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Is Congruence Dead? An Examination of the Correlation Between Holland’s Congruence and Job Satisfaction Using Improved Methodology
Shannon Marie Bowles
Dissertation submitted to the
College of Human Resources and Education at West Virginia University
in partial fulfillment of the requirements for the degree of
Doctor of Philosophy In
Counseling Psychology
Roy H. Tunick, Ed.D., Committee Chair Jennifer R. Adams, Ph.D. Donald E. Eggerth, Ph.D.
Ed E. Jacobs, Ph.D. Richard T. Walls, Ph.D.
Department of Counseling, Rehabilitation Counseling, and Counseling Psychology
Morgantown, West Virginia
2008
Keywords: Congruence, Job Satisfaction, John L. Holland, Methodology, RIASEC Copyright 2008 Shannon M. Bowles
ABSTRACT
Is Congruence Dead? An Examination of the Correlation Between Holland’s Congruence and Job Satisfaction Using Improved Methodology
Job satisfaction is considered to be the most important and frequently examined outcome variable in congruence research. The assumption that congruence results in job satisfaction is fundamental to Holland’s theory; however, the empirical evidence predominantly indicates that the congruence – job satisfaction correlation is, at best, equivocal. There is a movement within vocational psychology that the congruence construct is “dead” as a viable theoretical concept and that the field should abandon Holland’s theory. This idea does not exist without significant argument, however. It has been recognized widely that congruence has not fared better in the empirical research literature because methodological limitations have led to unimpressive and ambiguous findings. This study addressed the common methodological problems associated with congruence research and provided a rationale for identifying and comparing measurement alternatives. This study compared two methods for generating Holland summary codes and two indexes for calculating congruence and investigated three aspects of job satisfaction. Significant findings included support for a weak correlation between congruence and overall job satisfaction and a weak correlation between congruence and extrinsic job satisfaction; however, none of the significant relationships found in this study were in the predicted direction. It is discussed that the congruence construct should not be considered as dead, but instead should be reconceptualized if it is to remain a viable concept in the research and practice of vocational psychology. It is suggested here that contemporary views of congruence should reflect the social and economic shifts that have influenced the changing nature of the meaning of work.
Is Congruence Dead? iii
What doesn't kill us makes us stronger.
~ Friedrich Nietzsche
Many, many times over the past eight years, I have wondered whether
my name had been changed to Sisyphus, and no one let me in on the
ruse. If Nietzsche’s adage is true, by now I should be the greatest
superhero or Greek mythological character the world ever has known. I
have not yet discovered the full extent of my special powers. I have
learned, though, that I don’t have the ability to shimmy down to the
ground from a second-story balcony, but I can develop influenza and
bronchitis at precisely the worst moment in time.
Is Congruence Dead? iv
ACKNOWLEDGEMENTS
Dr. Ed E. Jacobs As you are the Coordinator of the Counselor Education program, you had virtually no contact with me and had no firsthand knowledge of my academic work. When changes in the Counseling Psychology program necessitated that I reconstitute my dissertation committee, you readily agreed to assume a vacancy with no questions asked. I greatly appreciate your apparent faith in me and willingness to help me at a time when I most needed it. Dr. Jennifer R. Adams You also had no idea of me and agreed to assume a place on my committee, and for that, I am grateful also for your leap of faith. Having also previously not experienced my academic work, you had no way of knowing of my bad habit of “overwriting.” What I thank you for most is your guidance in editing and in the procedures of scientific writing and your implicit permission to not feel compelled to explain everything in minute detail. It has been a challenge for me but also a very valuable learning experience. Dr. Richard T. Walls My professional preference for the practice of psychotherapy also means that statistics are not an area of strength for me. Thank you for your guidance in helping me to determine how to translate my research questions into testable procedures. I also appreciate that, in general, you are a very kind person. Your words of encouragement have meant much to me. Dr. Roy H. Tunick I suppose that I am considered to be a statistical outlier in terms of the number of years it has taken me to complete my degree. As my advisor, thank you for not giving up on me a long time ago. Your advocacy and support for me in the program made it possible for me to finally complete my degree and get about the business of being a psychologist. Dr. Donald E. Eggerth For reasons that still are unknown to me, you decided to “take me under your wing” very early on in my doctoral career. I believe it was my very first semester, in fact. Since that time, your personal and professional mentorship have been invaluable, and I would not have made it through this process without your support and understanding. Thank you for your patience and sense of humor. Dr. Neil R. Snyder You know better than anyone that, in this process, I quite literally almost died. In the past 2 ½ years, I have been knocked down seemingly at every turn. You always were there to pick me up. You have selflessly given of your strength, energy, and encouragement. You believed in me when I did not believe in myself, and I do credit you with saving my life. I am honored to call you a mentor and a friend.
Is Congruence Dead? v
TABLE OF CONTENTS
Abstract ii Dedication iii Acknowledgments iv Table of Contents v List of Tables xvii List of Figures xix CHAPTER ONE: INTRODUCTION 1 Introduction to Chapter One 1 From Parsons to Person–Environment Fit 1 Holland’s Theory of Vocational Personality Types and Model Work Environments 3 Primary Assumptions of Holland’s Theory 3 Primary Assumption One: Vocational Personality Types 3 Primary Assumption Two: Model Work Environments 4 Primary Assumption Three: Person-Environment Fit 4 Primary Assumption Four: Outcomes of Person - Environment Fit 4 Rationale for the Research Study 5 Statement of the Research Problem 6 Purpose of the Research Study 7 Sampling Issues 7 Assessment of Vocational Personality 7 Assessment of Work Environment 8 Calculation of Congruence 8
Is Congruence Dead? vi
Job Satisfaction Measurement 9 General Research Questions 9 General Research Question Set 1: Measuring Congruence – Job Satisfaction Correlations with Traditionally-Derived Codes and the Modified C Index 10 Question 1a 10 Question 1b 10 Question 1c 10 General Research Question Set 2: Measuring Congruence – Job Satisfaction Correlations with Traditionally-Derived Codes and the Substitution C Index 10 Question 2a 10 Question 2b 11 Question 2c 11 General Research Question Set 3: Measuring Congruence – Job Satisfaction Correlations with Decision-Derived Codes and the Modified C Index 11 Question 3a 11 Question 3b 11 Question 3c 11 General Research Question Set 4: Measuring Congruence – Job Satisfaction Correlations with Decision-Derived Codes and the Substitution C Index 12 Question 4a 12 Question 4b 12 Question 4c 12 General Research Question Set 5: Comparing Job Satisfaction Correlation Values 12 Question 5a 12 Question 5b 12
Is Congruence Dead? vii
Question 5c 13 General Research Question 6: Comparing the Overall Job Satisfaction Correlation to Established Meta-Analytic Values 13 Summary of Chapter One 13 CHAPTER TWO: LITERATURE REVIEW 15 Introduction to Chapter Two 15 Sampling Issues 16 College and University Student Samples 16 Single Occupation Samples 17 Vocational Personality 17 Vocational Personality: Types 17 Realistic Vocational Personality Type 17 Investigative Vocational Personality Type 18 Artistic Vocational Personality Type 18 Social Vocational Personality Type 18 Enterprising Vocational Personality Type 18 Conventional Vocational Personality Type 19 Vocational Personality: Instruments 19 The Self-Directed Search 19 The Vocational Preference Inventory 19 The Strong Interest Inventory 20 Vocational Personality: Limitations 20 Self-Directed Search 20 Construct Validity 20
Is Congruence Dead? viii
Scoring 21 Vocational Preference Inventory 23 Strong Interest Inventory 23 Scoring Options and Cost 23 Administration Time 24 Vocational Personality: Alternatives 24 The Strong Interest Explorer 24 Decision-Derived Rules for Assigning Holland Summary Codes. 25 Work Environment 25 Model Work Environment: Types 25 Realistic Model Work Environment 26 Investigative Model Work Environment 26 Artistic Model Work Environment 26 Social Model Work Environment 26 Enterprising Model Work Environment 27 Conventional Model Work Environment 27 Work Environment: Instruments 27 The Dictionary of Holland Occupational Codes 27 The Occupations Finder 28 The Environmental Assessment Technique 28 The Position Classification Inventory 28 The Occupational Information Network 29 Work Environment: Limitations 30
Is Congruence Dead? ix
The Dictionary of Holland Occupational Codes and The Occupations Finder 30 The Environmental Assessment Technique 30 The Position Classification Inventory 31 The Occupational Information Network 31 Compatibility of Holland Code Classification Systems 32 Work Environment: Instrument Alternatives 32 Strong Interest Inventory General Occupational Theme Codes 32 Measurement of Congruence 33 Secondary Assumptions of Holland’s Theory 33 The Hexagonal Model of RIASEC Types 33 Consistency 35 Measurement of Congruence: Congruence Indexes 36 The First Letter Hexagonal Distance Index 37 The Compatibility Index 37 The K-P Index 38 The M Index 38 The Sb Index 39 The C Index 39 Measurement of Congruence: Congruence Index Limitations 40 Failure to Incorporate the Circumplex Assumption 41 Limitation to Three-Letter Holland Summary Codes 41 Measurement of Congruence: Congruence Index Alternatives 41 The Modified C Index 41
Is Congruence Dead? x
Support for the Modified C Index 42 The Substitution C Index 43 Support for the Substitution C Index 43 Job Satisfaction 43 Job Satisfaction: Instruments 44 The Hoppock Job Satisfaction Blank 44 The Job Descriptive Index and the Job in General Scale 44 The Minnesota Satisfaction Questionnaire 45 One-Item Measures of Overall Job Satisfaction 45 Measures Developed by the Research Authors 46 Measurement of Job Satisfaction: Instrument Limitations 46 Measures of Unknown Reliability and Validity 46 One-Item Measures 47 Measurement of Overall Job Satisfaction 47 Measurement of Job Satisfaction Instrument Alternative 47 Short-Form Minnesota Satisfaction Questionnaire 47 Summary of Chapter Two 48 CHAPTER THREE: METHODOLOGY 50 Introduction to Chapter Three 50 General Sample Characteristics 50 Measures 50 Strong Interest Explorer 50 The Short-Form Minnesota Satisfaction Questionnaire 52
Is Congruence Dead? xi
Participant Recruitment 53 Data Evaluation 54 Instrument Scoring 54 Statistical Analysis of Data 59 Demographic Analysis 59 MSQ Score Analysis 59 Congruence Score Analysis 59 General Research Question Analysis 60 Summary of Chapter Three 60 CHAPTER FOUR: DATA ANALYSIS 61 Introduction to Chapter Four 61 Demographic analysis 61 Demographic Analysis for All Data 61 Demographic Analysis by Occupational Group 62 Demographic Analysis by Primary Holland Type 63 MSQ Score Analysis 65 MSQ Score Analysis for All Data 65 MSQ Score Analysis by Occupational Group 66 MSQ Score Analysis by Primary Holland Type 66 Congruence Score Analysis 68 Congruence Score Analysis for All Data 68 Congruence Score Analysis by Occupational Group 69 Congruence Score Analysis by Primary Holland Type 70
Is Congruence Dead? xii
General Research Question Analysis 72 Question 1a 72 All Data 73 Occupational Groups 73 Primary Holland Type 73 Question 1b 74 All Data 74 Occupational Groups 74 Primary Holland Type 74 Question 1c 76 All Data 76 Occupational Groups 77 Primary Holland Type 77 Question 2a 77 All Data 77 Occupational Groups 78 Primary Holland Type 78 Question 2b 78 All Data 78 Occupational Groups 79 Primary Holland Type 79 Question 2c 79 All Data 79
Is Congruence Dead? xiii
Occupational Groups 79 Primary Holland Type 80 Question 3a 80 All Data 80 Occupational Groups 80 Primary Holland Type 81 Question 3b 81 All Data 81 Occupational Groups 81 Primary Holland Type 81 Question 3c 82 All Data 82 Occupational Groups 82 Primary Holland Type 82 Question 4a 82 All Data 83 Occupational Groups 83 Primary Holland Type 83 Question 4b 83 All Data 83 Occupational Groups 84 Primary Holland Type 84 Question 4c 84
Is Congruence Dead? xiv
All Data 84 Occupational Groups 86 Primary Holland Type 86 Question 5a 86 All Data 86 Occupational Groups 86 Primary Holland Type 87 Question 5b 88 All Data 88 Occupational Groups 88 Primary Holland Type 88 Question 5c 89 All Data 89 Occupational Groups 89 Primary Holland Type 89 Question 6 90 Correlation between Congruence and Overall Job Satisfaction 90 Summary of Chapter Four 90 CHAPTER FIVE: DISCUSSION 91 Review of Results 92 Demographic Analysis 93 Recommendations for Further Research 93 Mean Job Satisfaction Scores 94
Is Congruence Dead? xv
Recommendations for Further Research 94 Mean Congruence Scores 95 Recommendations for Further Research 95 Congruence – Job Satisfaction Correlations 96 Recommendations for Further Research 96 Traditionally-Derived and Decision-Derived Holland Summary Codes 96 Recommendations for Further Research 98 The Modfied C Index and the Substitution C Index 98 Recommendations for Further Research 99 Is Congruence Dead? 100 Research Limitations 101 REFERENCES 104 APPENDICES 127 Appendix A: Compatibility Index 127 Appendix B: K-P Index 128 Appendix C: M Index 130 Appendix D: Sb Index 131 Appendix E: C Index 135 Appendix F: The Modified C Index 136 Appendix G: The Substitution C Index 141 Appendix H: Steps for the Selection of Occupational Groups 145 Appendix I: Strong Interest Explorer Directions and Items 146 Appendix J: Strong Interest Explorer Items by RIASEC Type and Scale 148
Is Congruence Dead? xvi
Appendix K: Short-Form Minnesota Satisfaction Questionnaire Directions and Items 151 Appendix L: Professional Organizations and Businesses Corresponding to the Occupational Groups 154 Appendix M: Introductory Cover Letter Mailed to Potential Participants 155 Appendix N: Consent for Participation in a Study of Interests and Job Satisfaction 156 Appendix O: Reminder Letter Mailed to Participants 160 Appendix P: Rules for Resolving Tied SIE Scores 161 Appendix Q: Rules for Generating Decision Derived Holland Codes 162
Is Congruence Dead? xvii
LIST OF TABLES
1. Qualitatively Different Self-Directed Search Profile Scores with the Same Summary Code 22 2. Self-Directed Search Profile Scores with Tied Scores 23 3. Equal, Alternate, and Opposite Segments of Holland’s Hexagonal Model 35 4. Holland’s Hexagonal Model According to Levels of Consistency 36 5. Occupational Groups Included in the Research Sample 51 6. Occupational Group Usable Date Response Rates 54 7. Traditionally-Derived Codes and Decision-Derived Codes According to Primary Holland Type 56 8. Occupational Group Hit Rates Between Summary Code Primary Types and GOT Code Primary Types 57 9. Holland Type Hit Rates Between Summary Code Primary Types and GOT Code Primary Types 57 10. Primary Holland Types by Coding Method 58 11. Primary Holland Types Changes after Conversion from Traditionally-Derived Codes to Decision-Derived Codes 58 12. Demographic Data for All Cases 62 13. Demographic Data According to Occupational Group 64 14. Demographic Data According to Primary Holland Type 65 15. MSQ Data for All Cases 66 16. MSQ Data According to Occupational Group 67 17. MSQ Data According to Primary Holland Type 68 18. Congruence Score Data for All Cases 69 19. Congruence Score Data by Occupational Group 71 20. Congruence Score Data by Primary Holland Type 72
Is Congruence Dead? xviii
21. Job Satisfaction Correlations with Congruence Scores for All Data 73 22. Occupational Group Job Satisfaction Correlations with Traditionally-Derived Congruence Scores 75 23. Holland Type Job Satisfaction Correlations with Traditionally-Derived Congruence Scores 76 24. Occupational Group Job Satisfaction Correlations with Decision-Derived Congruence Scores 85 25. Holland Type Job Satisfaction Correlations with Decision-Derived Congruence Scores 87 26. Comparisons of Congruence – Overall Job Satisfaction Correlations 90 B1. K-P Index Hexagonal Segment Distance Proportion Values 129 C1. M Index Two-Letter Codes Weights 130 C2. M Index Three-Letter Code Weights 130 D1. Sb Index Distances 132 E1. Distances between Holland Types Used in the Calculation of the C Index 135
Is Congruence Dead? 1
CHAPTER ONE: INTRODUCTION
INTRODUCTION TO CHAPTER ONE
The person-environment (P-E) fit model is discussed as the dominant theoretical
framework in vocational psychology. John L. Holland’s theory of vocational personality types
and model work environments is identified as the most widely applied P-E fit approach within
the field. Holland’s primary assumptions are described, and salient theoretical concepts are
reviewed. The relationship between Holland’s congruence construct and job satisfaction is
presented as the primary focus.
It is discussed that the relationship between congruence and job satisfaction is
equivocally empirically supported in the vocational psychology literature. The evidence
supporting the argument that Holland’s congruence is “dead” as a viable theoretical construct is
reviewed. The counterargument that the relationship between congruence and job satisfaction is
viable but has been obscured by methodological problems is reviewed.
It is argued that many studies examining the relationship between congruence and job
satisfaction are flawed because common elements of the typical congruence – job satisfaction
research framework have not been well operationalized. Common methodological limitations are
discussed, and an alternative approach with concomitant general research questions is presented.
FROM PARSONS TO PERSON–ENVIRONMENT FIT
Frank Parsons (1909) often is credited as the “father” of vocational guidance in the
United States (Heppner, 2000). He developed a rational, three-part process to follow when
selecting an occupation:
In the wise choice of a vocation there are three broad factors: (1) a clear
understanding of yourself, your aptitudes, abilities, interests, ambitions,
Is Congruence Dead? 2
resources, limitations, and their causes; (2) a knowledge of the requirements and
conditions of success, advantages and disadvantages, compensation,
opportunities, and prospects in different lines of work; (3) true reasoning on these
two groups of facts. (Parsons, 1909, p. 5)
The introduction of this model planted the seeds of modern vocational psychology and marked
the beginning of an organized, theoretical approach to vocational guidance (Brown, 2002;
Williamson, 1966).
The trait-and-factor model that emerged and grew out of Parsons’ method similarly is
based on the idea that occupational choice is a straightforward reasoning process that involves
matching individual traits to commensurate job requirements (Walsh, 1999). The trait-and-factor
model further specifies that positive job outcomes occur when there is a good match, more
commonly referred to as fit, between the individual’s traits and the requirements of the job (Betz,
Fitzgerald, & Hill, 1989).
Within the relatively short history of vocational psychology, the trait-and-factor approach
now has been replaced by person-environment (P-E) fit theories. Eggerth (2004) concisely sums
up P-E fit theory by stating, “the crux of P-E fit models is the ability to make meaningful
predictions about outcome based upon the quality of fit between the characteristics of a person
and of an environment” (p. 93). Swanson (1996) and Chartrand (1991) distinguish the trait-and-
factor approach from P-E fit by explaining that P-E fit incorporates trait-and-factor ideas but
more broadly defines vocational behavior and its salient concepts. The P-E fit approach, with its
intuitive appeal and solid theoretical framework, has grown to become the model of inquiry “par
excellence” (Dawis, 2000) for the field of vocational psychology.
Is Congruence Dead? 3
HOLLAND’S THEORY OF VOCATIONAL PERSONALITY TYPES AND
MODEL WORK ENVIRONMENTS
John L. Holland’s (1959,1966, 1973, 1985a, 1992, 1997) theory of vocational personality
types and model work environments is thought to be the most widely applied P-E fit approach in
vocational psychology. The theory is cited widely for its parsimony, definition of constructs, and
relationships among its principles. It generally is considered to be the most respected and
influential career theory within the field (Campbell & Borgen, 1999; Gottfredson, 1999; Griffin
& Hesketh, 2005).
Holland’s emphasis on the role of personality makes the theory distinctive from other
theories in vocational psychology (Osipow, 1994). According to the theory, an individual’s
occupational choices represent an extension of personality and an effort to apply broad personal
behavioral styles within the context of the work environment (Hogan & Blake, 1999; Holland,
1999; Walsh & Osipow, 1986).
PRIMARY ASSUMPTIONS OF HOLLAND’S THEORY
The essence of Holland’s (1997) theory can be found in four primary assumptions that
correspond to the basic aspects of P-E fit. These assumptions explain (1) vocational personality
types, (2) model work environments, (3) person-environment fit, and (4) outcomes of person-
environment fit.
Primary Assumption One: Vocational Personality Types
Holland (1997) states that, “in our culture, most persons can be categorized as one of six
personality types: Realistic, Investigative, Artistic, Social, Enterprising, or Conventional” (p. 2).
The acronym RIASEC typically is used as a shorthand to refer to this typology.
Is Congruence Dead? 4
Primary Assumption Two: Model Work Environments
According to Holland (1997), work environments cannot be separated from the
individuals who occupy them. From this tenet follows there are six model work environments
that are commensurate with the six vocational personality types. These environments also are
named as Realistic, Investigative, Artistic, Social, Enterprising, and Conventional.
Primary Assumption Three: Person–Environment Fit
Holland (1997) indicates that people are drawn to environments that allow them to use
their skills and abilities and to express their attitudes and values. This assertion specifically refers
to the idea that individuals tend to seek out occupational environments that are compatible to
their vocational personality types within the RIASEC scheme.
The term congruence commonly is used to imply the degree of fit, match, or similarity
between the individual and the requirements of the individual’s chosen work environment
(Edwards, 1994; Gothard, 1985). In Holland’s model, an individual is said to be congruent when
the vocational personality type is identical or highly similar to the work environment.
Conversely, an individual is incongruent when the vocational personality type and the work
environment are inconsistent.
Primary Assumption Four: Outcomes of Person–Environment Fit
Holland’s (1997) theory specifies that individuals will succeed in congruent work
environments because those environments, by definition, provide the kinds of opportunities and
rewards that are important. Congruence has been shown empirically to be positively correlated
with a variety of dependent outcomes, including vocational stability (e.g., Oleski & Subich,
1996; Villwock, Schnitzen, & Carbonari, 1976), occupational performance and productivity
Is Congruence Dead? 5
(e.g., Fritzsche, Powell, & Hoffman, 1999; Richards, 1993), and personal adjustment (e.g.,
Eagan & Walsh, 1995; Lachterman & Meir, 2004).
Job satisfaction is the most frequently examined outcome variable in congruence
research. Congruent individuals are expected to experience a higher level of job satisfaction than
those individuals who are incongruent (Carson & Mowsesian, 1993; Jagger, Neukrug, &
McAuliffe, 1992; Mount & Muchinsky, 1978; Smart, Elton, & McLaughlin, 1986; Wiggins,
1984; Wiggins, Lederer, Salkowe, & Rys, 1983). The assumption that congruence results in job
satisfaction is fundamental to Holland’s theory (Gottfredson & Holland, 1990).
