the follow-up study …128

Figures
Figure 1: From Eysenck; Intelligence: the new look (p. 334) …12
Figure 2: Model of psychostructure, from Lehrl and Fischer (p. 885) …21
Figure 3: Theoretical Circular Model, from Russel, 1980 (p.1164) …36
Figure 4: AA stimulus (shape same/ meaning same) for the emotional and non-emotional PP test …82
Figure 5: Ab stimulus (shape different/ meaning different) for the emotional PP test …83
Figure 6: Aa stimulus (shape different/ meaning same) for the emotional PP test …83
Figure 7: Ab stimulus (shape different/ meaning different) for the non-emotional PP test …84
Figure 8: Aa stimulus (shape different/ meaning same) for the non-emotional PP test …84
Figure 9: Correlations among LTM scores for emotional and non-emotional scores …95
Figure 10: Correlations among RT and LTM scores …96
Figure 11: AMOS Model (N=99, cases with missing values were deleted). …102
Figure 12: Modified AMOS model; changes base on the follow-up data. …129

Summary

The EI construct, which developed mainly during the last decade, has been split into an ability-EI and a trait-EI. Originally EI was proposed as an intelligence, needed because emotional information is processed differently from non-emotional information. However, due to the lack of adequate objective measures for ability-EI, trait-EI became popular. In this study, an innovative approach building on the use of mental speed (MS) measures was theoretically justified and applied to emotional information processing in order to tackle the criterion problem for emotional test items and to investigate the relationship between mental speed and intelligence. Emotional and non-emotional tests following a simple reaction time (RT) and the Posner paradigm were constructed and administered along with Raven′s APM to a sample of 121 college and university students at Hiroshima University, Japan. Approximately half of these students were Japanese nationals, while the other half were international students, coming from countries all over the world.
The APM score correlated low but significantly with both RT tests, but neither with the emotional nor the non-emotional long term memory (LTM) access times. In varimax factor analyses (FA) the emotional MS tests grouped together to one factor, while IQ and non-emotional MS tests formed two more factors. Additionally, an AMOS (Analysis of Moment Structures; an SPSS compatible program for structural equation modelling distributed by Smallwaters Company) model confirmed the existence of two factors, one for the emotional and one for the non-emotional testscores.
This general picture did also not change substantially, when the data were analysed separately for the two groups (Japanese, international students). Although there were some changes in the size of single correlations among MS testscores, the results of the FA as well as the AMOS model was supported in the separated group data.
In order to test temporal stability, the MS tests were re-administered to 48 students (20 Japanese and 28 international students) from the original sample. The test-retest reliability for most of the MS scores was low (between .35 and .80) compared to the reliability of psychometric tests. Additionally, the APM score from the main study was correlated significantly with all MS testscores in the follow-up data. Nonetheless after the speed and the emotional factor of the AMOS model were allowed to correlate to each other also on the level of single testscores, the corrected model showed very favourable fit indices for the follow-up data as well as for the data from the main study. Thus, the EI core assumption was supported in this investigation.

CHAPTER ONE

1. INTELLIGENCE

1.1. Introduction
Human intelligence is one of the best researched subjects in scientific psychology. Yet in the recent past the construct of intelligence itself became a matter of discussion and different researchers introduced new aspects of intelligence or proposed alternative constructs to substitute for so-called ′academic′ intelligence.
Such new constructs were proposed e.g. from Gardner (1998; multiple intelligences), Sternberg (e.g. Sternberg & Kaufman, 1998; practical intelligence), Salovey & Mayer (e.g. 1989-90; emotional intelligence) and others. The starting point of their criticism was similar - intelligence as measured with traditional tests seemed insufficient to describe human abilities. Soon the term "academic" intelligence was created to emphasize the context of academic settings and achievement. Academic intelligence tests are acknowledged as the best single predictor of success in a variety of school subjects. However, the same tests do not predict the performance in a variety of life settings, including such important issues as work performance or the quality of interpersonal relationships, very successfully.

