Understanding and Being Understood
The Impact of Intelligence and Dispositional Valuations on Social Relationships

Dissertation

zur Erlangung des akademischen Grades Dr. rer. nat.
im Fach Psychologie

eingereicht an der
Mathematisch-Naturwissenschaftlichen Fakultät II
der Humboldt-Universität zu Berlin

vorgelegt von
Jacobus J. A. Denissen, MA Psychology
geboren am 14. Februar 1978 in Udenhout, den Niederlanden

Präsident der Humboldt-Universität zu Berlin
Prof. Dr. Jürgen Mlynek

Dekan: der Mathematisch-Naturwissenschaftlichen Fakultät II
Prof. Dr. Uwe Küchler

Gutachter:
1. Jens B. Asendorpf, Humboldt-Universität zu Berlin
2. Alexandra M. Freund, Universität Zürich
3. Dan P. McAdams, Northwestern University

Eingereicht beim Promotionsausschuss am: 1. Juni, 2005

Tag der mündlichen Prüfung: 8. Juli, 2005

Man’s character is his daimon¹

Heraclitus, fragment 119

¹ For the ancient Greeks, the daimon was non-human power somewhere between people and gods, without any negative connotations. An example would be the daimon of Socrates. The daimon had a wisdom that has nothing to do with our modern conceptions of good or evil: It was a force of nature that could offer hints about fateful situations and actions.