RATIONALE FOR THE RESEARCH STUDY
The empirical evidence predominantly indicates that the congruence – job satisfaction
correlation is, at best, equivocal. While there are many studies that provide support for a positive
correlation between congruence and job satisfaction (e.g., Burgner, 1994; Smart, Elton, &
McLaughlin, 1986), there are many more studies that have failed to validate this relationship or
have produced mixed results (e.g., Cook, 1996; Harris, Mortizen, Robitschek, Imhoff, & Lynch,
2001; Meir, Keinan, & Segal, 1986; Tokar & Subich, 1997).
The results of three meta-analyses further support that congruence is not meaningfully
related to job satisfaction within Holland’s theory. After an analysis of 53 congruence studies,
Assouline and Meir (1987) report the weighted mean correlation between congruence and job
satisfaction to be a modest .21. The analysis conducted by Tranberg, Slane, and Ekeberg (1993)
found a comparably low mean correlation of .20. Tsabari, Tziner, and Meir (2005) performed a
meta-analysis of 53 samples and found the mean correlation between congruence and job
satisfaction to be weak at .166. Tsabari, et al. then corrected for sampling and measurement
errors that have been identified as ones that can obscure significant meta-analytic results
Is Congruence Dead? 6
(Holland, 1987; Meir, 1995). The modified analysis revealed an even lower mean congruence
correlation value of .158.
In the wake of these and related findings, there is a movement within vocational
psychology that the field should “move away” from Holland’s theory (Hesketh, 2000; Schwartz,
1992). Tinsley (2006), for example, states that the theory stands as an exception to the generally
positive performance of other P-E fit models and indicates there is no evidence that congruence
is a valid predictor of any meaningful work outcomes. Subich (1992) similarly advises that
Holland’s fundamental assumption of the ability to predict job satisfaction from congruence may
be too broadly stated. Even Holland himself has acknowledged the popular opinion within
vocational psychology that the congruence construct is “dead” as a viable theoretical concept
(Feller, Honaker, & Zagzebski, 2001; Holland, 1996). This is not to say that Holland has agreed
with this view.
In fact, the idea that Holland’s theory should be abandoned does not exist without
significant argument. The apparently dubious relationship between Holland’s congruence and
job satisfaction is a controversial issue within vocational psychology (Spokane, Luchetta, &
Richwine, 2002; Swanson & Gore, 2000). An alternative point of view within the field maintains
that congruence has not fared better in the empirical research literature because methodological
limitations have led to unimpressive and ambiguous findings (Chartrand, Strong, & Weitzman,
1995; Eggerth, Bowles, Tunick & Andrew, 2005; Fassinger, 2005; Furnham, 2001; Meir, 1995;
Phillips & Jome, 2005; Prediger & Vansickle, 1992; Swanson, 1992).
STATEMENT OF THE RESEARCH PROBLEM
Holland’s theory is expected to continue to dominate vocational behavior research
(Brown, 2003; Hansen, 1984; Lowman & Carson, 2000). This means that the continued vitality
Is Congruence Dead? 7
of the congruence construct depends upon the evolution of appropriate methodology (Prediger,
2000; Spokane, Meir, & Catalano, 2000). Many researchers have neither acknowledged the
methodological problems associated with congruence research nor implemented viable empirical
alternatives (Edwards, 1991).
PURPOSE OF THE RESEARCH STUDY
Chartrand and Walsh (1999) point out that congruence – job satisfaction correlation
research requires four methodological components: (1) the assessment of vocational personality,
(2) the assessment of the work environment, (3) the calculation of congruence, and (4) the
correlation of congruence to a job satisfaction outcome measure. This study addresses sampling
issues and common methodological problems associated with each of the four aspects outlined
by Chartrand and Walsh. This research additionally provides a rationale for identifying and
comparing measurement alternatives.
Sampling Issues
This study first addresses two sampling issues that have plagued congruence research.
Previous research has relied heavily on the sampling of college students and members
representing a single occupation or occupational group. The correction of previous errors is
described in Chapter Three through this study’s use of a sample of employed adults that is
representative of the entire RIASEC scheme.
Assessment of Vocational Personality
The Self-Directed Search (SDS; Holland, Fritzsche, & Powell, 1994), the Vocational
Preference Inventory (VPI; Holland, 1985b), and the Strong Interest Inventory (SII; Donnay,
Morris, Schaubhut, & Thompson, 2005) are discussed as the most common instruments used to
Is Congruence Dead? 8
measure vocational personality. Questionable construct validity, problems incurred with scoring
and coding procedures, and practical concerns are reviewed as they relate to these instruments.
The Strong Interest Explorer (SIE; Chartrand, 2001) is identified as the measure of
vocational personality chosen for this study. Research conducted by Dik, Hu, and Hansen (2007)
that describes an alternative method for generating Holland codes is reviewed. This research
generates traditionally-derived summary codes and decision-derived summary codes. It is
examined whether the congruence - job satisfaction correlation is dependent upon the summary
coding method that is applied.
Assessment of Work Environment
The Dictionary of Holland Occupational Codes (DHOC; Gottfredson & Holland, 1996),
the Occupations Finder (OF; Holland, 1994), the Environmental Assessment Technique (EAT;
Astin, 1963; Astin & Holland, 1961), the Position Classification Inventory (PCI; Gottfredson &
Holland, 1991), and the Occupational Information Network (O*NET; National O*NET
Consortium, n.d.) are identified as popular methods for assessing the Holland work environment.
Conceptual and practical problems are identified and discussed for each of these techniques.
The General Occupational Theme (GOT) codes of the SII are described. It is identified
that this research uses GOT codes to assess the work environment as they represent an
application of the RIASEC scheme that incorporates methods to limit potential measurement
error.
Calculation of Congruence
Six mathematical congruence indexes are identified and described: (1) the First Letter
Hexagonal Distance index (FLHD; Holland, 1973), (2) the Compatibility index (CI; Wiggins &
Moody, 1981; Moody, 1983), (3) the K-P index (Kwak & Pulvino, 1982), (4) the M index
Is Congruence Dead? 9
(Iachan, 1984, 1990), (5) the Sb Index (Gati, 1985), and (6) the C index (Brown & Gore, 1994).
The limitations of the use of these indexes in the calculation of congruence are discussed. The
modified C index, developed by Eggerth and Andrew (2006) in order to address these
limitations, is discussed. The substitution C index, developed by Gore and Brown (2006) as an
alternative to modified C index, is discussed as well. Both indexes are used in this research to
generate congruence scores. It is examined whether the congruence - job satisfaction correlation
is dependent upon the index that is used to calculate congruence scores.
Job Satisfaction Measurement
The most frequently used job satisfaction assessment techniques are identified as the
Hoppock Job Satisfaction Blank (HJSB; Hoppock, 1935), the Job Descriptive Index (JDI;
Baltzer, et al., 1997; Baltzer & Smith, 1990; Smith, Kendall, & Hulin, 1969), the Job in General
scale (JIG; Ironson, Smith, Brannick, Gibson, & Paul, 1989), (3) the Minnesota Satisfaction
Questionnaire (MSQ; Weiss, Dawis, England, & Lofquist, 1967) (4) one-item measures of
overall job satisfaction, and (5) measures developed by the research authors. Limitations related
to valid and reliable measurement are reviewed. The importance of examining intrinsic,
extrinsic, and overall aspects of job satisfaction is discussed, and the short-form MSQ is
identified as the measure used here.
GENERAL RESEARCH QUESTIONS
In order to examine the congruence – job satisfaction correlation while comparing two
methods for generating Holland codes and two indexes for calculating congruence and
investigating three aspects of job satisfaction, the following research questions are investigated.
It is recognized that other inferential procedures may be applied.
Is Congruence Dead? 10
General Research Question Set 1: Measuring Congruence – Job Satisfaction Correlations with
Traditionally-Derived Codes and the Modified C Index
Question 1a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
Question 1b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
Question 1c
Is there a significant positive correlation between congruence and overall job satisfaction
when traditionally-derived codes are used to measure vocational personality and the Modified C
index is used to calculate congruence scores?
General Research Question Set 2: Measuring Congruence – Job Satisfaction Correlations with
Traditionally-Derived Codes and the Substitution C Index
Question 2a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
Substitution C index is used to calculate congruence scores?
Is Congruence Dead? 11
Question 2b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
Substitution C index is used to calculate congruence scores?
Question 2c
Is there a significant positive correlation between congruence and overall job satisfaction
when traditionally-derived codes are used to measure vocational personality and the Substitution
C index is used to calculate congruence scores?
General Research Question Set 3: Measuring Congruence – Job Satisfaction Correlations with
Decision-Derived Codes and the Modified C Index
Question 3a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
Question 3b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
Question 3c
Is there a significant positive correlation between congruence and overall job satisfaction
when decision-derived codes are used to measure vocational personality and the Modified C
index is used to calculate congruence scores?
Is Congruence Dead? 12
General Research Question Set 4: Measuring Congruence – Job Satisfaction Correlations with
Decision-Derived Codes and the Substitution C Index
Question 4a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Substitution C index is used to measure congruence?
Question 4b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Substitution C index is used to measure congruence?
Question 4c
Is there a significant positive correlation between congruence and overall job satisfaction
when decision-derived codes are used to measure vocational personality and the Substitution C
index is used to measure congruence?
General Research Question Set 5: Comparing Job Satisfaction Correlation Values
Question 5a
Are there significant differences in the intrinsic job satisfaction correlation values
identified in Questions 1a, 2a, 3a, and 4a?
Question 5b
Are there significant differences in the extrinsic job satisfaction correlation values
identified in Questions 1b, 2b, 3b, and 4b?
Is Congruence Dead? 13
Question 5c
Are there significant differences in the overall job satisfaction correlation values
identified in Questions 1c, 2c, 3c, and 4c?
General Research Question 6: Comparing the Overall Job Satisfaction Correlation to Established
Meta-Analytic Values
Do any of the overall job satisfaction correlation values identified in Questions 1c, 2c, 3c,
and 4c meet or significantly exceed the meta-analytic correlations that were reported by
Assouline & Meir (1987), Tranberg, et al. (1993), and Tsabari, et al. (2005)?
SUMMARY OF CHAPTER ONE
The person-environment (P-E) fit model was discussed as the dominant theoretical
framework in vocational psychology. John L. Holland’s theory of vocational personality types
and model work environments was identified as the most widely applied P-E fit approach within
the field. Holland’s primary assumptions were described, and salient theoretical concepts were
reviewed. The relationship between Holland’s congruence construct and job satisfaction was
presented as the primary focus.
It was discussed that the relationship between congruence and job satisfaction is
equivocally empirically supported in the vocational psychology literature. The evidence
supporting the argument that Holland’s congruence is “dead” as a viable theoretical construct
was reviewed. The counterargument that the relationship between congruence and job
satisfaction is viable but has been obscured by methodological problems was reviewed.
It was argued that many studies examining the relationship between congruence and job
satisfaction are flawed because common elements of the typical congruence – job satisfaction
research framework have not been well operationalized. Common methodological limitations
Is Congruence Dead? 14
were discussed, and an alternative approach with concomitant general research questions was
presented.
Is Congruence Dead? 15
CHAPTER TWO: LITERATURE REVIEW
INTRODUCTION TO CHAPTER TWO
Chapter Two details the methodological limitations characteristic of congruence – job
satisfaction correlation research and discusses appropriate measurement alternatives. The
rationale for the comparison of two Holland summary coding methods and two congruence
indexes and the investigation of three aspects of job satisfaction is presented.
The six vocational personality types are outlined. The Self-Directed Search, the
Vocational Preference Inventory, and the Strong Interest Inventory are discussed as the major
vocational personality assessments that are used in congruence research. Construct validity,
traditionally-derived scoring issues, and practical concerns are described. The Strong Interest
Explorer is presented as the measurement option used in this research. Research on guidelines
for developing decision-derived Holland summary codes is described. It is discussed that the
research compares traditionally-derived codes with decision-derived codes that are generated
with a cut standard score method.
The six work environments are described. The Dictionary of Holland Occupational
Codes, the Occupations Finder, the Environmental Assessment Technique, the Position
Classification Inventory, and the Occupational Information Network are discussed as popular
work environment assessment methods. Conceptual and practical problems and a misassumption
regarding the interchangeability of these measures are presented. The SII General Occupational
Theme codes are identified as the work environment assessment approach that is used in this
research.
Holland’s circumplex model and secondary theoretical assumption of conistency are
explained. The First Letter Hexagonal Distance index, the Compatibility index, the K-P index,
Is Congruence Dead? 16
the M index, the Sb Index, and the C index are identified as well-known congruence indexes. The
methodological weaknesses of these indexes are discussed. The modified C index and the
substitution C index are identified and presented as alternative congruence measures that are
compared in this research.
Job satisfaction is identified as an affective state that results from the overall assessment
of job experiences. The Hoppock Job Satisfaction Blank, the Job Descriptive Index and the Job
in General scale, the Minnesota Satisfaction Questionnaire, one-item measures of overall job
satisfaction, and measures developed by the research authors are discussed as frequently used job
satisfaction assessment techniques. Validity and reliability issues associated with these methods
are described. It is explained that this research uses the short-form MSQ to measure intrinsic,
extrinsic, and overall job satisfaction.
SAMPLING ISSUES
College and University Student Samples
Congruence correlation research has relied heavily on the use of college and university
student samples (Hackett, Lent, & Greenhaus, 1991; Smart, 1976; Spokane, 1985; Thomas &
Robbins, 1979; Tinsley, 2000). Educational satisfaction, in particular, has been investigated often
as a dependent outcome of congruence (e.g., Allen, 1996; Frantz & Walsh, 1972; Morrow, 1971;
Nafziger, Holland, & Gottfredson, 1975; Shaw, 2005; Spokane, 1979; Spokane & Derby, 1979;
Walsh, 1974; Walsh & Lewis, 1972).The prevalence of this type of research has resulted in a
disproportionate focus on college and university students and reflects an assumption that
educational satisfaction can be considered as a proxy for job satisfaction. The investigation of
congruence in this manner is misguided as it fails to reflect Holland’s assumption that working
Is Congruence Dead? 17
adults seek out congruent work environments (Rounds, McKenna, Hubert, & Day, 2000;
Tsabari, et al., 2005).
Single Occupation Samples
Much of the congruence – job satisfaction correlation research has examined samples that
represent a single occupation or occupational group (e.g., Aranya, Barak, & Amernic, 1981;
Clark, 1991; Coddington, 1998; Finley, 1989; Furnham, Toop, Lewis, & Fisher, 1995; Hoile,
2000; Portscheller, 1992; Wiggins, 1984). As Holland uses the RIASEC scheme to define six
vocational personalities and six corresponding work environments, it is doubtful whether this
kind of research can be used to make appropriate statements regarding congruence. The use of
single-sample methodology may be better considered as an examination of a particular
occupational group or Holland type rather than as an investigation of the congruence – job
satisfaction relationship that is within the scope of the theory.
VOCATIONAL PERSONALITY
Vocational Personality: Types
Each personality type within the RIASEC scheme is an ideal model of behavior that is
defined by a characteristic personal repertoire of attributes, attitudes, and behaviors. Holland
states that one tends to most resemble one particular type. The theory specifies, though, that
individuals implement a range of behaviors and can resemble to a degree more than one, and in
most cases all, of the six personality types.
Realistic Vocational Personality Type
Realistic individuals tend to be interested more in dealing with things than with people or
ideas. They may prefer that which is tangible and concrete to that which is abstract and
Is Congruence Dead? 18
subjective. They are inclined to be oriented toward developing physical strength, honing motor
coordination, and engaging in activities that require mechanical and manual abilities.
Investigative Vocational Personality Type
Investigative individuals prefer to engage in activities that involve organizing and
understanding ideas. They tend to be task-oriented, analytical, and enjoy pursuing academic
activities. They often possess strong verbal, scientific, and mathematical skills.
Artistic Vocational Personality Type
Artistic individuals tend to enjoy activities that require self-expression and encourage
independence and subjectivity. They may prefer aesthetic endeavors that involve the use of
imaginative, introspective, and creative skills, and they tend to possess artistic and musical
ability. They may prefer to avoid highly controlled environments that require compliance to pre-
existing standards.
Social Vocational Personality Type
Social individuals seek situations where they can engage in social interactions and
exercise their interpersonal abilities. They tend to be sensitive to the needs of others and have a
strong interest in helping and understanding others. They may prefer teaching activities where
they can use their verbal and social skills.
Enterprising Vocational Personality Type
Enterprising individuals typically are verbally skilled, extroverted, and confident.
They tend to enjoy adventurous activities and value economic and political pursuits. They may
prefer roles that involve power and status and may enjoy organizing, directing, and persuading
others.
Is Congruence Dead? 19
Conventional Vocational Personality Type
Conventional individuals enjoy pursuing structured activities. They may prefer clear
guidelines and have the ability to adapt to the structure and demands of a particular situation.
They tend to be organized and practical, have numerical and clerical ability, and pursue business
and economic endeavors.
Vocational Personality: Instruments
The Self-Directed Search
The Self-Directed Search (SDS; Holland, et. al, 1994) is one of the most widely used
inventories in all of vocational interest research. The assessment booklet is an ipsative measure,
designed to be self-administered and self-scored. It consists of four primary sections, listings of
(1) 66 Activities, (2) 66 Competencies, (3) 84 Occupations, and (4) 12 Self-Estimates of abilities.
Each of these components represents each of the six dimensions in the RIASEC typology.
Responses regarding interest in Activities (“Like”, “Dislike”) and Occupations (“Yes”, “No”)
combined with responses regarding Competencies (“Yes”, “No”) and Self-Estimates of abilities
(scales ranging from 1 to 7) yield a raw score for each of the six types.
The Vocational Preference Inventory
The Vocational Preference Inventory (VPI; Holland, 1985b) first was developed in 1953
and currently is in its seventh edition. The full-scale VPI consists of 160 occupational titles that
represent each of the six dimensions in the RIASEC typology. Ipsative responses regarding level
of interest (“Yes”, “No”, “Undecided”) in the occupational titles yield a raw score for each type.
In addition to the six scales representing the RIASEC typology, the VPI contains five
supplemental scales: (1) Self-control, (2) Masculinity/Femininity, (3) Status, (4) Infrequency,
and (5) Acquiescence.
Is Congruence Dead? 20
The Strong Interest Inventory
The Strong Interest Inventory (SII; Donnay, et. al, 2005) has long been combined with
Holland’s RIASEC typology (Campbell & Holland, 1972). It consists of 291 items each with a
corresponding 5-point Likert-type response scale (“Strongly Like”, “Like”, “Indifferent”,
“Dislike”, “Strongly Dislike”). The SII is a computer-scored assessment that yields standardized
T-scores based on extensive normative data in the areas of six General Occupational Themes
(GOT), 30 Basic Interest Scales (BIS), 122 pairs of Occupational Scales (OS), and 5 Personality
Style Scales (PSS). The GOT and BIS components of the SII are the particular sections that are
commensurate with the RIASEC scheme and yield standard scores for each of the six types.
Vocational Personality: Limitations
Self-Directed Search
Construct Validity
The four sections of the SDS are approximately equally weighted and therefore confound
an individual’s vocational personality results with information regarding competencies (Lowman
& Williams, 1987). Swanson (1993) points out that interests, skills, and abilities are related, yet
distinct, constructs and highlights that having skill or ability in a certain area does not necessarily
equate with also having an interest in that area.
The incorporation of self-estimates into SDS scores assumes that individuals are able to
accurately approximate their own skills. There is evidence to indicate that this may not be the
case (Mabe & West, 1982; Poh, 1996). Kelso, Holland, and Gottfredson (1977) administered the
SDS and the Armed Services Vocational Aptitude Battery (ASVAB; Bayroff & Fuchs, 1970) to
a group of female preparatory school students. It was predicted that the SDS Self-Estimates and
Competencies scales would correspond with the commensurate scales of the ASVAB; however,
Is Congruence Dead? 21
the findings indicated that the SDS and the ASVAB scores were only moderately correlated.
Hodgson and Cramer (1977) investigated a group students who had been administered the
Differential Aptitude Tests (DAT; Bennett, Seashore, & Wesman, 1959). The students
completed the Self-Estimates portion of the SDS, and the Math Ability, Clerical Ability, and
Mechanical Ability scales of the SDS were compared with the commensurate, same-named DAT
scales. The overall findings did not support the use of self-estimates when assessing skills and
abilities. Lowman and Williams (1987) studied a group of college women in order to compare
self-estimates to objective measures of abilities. Each woman was administered the SDS and a
battery of 10 objective measures differentially corresponding to the six Holland types. Support
for the validity of the self-estimated abilities was mixed. The authors conclude that “it remains
open to debate what precisely the SDS is measuring” (p. 11).
Scoring
The scoring procedure of the SDS is designed to highlight what is termed here as an
individual’s traditionally-derived summary code, the three types within the RIASEC scheme that
correspond to the three highest SDS raw scores. Traditionally-derived summary codes have
grown to become standard shorthand in Holland’s theory. Despite this, the use of the
traditionally-derived approach creates both theoretical and practical difficulties and is
methodologically insensitive (Gati, 1987; Meir, 1993).
The rigid implementation of the traditional coding procedure does not take into
consideration the distances between scores or the overall magnitude of the scores (Arnold, 2004).
This permits qualitatively different profiles to be identified with the same code. The SDS
summary codes of Persons A, B, and C in Table 1 all would be reported as RAS even though the
scores illustrate three distinct patterns. Person A has Realistic interests that appear to be well-
Is Congruence Dead? 22
defined, and it is debatable whether the addition of Artistic and Social to the summary code of
Person A adds relevant information. Person B could be characterized as RAS, but all of the
scores are clustered close together. The flat and low profile of Person C demonstrates little
meaningful similarity to any of the six types.
Table 1
Qualitatively Different Self-Directed Search Profile Scores with the Same Summary Code
Realistic Investigative Artistic Social Enterprising Conventional
Person A 20 5 8 7 4 4
Person B 15 11 14 13 10 12
Person C 6 2 5 3 0 1
Formal methods for handling SDS tie scores have not been established; moreover,
procedures used for breaking ties often is not reported in congruence research (Spokane, et al.,
2000; Strahan & Severinghaus, 1992). The three highest SDS scores of Person D in Table 2 are
Social, Enterprising, and Conventional. As the Enterprising and Conventional scores are tied, it
must be decided whether the summary code should be SEC or SCE. The SDS profile of Person E
shows that Social and Enterprising and Artistic and Conventional scores are tied. It must be
decided whether the first two letters of the summary code should be SE or ES and whether the
third letter should be A or C. Finally, the highest scores for Person F appear in a three-way-tie
and potentially could be ordered to create six different summary codes.