1.2. Sternberg′s Theory of Successful Intelligence
Hence, new concepts were supposed to fill this gap. One citation from Sternberg (1979) reflects well the different approach he was taking toward human intelligence: "…factors (such as inductive reasoning or deductive reasoning), are constructs to be accounted for rather than the constructs that do the accounting." (p. 228). This approach also was an answer to Cronbach′s (1957, 1975) demand to merge two disciplines of science - experimental psychology and the study of individual differences. For Sternberg′s theory of mental abilities, the psychometric approach needed to be re-evaluated along the lines Cronbach had laid out. To develop a concept on intelligence is not facilitated by factor analyzing the results of different people, but by analyzing the difference among the mental tasks available. A deeper understanding of human problem solving abilities needs the understanding of the elements that constitute a certain task.
Sternberg later introduced the idea of practical intelligence, which is related to superior work performance of people, who are regarded less intelligent by traditional testing procedures, in comparison with worse work performance of supposedly more intelligent people. Practical intelligence, hence, should describe the ability "to implement options and to make them work […] is involved when intelligence is applied to real-world contexts"(Sternberg & Kaufman, 1998, p. 494). The key aspect of practical intelligence is the acquisition and use of "tacit" knowledge.
Sternberg (1985) divides tacit knowledge in three categories - tacit knowledge about managing self (how to manage one′s own daily condition, productivity and so on), managing others (how to use social relationships) and managing career (how to establish a reputation). In a series of experiments, Sternberg tried to evaluate the contribution of tacit knowledge to successfully handling real-world situations. The tacit knowledge measure was significantly correlated with important parameters of success in the field of business (i.e. with level of company reputation, years of schooling beyond high school, and salary, status as expert vs. novice).
Practical intelligence is but one of two concepts vital for interpreting individual differences in intelligence. The other construct is creative intelligence, which is also not well represented in traditional psychometric testing procedures (Neisser et al., 1996). Creative intelligence is mainly used to generate problem-solving options (Sternberg & Kaufman, 1998) and forms together with analytical (academic) and practical intelligence "successful" intelligence. Successful intelligence is the ability "…to adapt to, shape, and select environments to accomplish one′s goals and those of one′s society and culture." (Sternberg & Kaufman, 1998, p. 494).
Sternberg also criticizes the different kinds of problems used in academic intelligence tests compared to real world problems. Items in intelligence tests are formulated by people different from oneself, are clearly defined, come with all information needed, have only one single correct answer and often have little or no intrinsic value. Real world problems, however, tend to be poorly defined, require a lot more information seeking and have different, albeit adequate, solutions.

1.3. Social Intelligence
Social intelligence was already proposed by Thorndike but due to difficulties in measurement and ambiguity in the meaning of the term social intelligence, this construct never attracted as much research as the academic intelligence concept did.
With the academic intelligence construct under pressure, however, interest in social intelligence revived again. Hence, also measurement was improved and 1989 Costanzo and Archer published a measure for the ability "to observe and interpret the expressive behavior of others" (p. 226). This new measure - the Interpersonal Perception Task (IPT) - used video-taped scenes from real-life interactions between different people. The IPT′s construction also drew on the experiences gathered with a predecessor - the Social Interpretation Task (SIT, Archer & Akert, 1977). The task of the subject was to answer a certain question from a given social interaction. For instance, there was a dialogue between two women, while one child was present. The task was to infer from the film clip, who the mother of the child was. One advantage of the IPT certainly is the availability of a ′correct′ answer.
The newly available measurement further stimulated interest and research in the area of social intelligence. Brown and Anthony (1990), for instance, assessed its usefulness in relation to academic intelligence. The correlation between social intelligence and traditional intelligence was quite low (.15), and a regression analysis used both measures to predict scores on dependent variables.

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