Table of contents

• Introduction
• 1  Understanding and Being Understood
  • 1.1  Mutual Understanding
    • 1.1.1  Description and Definition
    • 1.1.2 Concepts Related to Mutual Understanding
      • 1.1.2.1 Empathy
      • 1.1.2.2 Social Support
      • 1.1.2.3 Rapport
      • 1.1.2.4 Intimacy
  • 1.2 Communicating Meaning
    • 1.2.1  A Model of Dyadic Communication
    • 1.2.2 Social Construction of Shared Codes
      • 1.2.2.1 Audience Design
      • 1.2.2.2 Perspective Taking
      • 1.2.2.3 Shared Experiences
      • 1.2.2.4 Metaphors
• 2 The Impact of Intelligence and Dispositional Valuations on Mutual Understanding
  • 2.1  Review of Independent Variables
    • 2.1.1  Fluid Intelligence
    • 2.1.2 Crystallized Intelligence
    • 2.1.3 Dispositional Valuations
      • 2.1.3.1  Openness to Experience
      • 2.1.3.2 Interests and Values
  • 2.2 Main Effects of Intelligence and Dispositional Valuations
    • 2.2.1  Fluid Intelligence
    • 2.2.2 Crystallized Intelligence
    • 2.2.3 Dispositional Valuations
      • 2.2.3.1 Openness to Experience
  • 2.3 Between-Person Differences in Intelligence and Dispositional Valuations
    • 2.3.1  General Intelligence
    • 2.3.2 Crystallized Intelligence
    • 2.3.3 Dispositional Valuations
    • 2.3.4 Interpretation of Assortative Patterns Regarding Intelligence
      • 2.3.4.1  Empirical Evidence
      • 2.3.4.2 Alternative Explanations
      • 2.3.4.3 Illusory Similarity
  • 2.4 Dyadic Effects of Intelligence and Dispositional Valuations
    • 2.4.1  Fluid Intelligence
      • 2.4.1.1  Shared Experiences and Evaluations
      • 2.4.1.2 Insight and Ideas
    • 2.4.2 Crystallized Intelligence
    • 2.4.3 Dispositional Valuations
  • 2.5 Combining Main and Dyadic Effects
    • 2.5.1  Simonton’s (1985) Model of Intelligence and Group Influence
      • 2.5.1.1 Description of the Model
      • 2.5.1.2 Empirical evidence
    • 2.5.2 Application of the Simonton (1985) Model to the Adjustment and Social Relationships of Gifted Individuals
      • 2.5.2.1 Studies Showing Superior Adjustment of Gifted Individuals
      • 2.5.2.2 Studies Showing Some Adjustment Problems of Gifted Individuals
      • 2.5.2.3 Conclusion
  • 2.6 Summary of Main and Dyadic Hypotheses
• 3 Method
  • 3.1  Sample Characteristics
    • 3.1.1  Rationale for Sample Selection
    • 3.1.2 Sample 1
    • 3.1.3 Sample 2
      • 3.1.3.1 High Achieving (HA) Alumni
      • 3.1.3.2 Average Achieving (AA) Alumni
    • 3.1.4 Sample 3
    • 3.1.5 Sample 4
  • 3.2 Procedure
    • 3.2.1  Studies 1.I, 2, and 3
    • 3.2.2 Study 1.II
    • 3.2.3 Study 4
      • 3.2.3.1  Creation of Dyads
      • 3.2.3.2 Experimental Setting and Instructions
  • 3.3 Measures
    • 3.3.1  Mutual Understanding and Related Constructs
      • 3.3.1.1 Social Network Characteristics (Sample 1-3)
      • 3.3.1.2 Self-concept of Social Relationships With Peers (Sample 1-2)
      • 3.3.1.3 Loneliness (Samples 1-2)
      • 3.3.1.4 Evaluation of Dyadic Communication
    • 3.3.2 Intelligence
      • 3.3.2.1 Intelligence Ratings (Samples 1-4)
      • 3.3.2.2 Self-Concept of Intelligence (Samples 1-2)
      • 3.3.2.3 Psychometrically Tested Numerical Intelligence (Sample 4)
      • 3.3.2.4 Psychometrically Tested Figural Intelligence (Sample 4)
      • 3.3.2.5 Psychometrically Tested Vocabulary (Samples 3-4)
      • 3.3.2.6 Self-Reported IQ-Test Results (Sample 1)
    • 3.3.3 Dispositional Valuations
      • 3.3.3.1 Interests
      • 3.3.3.2 Values
      • 3.3.3.3 Openness to Experience
    • 3.3.4 Control Variables
      • 3.3.4.1 Big Five (Samples 1-4)
    • 3.3.5 Coding of MU From Behavioral Observations in Study 4
  • 3.4 Analysis Strategy
    • 3.4.1  Data Reduction
    • 3.4.2 Nested Structure of Data
    • 3.4.3 Testing Dyadic Effects
    • 3.4.4 Groups Comparisons
• 4 Results
  • 4.1  Data Reduction
    • 4.1.1  Ego-Centered Social Relationship Quality
      • 4.1.1.1 Samples 1 and 2
      • 4.1.1.2 Sample 1.II
      • 4.1.1.3 Sample 3
    • 4.1.2 Post-Interaction Ratings in Sample 4
      • 4.1.2.1 Assessment of Conversation Quality
      • 4.1.2.2 Effect of Manipulation on Intelligence Ratings
    • 4.1.3 Agreement Across Data Sources
    • 4.1.4 Interdependence of Data
  • 4.2 Main Effects of Intelligence and Dispositional Valuations
    • 4.2.1  Samples 1-2
    • 4.2.2 Sample 1.II
    • 4.2.3 Sample 3
    • 4.2.4 Sample 4
  • 4.3 Dyadic Effects of Intelligence and Dispositional Valuations
    • 4.3.1  Sample 1.I
    • 4.3.2 Sample 1.II
    • 4.3.3 Sample 2
    • 4.3.4 Sample 4
  • 4.4 Group Differences
    • 4.4.1  Differences in Self-report Scales
    • 4.4.2 Differences in Social Network Composition
    • 4.4.3 Compensation Mechanisms
• 5 Discussion
  • 5.1  The Process of Mutual Understanding
    • 5.1.1  Discriminant Validity of MU
    • 5.1.2 Convergent Validity of MU Assessments Across Information Sources
    • 5.1.3 Chronological Correlates of MU
  • 5.2 Discussion of Main effects
    • 5.2.1  Main Effects of Fluid Intelligence on MU
      • 5.2.1.1 Lack of Psychometric and Self-Report Effects
      • 5.2.1.2 Presence of Perceived Effects
    • 5.2.2 Main Effects of Crystallized Intelligence on MU
      • 5.2.2.1 Positive Effect of Crystallized Intelligence
    • 5.2.3 Main Effects of Openness to Experience on MU
      • 5.2.3.1 Explanation for Inconsistency with Previous Literature
  • 5.3 Discussion of Dyadic Effects
    • 5.3.1  Status of Dyadic Effect Hypotheses
      • 5.3.1.1 Dyadic Effects of Fluid Intelligence on MU
      • 5.3.1.2 Dyadic Effects of Crystallized Intelligence on MU
      • 5.3.1.3 Dyadic Effects Openness to Experience on MU
      • 5.3.1.4 Dyadic Effects Interests and Values on MU
    • 5.3.2 Implications of the Lack of Dyadic Effects
      • 5.3.2.1 Bridging Personality Differences
  • 5.4 Differences Between Gifted and Comparison Individuals
    • 5.4.1  Self-Selection
  • 5.5 Limitations
    • 5.5.1  Subjective Assessment of MU
    • 5.5.2 Reliability and Validity of Intelligence Assessment
    • 5.5.3 Sampling Bias
    • 5.5.4 Lack of Experimental Data
  • 5.6 Strengths
    • 5.6.1  Use of Multiple Assessment Methods
    • 5.6.2 Use of Dyadic Design
    • 5.6.3 Modeling Nested Data
  • 5.7 Conclusions and Recommendations for Future Research
    • 5.7.1  Usefulness of MU Construct
    • 5.7.2 Limited Main Effects in Study 4
    • 5.7.3 Bridging Between-Person Differences
    • 5.7.4 Recommendations
      • 5.7.4.1 More Representative Samples
      • 5.7.4.2 Objective Tests of MU
      • 5.7.4.3 Online Measurement of Perception Changes
      • 5.7.4.4 Variation of Task Demands
• 6 References
• 7 Appendices
  • 7.1 Setup of Dyadic Conversation in Study 4
  • 7.2 Ego-Centered Social Network Instrument
  • 7.3 Self-Concept Questionnaire
  • 7.4 Interaction Quality Questionnaire
  • 7.5 Single-Item Intelligence Rating Instrument
  • 7.6 Summary of Studies Assessing the Validity of Intelligence Self-Ratings
  • 7.7 Numerical Intelligence Test
  • 7.8 Short Version of the German General Interests Structure Test
  • 7.9 Schematic Depiction of HLM Analysis Logic
• Curriculum Vitae
• Selbständigkeitserklärung