Is Congruence Dead? 23
Table 2
Self-Directed Search Profile Scores with Tied Scores
Realistic Investigative Artistic Social Enterprising Conventional
Person D 13 12 15 25 20 20
Person E 8 11 14 17 17 14
Person F 13 19 22 28 28 28
Vocational Preference Inventory
The VPI is a more construct valid measure of vocational interests when compared to the
SDS. The VPI does yield RIASEC raw data that is comparable to that of the SDS. The VPI thus
incurs the same scoring issues that already have been outlined for the SDS.
Strong Interest Inventory
The SII is one of the most respected and technologically sound vocational interest
inventories that currently is available (Borgen & Harmon, 1996; Hansen, 2000). Extensive
studies support its validity and indicate that the SII best fits the RIASEC model when compared
with the SDS and the VPI (Hubert & Arabie, 1987; Tracey & Rounds, 1993). Despite this, the
SII is not often used in congruence – job satisfaction correlation research. Despite the empirical
superiority of the SII, there are practical concerns associated with the use of this instrument.
Scoring Options and Cost
The SII can be purchased with options for either mail-in scoring or internet scoring. The
cost of the SII can be expensive, and in fact, could be prohibitive for the independent researcher
or for an organization with a limited research budget. Moreover, the mail-in scoring option has
the potential to hinder efficient research as one must wait for the instrument to be scored and
Is Congruence Dead? 24
returned before data can be analyzed. While the internet option provides a faster alternative, this
option also would require adequate access to a computer with internet capabilities. Sufficient
access to up-to-date equipment and office space is not always an uncomplicated matter in the
research process.
Administration Time
Manual information indicates that an individual should be able to complete the SII in an
average time of 35 to 40 minutes. Today, in the 21st century, when time is considered more than
ever to be a premium commodity, many potential research participants may not be willing to take
the SII. Researchers have the responsibility of weighing their instrument choices against
potential respondent burden (Sharp & Frankel, 1983), and subject willingness to participate is as
much a practical consideration as protection of research participants is an ethical consideration.
Vocational Personality: Alternatives
The Strong Interest Explorer
The SII has been used to develop the Strong Interest Explorer (SIE; Chartrand, 2001).
The SIE differs from the SII in that it is a simplified alternative. The SIE is designed to be
quickly self-administered and self-scored and can be purchased at prices that are more affordable
than those of the SII. The SIE is a relatively new and lesser-known instrument. There exists no
known published research with the SIE outside of its development and the initial establishment
of validity and reliability (Research Department, 2002). The SIE warrants empirical study. This
instrument may provide a more practical, and yet still highly valid, measurement option in
congruence research.
Is Congruence Dead? 25
Decision-Derived Rules for Assigning Holland Summary Codes
Dik, et al. (2007) point out that research on congruence – job satisfaction correlations
across methods of assigning Holland codes has been “virtually non-existent.” In an effort to
address this gap in the literature, the authors used gender-normed standard scores based on the
GOT scales of the 1985 version of the SII (Hansen & Campbell, 1985) to develop and compare
the utility of four sets of Holland code assignment methods.
All of the coding methods were sensitive both to the elevation of scores and to the
magnitude of the differences between the scores. Two coding assignment approaches used
decision rules based on a mean T score cut score process. Two techniques used decision rules
based on an individual’s highest GOT score relative to the standard deviation of difference
scores. Data analysis indicated that the largest mean congruence value was associated with the
cut score method anchored by a mean T score of 60. It is this method that is used here to
generate the decision-derived summary codes that are compared to the traditionally-derived
codes.
WORK ENVIRONMENT
Model Work Environment: Types
In Holland’s theory, work environments are seen as a function of the individuals who
occupy them. “The people make the place” (Schneider, 1987) as individuals tend to create work
environments where certain characteristics dominate. Work environments in turn become
settings that elicit, develop, and reward the behaviors of the individuals who resemble the
prevailing environmental type. These factors combine such that work environments and
personality types mirror one another.
Is Congruence Dead? 26
Realistic Model Work Environment
Realistic work environments encourage the development of technical competency and
psychomotor skills. They encourage achievement in skilled trades and mechanical occupations
and provide opportunities to build or repair with the use of tools or machines. Examples of
Realistic occupations include automobile mechanic, construction worker, emergency medical
technician, and bus driver.
Investigative Model Work Environment
Investigative work environments encourage the application of analytical ability in the
observation and investigation of physical, biological, and cultural phenomena. They provide
opportunities to work independently on conceptual tasks and tend to support perseverance in
solving problems. Examples of Investigative occupations include astronomer, chemist, medical
technologist, mathematician, anthropologist, and veterinarian.
Artistic Model Work Environment
Artistic work environments encourage the development of creativity, originality,
imagination, artistic ability, and verbal skills. They stimulate artistic, musical, and literary
achievement in unstructured and flexible environments. Examples of Artistic occupations
include composer, poet, singer, book editor, wedding consultant, actor, interior designer,
architect, and illustrator.
Social Model Work Environment
Social work environments promote social, interpersonal, and teaching skills and the
ability to understand and empathize with others. They stimulate performance in occupations
where individuals can demonstrate a desire to inform, train, develop, enlighten or improve the
Is Congruence Dead? 27
lives of others. Examples of Social occupations include family counselor, clergy member,
secondary school teacher, registered nurse, and physical therapist.
Enterprising Model Work Environment
Enterprising work environments encourage the development of verbal and leadership
skills and promote achievement in managing others and in purchasing and selling. Enterprising
work environments provide the opportunity for individuals to meet organizational, project, and
personal goals by persuading others. Examples of Enterprising occupations include hotel
manager, real estate agent, flight attendant, buyer, urban planner, and estate planner.
Conventional Model Work Environment
Conventional work environments encourage the development of efficiency, data
management, mathematical skills, and attention to detail. They provide opportunities for
individuals to manage procedures, oversee files, write reports, and operate business machines in
order to attain organizational goals. Examples of Conventional occupations include bookkeeper,
accountant, bank teller, payroll clerk, and credit analyst.
Work Environment: Instruments
The Dictionary of Holland Occupational Codes
In the development of the Dictionary of Holland Occupational Codes (DHOC,
Gottfredson & Holland, 1996), Holland and his colleagues rationally derived three-letter
summary codes for occupations primarily by examining job analysis data gathered by the United
States Department of Labor Employment and Training Administration (1972, 1974, 1977). A
classification algorithm was developed and validated and since has been used to generate
Holland codes for many federal classification systems including the Dictionary of Occupational
Titles (DOT; United States Department of Labor, 1991), the Occupational Outlook Handbook
Is Congruence Dead? 28
(OOH; Bureau of Labor Statistics, 1996), the Standard Occupational Classification manual
(SOC; Office of Federal Statistical Policy and Standards, 1980), and the Guide for Occupational
Exploration (GOE; Harrington & O’Shea, 1984; United States Department of Labor, 1979).
The Occupations Finder
The Occupations Finder (OF, Holland, 1994) exists today as an abridged version of the
DHOC. It lists selected occupational titles along with their corresponding Holland summary
codes. The OF most frequently is seen as a career counseling companion tool that is sold with
SDS product assessment packages.
The Environmental Assessment Technique
The Environmental Assessment Technique (EAT; Astin, 1963; Astin & Holland, 1961)
first was developed as a method for conducting research on the impact of college environments
on students. Major areas of study at 411 colleges and universities were examined, and each field
was assigned a primary Holland type that best matched its academic requirements. It was
assumed that students selected majors that matched their own primary Holland type. The Holland
type of the institutions thus was classified according to the proportion of students in each major.
Holland (1997) discusses the current application of the EAT as a very similar process of taking a
census of the primary types that exist in a particular environment.
The Position Classification Inventory
The use of the Position Classification Inventory (PCI; Gottfredson & Holland, 1991) for
the assessment of work environments is analogous to the use of the SDS for the assessment of
vocational personality. The PCI is a subjective job analysis inventory that tabulates raw scores to
yield a three-letter Holland code. The inventory consists of a total of 84 items that evaluate the
six Holland types as they apply to the work environment. The items are arranged into seven
Is Congruence Dead? 29
questions, each with 12 occupational aspects that evaluate the position. The questions are
presented according to (1) position requirements, (2) skills and abilities used in the position, (3)
outlook/perspective demand of the position, (4) personal style/values expressed in the position,
(5) personal characteristics required in the position, (6) abilities/skills/talents needed in the
position, and (7) frequency of certain activities in the position. Items are answered based on
whether the respondent thinks the item “Often”, “Sometimes”, or “Seldom/Never” describes the
position being evaluated.
The Occupational Information Network
The Occupational Information Network (O*NET, National O*NET Consortium, n.d.) is
an interactive World Wide Web database application that is a resource for information on a
variety of occupations. The O*NET replaces the DOT and all other federal occupational
classification systems. Occupational Interest Profiles (OIPs) were established for the occupations
in the database through the use of expert ratings of three trained judges (Rounds, Smith, Hubert,
Lewis, & Rivkin, 1999). Each OIP consists of six standard scores that correspond to the RIASEC
types. A proportion cut-off score method was applied in order to create a “reasonable
distribution” of one-, two-, and three-letter Holland summary codes. The O*NET taxonomy was
updated in 2000 in order to be compatible with the Standard Occupational Classification (SOC)
system (Levine, Nottingham, Paige, & Lewis, 2000) and recently was updated again in 2006
(National Center for O*NET Development, 2006). The O*NET has maintained the OIP
information throughout these database revisions.
Is Congruence Dead? 30
Work Environment: Instrument Limitations
The Dictionary of Holland Occupational Codes and The Occupations Finder
The accuracy of the classification algorithm that was used to generate the three letter
Holland codes that now make-up the DHOC and the OF has been questioned. There is evidence
to suggest that the algorithm may lead to arbitrary code assignments (Rounds, et al, 1999).
Gottfredson and Holland (1996) acknowledge that the information used to create the codes now
is dated, sometimes was unreliable, and was incomplete for some occupations. The algorithm
was not validated for second-letter and third–letter agreement, and additional data suggest that
even first-letter assignments may be inaccurate. Using a sample of 289 occupations, Gottfredson
and Holland conducted a “quality control check” by comparing first-letter code agreement based
on their own judgment and based on the algorithm. They found overall hit rate of 77.4%. If one
applied Meehl and Rosen’s (1955) argument of antecedent probability and arbitrarily assigned all
occupational titles as Realistic, one would have been correct 82% of the time. This is a 4.6%
improvement over the cross-validation rate that actually was observed.
The Environmental Assessment Technique
A cursory review of the literature indicates that the EAT has been the subject of little
research outside of Holland’s own work with college environments. A PsycINFO search using
Environmental Assessment Technique as a keyword resulted in merely 14 hits. Among these,
only two studies assessed the work environment and also were authored by someone other than
Holland himself (Jaskolski, 1997; Wigington & Apostal, 1973). Moreover, the EAT is not an
actual measurement, but a concept that relies on Holland’s second primary assumption. The
implementation of the EAT actually requires the use of a vocational personality measurement in
order to take a census of the Holland types in a given work environment. The use of the EAT
Is Congruence Dead? 31
therefore can be only as valid as the vocational personality instrument used, and the limitations
associated with the most popular methods such as the SDS and the VPI already have been
reviewed. Finally, as the EAT originally was developed as an assessment technique for an entire
environment, the use of the EAT in congruence research seems to be theoretically incompatible
with Holland’s intent to more narrowly focus on the level of the occupation or occupational
group.
The Position Classification Inventory
As the use of the PCI is analogous to the use of the SDS, the PCI incurs construct validity
and scoring limitations similar to the ones previously identified with the SDS. The PCI asks
respondents to report on work aspects that includes skills and abilities. Summary codes derived
from the PCI therefore are not a pure reflection of the vocational interests associated with the
environment that is being measured. With no formally established methods for handling tied raw
scores, the kinds of SDS scoring limitations that were illustrated in Table 1 and Table 2 are
similarly characteristic of the PCI. Spokane, et al. (2002) additionally point out that users of the
PCI should remain aware that this method for classifying work environments relies on subjective
judgment of a particular position rather than on a broader, objective analysis of an occupation or
occupational group.
The Occupational Information Network
A comparison of the O*NET-SOC 2000 database to the O*NET-SOC 2006 database
indicates that changes were made to the manner in which Holland summary codes are reported.
In some instances, codes were extended, shortened, or reordered. An inquiry via electronic mail
with the National Center for O*NET Development customer service department resulted in an
explanation that code lengths were modified to include Holland types that have an OIP standard
Is Congruence Dead? 32
score of at least 50. Codes were reordered to reflect the alphabetical ordering of types with tied
OIP scores (personal communication, January 31, 2007). An inspection of the O*NET-SOC
2006 database resulted in the identification of cases where these updated decision rules were
inconsistently applied. Moreover, as the O*NET is scheduled for major updates twice annually
(Data Publication Schedule, n.d.), it is apparent that it was developed to be a continuously
reviewed interactive internet application rather than as a stable research tool.
Compatibility of Holland Code Classification Systems
There generally exists the assumption that Holland work environment classification
systems should agree. As these methods theoretically generate the same work environment data,
one might rely on the concept of convergent validity (Campbell & Fiske, 1959) and simply
assume that these systems indeed are compatible (Eggerth, et. al, 2005). Research suggests that
this is far from the case. Eggerth, et al. investigated DHOC, SII, and O*NET agreement rates by
comparing the same or very similar occupational titles. Three-way first-letter agreement was
60.21%. Three-way first- and second-letter agreement dropped to 15.71%. The first, second- and
third-letter percentage agreement rate among all three of the taxonomies was found to be only
2.62%. In a study with similar results, Lent and Lopez (1996) used both the DHOC and the EAT
to generate work environment Holland codes for two different samples. The correlational data
indicated that congruence levels were the lowest when the same congruence index was used
between the DHOC and the EAT.
Work Environment: Instrument Alternatives
Strong Interest Inventory General Occupational Theme Codes
Dik, et al. (2007) used the O*NET, the DHOC, and the GOTS of the SII to generate three
sets of Holland work environment codes. Pairwise comparisons indicated that the mean
Is Congruence Dead? 33
congruence values associated with the GOTs were higher that those of both the O*NET and the
DHOC. The authors conclude that the GOT codes should serve as the “codes of choice” when
assigning work environment codes in congruence research. A perusal of the Strong Interest
Inventory manual (Donnay, et al., 2005; pp. 114-120) demonstrates that the GOT codes are
developed with a methodology that reflects the basic tenets of Holland’s theory of working
adults, is an empirically-derived and standardized application of the RIASEC scheme, and limits
potential error.
MEASUREMENT OF CONGRUENCE
Secondary Assumptions of Holland’s Theory
The Hexagonal Model of RIASEC Types
The psychological similarities and differences among the RIASEC types can be
represented graphically by an equilateral hexagon that plots the six types in a clockwise circular
order (see Figure 1). The hexagonal model is essential in understanding the congruence
construct.
Each of the six types appears at one point on the perimeter of the hexagon in a manner
that is intended to reflect a predictable ordering of the types and the magnitude of the
relationships among them. The hexagonal distances among the types are inversely proportional
to the theorized relationships between them. The types that appear closest together in the
hexagon are considered to be psychologically related, and types that are further removed from
one another are considered to be psychologically different (Tracey & Rounds, 1996, 1997).
Is Congruence Dead? 34
Figure 1
Hexagonal Model of Holland Types
Holland’s hexagon has been discussed in the literature as a model that meets the
assumptions of a circumplex (Arnold, 2004; Rounds, Tracey, & Hubert, 1992; Tinsley, 2000).
Guttman (1954) defines a circumplex as a circular order of components where adjacent
components around the circle are equally correlated, alternate components are equally correlated,
and opposite components are equally correlated. Correlations between the adjacent components
are greater than the correlations between the alternate components, and the correlations between
alternate components are greater than correlations between opposite components. In Holland’s
model of RIASEC types as it applies to the definition of a circumplex, equal segments lie
adjacent on the hexagon (e.g., R-I), alternate segments are separated by an intermediate type
(e.g., R-A), and opposite segments are separated by two intervening types (e.g., R-S). Table 3
illustrates all segments of the hexagon as they are considered respectively to be equal, alternate,
and opposite.
Is Congruence Dead? 35
Table 3
Equal, Alternate, and Opposite Segments of Holland’s Hexagonal Model
Equal Segments R-I, R-C, I-R, I-A, A-I, A-S, S-A, S-E, E-S, E-C, C-E, C-R
Alternate Segments R-A, R-E, I-S, IC, A-R, A-E, S-I. S-C, E-A, E-R, C-S, C-I
Opposite Segments R-S, I-E, A-C, S-R, E-I, C-A
If the model were plotted to scale and drawn to reflect the empirically-derived
correlations among the types, the figure would resemble a misshapen polygon rather than an
equilateral hexagon. Most vocational psychologists within the field agree that evidence supports
the roughly hexagonal circumplex arrangement of Holland’s RIASEC types (Bobele, Alston,
Wakefield, & Schnitzen, 1975; Borgen & Donnay, 1996; Cole, Whitney, & Holland, 1971;
Dawis, 1992; Edwards & Whitney, 1972; Holland, Whitney, Cole, & Richards, 1969; Khan,
Alvi, & Kirkwood, 1990; Prediger, 1982, Rounds, 1995; Spokane & Cruza-Guet, 2005; Toenjes
and Borgen, (1974; Wakefield & Doughtie, 1973). The hexagon generally is accepted as an
adequate “approximation of reality” (Prediger, 2000) and as close enough to lend strength to the
veracity of Holland’s congruence concept.
Consistency
Holland uses the term consistency to refer to the fact that there are differing degrees of
relatedness among the RIASEC types. Consistency is determined according to the properties of
the circumplex model. RIASEC types that are identical (e.g., I-I) of course represent maximum
consistency. Adjacent types on the perimeter of the hexagon (e.g., I-A) reflect the next highest
level of consistency. Alternate types on the perimeter of the hexagon (e.g., I-S) represent
moderate consistency. Types that lie opposite each other on the hexagon (e.g., I-E) are
Is Congruence Dead? 36
considered to reflect the lowest degree of consistency among the six types (i.e., inconsistency).
Table 4, which is directly comparable to Table 3, illustrates the segments of the hexagon
according to their level of consistency.
Table 4
Holland’s Hexagonal Model According to Levels of Consistency
Most Consistent (Identical) R-R I-I, A-A, S-S, E-E, C-C
Consistent (Equal/Adjacent) R-I, R-C, I-R, I-A, A-I, A-S, S-A, S-E, E-S,
E-C, C-E, C-R
Moderately Consistent (Alternate) R-A, R-E, I-S, IC, A-R, A-E, S-I. S-C, E-A,
E-R, C-S, C-I
Inconsistent (Opposite) R-S, I-E, A-C, S-R, E-I, C-A
Measurement of Congruence: Congruence Indexes
The earliest studies of congruence involved simply determining whether the individual’s
primary type matched the work environment’s primary type (Holland, 1963). This first-letter
agreement index takes a dichotomous approach in the assessment of congruence, assuming that
congruence either is or is not present. The contemporary research paradigm places congruence
on a continuum, measuring the degree of fit between vocational personality and work
environment.
Quite a few mathematical indexes have been developed for the purpose of measuring
congruence (e.g., Brown & Gore, 1994; Gati, 1985; Grotevant, Cooper, & Kramer, 1986; Healy
& Mourton, 1983; Holland, 1973; Iachan 1984, 1990; Kwak & Pulvino, 1982; Moody, 1983,
Robbins, Thomas, Harvey, & Kandefer, 1978; Swaney & Prediger, 1985; Wiggins & Moody,
Is Congruence Dead? 37
1981; Wolfe & Betz, 1981; Zener & Schnuelle, 1972). Six of these indexes have been selected
for discussion here as they appear to be the ones most well-known and most often used in
congruence research: (1) the First Letter Hexagonal Distance index (Holland), (2) the
Compatibility index (Wiggins & Moody), (3) the K-P index (Kwak & Pulvino), (4) the M index
(Iachan), (5) the Sb Index (Gati), and (6) the C index (Brown & Gore).
First Letter Hexagonal Distance Index
The First Letter Hexagonal Distance (FLHD; Holland, 1973) index uses the hexagonal
model and degrees of consistency (see Table 4) to determine congruence values. There are a total
of four possible levels of congruence. The highest level of congruence signifies that the primary
vocational personality type exactly matches the primary work environment type (e.g., C – C).
The second highest level of congruence is represented when the primary vocational personality
type and the primary work environment type are adjacent (e.g., S – E). A third, and lesser, level
of congruence occurs when the primary vocational personality type appears alternate on the
hexagon to the primary work environment type (e.g., R – A). The primary vocational personality
type is considered to be incongruent with the primary work environment type when the types lie
opposite each other on the hexagon (e.g., I – E). The FLHD index commonly is operationalized
on an integer scale ranging from 1 to 4, where higher values designate a greater degree of
congruence.
Compatibility Index
The Compatibility Index (CI; Wiggins & Moody, 1981; Moody, 1983) initially was
developed by Wiggins and Weslander (1979) as an expansion of the Z-S index (Zener &
Schnuelle, 1972) and was intended as a measure of compatibility between married couples.
Wiggins and Moody (1981) then broadened the use of the CI to vocational purposes. In
Is Congruence Dead? 38
congruence research, a CI score is derived by assessing the degree of fit between any two three-
letter Holland codes using a 9-point scale that is weighted according to the relative positioning of
the types. Decision rules are used to assign congruence values that range from 0 to 8, where
higher scores are associated with greater congruence (see Appendix A).
K-P Index
Kwak and Pulvino (1982) developed the K-P index for the assessment of congruence
across all three letters of Holland summary codes. The formula for the index reflects the relative
importance of type positioning, using rationally-derived weights of 4, 2, and 1, respectively. The
first-letter position is calculated as twice as important as the second-letter position, which is
calculated as twice as important as the third-letter position. The K-P index also incorporates the
circumplex assumption in its formula through the use of empirically-determined, hexagonal
segment distance proportion values that originally were derived by Holland, et al. (1969). K-P
index congruence scores range from 0 to 1, where values closer to 1 represent greater congruence
(see Appendix B).
M Index
The K-P index prompted Iachan (1984, 1990) to create the M index as a method that
could be used for a wider range of purposes. The M index can derive congruence values between
two two-letter summary codes or between two three-letter summary codes. Congruence scores
are calculated by summing rationally-derived weights of pairs of matching types within two
Holland codes. Numerical weights are assigned based on the importance of the relative
positioning of pairs of matched types. For example, a match between types in the first-letter
position is considered to be more important (i.e., more congruent) than a match between types in
the first-letter and third-letter positions. Three-letter code comparison congruence scores range
Is Congruence Dead? 39
from 0 to 28, and two-letter code comparison congruence scores range from 0 to 6, where higher
values represent greater congruence (see Appendix C).
Sb Index
The Sb index (Gati, 1985) incorporates the use of a 0 – 1 vector approach and subjective
judgment in order to address potential problems related to tied profile scores and qualitative
issues among profiles (e.g., spiked scores, flat profiles). The index takes into account the relative
number of and distances between types that are both common and unique to each code. The
index assumes certain distance values ranging between 1 and 3 based on the principles of
consistency. These values reflect that more proximal types are associated with lower values. The
Sb index incorporates these distances in order to assign higher values to pairs of codes that have
relatively more shared types and relatively fewer unshared types, or fewer unshared types that
are relatively distant. Scores can range from 0 to 5, where higher values represent greater
congruence (see Appendix D).
C Index
Brown and Gore (1994) assessed the strengths and limitations of 9 well-known
congruence indexes (i.e., Gati, 1985; Healy & Mourton, 1983; Holland, 1963; Iachan, 1984;
Kwak & Pulvino, 1982; Robbins, et al., 1978; Wiggins & Moody, 1981; Wolfe & Betz, 1981;
Zener & Schnuelle, 1972). Only the K – P index was determined to be a congruence index that
both incorporates the circumplex assumption and is sensitive enough to discriminate between
identical but out-of-order codes. The shape of the K – P score distributions was found to be
positively skewed, and the index was noted as being difficult to calculate, however. Brown and
Gore developed the C index to retain the advantages of the K-P index as well as to symmetrically
distribute scores and to simplify computation.
Is Congruence Dead? 40
The formula for the C index uses the weights 3, 2, and 1 to calculate the first-letter
position as 1.5 times as important as the second-letter position, which is calculated as twice as
important as the third-letter position. A congruence value is obtained by multiplying the weights
by rationally-derived hexagonal distances between sequential pairs of types. Identical matches
are assigned a distance value equal to 3. Adjacent segments are assigned a distance value equal
to 2, alternate segments are assigned a distance value equal to 1, and opposite segments are
assigned a distance value of 0. The values then are summed. C index scores can range from 0 to
18, where a higher value represents a greater level of congruence (see Appendix E).
Measurement of Congruence: Congruence Index Limitations
A review of congruence indexes illustrates that these measures have been developed with
increasing mathematical precision. Despite this, the computation of congruence remains an area
of great concern. Research illustrates the index considered to be the best measure of the construct
remains debatable (Miller, 1992; Osipow, 1987; Osipow & Fitzgerald, 1996; Rounds, et al.,
2000). Camp and Chartrand (1992) evaluated 13 congruence indexes and conclude that none of
them is “completely satisfactory.” In a similar study, Young, Tokar, and Subich (1998) found no
significant relationships among the possible combinations of 11 congruence indexes and two job
satisfaction measures. While Assouline and Meir (1987) and Meir (1995) indicate that
congruence correlations are higher when more complex congruence indexes are used, Tsabari, et
al. (2005) showed that more sophisticated indexes were associated with weaker mean
correlations. These seemingly ambiguous findings become clearer when it is considered that all
of the most well-known congruence indexes fail to incorporate the circumplex assumption and/or
are limited to the use of three-letter Holland summary codes.
Is Congruence Dead? 41
Failure to Incorporate the Circumplex Assumption
It has been noted frequently that the indexes considered to best operationalize congruence
are the ones that integrate the circumplex assumption. Camp and Chartrand (1992) assert that
congruence indexes that do not include the circumplex assumption should not be used in
Holland-type congruence studies. Tracey and Rounds (1992) similarly state that important
information inherent in Holland’s theory is lost when congruence indexes ignore hexagonal
properties. Moreover, Gati (1989) indicates congruence studies that do not take into account the
circumplex assumption may blur meaningful correlations.
Limitation to Three-Letter Holland Summary Codes
Congruence indexes that incorporate three-letter codes in their calculations cannot be
used in research with methods such as the SII and the O*NET make use of summary codes that
vary in length. Moreover, congruence indexes that include three-letter codes force the use of
measures such as the SDS, the VPI, the DHOC, the OF, and the PCI. Given the concerns
associated with these measures that already have been discussed, congruence indexes that use
three-letter codes necessarily limit and potentially may compromise valid research from the very
beginning of the process.
Measurement of Congruence: Index Alternatives
The Modified C Index
Despite the fact that Brown and Gore’s C index is limited to the use of three-letter
Holland codes, it has been the congruence index that most often is recommended for use in
research (Holland, 1997; Tinsley, 2000). Eggerth, et al. (2005) note work needs to be done to
design a congruence index that both reflects the mathematical precision of the C index and has
Is Congruence Dead? 42
the ability to compare Holland codes of differing lengths. In response to this, Eggerth and
Andrew (2006) developed the modified C index.
The modified C index is based on the same rationally derived weights, hexagonal
distance values, and scoring range that are used by the C index. It assumes that codes of unequal
lengths are, in fact, equivalent in their quantity of descriptive information. Relatively shorter
codes merely reflect a greater “concentration” of information where the types that are included in
the code hold the information of the “missing” types. Eggerth and Andrew (2006) provide
equations for six possible combinations of code comparisons: (1) three letters x three letters, (2)
two letters x two letters, (3) one letter x one letter, (4) three letters x one letter, (5) two letters x
one letter, and (6) three letters x two letters (see Appendix F).
Support for the Modified C Index
Preliminary research on the modified C index supports the efficacy of its use. Dik and
Hansen (2004) compared mean congruence scores using both the C index and the modified C
index. Statistical analyses suggested that the modified C index was associated with slightly, yet
significantly, higher mean congruence scores. Dik and Hansen also examined the performance of
the modified C index, the C index, and the K-P index by comparing correlations between
congruence and overall job satisfaction and between congruence and intrinsic job satisfaction.
The correlation between congruence and overall job satisfaction statistically was highest when
measured by the modified C index. The correlation between congruence and intrinsic job
satisfaction also was highest in favor of the modified C index, but those results did not reach
statistical significance. Dik and Hansen conclude that the modified C index should serve as the
“congruence index of choice” when conducting research on Holland’s theory.
Is Congruence Dead? 43
The Substitution C Index
Despite the theoretical and empirical support the modified C index has received, Gore
and Brown (2006) do not endorse its use, indicating that the modified C index is unnecessarily
computationally complex. Gore and Brown suggest a different index that is easier to calculate
while remaining logically sound. This alternative extends shorter codes to the three-letter length
by using the type in the first-letter position as a substitute for any “missing” types in the code.
The C index (Brown & Gore, 1994) formula then can be applied to compute congruence scores
to cases that are commensurate with those of Eggerth and Andrew (2006) (see Appendix G).
Support for the Substitution C Index
Gore and Brown (2006) compare scores derived by the modified C index and by the
substitution C index to show that the two congruence indexes yield very similar, and in some
cases identical, congruence values. Eggerth (2006) responds to this by pointing out that the
substitution C index assigns exaggerated influence to the first-letter position and is not consistent
with what Brown and Gore (1994) originally proposed. Eggerth moreover indicates that the
modified C index takes into account the contribution of types in the second-letter position,
asserting that the modified C index thus is more logically consistent with the C index. Eggerth
concludes by indicating “ultimately the question of whether the greater mathematical rigor of
Eggerth and Andrew will outweigh the computational ease of Gore and Brown is one that must
be answered empirically” (p. 290). This research therefore uses both the modified C index and
the substitution C index to generate congruence scores.
JOB SATISFACTION
It has been noted extensively that job satisfaction is a complex construct that evades
definition as a singular term (Herr, Cramer, & Niles, 2004; Herzberg, Mausner, Peterson, &
Is Congruence Dead? 44
Capwell, 1957; Locke, 1969; Strong, 1958; Wanous & Lawler, 1972; Warr, 1991). There does
seem to be general agreement, though, that job satisfaction is an affective state that results from
an individual’s overall assessment of job experiences (Dawis, 1984; Fritzsche & Parrish, 2005;
Kalleberg, 1977; Locke, 1983). Given that the construct of job satisfaction is quite broad, many
methods have been developed for its measurement. The five most frequently used techniques
will be detailed here: (1) the Hoppock Job Satisfaction Blank, (2) the Job Descriptive Index and
the Job in General scale, (3) the Minnesota Satisfaction Questionnaire, (4) one-item measures of
overall job satisfaction, and (5) measures developed by the research authors.
Job Satisfaction: Instruments
The Hoppock Job Satisfaction Blank
The Hoppock Job Satisfaction Blank (HJSB; Hoppock, 1935) is a global (i.e., overall)
measure of job satisfaction that determine an individual’s likes and dislikes for a job. Four
questions assess (1) how much an individual likes the job, (2) how much of the time the
individual feels satisfied with the job, (3) how the individual feels about changing jobs, and (4)
how the individual compares self to others regarding liking or disliking the job. Each item is
scored according to a 7-point Likert-type scale (e.g., I hate it – I love it, All of the time – Never).
The HJSB yields total scores that range between 4 and 28 where higher scores indicate a greater
feeling of job satisfaction.
The Job Descriptive Index and the Job in General Scale
The Job Descriptive Index originally was developed by Smith, et al., (1969). The JDI was
revised in 1990 and again in 1997 (Baltzer, et al., 1997; Baltzer & Smith, 1990). The current
version of the instrument provides measures of satisfaction on five scales: (1) Work on Present
Job, (2) Present Pay, (3) Opportunities for Promotion, (4) Supervision, and (5) Co-Workers.
Is Congruence Dead? 45
Instrument items consist of a list of adjectives or short phrases pertaining to the various scales.
Respondents indicate whether the adjective or phrase describes their job and are provided with
the response choices Y (i.e., yes), ? (i.e., undecided), and N (i.e., no). Positive items are scored as
3, 1, and 0, respectively, and negative items are scored as 0, 1, and 3, respectively. In 1989,
Ironson, et al. developed the Job in General scale to supplement the JDI scales. The JIG scale is a
measure of overall job satisfaction and is included in the 1997 revision of the JDI (Baltzer, et al.,
1997). JIG items and scoring procedures are similar to the JDI, yielding total scores that range
between 0 and 54 where higher scores indicate a greater feeling of job satisfaction.
The Minnesota Satisfaction Questionnaire
The Minnesota Satisfaction Questionnaire (MSQ; Weiss, et al. 1967) measures the degree
to which an individual perceives that a job satisfies vocational needs and values. Both a long-
form MSQ and a short-form MSQ are available. The long-form consists of 120 items that
measure job satisfaction according to a 20-item general job satisfaction scale and 20 scales each
containing five items. The more popular short-form MSQ is composed of 20 items that are taken
from the long-form. Each item is scored according to a 5-point Likert-type scale where response
choices are Very Dissatisfied (i.e., 1), Dissatisfied (i.e., 2), Neither (i.e., 3), Satisfied (i.e., 4), and
Very Satisfied (i.e., 5). The short-form MSQ yields a general job satisfaction score that ranges
between 20 and 100 where higher scores indicate a greater feeling of job satisfaction. The short-
form additionally breaks down into an intrinsic job satisfaction scale, where scores range
between 12 and 60, and an extrinsic job satisfaction scale, where scores range between 6 and 30.
One-Item Measures of Overall Job Satisfaction
The use of one-item overall job satisfaction measures is popular in congruence – job
satisfaction research. These items typically are assessed on a Likert-type scale and include
Is Congruence Dead? 46
questions such as “How satisfied are you with your vocational choice?” (Aranya, et al., 1981),
“I am very satisfied with my current job.” (Heesacker, Elliott, & Howe, 1988), “To what extent
are you satisfied with your crew your place of work / educational institution / residential unit?”
(Meir, et al., 1986; Meir, Hadas, & Noyfeld, 1997).
Measures Developed by the Research Authors
Measures developed for specific congruence – job satisfaction studies are as varied as the
researchers who have designed them. LaBarbera (2005), for example, developed a 14-item
survey for a sample of Physician Assistants to evaluate factors such as demographics and
attitudes towards overall career as well as specialty choice. Meir and colleagues developed a 20-
item survey that has been used and modified in a series of studies that examine different
occupational samples. This instrument also assesses both occupational and job-specific
satisfaction (Meir & Green-Eppel, 1999; Meir & Navon, 1992; Meir & Segal-Halevi, 2001;
Meir, Tziner, & Glazner, 1997; Meir & Yaari, 1988).
Measurement of Job Satisfaction: Instrument Limitations
Measures of Unknown Reliability and Validity
Hulin and Judge (2003) and Betz and Fitzgerald (1987) point out that much of the
congruence - job satisfaction research has been based on “homegrown” and “homemade”
measures of satisfaction. Locke (1983) similarly indicates that it is common for congruence
research to use arbitrarily chosen operational definitions of job satisfaction where the definition
of satisfaction is not part of a predetermined methodology, but instead is defined by the measure
that happens to be used. Specific congruence research examples that reflect this include Swaney
and Prediger (1985), who discuss that a reliability estimate was not available for their job
Is Congruence Dead? 47
satisfaction measure, and Heesacker, et al. (1988), who state that reliability and validity data for
their job satisfaction instrument was not available.
One-Item Measures
Betz and Fitzgerald (1987) assert that the common use of one-item measures of job
satisfaction is an “unfortunate practice”. Single-item measures have been shown to be associated
with low reliability and restricted research findings (Quinn, Staines, & McCullough, 1974;
Rounds, et al., 2000). Much congruence – job satisfaction studies that use one-item measures of
job satisfaction cite the meta-analysis conducted by Wanous, Reichers, and Hudy (1997) where
single-item measures were found to be valid. Wanous, et al. also point out that there are good
reasons to prefer job satisfaction scales to single items.
Measurement of Overall Job Satisfaction
The use of global measures is perhaps the largest criticism of job satisfaction in
congruence research. It has been noted widely that job satisfaction is a broad construct with
various components. It is best assessed with a multifaceted approach as overall satisfaction
measures confound the contributions of particular job satisfaction features (Dawis, 1984, 1991;
Edwards, 1991; Hansen, 2005; Kahn; 1972). Moreover, even though the division of job
satisfaction into intrinsic and extrinsic components is well-supported by research and leads to
more precise congruence information, it is infrequently found in the research (Betz, et al.; 1989;
Elton & Smart, 1988).
Measurement of Job Satisfaction: Instrument Alternative
Short-Form Minnesota Satisfaction Questionnaire
The short-form MSQ (Weiss, et al. 1967) has been extensively researched and is
recognized for its internal consistency and construct validity (Hulin & Judge, 2003; Prediger,
Is Congruence Dead? 48
2000). Morris (2003) conducted a meta-analysis of studies evaluating the congruence – job
satisfaction relationship and found the mean effect size was larger among studies where the MSQ
was used to measure job satisfaction. Factor analysis additionally supports the division of the
MSQ into its intrinsic and extrinsic scales (Weiss, et al. 1967). This research therefore uses the
short-form MSQ to measure the intrinsic, extrinsic, and overall components of job satisfaction.
SUMMARY OF CHAPTER TWO
Chapter Two detailed the methodological limitations characteristic of congruence – job
satisfaction correlation research and discussed appropriate measurement alternatives. The
rationale for the comparison of two Holland summary coding methods and two congruence
indexes and the investigation of three aspects of job satisfaction was presented.
The six vocational personality types were outlined. The Self-Directed Search, the
Vocational Preference Inventory, and the Strong Interest Inventory were discussed as the major
vocational personality assessments that were used in congruence research. Construct validity,
traditionally-derived scoring issues, and practical concerns were described. The Strong Interest
Explorer was presented as the measurement option used in this research. Research on guidelines
for developing decision-derived Holland summary codes was described. It was identified that the
research compares traditionally-derived codes with decision-derived codes that are generated
with a cut standard score method.
The six work environments were described. The Dictionary of Holland Occupational
Codes, the Occupations Finder, the Environmental Assessment Technique, the Position
Classification Inventory, and the Occupational Information Network were discussed as popular
work environment assessment methods. Conceptual and practical problems and a misassumption
regarding the interchangeability of these measures were presented. The SII General Occupational
Is Congruence Dead? 49
Theme (GOT) codes were identified as the work environment assessment approach that was used
in this research.
Holland’s circumplex model and consistency secondary theoretical assumptions were
explained. The First Letter Hexagonal Distance index, the Compatibility index, the K-P index,
the M index, the Sb Index, and the C index were identified as well-known congruence indexes.
The methodological weaknesses of these indexes were discussed. The modified C index and the
substitution C index were identified and presented as alternative congruence measures that are
compared in this research.
Job satisfaction was identified as an affective state that results from the overall
assessment of job experiences. The Hoppock Job Satisfaction Blank, the Job Descriptive Index
and the Job in General scale, the Minnesota Satisfaction Questionnaire, one-item measures of
overall job satisfaction, and measures developed by the research authors were discussed as
frequently used job satisfaction assessment techniques. Validity and reliability issues associated
with these methods were described. It was explained that this research uses the short-form
Minnesota Satisfaction Questionnaire to measure intrinsic, extrinsic, and overall job satisfaction.
Is Congruence Dead? 50
CHAPTER THREE: METHODOLOGY
INTRODUCTION TO CHAPTER THREE
Chapter Three presents the methodological components that were used to implement this
study. General research sample characteristics first are explained. The instruments used in this
research then are described. Details of participant recruitment and data gathering are discussed.
Methods of data evaluation and the statistical analysis of data are reviewed.
GENERAL SAMPLE CHARACTERISTICS
A total of twelve occupational groups, 2 per primary Holland type, were pre-selected for
examination in this study according to the Strong Interest Inventory General Occupational
Theme codes (Donnay, et al., 2005; Harmon, Hansen, Borgen, & Hammer, 1994). The groups
were selected in a manner that served not only as the measure of work environment, but also as
an accounting for the fact that GOT codes are gender-normed. The standardized scores that were
generated with the SIE data are based on a mixed-gender sample. The 12 occupational groups
therefore were chosen in order to reflect pairs of corresponding male and female GOT codes that
are as equal as practically possible. The five steps taken to select the groups are detailed in
Appendix H. A listing of the occupational groups examined in this study is presented in Table 5.
MEASURES
Strong Interest Explorer
The Strong Interest Explorer (SIE; Chartrand, 2001) is made-up of a total of 140 items.
Sixty items were drawn from the 1994 SII (Harmon, et al., 1994), 33 items were generated from
the 2002 research on the SII, 35 items were written specifically for the SIE by the CPP research
staff, and 12 items were modified from either 1994 SII items or 2002 SII research items
(Research Department, 2002).
Is Congruence Dead? 51
Table 5
Occupational Groups Included in the Research Sample
Holland Type
SII Occupational Group GOT Code
Realistic
Forester
Engineer
RI (female) RI (male)
RI (female) RI (male)
Investigative
Medical Technologist
Psychologist
IRC (female) IRC (male)
IA (female) IA (male)
Artistic
Attorney
Librarian
A (female) A (male)
A (female) A (male)
Social
Licensed Practical Nurse
Social Worker
SCE (female) SCE (male)
SA (female) SA (male)
Enterprising
Florist
Real Estate Agents
EAC (female) EAC (male)
E (female) E (male)
Conventional
Accountant
Banker
CE (female) CE (male)
CE (female) CE (male)
Is Congruence Dead? 52
Items include job titles, occupationally- related activities, and school subjects that are endorsed
based on whether the respondent “likes an item” (see Appendix I). The selected items are
summed and yield raw scores for 14 basic interest areas each containing 10 items. The areas are
commensurate with the RIASEC typology so that raw scores then can be combined to generate a
Holland summary code (see Appendix J).
The SIE was administered to samples of college students, high school students, and
employed adults in order to establish initial reliability and validity estimates. In most cases, all
basic interest scales across the three groups had internal consistency alpha levels of at least .80.
Validity was evaluated with the employed adults only. Members of this group were administered
a supplemental, self-expressed interests questionnaire in addition to the SIE. Results indicated a
significant and positive mean correlation of .55 between self-expressed interests and the SIE
scales. More detailed information regarding SIE reliability and validity can be found in Research
Department (2002).
The Short-Form Minnesota Satisfaction Questionnaire
The 20 Likert-type items of the short-form MSQ (Weiss, et al., 1967) represent the ones
that have been found to be the most highly correlated with their respective long-form scales. The
instrument additionally includes short-answer type demographic questions (see Appendix K).
Norms for the short-form MSQ were developed with data from 7 occupational samples of
varying sizes. Median reliability coefficients obtained for the three scales across all occupational
samples were .90 for General Satisfaction (range .87 to .92), .86 for Intrinsic Satisfaction (range
.84 to .91), and .80 for Extrinsic Satisfaction (range .77 to .82). Additional information regarding
short-form MSQ reliability and validity can be found in Lofquist and Dawis (1969) and in Weiss,
Dawis, England, and Lofquist (1966).
Is Congruence Dead? 53
PARTICIPANT RECRUITMENT
The participants for this study were recruited largely through their association with
commensurate professional organizations and convenience sampling methods (see Appendix L).
Membership lists that were posted on the internet and considered to be public information were
identified. Individuals on these lists were contacted based on a random number generator
approach. Among the businesses that were identified, all employees were invited to participate in
this study. Potential participants were mailed packets containing an introductory cover letter
reflecting research interest in their particular occupational group (see Appendix M), two copies
of the Consent for Participation in a Study of Work Interests and Job Satisfaction form (see
Appendix N), a short-form MSQ, a copy of the SIE, and a self-addressed, stamped return
envelope. Most participants who did not return their packets were mailed at least two follow-up,
reminder letters at two to three week intervals (see Appendix O).
The professional organization lists and businesses were sampled and data packets were
mailed to potential participants until usable data from at least 15 participants per occupational
group, 30 participants per RIASEC primary type, were received. Research information was
received from all 48 continuous states except South Dakota. The overall response rate for valid
data received was approximately 25.80%, with the percentage per occupational group ranging
between 18.75% (Accountants, Bankers) and 36.67% (Medical Technologists) (see Table 6).
Complete data were analyzed for a total of 180 participants. If the usable data per occupational
group exceeded 15 subjects, “extra” cases were eliminated from analysis in a manner that
minimized occurrence of missing data.