Tables

• Table 1 Summary of Four Techniques for the Social Construction of Shared Codes
• Table 2 Spousal Correlations for General Intelligence, Crystallized Intelligence, and Education
• Table 3 Description of Demographic Information and Study Procedure Across Samples
• Table 4 Normed Results and Psychometric Properties of Intelligence Tests Used in Sample 4
• Table 5 Overview of Self-Report Scales Across Samples
• Table 6 Social Network Composition Across Samples
• Table 7 Psychometric Properties and Normed Scores of Big Five Scales Across Samples
• Table 8 Loadings of Social Relationships Ratings on Relationship Quality Factors in Samples 1-3
• Table 9 Loadings of Ratings of Interviewer Behavior on Conversation Quality Factors in Sample 4
• Table 10 Correlations Between Self-Reported and Observed Indices of MU
• Table 11 HLM Regression Coefficients of the Effect of Rated Intelligence, Openness, and Vocabulary on Relationship Quality in Samples 1-2 and 3
• Table 12 HLM Regression Coefficients of the Effect of Ratings of Network Partner Intelligence on Relationship Quality in Sample 1.II
• Table 13 Correlations Among Predictor Variables in Sample 4 (Intelligence and Openness to Experience)
• Table 14 Correlations Between Intelligence/Dispositional Valuations and MU in Sample 4
• Table 15 HLM Regression Coefficients of the Effect of Between-Person Differences in Rated Intelligence and Relationship Quality in Sample 2
• Table 16 Correlations Between MU and Between-Person Differences in Intelligence and Dispositional Valuations in Sample 4
• Table 17 Differences Between Mensa Members and University Alumni in Self-Reported Social Adjustment
• Table 18 HLM Regression Coefficients of the Effect of Ratings of Network Partner Intelligence and Mensa Membership on Relationship Quality Across Different Relational Categories
• Table 19 Summary of Results Across Main Effect Hypotheses
• Table 20 Summary of Results Across Dyadic Effect Hypotheses

Images

• Figure 1. Schematic Depiction of Sign Elements According to de Saussure (1916).
• Figure 2. Schematic Depiction of the Dyadic Communication Process
• Figure 3. Model of the Serial Construction of Meaning According to Duck (1994)
• Figure 4. Sample Item of a Matrices: Test of Fluid Intelligence
• Figure 5. Model of the Relation Between Intelligence and Group Influence According to Simonton (1985).
• Figure 6. Mean Level Differences in Self-Rated Social Adjustment Between Intellectually Gifted Mensa Members, Highly Achieving University Alumni, and Averagely Achieving University Alumni.