Is Congruence Dead? 54
Table 6
Occupational Group Usable Date Response Rates
Occupational Group Response Rate
Accountant 18.75%
Attorney 20.0%
Banker 18.75%
Engineer 26.03%
Florist 25.0%
Forester 35.71%
Librarian 32.73%
Licensed Practical Nurse 24.59%
Medical Technologist 36.67%
Psychologist 26.56%
Real Estate Agents 24.66%
Social Worker 25.42%
DATA EVALUATION
Instrument Scoring
The MSQ was hand scored according to technical manual guidelines. In order to generate
complete scale scores for the intrinsic, extrinsic, and overall job satisfaction scales, missing data
on MSQ items were assigned a score of 3 (i.e., Neither). This procedure was implemented as the
majority of missing data reflected respondents marking “NA” by the item and indicating that the
Is Congruence Dead? 55
item was not salient to them (e.g., a self-employed participant with no direct supervisor). This
method was used for a total of 43 missing values.
The SIE was hand scored according to instrument guidelines. SIE traditionally-derived
summary codes were calculated according to the Holland types that corresponded to the three
highest raw scores. A list of rules for resolving tied scores was created and followed according to
the secondary assumption of consistency (see Appendix P). Tied scores were resolved among
traditionally-derived codes in 90 cases.
In order to generate SIE decision-derived codes, it was necessary to first create
standardized scores for each Holland type using a z-score to T-score transformation method.
Standardized scores then were used to generate decision-derived codes based on Dik et al.’s
(2007) standardized cut score method anchored by a mean T-score of 60. Rules that were used
for generating decision-derived codes are presented in Appendix Q. Rules for breaking ties
among decision-derived codes were resolved according to the same consistency guidelines that
are presented in Appendix P. Tied scores were resolved among decision-derived codes in 14
cases.
Participants’ traditionally-derived codes and decision-derived codes are presented
according to primary Holland type in Table 7. Traditionally-derived codes and decision-derived
codes generated identical overall hit rates of 38.33% when the primary Holland types of the
participants’ summary codes were compared to the primary Holland types of the GOT codes.
An analysis of traditionally-derived codes by occupational group generated a range of hit
rates between 20.0% (Florist, Psychologist) and 86.67% (Social Worker). An analysis of
decision-derived codes by occupational group generated a range of hit rates between 20.0%
(Florists) and 66.67% (Social Workers) (see Table 8). An analysis of traditionally-derived codes
Is Congruence Dead? 56
by primary Holland type generated a range of hit rates between 23.33% (Enterprising) and
76.67% (Social). An analysis of decision-derived codes by primary Holland type generated a
range of hit rates between 33.33% (Enterprising) and 40.0% (Artistic, Social) (see Table 9).
Table 7
Traditionally-Derived Codes and Decision-Derived Codes According to Primary Holland Type
Traditionally-Derived
Summary Codes Decision-Derived Summary Codes
R I A S E C R I A S E C Realistic Engineer 5 4 6 5 4 1 5 Forester 8 2 2 3 6 2 1 1 5
Investigative Medical Technologist 3 5 2 4 1 3 6 3 2 1
Psychologist 2 3 1 9 1 5 3 6 Artistic
Attorney 2 4 3 6 1 5 1 8 Librarian 1 5 7 2 7 3 1 4
Social Licensed Practical Nurse 2 1 10 2 2 1 3 4 5
Social Worker 1 1 13 1 3 10 1 Enterprising
Florist 3 1 5 2 3 1 1 2 5 2 3 2 Real Estate Agent 3 2 2 4 4 3 2 1 1 7 1
Conventional Accountant 4 5 1 5 2 6 1 6
Banker 1 3 7 4 2 2 4 2 5
Bold indicates hits between summary code primary types and GOT code primary types
An examination of summary coding methods indicates that the conversion from
traditionally-derived codes to decision-derived codes resulted in some changes among the
frequencies of primary Holland types (see Table 10). There was an increase in the frequency of
Investigative, Artistic, Enterprising, and Conventional primary types ranging between 5.0%
Is Congruence Dead? 57
(Investigative) and 6.11% (Enterprising) while there was a 4.44% decrease in Realistic primary
Holland types and a 17.78% decrease in Social primary Holland types (see Table 11).
Table 8
Occupational Group Hit Rates Between Summary Code Primary Types and GOT Code Primary Types
Traditionally-Derived Summary Codes
Decision-Derived Summary Codes
Accountant 33.33% 40.0% Attorney 26.67% 33.33% Banker 26.67% 33.33% Engineer 33.33% 33.33% Florist 20.0% 20.0% Forester 53.33% 40.0% Librarian 33.33% 46.67% Licensed Practical Nurse 66.67% 26.67% Medical Technologist 33.33% 40.0% Psychologist 20.0% 33.33% Real Estate Agent 26.67% 46.67% Social Worker 86.67% 66.67%
Table 9
Holland Type Hit Rates Between Summary Code Primary Types and GOT Code Primary Types
Traditionally-Derived Summary Codes
Decision-Derived Summary Codes
Realistic 43.33% 36.67% Investigative 26.67% 36.67% Artistic 30.0% 40.0% Social 76.67% 40.0% Enterprising 23.33% 33.33% Conventional 30.0% 36.67%
Is Congruence Dead? 58
Table 10
Primary Holland Types by Coding Method
Traditionally-Derived Codes Decision-Derived Codes
Realistic n = 35 (19.44%) n = 27 (15.0%)
Investigative n = 21 (11.67%) n = 30 (16.67%)
Artistic n = 21 (11.67%) n = 31 (17.22%)
Social n = 65 (36.11%) n = 33 (18.33%)
Enterprising n = 14 (7.78%) n = 25 (13.89%)
Conventional n = 24 (13.33%) n = 34 (18.89%)
Total n = 180 (100%) n = 180 (100%)
Table 11
Primary Holland Types Changes after Conversion from Traditionally-Derived Codes to Decision-Derived Codes
Realistic 4.44%
Investigative 5.0%
Artistic 5.55%
Social 17.78%
Enterprising 6.11%
Conventional 5.56%
Is Congruence Dead? 59
Statistical Analysis of Data
Study data were evaluated according to all cases, and results additionally were analyzed
by occupational group and by primary Holland type. All data analyses were conducted according
to the descriptive and inferential statistics that were appropriate for addressing the study’s
research questions.
Demographic Analysis
An analysis of overall demographic data was performed. Gender was assessed through a
frequency count procedure. Means, standard deviations, and values ranges for the variables Age,
Years of Education, Years on Present Job, Years in Occupation, and Hours Worked per week
were calculated. An analysis for significant differences in gender among occupational groups
and primary Holland types was conducted with the Chi Square Test of Independence. An
analysis for significant differences among the other demographic variables was conducted with a
one-way Analysis of Variance (ANOVA). Tukey's HSD post hoc test was conducted when
ANOVAs indicated significant differences.
MSQ Score Analysis
MSQ mean scores were analyzed according to intrinsic, extrinsic, and overall job
satisfaction for all data, for occupational groups, and for primary Holland types. An analysis for
significant mean MSQ score differences was conducted with a one-way Analysis of Variance
(ANOVA). Tukey's HSD post hoc test was performed when ANOVAs indicated significant
differences.
Congruence Score Analysis
Congruence mean scores were analyzed according to the modified C index, the
substitution C index, traditionally-derived Holland codes, and decision-derived Holland codes
Is Congruence Dead? 60
for all data, for occupational groups, and for primary Holland types. An analysis for significant
mean congruence score differences was conducted with a one-way Analysis of Variance
(ANOVA). Tukey's HSD post hoc test was performed when ANOVAs indicated significant
differences.
General Research Question Analysis
General research questions were analyzed according to all data, for occupational groups,
and for primary Holland types. General Research Question Sets 1, 2, 3, and 4 used the one-tailed,
Pearson Product Moment Correlation statistic to assess the specified relationships between
congruence and job satisfaction. General Research Question Set 5 and General Research
Question 6 used the Fisher’s r-to-z’ Transformation to assess significant differences among the
correlations found in General Research Question Sets 1, 2, 3, and 4.
SUMMARY OF CHAPTER THREE
Chapter Three presented the methodological components that were used to implement
this study. General research sample characteristics first were explained. The instruments used in
this research then were described. Details of participant recruitment and data gathering were
discussed. Methods of data evaluation and the statistical analysis of data were reviewed.
Is Congruence Dead? 61
CHAPTER FOUR: DATA ANALYSIS
INTRODUCTION TO CHAPTER FOUR
Chapter Four presents the research data analyzed according to all cases, occupational
groups, and primary Holland types. Demographic information first is evaluated. MSQ score and
congruence score data are analyzed and discussed. An analysis of this study’s general research
questions then is presented.
DEMOGRAPHIC ANALYSIS
Demographic data were obtained via MSQ short-answer questions. This information
includes the variables Gender, Age, Years of Education, Time on Present Job, Years in
Occupation, and Hours Worked Per Week. Data are presented according to all cases (see Table
12) and are further analyzed according to occupational group (see Table 13) and primary Holland
type (see Table 14).
Demographic Analysis for All Data
Demographic categories with missing cases were calculated according to the number of
cases that were reported. Mean data for all available cases indicated that, overall, the sample was
fairly evenly divided between men and women (Females = 96, Males = 84). Participants tended
to be of middle-age (M = 50.31, SD = 11.26), but with a range in ages between 24 years and 73
years. Overall, participants were college-educated or the equivalent (M = 16.80, SD = 2.57).
Mean data indicated that participants tended to be experienced in their occupations (M = 22.56,
SD = 11.65), but the range was wide, between 1 year and 50.17 years. Data indicated that
participants tended also to be experienced in their current positions (M = 13.06, SD = 10.85), the
range here also was wide, between 1 month and 42 years. Mean data indicated that participants
Is Congruence Dead? 62
predominantly worked full-time (M = 43.51, SD = 12.79), but again the range was quite wide,
between 5 and 80 hours per week.
Table 12
Demographic Data for All Cases
Gender Age Years of Education
Years on Present Job
Years in Occupation
Hours Worked
Per Week Females 96 Males 84
M = 50.31 b
SD = 11.26 M = 16.80 SD = 2.57
M = 13.06 SD = 10.85
M = 22.56 a
SD = 11.65 M = 43.51 c
SD = 12.79 a 1 missing case b 2 missing cases c 7 missing cases
Demographic Analysis by Occupational Group
A Chi Square Test of Independence indicated a relationship between occupational group
and gender, x2 (11, n = 180) = 19.68, p < .05. The most significant differences occurred among
engineers, librarians, and licensed practical nurses. No engineers in the sample were female.
Only 1 librarian was male, and 13 licensed practical nurses were female.
An ANOVA for Age indicated significant differences, F(11, 166) = 3.01, p < .01. The
Tukey HSD revealed that Bankers were significantly younger than Accountants, Engineers,
Licensed Practical Nurses, Social Workers, and Medical Technologists.
An ANOVA for Years of Education indicated significant differences, F(11, 168) = 25.14,
p < .0001. The Tukey HSD revealed that Licensed Practical Nurses reported spending
significantly less time in school than all other occupational groups except Bankers and Florists.
As a group, Bankers, Florists, Medical Technologists and Real Estate Agents reported fewer
years of education when compared to Librarians, Social Workers, Foresters, Attorneys, and
Is Congruence Dead? 63
Psychologists. Engineers reported less time in school than Foresters, Attorneys, and
Psychologists.
An ANOVA for Time on Present Job indicated significant differences, F(11, 168) = 2.17,
p < .05. The Tukey HSD revealed that Florists and Accountants reported more time on their
present jobs when compared to Bankers.
An ANOVA for Years in Occupation indicated significant differences, F(11, 167) = 5.98,
p < .0001. The Tukey HSD revealed that Bankers reported less time spent in their occupations
when compared to Florists, Accountants, Licensed Practical Nurses, Engineers, and Medical
Technologists. Real Estate Agents reported less time spent in their occupations when compared
to Accountants, Licensed Practical Nurses, Engineers, and Medical Technologists. Psychologists
reported less time spent in their occupations when compared to Licensed Practical Nurses,
Engineers, and Medical Technologists.
An ANOVA for Hours Worked Per Week indicated significant differences, F(11, 161) =
2.45, p < .01. The Tukey HSD revealed that Florists reported working significantly more hours
when compared to Social Workers.
Demographic Analysis by Primary Holland Type
A Chi Square Test of Independence indicated a relationship between primary Holland
type and gender, x2 (5, n = 180) = 11.07, p < .05. The significant differences occurred among the
Realistic (Engineer, Forester) and Social (Licensed Practical Nurse, Social Worker) types.
Realistic types predominantly were male while Social types predominantly were female.
An ANOVA for Age indicated significant differences, F(5, 172) = 2.44, p < .05. The
Tukey HSD revealed that Social types (Licensed Practical Nurse, Social Worker) were
significantly older when compared with Conventional types (Accountant, Banker).
Is Congruence Dead? 64
Table 13
Demographic Data According to Occupational Group
Occupational Group
Gender Age Years of Education
Time on Present Job
Years in Occupation
Hours Worked
Per Week Accountant Females 6
Males 9 M = 52.73
SD = 8.54 M = 16.80 SD = 1.08
M = 19.82 SD = 10.87
M = 27.17 a
SD = 8.97 M = 39.64 a
SD = 12.12 Attorney Females 5
Males 10 M = 48.27 SD = 12.58
M = 19.13 SD = 0.35
M = 11.42 SD = 9.28
M = 20.26 SD = 12.58
M = 47.40 SD = 16.94
Banker Females 10 Males 5
M = 39.37 SD = 13.07
M = 14.87 SD = 2.47
M = 5.71 SD = 7.49
M = 13.79 SD = 12.94
M = 48.27 SD =9.61
Engineer Females 0 Males 15
M = 53.40 SD = 8.68
M = 16.67 SD = 1.05
M = 13.24 SD = 9.67
M = 28.98 SD = 8.31
M = 49.0 SD = 6.03
Florist Females 8 Males 7
M = 50.20 SD = 7.83
M = 14.90 SD = 1.73
M = 18.65 SD = 13.58
M = 26.22 SD = 9.93
M = 51.83 SD = 11.79
Forester Females 4 Males 11
M = 45.60 SD = 9.62
M = 18.73 SD = 1.98
M = 11.42 SD = 9.57
M = 17.14 SD = 8.01
M = 40.37 SD = 3.31
Librarian Females 14 Males 1
M = 49.87 SD = 10.23
M = 17.80 SD = 2.51
M = 9.68 SD = 8.69
M = 19.48 SD = 7.65
M = 45.0 SD = 7.73
Licensed Practical Nurse
Females 13 Males 2
M = 54.57 a
SD = 12.31 M = 13.20 SD = 0.77
M = 13.46 SD = 13.73
M = 28.60 SD = 14.34
M = 43.62 b
SD = 11.27 Medical
Technologist Females 10 Males 5
M = 56.40 SD = 8.27
M = 15.33 SD = 1.63
M = 14.24 SD = 11.87
M = 33.06 SD = 10.21
M = 37.10 SD = 14.25
Psychologist Females 7 Males 8
M = 49.20 SD = 10.75
M = 20.30 SD = 1.07
M = 9.10 SD = 7.4
M = 16.22 SD = 8.09
M = 40.54 c
SD = 15.21 Real Estate
Agent Females 8 Males 7
M = 49.13 SD = 13.15
M = 15.53 SD = 2.26
M = 13.95 SD = 9.82
M = 14.57 SD = 9.58
M = 42.14 a SD = 17.26
Social Worker Females 11 Males 4
M = 55.79 a
SD = 10.48 M = 18.33 SD = 0.72
M = 15.99 SD = 11.52
M = 25.56 SD = 8.95
M = 36.37 SD = 13.99
a 1 missing case b 2 missing cases c 3 missing cases
An ANOVA for Years of Education indicated significant differences, F(5, 174) = 10.54,
p < .0001. The Tukey HSD revealed that Enterprising (Florist, Real Estate Agent), Social
(Licensed Practical Nurse, Social Worker), and Conventional types (Accountant, Banker)
reported spending less time in school than the Realistic (Engineer, Forester), Investigative
(Medical Technologist, Psychologist), and Artistic types (Attorney, Librarian).
Is Congruence Dead? 65
When the data were collapsed into Holland type, ANOVAS did not indicate significant
differences for Time on Present Job, Years in Occupation, or Hours Worked Per Week.
Table 14
Demographic Data According to Primary Holland Type
Holland Type Gender Age Years of Education
Time on Present Job
Years in Occupation
Hours Worked
Per Week Realistic Females 4
Males 26 M = 49.50 SD = 9.83
M = 17.70 SD = 1.88
M = 12.34 SD = 9.50
M = 23.06 SD = 10.03
M= 44.68 SD = 6.49
Investigative Females 17 Males 13
M = 52.80 SD = 10.11
M = 17.82 SD = 2.86
M= 11.67 SD = 10.07
M = 24.64 SD = 12.46
M = 38.63 c SD = 14.50
Artistic Females 19 Males 11
M = 49.07 SD = 11.30
M = 18.47 SD = 1.88
M = 10.55 SD = 8.88
M = 19.87 SD = 10.24
M = 46.20 SD = 13.00
Social Females 24 Males 6
M = 55.18 b SD = 11.24
M = 15.77 SD = 2.71
M = 14.73 SD = 12.52
M = 27.08 SD = 11.85
M = 39.73 b SD = 13.09
Enterprising Females 16 Males 14
M = 49.67 SD = 10.65
M = 15.22 SD = 2.00
M = 16.30 SD = 11.88
M = 20.39 SD = 11.27
M = 47.16 a SD = 15.23
Conventional Females 16 Males 14
M = 46.0 SD = 12.82
M = 15.83 SD = 2.19
M = 12.76 SD = 11.64
M = 20.25 a SD = 12.94
M = 44.10 a SD = 11.56
a 1 missing case b 2 missing cases c 3 missing cases
MSQ SCORE ANALYSIS
MSQ mean scores were analyzed according to intrinsic, extrinsic, and overall job
satisfaction for all data, for occupational groups, and for primary Holland types. Data are
presented according to all cases (see Table 15) and are further analyzed according to
occupational group (see Table 16) and primary Holland type (see Table 17).
MSQ Score Analysis for All Data
Mean MSQ data for all cases indicated that, overall, the sample reported moderately high
levels of intrinsic (M = 50.51, SD = 6.99), extrinsic (M = 20.58, SD = 11.26), and overall (M
=78.88, SD = 12.35) job satisfaction. Value ranges were large; intrinsic satisfaction scores
Is Congruence Dead? 66
ranged from 12 to 60, extrinsic satisfaction scores ranged from 6 to 30, and overall satisfaction
scores ranged from 22 to 99.
Table 15
MSQ Data for All Cases
Intrinsic Satisfaction
Extrinsic Satisfaction
Overall Satisfaction
M = 50.51 SD = 6.99
M = 20.58
SD = 5.42 M = 78.88 SD = 12.35
MSQ Score Analysis by Occupational Group
An ANOVA did not indicate significant differences in intrinsic job satisfaction scores
among occupational groups.
An ANOVA for extrinsic job satisfaction indicated significant differences, F(11, 168) =
2.10, p < .05. The Tukey HSD revealed that Licensed Practical Nurses and Medical
Technologists reported lower levels of extrinsic satisfaction when compared to Real Estate
Agents.
An ANOVA for overall job satisfaction indicated significant differences, F(11, 168) =
2.04, p < .05. The Tukey HSD revealed that Licensed Practical Nurses reported lower levels of
overall job satisfaction when compared to Real Estate Agents.
MSQ Score Analysis by Primary Holland Type
An ANOVA did not indicate significant differences in intrinsic job satisfaction scores
among Holland types.
An ANOVA for extrinsic job satisfaction indicated significant differences, F(5, 174) =
2.84, p < .05. The Tukey HSD revealed that Social types (Licensed Practical Nurse, Social
Is Congruence Dead? 67
Worker) reported lower levels of extrinsic satisfaction when compared to Enterprising types
(Florist, Real Estate Agent).
When the data were collapsed into Holland type, an ANOVA did not indicate significant
differences in overall job satisfaction.
Table 16
MSQ Data According to Occupational Group
Occupational Group
Intrinsic Satisfaction
Extrinsic Satisfaction
Overall Satisfaction
Accountant M = 51.0 SD = 5.61
M = 21.93 SD = 3.92
M = 81.13 SD = 9.90
Attorney M = 49.93 SD =6.12
M = 19.73 SD = 5.26
M = 77.13 SD = 10.77
Banker M = 47.27 SD =5.43
M = 20.60 SD = 4.80
M = 75.47 SD = 9.16
Engineer M = 51.07 SD =7.09
M = 21.2 SD = 5.95
M = 80.07 SD = 12.96
Florist M = 52.07 SD =11.33
M = 21.20 SD = 4.89
M = 80.73 SD = 16.55
Forester M = 47.80 SD =6.88
M = 19.33 SD = 6.53
M = 74.33 SD = 13.06
Librarian M = 54.73 SD =4.49
M = 22.53 SD = 5.24
M = 85.47 SD = 9.82
Licensed Practical Nurse
M = 47.33 SD =11.23
M = 17.87
SD = 6.98 M = 72.13 SD = 18.76
Medical Technologist
M = 49.67 SD =5.12
M = 18.47 SD = 6.56
M = 75.47 SD = 12.51
Psychologist M = 50.47 SD =4.72
M = 20.33 SD = 4.69
M = 79.20 SD = 9.32
Real Estate Agent
M = 53.60 SD =4.29
M = 24.93 SD = 2.79
M = 87.13 SD = 6.15
Social Worker M = 51.27 SD =4.80
M = 18.93
SD = 3.58 M = 78.33 SD = 8.94
Is Congruence Dead? 68
Table 17
MSQ Data According to Primary Holland Type
Holland Type Intrinsic Satisfaction
Extrinsic Satisfaction
Overall Satisfaction
Realistic M = 49.43 SD = 7.06
M = 20.27 SD = 6.21
M = 77.20 SD = 13.11
Investigative M = 50.07 SD = 4.86
M = 19.40 SD = 5.68
M= 77.33 SD = 11.01
Artistic M = 52.33 SD = 5.81
M = 21.13 SD = 5.35
M = 81.30 SD = 10.98
Social M = 49.30 SD = 8.72
M = 18.40 SD = 5.47
M = 75.23 SD = 14.78
Enterprising M = 52.83 SD = 8.45
M = 23.07 SD = 4.34
M = 89.93 SD = 12.70
Conventional M = 49.13 SD = 5.75
M = 21.27 SD = 4.36
M = 78.3 SD = 9.80
CONGRUENCE SCORE ANALYSIS
Congruence mean scores were analyzed according to the modified C index, the
substitution C index, traditionally-derived Holland codes, and decision-derived Holland codes.
Data are presented according to all cases (see Table 18), for occupational groups (see Table 19),
and for primary Holland types (see Table 20).
Congruence Score Analysis for All Data
Mean congruence score data for all cases indicated that, overall, the two congruence
indices and the two methods of congruence generated very similar values and score ranges.
While the data indicated that decision-derived Holland codes are associated with slightly higher
mean congruence scores, an ANOVA indicated that there are no significant differences among
any of the congruence values.
An analysis of the ranges of values indicated that 0 was the lowest value associated with
the decision-derived codes while 1 was the lowest value associated with the traditionally-derived
Is Congruence Dead? 69
codes. This means that it was possible for congruence to be mathematically absent when using
the decision derived method. In contrast, the traditionally-derived method always detected some
degree of congruence.
Table 18
Congruence Score Data for All Cases
Modified C Index Substitution C Index
Traditionally-Derived Holland Codes
M = 10.95 SD = 3.60
Score Range 1.4 - 18
M = 10.90 SD = 3.60
Score Range 1 – 18 Decision-Derived
Holland Codes M = 11.20 SD = 4.56
Score Range 0 - 18
M = 11.21 SD = 4.62
Score Range 0 - 18
Congruence Score Analysis by Occupational Group
An ANOVA examining congruence means as measured by the modified C index and
traditionally-derived Holland codes indicated significant differences, F(11, 168) = 2.17, p < .05.
The Tukey HSD revealed congruence scores for Social Workers were higher when compared to
Florists, Medical Technologists, and Licensed Practical Nurses.
An ANOVA examining congruence means as measured by the substitution C index and
traditionally-derived Holland codes indicated significant differences, F(11, 168) = 1.99, p < .05.
The Tukey HSD revealed congruence scores for Social Workers were higher when compared to
Florists and Medical Technologists.
An ANOVA examining congruence means as measured by the modified C index and
decision-derived Holland codes indicated significant differences, F(11, 168) = 2.13, p < .05.
Even though a significant F value was obtained, the Tukey HSD did not detect where the source
of the significant differences.
Is Congruence Dead? 70
An ANOVA examining congruence means as measured by the substitution C index and
decision-derived Holland codes indicated significant differences, F(11, 168) = 2.02, p < .05.
Even though a significant F value was obtained, the Tukey HSD did not detect the source of the
significant differences.
Congruence Score Analysis by Primary Holland Type
When the data were collapsed into Holland type, an ANOVA did not indicate significant
differences in congruence means as measured by the modified C index and traditionally-derived
Holland codes.
When the data were collapsed into Holland type, an ANOVA did not indicate significant
differences in congruence means as measured by the substitution C index and traditionally-
derived Holland codes.
When the data were collapsed into Holland type, an ANOVA did not indicate significant
differences in congruence means as measured by the modified C index and decision-derived
Holland codes.
When the data were collapsed into Holland type, an ANOVA did not indicate significant
differences in congruence means as measured by the substitution C index and decision-derived
Holland codes.
Is Congruence Dead? 71
Table 19
Congruence Score Data by Occupational Group
Occupational Group Modified C Index Substitution C Index Traditionally-Derived
Holland Codes Accountant M = 10.75, SD = 3.09 M = 10.67, SD = 3.20
Attorney* M = 10.87, SD =3.07 M = 10.87, SD =3.07
Banker M = 10.33, SD =3.93 M = 10.2, SD = 4.04
Engineer M = 11.19, SD = 4.10 M = 11.27, SD = 4.28
Florist* M = 9.40, SD =3.11 M = 9.40, SD =3.11
Forester M = 12.54, SD =3.48 M = 12.27, SD = 3.41
Librarian* M = 10.53, SD = 2.85 M = 10.53, SD = 2.85
Licensed Practical Nurse* M = 10.00, SD = 4.77 M = 10.00, SD = 4.77
Medical Technologist* M = 9.93, SD =2.91 M = 9.93, SD =2.91
Psychologist M = 11.25, SD =3.15 M = 11.07, SD = 3.13
Real Estate Agent* M = 10.40, SD = 3.62 M = 10.40, SD = 3.62
Social Worker M = 14.36, SD =3.10 M = 14.2, SD = 2.96
Decision –Derived Holland Codes
Accountant M = 10.40, SD = 5.34 M = 10.67, SD = 5.32
Attorney M = 10.01, SD = 5.60 M = 10.07, SD = 5.63
Banker M = 11.13, SD = 4.27 M = 11.13, SD = 4.29
Engineer M = 11.95, SD = 3.91 M = 12.27, SD = 3.84
Florist M = 9.08, SD = 3.47 M = 9.00, SD = 3.61
Forester M = 13.49, SD = 3.53 M = 13.47, SD = 3.56
Librarian M = 9.31, SD = 6.02 M = 9.47, SD = 6.15
Licensed Practical Nurse M = 9.00, SD = 3.63 M = 9.00, SD = 3.64
Medical Technologist M = 11.56, SD = 3.05 M = 11.53, SD = 3.06
Psychologist M = 12.16, SD = 3.23 M = 12.13, SD = 3.48
Real Estate Agent M = 12.51, SD = 5.69 M = 12.40, SD = 5.81
Social Worker M = 13.81, SD = 3.81 M = 14.00, SD = 4.05
* Modified C Index and substitution C index calculations are computationally equivalent.
Is Congruence Dead? 72
Table 20
Congruence Score Data by Primary Holland Type
Occupational Group Modified C Index Substitution C Index Traditionally-Derived
Holland Codes Realistic M = 11.82, SD = 3.79 M = 11.77 , SD = 3.84
Investigative M = 10.59, SD = 3.05 M = 10.50, SD = 3.03
Artistic* M = 10.70, SD = 2.91 M = 10.70 , SD = 2.91
Social M = 12.18 , SD = 4.53 M = 12.10 , SD = 4.44
Enterprising* M = 9.90 , SD = 3.35 M = 9.90, SD = 3.36
Conventional M = 10.54, SD = 3.48 M = 10.43, SD = 3.59 Decision –Derived
Holland Codes Realistic M = 12.72, SD = 3.74 M = 12.87, SD = 3.69
Investigative M = 11.86, SD = 3.11 M = 11.83, SD = 3.24
Artistic M = 9.66, SD = 5.72 M = 9.77, SD = 5.81
Social M = 11.41, SD = 4.40 M = 11.50 , SD = 4.56
Enterprising M = 10.79, SD = 4.94 M = 10.70, SD = 5.06
Conventional M = 10.77, SD = 4.76 M = 10.90, SD = 4.76
* Modified C Index and substitution C index calculations are computationally equivalent.
GENERAL RESEARCH QUESTION ANALYSIS
General research questions were analyzed according to all data, for occupational groups,
and for primary Holland types. Tables indicating relevant data are indicated with each question.
Question 1a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
Is Congruence Dead? 73
All Data
An analysis of all data indicates there is no significant correlation between congruence
and intrinsic job satisfaction when traditionally-derived codes are used to measure vocational
personality and the Modified C index is used to calculate congruence scores (see Table 21).
Occupational Groups
An analysis of occupational group data indicates there is no positive correlation between
congruence and intrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores. The data
do indicate a strong negative correlation among Medical Technologists, r(13) = - .643, p < .01
(see Table 22).
Primary Holland Types
An analysis of Holland type data indicates there is no positive correlation between
congruence and intrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores. The data
do indicate a moderate negative correlation among Investigative types (Medical Technologist,
Psychologist), r(28) = - .380, p < .05 (See Table 23).
Table 21 Job Satisfaction Correlations with Congruence Scores for All Data
Modified C Index Substitution C Index Traditionally
Derived Decision Derived
Traditionally Derived
Decision Derived
Intrinsic Job Satisfaction
-.083 (α = .135)
-.025 (α = .369)
-.075 (α = .159)
-.024 (α = .375)
Extrinsic Job Satisfaction
-.176 (p < .01)*
-.019 (α = .403)
-.167 (p < .05)*
-.030 (α = .346)
Overall Job Satisfaction
-.131 (p < .05)*
-.009 (α = .454)
-.123 (α = .051)
-.013 (α = .429)
Is Congruence Dead? 74
Question 1b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
All Data
An analysis of all data indicates there is no positive correlation between congruence and
extrinsic job satisfaction when traditionally-derived codes are used to measure vocational
personality and the Modified C index is used to calculate congruence scores. The data do
indicate a weak negative correlation between congruence and extrinsic job satisfaction, r(178) =
- .176, p < .01 (see Table 21).
Occupational Groups
An analysis of occupational group data indicates there is no positive correlation between
congruence and extrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores. The data
do indicate a strong negative correlation among Accountants r(13) = - .609, p < .01 and a
moderate negative correlation among Medical Technologists, r(13) = - .555, p < .05 (see Table
22).
Primary Holland Types
An analysis of Holland type data indicates there is no positive correlation between
congruence and extrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores. The data
do indicate a moderate negative correlation among Investigative types (Medical Technologist,
Psychologist), r(28) = - .360, p < .05 (See Table 23).
Is Congruence Dead? 75
Table 22 Occupational Group Job Satisfaction Correlations with Traditionally-Derived Congruence Scores
Modified C Index Substitution C Index Intrinsic Job Satisfaction Accountant
Attorney Banker Engineer Florist Forester Librarian Licensed Practical Nurse Medical Technologist* Psychologist Real Estate Agent Social Worker
-.238 (α = .196) .258 (α = .177) .176 (α = .266) .064 (α = .411) -.021 (α = .470) -.384 (α = .079) .213 (α = .223) -.228 (α = .207) -.643 (p < .01) -.179 (α = .261) -.145 (α = .303) .171 (α = .272)
-.279 (α = .157) .258 (α = .177) .209 (α = .227) .086 (α = .380) -.021 (α = .470) -.363 (α = .092) .213 (α = .223) -.228 (α = .207) -.643 (p < .01) -.157 (α = .288) -.145 (α = .303) .172 (α = .270)
Extrinsic Job Satisfaction
Accountant Attorney Banker Engineer Florist Forester Librarian Licensed Practical Nurse Medical Technologist* Psychologist Real Estate Agent Social Worker
-.609 (p < .01) -.025 (α = .465) -.044 (α = .438) -.024 (α = .466) -.363 (α = .092) -.188 (α = .251) .281 (α = .155) -.395 (α = .072) -.555 (p < .05) -.248 (α = .187) .335 (α = .111) .220 (α = .215)
-.629 (p < .01) -.025 (α = .465) -.054 (α = .424) .020 (α = .472) -.363 (α = .092) -.152 (α = .295) .281 (α = .155) -.395 (α = .072) -.555 (p < .05) -.216 (α = .220) .335 (α = .111) .224 (α = .211)
Overall Job Satisfaction Accountant Attorney Banker Engineer Florist Forester Librarian Licensed Practical Nurse Medical Technologist* Psychologist Real Estate Agent Social Worker
-.428 (α = .056) .128 (α = .325) .020(α = .472) .043 (α = .440) -.142 (α = .307) -.307 (α = .133) .297 (α = .141) -.319 (α = .123) -.573 (p < .05) -.218 (α = .218) .142 (α = .307) .152 (α = .295)
-.461 (p <.05) .128 (α = .325) .036 (α = .449) .079 (α = .389) -.142 (α = .307) -.278 (α = .158) .297 (α = .141) -.319 (α = .123) -.573 (p < .05) -.192 (α = .247) .142 (α = .307) .157 (α =. 289)
* Medical Technologist correlation calculations are computationally equivalent.
Is Congruence Dead? 76
Table 23 Holland Type Job Satisfaction Correlations with Traditionally-Derived Congruence Scores
Modified C Index Substitution C Index Intrinsic Job Satisfaction Realistic
Investigative
Artistic
Social
Enterprising
Conventional
-.172 (α = .182)
-.380 (p < .05)
.191 (α = .155)
-.006 (α = .488)
-.037 (α = .423)
.010 (α = .478)
-.136 (α = .237)
-.375 (p < .05)
.191 (α = .155)
-.011 (α = .476)
-.037 (α = .423)
.012 (α = .475)
Extrinsic Job Satisfaction Realistic
Investigative
Artistic
Social
Enterprising
Conventional
-.125 (α = .255)
-.360 (p < .05)
.102 (α = .295)
-.160 (α = .199)
-.004 (α = .491)
-.252 (α = .090)
-.078 (α = .341)
-.355 (p < .05)
.102 (α = .295)
-.166 (α = .190)
-.004 (α = .491)
-.265 (α = .078)
Overall Job Satisfaction Realistic
Investigative
Artistic
Social
Enterprising
Conventional
-.151 (α = .213)
-.354 (p < .05)
.167 (α = .189)
-.071 (α = .355)
-.008 (α = .483)
-.158 (α =. 203)
-.106 (α = .289)
-.351 (p < .05)
.167 (α = .189)
-.076 (α = .344)
-.008 (α = .483)
-.163 (α = .195)
Question 1c
Is there a significant positive correlation between congruence and overall job satisfaction
when traditionally-derived codes are used to measure vocational personality and the Modified C
index is used to calculate congruence scores?
All Data
An analysis of all data indicates there is no positive correlation between congruence and
overall job satisfaction when traditionally-derived codes are used to measure vocational
personality and the Modified C index is used to calculate congruence scores. The data do
Is Congruence Dead? 77
indicate a weak negative correlation between congruence and overall job satisfaction, r(178) = -
.131, p < .05 (see Table 21).
Occupational Groups
An analysis of occupational group data indicates there is no positive correlation between
congruence and overall job satisfaction when traditionally-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores. The data
do indicate a moderate negative correlation among Medical Technologists, r(13) = - .573, p < .05
(see Table 22).
Primary Holland Types
An analysis of Holland type data indicates there is no positive correlation between
congruence and overall job satisfaction when traditionally-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores. The data
do indicate a moderate negative correlation among Investigative types (Medical Technologist,
Psychologist), r(28) = - .354, p < .05 (See Table 23).
Question 2a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
substitution C index is used to calculate congruence scores?
All Data
An analysis of all data indicates there is no significant correlation between congruence
and intrinsic job satisfaction when traditionally-derived codes are used to measure vocational
personality and the substitution C index is used to calculate congruence scores (see Table 21).
Is Congruence Dead? 78
Occupational Groups
An analysis of occupational group data indicates there is no positive correlation between
congruence and intrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the substitution C index is used to calculate congruence scores. The
data do indicate a strong negative correlation among Medical Technologists, r(13) = - .643, p <
.01 (see Table 22).
Primary Holland Types
An analysis of Holland type data indicate there is no positive correlation between
congruence and intrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the substitution C index is used to calculate congruence scores. The
data do indicate a moderate negative correlation among Investigative types (Medical
Technologist, Psychologist), r(28) = - .375, p < .05 (see Table 23).
Question 2b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when traditionally-derived codes are used to measure vocational personality and the
substitution C index is used to calculate congruence scores?
All Data
An analysis of all data indicate there is no positive correlation between congruence and
extrinsic job satisfaction when traditionally-derived codes are used to measure vocational
personality and the substitution C index is used to calculate congruence scores. The data do
indicate a weak negative correlation between congruence and extrinsic job satisfaction, r(178) =
- .167, p < .05 (see Table 21).
Is Congruence Dead? 79
Occupational Groups
An analysis of occupational group data indicates there is no positive correlation between
congruence and extrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the substitution C index is used to calculate congruence scores. The
data do indicate a moderate negative correlation among Medical Technologists, r(13) = - .555, p
< .05 and a strong negative correlation among Accountants r(13) = - .629, p < .05 (see Table 22).
Primary Holland Types
An analysis of Holland type data indicate there is no positive correlation between
congruence and extrinsic job satisfaction when traditionally-derived codes are used to measure
vocational personality and the substitution C index is used to calculate congruence scores. The
data do indicate a moderate negative correlation among Investigative types (Medical
Technologist, Psychologist) r(28) = - .355, p < .05 (see Table 23).
Question 2c
Is there a significant positive correlation between congruence and overall job satisfaction
when traditionally-derived codes are used to measure vocational personality and the substitution
C index is used to calculate congruence scores?
All Data
The is no significant correlation between congruence and overall job satisfaction when
traditionally-derived codes are used to measure vocational personality and the substitution C
index is used to calculate congruence scores (see Table 21).
Occupational Groups
An analysis of occupational group data indicates there is no positive correlation between
congruence and overall job satisfaction when traditionally-derived codes are used to measure
Is Congruence Dead? 80
vocational personality and the substitution C index is used to calculate congruence scores. The
data do indicate a moderate negative correlation among Accountants, r(13) = - .461, p < .05, and
among Medical Technologists, r(13) = - .573, p < .05 (see Table 22).
Primary Holland Types
An analysis of Holland type data indicates there is no positive correlation between
congruence and overall job satisfaction when traditionally-derived codes are used to measure
vocational personality and the substitution C index is used to calculate congruence scores. The
data do indicate a moderate negative correlation among Investigative types (Medical
Technologist, Psychologist) r(28) = - .351, p < .05 (see Table 23).
Question 3a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
All Data
An analysis of all data indicates there is no significant correlation between congruence
and intrinsic job satisfaction when decision-derived codes are used to measure vocational
personality and the Modified C index is used to calculate congruence scores (see Table 21).
Occupational Groups
An analysis of occupational group data indicates there is no significant correlation
between congruence and intrinsic job satisfaction when decision-derived codes are used to
measure vocational personality and the Modified C index is used to calculate congruence scores
(see Table 24).
Is Congruence Dead? 81
Primary Holland Types
An analysis of Holland type data indicates there is no significant correlation between
congruence and intrinsic job satisfaction when decision-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores (see
Table 25).
Question 3b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Modified C index is used to calculate congruence scores?
All Data
An analysis of all data indicate there is no significant correlation between congruence and
extrinsic job satisfaction when decision-derived codes are used to measure vocational personality
and the Modified C index is used to calculate congruence scores (see Table 21).
Occupational Groups
An analysis of occupational group data indicates that there is no significant correlation
between congruence and extrinsic job satisfaction when decision-derived codes are used to
measure vocational personality and the Modified C index is used to calculate congruence scores
(see Table 24).
Primary Holland Types
An analysis of Holland type data indicate that there is no significant correlation between
congruence and extrinsic job satisfaction when decision-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores (see
Table 25).
Is Congruence Dead? 82
Question 3c
Is there a significant positive correlation between congruence and overall job satisfaction
when decision-derived codes are used to measure vocational personality and the Modified C
index is used to calculate congruence scores?
All Data
An analysis of all data indicate that there is no significant correlation between
congruence and overall job satisfaction when decision-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores (see table
21).
Occupational Groups
An analysis of all data indicate that there is no significant correlation between
congruence and overall job satisfaction when decision-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores (see table
24).
Primary Holland Types
An analysis of Holland type data indicate that there is no significant correlation between
congruence and overall job satisfaction when decision-derived codes are used to measure
vocational personality and the Modified C index is used to calculate congruence scores (see table
25).
Question 4a
Is there a significant positive correlation between congruence and intrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Substitution C index is used to measure congruence?
Is Congruence Dead? 83
All Data
An analysis of all data indicates that there is no significant correlation between
congruence and intrinsic job satisfaction when decision-derived codes are used to measure
vocational personality and the Substitution C index is used to measure congruence (see Table
21).
Occupational Groups
An analysis of occupational group data indicates there is no significant correlation
between congruence and intrinsic job satisfaction when decision-derived codes are used to
measure vocational personality and the Substitution C index is used to measure congruence (see
Table 24).
Primary Holland Types
An analysis of Holland type data indicates that there is no significant correlation between
congruence and intrinsic job satisfaction when decision-derived codes are used to measure
vocational personality and the Substitution C index is used to measure congruence (see Table
25).
Question 4b
Is there a significant positive correlation between congruence and extrinsic job
satisfaction when decision-derived codes are used to measure vocational personality and the
Substitution C index is used to measure congruence?
All Data
An analysis of all data indicate there is no significant correlation between congruence and
extrinsic job satisfaction when decision-derived codes are used to measure vocational personality
and the Substitution C index is used to measure congruence (see Table 21).
Is Congruence Dead? 84
Occupational Groups
An analysis of occupational group data indicate there is no significant correlation
between congruence and extrinsic job satisfaction when decision-derived codes are used to
measure vocational personality and the Substitution C index is used to measure congruence (see
Table 24).
Primary Holland Types
An analysis of Holland type data indicate there is no significant correlation between
congruence and extrinsic job satisfaction when decision-derived codes are used to measure
vocational personality and the Substitution C index is used to measure congruence (see Table
25).
Question 4c
Is there a significant positive correlation between congruence and overall job satisfaction
when decision-derived codes are used to measure vocational personality and the Substitution C
index is used to measure congruence?
All Data
An analysis of all data indicate that there is no significant correlation between
congruence and overall job satisfaction when decision-derived codes are used to measure
vocational personality and the Substitution C index is used to measure congruence (see Table
21).
Is Congruence Dead? 85
Table 24
Occupational Group Job Satisfaction Correlations with Decision-Derived Congruence Scores
Modified C Index
Substitution C Index
Overall Job Satisfaction
Accountant Attorney Banker Engineer Florist Forester Librarian Licensed Practical Nurse Medical Technologist Psychologist Real Estate Agent Social Worker
-.375 (α = .084) -.068 (α = .404) -.124 (α = .330) .140 (α = .309) .109 (α = .349) .368 (α = .089) .124 (α = .330) -.199 (α = .238) -.252 (α = .182) .013 (α = .482) .090 (α = .375) .201 (α = .237)
-.365 (α = .091) -.063 (α = .412) -.098 (α = .364) .103 (α = .358) .101 (α = .361) .350 (α = .101) .101 (α = .360) -.192 (α = .246) -.247 (α = .187) -.010 (α = .486) .122 (α = .332) .173 (α = .268)
Intrinsic Job Satisfaction
Accountant Attorney Banker Engineer Florist Forester Librarian Licensed Practical Nurse Medical Technologist Psychologist Real Estate Agent Social Worker
-.318 (α = .124) .027 (α = .462) -.067 (α = .406) .213 (α = .223) .161 (α = .284) .324 (α = .119) -.161 (α = .283) -.183 (α = .257) -.361 (α = .093) .033 (α = .453) -.125 (α = .329) .221 (α = .215)
-.311 (α = .130) .025 (α = .465) -.032 (α = .455) .180 (α = .260) .149 (α = .299) .296 (α = .142) -.171 (α = .271) -.183 (α = .257) -.356 (α = .096) .009 (α = .487) -.113 (α = .344) .202 (α = .235)
Extrinsic Job Satisfaction
Accountant Attorney Banker Engineer Florist Forester Librarian Licensed Practical Nurse Medical Technologist Psychologist Real Estate Agent Social Worker
-.386 (α = .077) -.210 (α = .226) -.134 (α = .317) -.041 (α = .443) -.004 (α = .495) .306 (α = .134) .261 (α = .174) -.140 (α = .310) -.216 (α = .220) -.030 (α = .457) .204 (α = .233) .234 (α = .201)
-.374 (α = .085) -.195 (α = .244) -.122 (α = .333) -.074 (α = .396) -.012 (α = .483) .297 (α = .141) .242 (α = .192) -.124 (α = .330) -.209 (α = .228) -.047 (α = .434) .248 (α = .186) .197 (α =. 241)
Is Congruence Dead? 86
Occupational Groups
An analysis of occupational group data indicate there is no significant correlation
between congruence and overall job satisfaction when decision-derived codes are used to
measure vocational personality and the Substitution C index is used to measure congruence (see
Table 24).
Primary Holland Types
An analysis of Holland type data indicate that there is no significant correlation between
congruence and overall job satisfaction when decision-derived codes are used to measure
vocational personality and the Substitution C index is used to measure congruence (see Table
25).
Question 5a
Are there significant differences in the intrinsic job satisfaction correlation values
identified in Questions 1a, 2a, 3a, and 4a?
All Data
Questions 1a, 2a, 3a, and 4a did not indicate any significant correlations between
congruence and intrinsic job satisfaction.
Occupational Groups
Questions 1a and 2a indicated a strong negative correlation between congruence and
intrinsic job satisfaction among Medical Technologists when traditionally-derived codes were
used with the modified C index and the substitution C index. These calculations were based on
identical congruence scores. No significant difference exists between the two correlations.
Is Congruence Dead? 87
Primary Holland Types
Questions 1a and 2a indicated a moderate negative correlation between congruence and
intrinsic job satisfaction among Investigative (Medical Technologist, Psychologist) types when
traditionally-derived codes were used with the modified C index and the substitution C index. A
Fisher’s r to z’ Transformation indicated no difference between the two correlations (z = -0.021).
Table 25 Holland Type Job Satisfaction Correlations with Decision-Derived Congruence Scores
Modified C Index Substitution C Index Overall Job Satisfaction Realistic
Investigative
Artistic
Social
Enterprising
Conventional
.190 (α = .157)
-.114 (α = .275)
.000 (α = .499)
.069 (α = .359)
.163 (α = .195)
-.278 (α = .068)
.176 (α = .175)
-.116 (α = .270)
-.003 (α = .494)
.070 (α = .357)
.166 (α = .191)
-.254 (α = .088)
Intrinsic Job Satisfaction Realistic
Investigative
Artistic
Social
Enterprising
Conventional
.202 (α = .142)
-.156 (α = .205)
-.076 (α = .345)
.084 (α = .329)
.070 (α = .356)
-.221 (α = .120)
.186 (α = .162)
-.159 (α = .200)
-.077 (α = .342)
.085 (α = .328)
.068 (α = .360)
-.194 (α = .153)
Extrinsic Job Satisfaction
Realistic
Investigative
Artistic
Social
Enterprising
Conventional
.095 (α = .309)
-.114(α = .274)
.015 (α = .468)
.048 (α = .401)
.225 (α = .116)
-.264 (α = .080)
.084 (α = .329)
-.114 (α = .274)
.018 (α = .463)
.050 (α = .397)
.233 (α = .108)
-.248 (α = .093)
Is Congruence Dead? 88
Question 5b
Are there significant differences in the extrinsic job satisfaction correlation values
identified in Questions 1b, 2b, 3b, and 4b?
All Data
Questions 1b and 2b indicated a weak, negative correlation between congruence and
extrinsic job satisfaction when traditionally-derived codes were used with the modified C index
and the substitution C index. A Fisher’s r to z’ Transformation indicated no difference between
the two correlations (z = -0.087).
Occupational Groups
Questions 1b and 2b indicated a strong, negative correlation between extrinsic job
satisfaction and congruence among Accountants when traditionally-derived codes were used
with the modified C index and the substitution C index. A Fisher’s r to z’ Transformation
indicated no difference between the two correlations (z = 0.119).
Questions 1b and 2b indicated a moderate, negative correlation between extrinsic job
satisfaction and congruence among Medical Technologists when traditionally-derived codes
were used with the modified C index and the substitution C index. These calculations were based
on identical congruence scores. No significant difference exists between the two correlations.
Primary Holland Types
Questions 1b and 2b indicated a moderate, negative correlation between congruence and
extrinsic job satisfaction among Investigative types (Medical Technologist, Psychologist) when
traditionally-derived codes were used with the modified C index and the substitution C index. A
Fisher’s r to z’ Transformation indicated no difference between the two correlations (z = -0.021).
Is Congruence Dead? 89
Question 5c
Are there significant differences in the overall job satisfaction correlation values
identified in Questions 1c, 2c, 3c, and 4c?
All Data
Only Question 1c indicated a weak negative correlation between congruence and overall
job satisfaction for all data.
Occupational Groups
Question 1c indicated a moderate, negative correlation between congruence and overall
job satisfaction among Accountants when traditionally derived codes were used with the
substitution C index. Question 2c did not indicate a significant correlation between congruence
and overall job satisfaction among Accountants when traditionally derived codes were used with
the modified C index.
Questions 1c and 2c indicated a moderate, negative correlation between congruence and
overall job satisfaction among Medical Technologists when traditionally derived codes were
used with the modified C index and the substitution C index. These calculations were based on
identical congruence scores. No significant difference exists between the two correlations.
Primary Holland Types
Questions 1c and 2c indicated a moderate, negative correlation between congruence and
overall job satisfaction among Investigative types (Medical Technologist, Psychologist) when
traditionally derived codes were used with the modified C index and the substitution C index. A
Fisher’s r to z’ Transformation indicated no difference between the two correlations (z = -0.013).
Is Congruence Dead? 90
Question 6
Do any of the overall job satisfaction correlation values identified in Questions 1c, 2c, 3c,
and 4c meet or significantly exceed the meta-analytic correlations that were reported by
Assouline & Meir (1987), Tranberg, et al. (1993), and Tsabari, et al. (2005)?
Correlation between Congruence and Overall Job Satisfaction
Only Question 1c identified a significant correlation between congruence and overall job
satisfaction, a negative correlation value of r = -.131, when traditionally-derived codes were used
with the Modified C index. Fisher’s r to z’ Transformations indicated that this correlation value
is significantly lower than the values obtained by Assouline & Meir (1987), Tranberg, et al.
(1993), and Tsabari, et al. (2005) (see Table 26).
Table 26
Comparisons of Congruence – Overall Job Satisfaction Correlations
Assouline & Meir (1987)
r =.21 (N = 9,041)
Tranberg, et al. (1993)
r =.20 (N = 11,104)
Tsabari, et al. (2005) r = .158 (N = 5,805)
r = -.131 (N = 180)
z = -4.545
(p < 0.001)
z = -4.415
(p < 0.001)
z = -3.815
(p < 0.001)
SUMMARY OF CHAPTER FOUR
Chapter Four presented the research data analyzed according to all cases, occupational
groups, and primary Holland types. Demographic information first was evaluated. MSQ score
and congruence score data were analyzed and discussed. An analysis of this study’s general
research questions then was presented.
Is Congruence Dead? 91
CHAPTER FIVE: DISCUSSION
Job satisfaction is considered to be the most important outcome variable in congruence
research. Even though the assumption that there is a positive correlation between congruence and
job satisfaction is fundamental to Holland’s theory, the empirical evidence to support this
relationship is, at best, equivocal. While there is popular opinion within the vocational
psychology field that the congruence construct is “dead” as a viable theoretical concept, an
alternative point of view maintains that congruence has not fared better in the research literature
because methodological limitations have led to unimpressive and ambiguous findings. Many
researchers have neither acknowledged the methodological problems associated with congruence
research nor implemented viable empirical alternatives. The purpose of this study was to address
the common problems associated with congruence – job satisfaction research and to provide a
rationale for identifying and comparing measurement alternatives.
Sampling issues were addressed through the use of a sample of employed adults that was
representative of the entire RIASEC scheme. The Strong Interest Explorer (SIE; Chartrand,
2001) was chosen as the measure of vocational personality as it is based upon the psychometric
strength of the Strong Interest Inventory (SII; Donnay, et. al, 2005) but heretofore had not been
used in empirical research. The SIE was scored in a manner to compare a traditionally-derived
summary coding method to a decision-derived summary coding method. It was examined
whether the congruence - job satisfaction correlation was dependent upon the summary coding
method that was applied. The General Occupational Theme (GOT) codes of the SII were
identified to assess the work environment as they represent an application of the RIASEC
scheme that incorporates methods to limit potential measurement error. The modified C index
(Eggerth & Andrew, 2006) and the substitution C index (Gore & Brown, 2006) were used in this
Is Congruence Dead? 92
research to generate congruence scores. It was examined whether the congruence - job
satisfaction correlation was dependent upon the index that was used to calculate congruence. The
Minnesota Satisfaction Questionnaire (MSQ; Weiss, et. al, 1967) was selected as a valid and
reliable measure to investigate facets of intrinsic, extrinsic, and overall job satisfaction.
This research supports the use of a sample composed of working adults from multiple
occupational groups that is representative of the entire RIASEC scheme. This approach allowed
for a more specific identification of significant findings and more thorough analysis of the data.
Research results indicated that, overall, the traditionally-derived coding method performed better
than the decision-derived coding method. The data showed equivocal findings when the
modified C index and the substitution C index were compared. Job satisfaction correlation data
supported the use of a multifaceted measure.
The most noteworthy findings of this research are that significant, yet weak, correlations
were detected between congruence and extrinsic job satisfaction and between congruence and
overall job satisfaction. These relationships were not in the predicted direction. In fact, none of
the significant relationships detected in this study were in the predicted direction. In addressing
the question of whether the congruence construct is “dead”, it may be interpreted that the concept
is changing to reflect the social and economic shifts that have influenced the changing nature of
the meaning of work. This research suggests that congruence should be reconceptualized if it is
to remain a viable concept in the research and practice of vocational psychology.
REVIEW OF RESULTS
The use of a sample composed of multiple occupational groups that is representative of
the entire RIASEC scheme allowed for an analysis of the study data according to all cases and
also by occupational group and by primary Holland type. Demographic data, mean job
Is Congruence Dead? 93
satisfaction scores, mean congruence scores, and congruence – job satisfaction correlations were
able to be examined more thoroughly. If the sample had been composed of only one
occupational group or one primary type, an analysis would not have identified important
information regarding differences among occupational groups and among primary Holland types.
Demographic Analysis
An analysis of the demographic data by occupational group indicated significant
differences among occupations on all demographic variables. Those differences on three
variables disappeared when the data were analyzed according to primary Holland type. While it
was not within the scope of this research to examine the relationship between demographic
variables and the congruence – job satisfaction correlation, the sampling method used here did
permit the gathering and analysis of that data in order to provide areas of inquiry for further
research.
Recommendations for Further Research
An interesting finding among the overall demographic data for this sample is that all
variables except Years of Education indicated quite a range of values. Years on Present Job, for
example, yielded an overall mean value of 13.06. With a standard deviation of 10.85,
approximately 68% of the sample reported values between 2.21 years and 23.91 years. Among
occupational groups, mean reported Years on Present Job values ranged from 5.71 years for
Bankers and 19.82 years for Accountants, the two occupational groups that were selected to
represent the Conventional type. Further study may be designed in order to examine
demographic variables in order to assess whether there are significant relationships with the
congruence – job satisfaction correlation. Additional research may uncover information that
provides a clearer picture of the demographic factors that affect these variables. An analysis of
Is Congruence Dead? 94
Years on Present Job, for example, may indicate a meaningful relationship between job tenure
and job satisfaction.
Mean Job Satisfaction Scores
When MSQ scores were analyzed separately, the data for all cases indicated that the
sample tended to report moderately high levels of intrinsic, extrinsic, and overall job satisfaction
regardless of congruence. While an analysis of MSQ scores by occupational group did not show
differences in intrinsic satisfaction scores, some significant differences did appear among the
groups for extrinsic and overall job satisfaction. When the data were collapsed into primary
Holland types, the differences in overall job satisfaction disappeared. The analysis continued to
show mean extrinsic score differences among two of the primary types.
Recommendations for Further Research
The analysis of this study’s MSQ information suggests interesting areas for further
inquiry. When the data were collapsed into primary Holland type, there remained a significant
difference in extrinsic satisfaction between the Social and Enterprising types. Additional
congruence – job satisfaction studies should continue to examine a range of occupational groups
and primary Holland types as relationships between congruence and job satisfaction that are
particular to occupational groups or primary Holland types may be uncovered. For example,
Social occupations such as Social Worker, Licensed Practical Nurse, Elementary School
Teacher, and High School Counselor stereotypically are the ones that tend to be associated
systematically with fewer opportunities for extrinsic satisfaction (e.g., poorer working
conditions, lower pay and benefits, etc.). It could be that congruence – job satisfaction studies
always or almost always will find comparably lower satisfaction scores among Social types.
Is Congruence Dead? 95
Given the limited variability in this study’s MSQ scores, it additionally is recommended
that further research pay particular attention to the potential effects of range restriction among
the data.
Mean Congruence Scores
When mean congruence scores were analyzed separately, an examination of data for all
cases indicated that the decision-derived codes were associated with slightly higher congruence
means, but these differences were not found to be significant. A further examination of mean
congruence scores by occupational group showed significant differences among some of the
occupations when the traditionally-derived codes were used to measure congruence. These
differences disappeared when the data were collapsed into primary Holland type.
Recommendations for Further Research
Similar to the measurement of job satisfaction, additional congruence – job satisfaction
studies should continue to examine a range of occupational groups and primary Holland types in
order to uncover whether there are particular relationships between congruence and job
satisfaction that provide more information to explain the correlation. It may be found that certain
occupations necessarily require higher levels of congruence for successful employment. For
example, while it is difficult to imagine someone who is employed as a musician who does not
also have a high level of Artistic interest, it may be plausible for a retail sales representative to be
successfully employed with only moderate Enterprising interests. It additionally is recommended
that congruence – job satisfaction studies continue to measure congruence in a variety of ways.
The comparison of several methods more readily allows for an analysis regarding whether results
can be considered to be valid or perhaps are more a product of measurement error.
Is Congruence Dead? 96
Congruence – Job Satisfaction Correlations
When all data were analyzed, weak, negative correlations were found between
congruence and extrinsic job satisfaction and between congruence and overall job satisfaction.
An overall relationship between congruence and intrinsic satisfaction was not detected. A further
analysis of the data by occupational group indicated moderate to strong significant negative
relationships between congruence and overall job satisfaction and between congruence and
extrinsic job satisfaction for two of the occupational groups and a strong negative correlation
between congruence and intrinsic job satisfaction for just one of the occupational groups. When
data were collapsed into primary Holland type, a moderate, negative correlation was found
between all facets of job satisfaction and only one primary type.
Recommendations for Further Research
Overall, this study’s analysis of facets of job satisfaction revealed relationships that
would have been hidden had only an overall measure of job satisfaction been used. For example,
while an analysis of all data indicated a weak, negative correlation between congruence and job
satisfaction, a further analysis of intrinsic and extrinsic aspects suggests that it appears to be the
correlation between extrinsic satisfaction and congruence that is contributing more to the
significance of the correlation with overall job satisfaction. It is recommended that congruence –
job satisfaction research continue to measure facets of job satisfaction in order to obtain a clearer
picture of the job satisfaction construct.
Traditionally-Derived and Decision-Derived Holland Summary Codes
Congruence score comparisons of overall data indicated that the decision-derived codes
were associated with slightly higher congruence means. These mean differences were not found
to be significant when compared to traditionally-derived codes. In fact, an analysis of the data by
Is Congruence Dead? 97
occupational group showed that decision-derived codes were associated with lower congruence
means approximately 50% of the time. An analysis of the data by primary Holland type indicated
that decision-derived codes were associated with lower congruence means approximately 30% of
the time. Statistical procedures examining the differences among congruence means when the
decision-derived codes were used did indicate significant differences among means by both
occupational group and by Holland type. Post hoc testing suggested that none of the pairwise
comparisons showed a level of variance large enough to indicate the source of the significant
differences. Moreover, the use of decision-derived codes did not result in any significant
correlations between congruence and job satisfaction.
Statistical procedures examining differences among congruence means when the
traditionally-derived codes were used did indicate significant differences among means by
occupational group, and post hoc testing did detect the source of significant differences.
Moreover, the data indicated that it was only the use of traditionally-derived codes that was
associated with significant correlations between congruence and job satisfaction. This result was
illustrated when correlation data were analyzed according to congruence index and facet of job
satisfaction and by occupational group and primary Holland type.
The better performance of the traditionally-derived codes is surprising given the
methodological limitations that are associated with this approach to coding and Dik, et al.’s
(2007) and Dik & Hansen’s (2004) empirical support of decision-derived codes. There are
several reasons that may explain this finding. This study did correct for previous methodological
limitations by implementing tie-breaking guidelines based on Holland’s assumptions of
consistency. It also should be noted that Dik, et al.’s (2007) research compared four decision-
Is Congruence Dead? 98
derived methods of generating Holland codes without also examining traditionally-derived
codes.
Recommendations for Further Research
It is recommended that congruence research continue to make methodological
refinements in the measurement of vocational personality. Further investigation of the
appropriateness of the SIE as a research instrument is warranted. It is recommended that the SIE
be measured directly against the SII in order to make comparisons regarding the compatibility of
Holland summary codes between the two instruments. Moreover, it is suggested that the SIE
continue to be used in order to generate further standardization data that can be used in the
development of decision-derived coding methods. Finally, this study also indicates support for
additional work regarding the implementation of a summary coding method that is theoretically
based on Holland’s hexagonal assumptions.
The Modified C Index and the Substitution C Index
This study’s findings on the modified C index and the substitution C index are somewhat
equivocal. Overall, the indexes generated almost identical congruence means regardless of
summary coding method. When congruence – job satisfaction correlations were analyzed for all
data, neither index was associated with a significant correlation between congruence and
intrinsic job satisfaction. Both indexes measured a weak negative correlation between
congruence and extrinsic job satisfaction. While the substitution C index correlation was lower,
it was not found to be significantly different from the modified C index correlation. The
modified C index did measure a weak significant negative correlation between congruence and
overall job satisfaction while the substitution C index was not associated with a significant
Is Congruence Dead? 99
correlation at the p = .05 level. The substitution C index correlation was significant at the p = .06
level.
A further analysis of congruence means and congruence – job satisfaction correlations by
occupational group and by Holland type yielded comparable results regarding the similar
performance of the modified C index and the substitution C index. The indexes detected negative
correlations between congruence and facets of job satisfaction for the same occupational groups
and primary Holland types. In cases where the correlations were not identical due to
computationally equivalent results, there were no significant differences. The substitution C
index did measure a moderately significant negative correlation between congruence and overall
job satisfaction among Accountants, while the modified C index did not. The modified C index
correlation was significant at the p = .06 level.
Recommendations for Further Research
Given that this research represents the first empirical study to compare the modified C
index and the substitution C index, further research needs to be conducted before definitive
statements can be made regarding the relative efficacy of these two indexes. As the modified C
index and the substitution C index are computationally equivalent in many cases, it is suggested
that further research focus on where the scores of these two indexes diverge. Additional study
should compare, in particular, the calculation of congruence scores in the cases of one letter x
two letters, two letters x two letters, and two letters x three letters. This may provide a clearer
picture of the differences between the modified C index and substitution C index and permit
recommendations for their use based on the types of congruence calculations are to be
performed.
Is Congruence Dead? 100
IS CONGRUENCE DEAD?
On the whole when all data were analyzed, this study did find a weak, yet significant,
relationship between congruence and overall job satisfaction. The correlation did not reach the
level of significance that was obtained in the meta-analyses by Assouline and Meir (1987),
Tranberg, et al. (1993), or Tsabari, et al. (2005). What is noteworthy is that the correlation found
here between congruence and overall job satisfaction was not in the predicted direction, and
instead was negative. Moreover, the data suggested that it could be a weak, yet significant,
negative relationship between congruence and extrinsic job satisfaction that especially
contributed to this finding. The relationship between congruence and intrinsic job satisfaction
was not found to be significant. What does this mean given Holland’s theory assumes that there
is a positive correlation between congruence and job satisfaction?
The finding of increasing levels of extrinsic satisfaction as levels of congruence decrease
makes logical sense. The concept of congruence as it is reflected in vocational personality
assessments and Holland summary codes tends to be one that emphasizes aspects of intrinsic
satisfaction. If congruence is low, it also is likely that intrinsic job satisfaction will be low.
Individuals must achieve some sense of job satisfaction in order to sustain their employment,
which means an increasing reliance on extrinsic factors for job satisfaction.
The negative correlation between congruence and extrinsic job satisfaction with no
significant corresponding correlation between congruence and intrinsic job satisfaction may
suggest an increasing importance of extrinsic factors over intrinsic factors. This finding makes
sense when one considers contemporary social, economic, technological, legal, and political
shifts that have influenced the contemporary meaning of work.
Is Congruence Dead? 101
We live in a time where the organization of work is changing at “whirlwind speed”
(National Institute for Occupational Safety and Health, 1999). The workforce has experienced
widespread restructuring and downsizing. Employment practices increasingly depend upon
flexible staffing, temporary workers, and contract-supplied labor. Increases in involuntary job
displacement are associated with decreased job stability and delayed retirement. Moreover,
increases in workload, work roles, and work hours now are common experiences (National
Institute for Occupational Safety and Health, 2002).
A series of surveys reported by NIOSH (1999) indicated that 26% to 40% of workers
reported that their jobs were very stressful. It may be that intensifying individual and situational
job stressors are resulting in decreased opportunities to experience the internal motivations such
as autonomy and competence that are necessary for the facilitation of intrinsic job satisfaction
(Ryan & Deci, 2000). Individuals consequently may tend increasingly to seek employment based
on factors of extrinsic satisfaction.
When one considers that the meaning of work has changed significantly and rapidly, it
seems only logical that we might see changes in the nature of the correlation between
congruence and job satisfaction. Therefore, in addressing the issue of whether congruence is
“dead”, the answer may be “no” – as long as we are able to conceptualize that the relationship
between congruence and job satisfaction necessarily must be fluid and reflect changes over time.
We cannot expect congruence to exist in a vacuum if the construct is to continue to be useful to
the research and practice of vocational psychology.
RESEARCH LIMITATIONS
Given that the findings of this study contradict over 40 years of research on Holland’s
congruence construct, it is especially important to acknowledge the methodological limitations
Is Congruence Dead? 102
that may be impacting the results. First of all, the selection of occupational groups from the SII
necessarily represents a restriction in the occupational groups that could be sampled. Moreover,
the comparison of gender-normed GOT codes to ones from a mixed-gender sample further
reduces the generalizability of the results that were obtained here.
Dik, et al. (2007) generated standardized scores for their decision-based rules using years
of SII research data. The use of the SIE in this study necessitated the creation of a standardized
sample that was tested against itself. The conversion from traditionally-derived codes to decision
derived codes further highlighted reasons to suggest that, generally, the use of the SIE may have
been problematic. The basic interest areas that are part of the Social and Realistic scales create a
possible total on each of these scales of 30 points. The basic interest areas that are part of the
Investigative, Artistic, Enterprising, and Conventional scales create a possible total on each of
these scales of 20 points. Given that over half of the traditionally-derived codes reflected Social
and Realistic primary Holland types, the predominance of these types simply may have been a
function of the fact that there were more opportunities to score highly on these scales. The
subsequent decrease among Realistic and Social primary Holland types and increase among
Investigative, Artistic, Enterprising, Conventional types primary Holland types that was
associated with the decision-derived codes further calls into question the validity of the SIE.
It is acknowledged that the method of data gathering that was used here is a limitation of
the study. Participants were individuals who happened to be members of certain professional
organizations with public information membership lists or who were sampled at appropriate
businesses for the sake of convenience. Moreover, participants represented a group of individuals
who all volunteered for this study and who, by their participation, implicitly expressed an interest
in a study about job satisfaction. Analysis and interpretation of the results must be tempered with
Is Congruence Dead? 103
the knowledge that the data, to some degree, reflect those individuals who self-selected to
compose the sample.
Is Congruence Dead? 104
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Wiggins, J. D., & Weslander, D. L. (1979). Tested personality typologies and marital
compatibility. American Mental Health Counselors Association Journal, 1(1), 44 – 52.
Wigington, J. H., & Apostal, R. A. (1973). Personality differences among men in selected Air
Force specialties. Journal of Counseling Psychology, 20(5), 454 – 458.
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Wolfe, L. K., & Betz, N. E. (1981). Traditionality of choice and sex-role identification as
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Johns Hopkins University Center for Social Organization of Schools.
Is Congruence Dead? 127
Appendix A
Compatibility Index
Scale
Score CI Decision Rule 8 The letters and ordering of both codes match exactly (e.g., ASE – ASE). 7 The first letters match. The second and third letters of one code are reversed in the
other code (e.g. ASE – AES), or the first and second letters of both codes match in the same order (e.g., ASE – ASI).
6 All three letters of both codes match, but the first letters are not the same (e.g.,
ASE – SEA). 5 The first letters match, with the second or third letter of one code matching the
third letter of the other code (e.g., ASE – AIS), or the first and second letters match in reverse order (e.g., ASE – SAI), or the first and second letters of one code match the first and third letters of the other code in reverse order (e.g., ASE – SIA).
4 The first and second or third letters of one code match any two letters of the other
code in any order (e.g., ASE – SIA), or the first letter of one code matches the first letter of the other code (e.g., ASE – AIR).
3 The second and third letters of one code are found in the other code in any order
(e.g., ASE – EIS), or the first letter of one code matches the second letter of the other code (e.g., ASE – RAC).
2 The first letter of one code matches the third letter of the other code (e.g., ASE –
RCA), or the second letter of one code matches the second or third letter of the other code (e.g., ASE – IRS).
1 The third letters of both codes match (e.g., ASE – ICE). 0 No letters match in either code (e.g., ASE – CRI).
Calculation
CAE – CRI
The types in the first-letter positions match each other (i.e., C). The second and third letters of the codes (i.e., A, E, R, I) are unique and do not match in any combination. The CI calculation of CAE – CRI therefore equals a congruence score of 4.
Is Congruence Dead? 128
Appendix B
K – P Index
Formula
X = (W1 + W2 + W3)-1 (W1AD + W2BE + W3CF)
Variable Values
X = K-P index congruence value
W1 = Weight assigned to the first-letter position
W2 = Weight assigned to the second-letter position
W3 = Weight assigned to the third-letter position
A = Type in the first-letter position of code 1
B = Type in the second-letter position of code 1
C = Type in the third-letter position of code 1
D = Type in the first-letter position of code 2
E = Type in the second-letter position of code 2
F = Type in the third-letter position of code 2
AD = Value of the hexagonal segment distance between the type in the first-letter position of code 1 and the type in the first-letter position of code 2
BE = Value of the hexagonal segment distance between the type in the second-letter position
of code 1 and the type in the second-letter position of code 2 CF = Value of the hexagonal segment distance between the type in the third-letter position of
code 1 and the type in the third-letter position of code 2
Is Congruence Dead? 129
Table B1 K – P Index Hexagonal Segment Distance Proportion Values
Hexagonal Segment
Distance Proportion
Value
Hexagonal Segment
Distance Proportion
Value
Hexagonal Segment
Distance Proportion
Value A-A 1.0 E-A .35 R-A .16 A-C .11 E-C .68 R-C .36 A-E .35 E-E 1.0 R-E .30 A-I .34 E-I .16 R-I .46 A-R .16 E-R .30 R-R 1.0 A-S .42 E-S .54 R-S .21 C-A .11 I-A .34 S-A .42 C-C 1.0 I-C .16 S-C .38 C-E .68 I-E .16 S-E .54 C-I .16 I-I 1.0 S-I .30 C-R .36 I-R .46 S-R .21 C-S .38 I-S .30 S-S 1.0
Calculation
SEC – SCE
W1 = 4 W2 = 2 W3 = 1 A = S B = E C = C
D = S E = C F = E AD = 1.0 BE = .68 CF = .68
X = (4 + 2 + 1) -1 [(4)SS + (2)EC + (1)CE]
X = (1/7)[(4)1.0 + (2).68 + (1).68]
X = (1/7) [4 + 1.36 + .68]
X = (1/7) (6.04)
X = .8629
Is Congruence Dead? 130
Appendix C
M Index
Tables
Table C1 M Index Two-Letter Code Weights
First Letter Second Letter Other Letters
First Letter 5 2 0 Second Letter 2 1 0
Table C2 M Three-Letter Code Weights
First Letter Second Letter Third Letter Other Letters
First Letter 22 10 4 0 Second Letter 10 5 2 0 Third Letter 4 2 1 0
Calculation
REC – CIR
• The type in the first-letter position of the first code matches the type in the third-letter position of the second code (i.e., R). This combination has a weighted value of 4.
• The type in the third-letter position of the first code matches the type in the first-letter
position of the second code (i.e., C). This combination has a weighted value of 4.
• There are no other pairs of matching types within the two codes.
M = R1R3 + C3C1
M = 4 + 4
M = 8
REC – CIR = 8
Is Congruence Dead? 131
Appendix D
Sb Index
Step 1
Determine which summary codes will be examined. For example, RIASEC profile scores may be 14, 12, 3, 0, 5, and 5, respectively. As the scores for R and I are relatively higher than the scores for A, S, E, and C, it seems most reasonable to consider this code to be RI. Here, for purposes of the example, RI will be compared to the code IEA.
Step 2
Assign vector values. Each summary code is assigned values to the types that appear in the respective codes. A value of 0 is assigned to the types that do not appear in the codes, and a value of 1 is assigned to the types that do appear in the codes. Additionally, in this example, here the code RI has been assigned as code x and the code IEA has been assigned as code y in order to facilitate later calculations:
Vector for Code RI (code x) Vector for Code IEA code (y)
R = 1 R = 0 I = 1 I = 1 A = 0 A = 1 S = 0 S = 0 E = 0 E = 1 C = 0 C = 0
Formula
Sb = αC + L – D
Variable Values
α = Weighting parameter equal to the relative number of shared types between codes
C = Relative number of types common to both codes defined as
K .. K + I + J
K = Number of common types between codes (i.e., the number of types common to both profiles that have a vector value of 1).
I = Number of unshared types in code x (i.e., the number of types that have a vector value of 1 in code x and a vector value of 0 in code y).
Is Congruence Dead? 132
J = Number of unshared types in code y (i.e., the number of types that have a vector value of 1 in code y and a vector value of 0 in code x).
L = Positive constant added to the Sb index in order to prevent negative values. Equal to the value of the largest possible distance between two types.
D = Mean distances between the unshared types defined as
ΣiΣjd(xi,yj) + βΣiΣkd(xiyk) + γΣjΣkd(xkyj)
(I x J) + K x (I + J)
β = Weighting parameter
γ = Weighting parameter
ΣiΣjd(xi,yj) = Sum of the distances between the unshared types in code x and the unshared types in code y.
ΣiΣkd(xiyk) = Sum of the distances between the unshared types in code x and the
shared types in code y.
γΣjΣkd(xkyj) = Sum of the distances between the shared types in code x and the unshared types in code y.
Table D1 Sb Index Distances
Holland Type R I A S E C
R --- --- --- --- --- ---
I 1 --- --- --- --- ---
A 2 1 --- --- --- ---
S 3 2 1 --- --- ---
E 2 3 2 1 --- ---
C 1 2 3 2 1 ---
Is Congruence Dead? 133
Calculation
RI – IEA
α = 1 C = ¼
K = 1 I = 1 J = 2 C = 1 .. = 1/4
1 + 1 + 2 L = 3
D = 1 β = 1
γ = 1 ΣiΣjd(xi,yj) = 4 ΣiΣkd(xiyk) = 1 γΣjΣkd(xkyj) = 4
D = 4 + (1)(1) + (1)(4) D = 4 + 1 + 4 D = 9 D = 1 (1 x 2) + 1 x (1 + 2) (2 + 1) x 3 9
Is congruence dead?
135
Appendix E
The C Index
Formula
C = (3)(Xi) + (2)(Xi) + (1)(Xi)
Variable Values
Xi = Hexagonal distances between pairs of Holland types Table E1 Distances between Holland Types Used in the Calculation of the C Index
Holland Type R I A S E C
R 3 --- --- --- --- --- I 2 3 --- --- --- --- A 1 2 3 --- --- --- S 0 1 2 3 -- -- E 1 0 1 2 3 -- C 2 1 0 1 2 3
Calculation
AEI – CAE
Xi
A – C = 0
E – A = 1
I – E = 0
C = (3)(AC) + (2)EA) + (1)(IE)
C = (3)(0) + (2)(1) + (1)(0)
C = 0 + 2 + 0
C = 2
Is congruence dead?
136
Appendix F
The Modified C Index
Case 1: Three Letters x Three Letters
Formula
C3x3 = 3 ( X1Y1) + 2 ( X2Y2) + 1 ( X3Y3)
Example
The modified C index and the C index are computationally equivalent in this case. Mathematical modification of the C index is not necessary. The two indexes yield identical scores.
Case 2: Two Letters x Two Letters
Formula
In this case, the expression
Ccase 2 = 3 ( X1Y1) + 2 ( X2Y2)
represents the comparison of two two-letter codes according to the modified C index model. Calculation using the same values that are used for the C3x3 index could equal only a maximum value of 15, however. Eggerth and Andrew (2006) explain that perfect congruence between two-letter profiles should count for the same as perfect congruence between three-letter profiles (i.e., a value of 18). A multiplicative scaling constant of 18/15 is added to this formula in order to put the C2x2 index on the same metric with the C3x3 index:
C2x2 = 18/15 [3 ( X1Y1) + 2 ( X2Y2)]
Example
AE – CA
Variable Values
X1Y1 = Hexagonal distance value between A and C is 0.
X2Y2 = Hexagonal distance value between E and A is 1.
Is congruence dead?
137
Calculation
C2x2 = 18/15 [3 (AC) + 2 (EA)]
C2x2 = 18/15 [3(0) + 2(1)]
C2x2 = 18/15 (0 + 2)
C2x2 = 18/15 (2)
C2x2 = 2.4
Case 3: One Letter x One Letter
Formula
Similar to Case 2, the expression
Ccase 3 = 3 ( X1Y1)
could have a maximum value of only 9 using the same values that are used for the C3x3 index. A multiplicative scaling constant of 18/9 is added, which reduces to a value of 2:
C1x1 = 2 [3 ( X1Y1)]
which can be reduced further to
C1x1 = 6 ( X1Y1)
Example
A – A
Variable Values
X1Y1 = Hexagonal distance value between A and A is 3.
Calculation
C1x1 = 6 (AA)
C1x1 = 6 (3)
C1x1 = 18
Is congruence dead?
138
Case 4: Three Letters x One Letter
Formula
In this case, the type that makes-up the one-letter code “stands for” the second- and third-letter positions so that it can be compared to a three-letter summary code:
C3x1 = 3 ( X1Y1) + 2 ( X2Y1) + 1 ( X3Y1)
Example
S - SER
Variable Values
X1Y1 = Hexagonal distance value between S and S is 3.
X2Y1 = Hexagonal distance value between S and E is 2.
X3Y1 = Hexagonal distance value between S and R is 0.
Calculation
C3x1 = 3 (SS) + 2 (SE) + 1 (SR)
C3x1 = 3 (3) + 2 (2) + 1 (0)
C3x1 = 9 + 4 + 0
C3x1 = 13
Case 5: Two Letters x One Letter
Formula
The C2x1 index combines the rationales of the C2x2 index and the C3x1 index. A multiplicative scaling constant of 18/15 is added, and the type that makes-up the one-letter code “stands for” the second-letter position:
C2x1 = 18/15 [3 (X1Y1) + 2 (X2Y1)]
Example
CR – C
Is congruence dead?
139
Variable Values
X1Y1 = Hexagonal distance value between C and C is 3.
X2Y1 = Hexagonal distance value between R and C is 2.
Calculation
C2x1 = 18/15 [3 (CC) + 2 (RC)]
C2x1 = 18/15 [3 (3) + 2 (2)]
C2x1 = 18/15 (9 + 4)
C2x1 = 18/15 (13)
C2x1 = 15.6
Case 6: Three Letters x Two Letters
Formula
This case necessitates the use of a weighted composite of the types that compose the two-letter summary code. This value accounts for the “missing” third-letter position in the two-letter code. As the C index uses the weights 3 and 2 for the first and second code letter positions, the modified C index weighting ratio of the first-letter type to the second-letter type is 3:2:
WC = 1 {1/5 [3 (X3Y1) + 2 (X3Y2)]}
The substitution of the WC value into the third-letter position results in the formula:
C3x2 = 3 (X1Y1) + 2 (X2Y2) + 1 {1/5 [3 (X3Y1) + 2 (X3Y2)]}
Example
IA – CAI
Variable Values
X1Y1 = Hexagonal distance value between I and C is 1.
X2Y2 = Hexagonal distance value between A and A is 3.
X3Y1 = Hexagonal distance value between I and I is 3.
X3Y2 = Hexagonal distance value between I and A is 2.
Is congruence dead?
140
Calculation
C3x2 = 3 (IC) + 2 (AA) + 1 {1/5 [3 (II) + 2 (IA)]}
C3x2 = 3 (1) + 2 (3) + 1 {1/5 [3 (3) + 2 (2)]}
C3x2 = 3 + 6 + 1 [(1/5) (9 + 4)]
C3x2 = 3 + 6 + 1 [(1/5) (13)]
C3x2 = 3 + 6 + (1) (2.6)
C3x2 = 3 + 6 + 2.6
C3x2 = 11.6
Is congruence dead?
141
Appendix G
The Substitution C Index
Case 1: Three Letters x Three Letters
Formula
C3x3 = 3 ( Xi) + 2 ( Xi) + 1 ( Xi)
Example
The C index and the substitution C index are computationally equivalent in this case. The two indexes yield identical scores.
Case 2: Two Letters x Two Letters
Example
AE – CA
A is substituted in the third-letter position in code AE. C is substituted in the third-letter position in code CA:
AEA – CAC
Variable Values
Xi = Hexagonal distance value between A and C is 0.
Hexagonal distance value between E and A is 1.
Calculation
C = (3) (AC) + (2) (EA) + (1) (AC)
C = (3) (0) + (2) (1) + (1) (0)
C = 0 + 2 + 0
C = 2
Is congruence dead?
142
Case 3: One Letter x One Letter
Example
A – A
In both codes, A is substituted in the second-letter and third-letter positions:
AAA – AAA
Variable Values
Xi = Hexagonal distance value between A and A is 3.
Calculation
C = (3)(AA) + (2)(AA) + (1)(AA)
C = (3)(3) + (2)(3) + (1)(3)
C = 9 + 6 + 3
C = 18
Case 4: Three Letters x One Letter
Example
S - SER
S is substituted in the second-letter and third-letter positions in code S:
SSS – SER
Variable Values
Xi = Hexagonal distance value between S and S is 3.
Hexagonal distance value between S and E is 2.
Hexagonal distance value between S and R is 0.
Is congruence dead?
143
Calculation
C = (3)(SS) + (2)(SE) + (1)(SR)
C = (3)(3) + (2)(2) + (1)(0)
C = 9 + 4 + 0
C = 13
Case 5: Two Letters x One Letter
Example
CR – C
C is substituted for the third-letter position of code CR. C is substituted for the second-letter and third-letter positions of code C:
CRC – CCC
Variable Values
Xi = Hexagonal distance value between C and C is 3.
Hexagonal distance value between R and C is 2.
Calculation
C = (3)(CC) + (2)(RC) + (1)(CC)
C = (3)(3) + (2)(2) + (1)(3)
C = 9 + 4 + 3
C = 16
Case 6: Three Letters x Two Letters
Example
IA – CAI
I is substituted for the third-letter position of code IA:
IAI – CAI
Is congruence dead?
144
Variable Values
Xi = Hexagonal distance value between I and C is 1.
Hexagonal distance value between A and A is 3.
Hexagonal distance value between I and I is 3.
Calculation
C = (3)(IC) + (2)(AA) + (1)(II)
C = (3)(1) + (2)(3) + (1)(3)
C = 3 + 6 + 3
C = 12
Is congruence dead?
145
Appendix H
Steps for Selection of Occupational Groups
Step 1
GOT codes were sorted according to their primary type. This step resulted in the following breakdown: Realistic = 35, Investigative = 46, Artistic = 45, Social = 40, Enterprising = 44, and Conventional = 34.
Step 2
GOT codes were arranged according to whether the female and male codes of the occupation had the same primary type. This step resulted in the elimination of 20 codes and the following breakdown according to the remaining codes: Realistic = 28, Investigative = 42, Artistic = 43, Social = 38, Enterprising = 43, and Conventional = 30.
Step 3
The GOT codes were organized according to whether the female and male codes of the occupation were identical. This step resulted in the elimination of 104 codes and the following breakdown according to the remaining 120 identical GOT codes: Realistic = 10, Investigative = 16, Artistic = 30, Social = 18, Enterprising = 24, and Conventional = 22.
Step 4
Pairs of male and female GOT standard scores were compared in order to determine which pairs of codes were most similar according to mean scores. Pairs of codes where there was at least one instance of a more than 5 point difference (i.e., more than half of a standard deviation) between types were identified and eliminated. The scales for Engineering Technician, Urban and Regional Planner, Editor, ESL Instructor, Rehabilitation Counselor, Top Executive, Retail Sales Representative, Financial Analyst, and Financial Manager were eliminated at this point in the study as these are new occupational groups, and appropriate gender-normed GOT mean scores are not provided in the updated (i.e., 2005) technical manual. This step resulted in the elimination of 20 codes and the following breakdown according to the remaining 50 pairs of male and female identical GOT codes: Realistic = 6, Investigative = 16, Artistic = 24, Social = 16, Enterprising = 20, and Conventional = 18.
Step 5
The selection of the final 12 occupational groups was based on further minimizing differences between pairs of gender-normed mean GOT scores. Realistic considerations regarding occupational group accessibility also were considered.
Is congruence dead?
146
Appendix I
Strong Interest Explorer Directions and Items
Directions
The next three pages list many different jobs, school subjects, and activities. If you like an item, place an X in the box next to the item. If you do not like an item, leave the box empty. It does not matter how many or how few items you like. Do not stop to total your score. When considering a job, school subject, or activity, don’t worry about whether you would be good at it or concern yourself about not being trained for it. This is not a test of your abilities. And don’t think about how much money you would make or whether you could get ahead. There are no right or wrong answers. Give the first answer that comes to mind and work quickly, but consider each item.
Items
Accounting Biologist Algebra Chemistry
Creating a budget Dentist Geometry Determining the cause of a disease Making statistical charts Examining blood samples under a microscope Mathematician Medical doctor
Mathematics Paramedic Statistics Performing scientific experiments Using a calculator Watching an open heart operation Using math to solve problems X-ray technician Drama Author of novels Actor / actress Editing a paper Art English composition Artist Journalism Cartoonist Literature Illustrator Making a speech Musician Newspaper reporter Performing in a musical Poet Sculptor Writing Singing in a choir Writing a one-act play Bilingual teacher Counseling distressed individuals Creating harmony among ethnic groups Day-care worker Cultural relations Helping others overcome their difficulties Ethnic studies Providing spiritual counseling Helping immigrants adapt to a new culture School counselor Improving racial understanding School nurse Learning about cultural differences Serving as a foster parent Learning about gender differences Social worker Working for cultural diversity Special education teacher
Is congruence dead?
147
Working in international relations Volunteering for community service Being a teaching assistant Debating a political opponent College professor Discussing politics Education Government High school teacher Governor of a state Instructing people in a new method Judge Leading a discussion group Lawyer Preparing lesson plans Political science School principal Politician Teaching Providing legal advice to a clients Training new employees Persuading a jury Advertising executive Managing business / office work Business management Office manager Displaying merchandise in a store Project manager Earning an income based on commission Planning and organizing a detailed event Hotel manager Scheduling tasks for a project Marketing Tracking inventory Sales Using an electronic organizer Sales manager Using computer spreadsheets Tracking a company’s profits and losses Word processing Trading stocks Working with new office equipment Computer programming Agriculture Computer science Training animals Constructing a website Working outdoors Fixing computer hardware problems Environmental science Installing computer software Fish and wildlife management Managing a computer database Forester Networking computer systems Landscape designer Providing technical support Nature study Setting up a new computer Planting natural grasses in a park reserve Using computer-aided design software Raising flowers and vegetables Architectural drafting Examining a crime scene Building contractor Firefighter Building projects Learning the proper use of firearms Carpenter Military training Civil Engineer Police officer Designing bridges and roads Private investigator Industrial arts Providing security for a concert Mechanical drafting Rescuing climbers on a mountain Reading a blueprint Secret service agent Woodworking Security guard
Is congruence dead?
148
Appendix J
Strong Interest Explorer Items by RIASEC Type and Scale
REALISTIC INVESTIGATIVE Outdoor, Environment, Plants, and Animals Working with Numbers
Agriculture Accounting Training animals Algebra Working outdoors Creating a budget Environmental science Geometry Fish and wildlife management Making statistical charts Forester Mathematician Landscape designer Mathematics Nature study Statistics Planting natural grasses in a park reserve Using a calculator Raising flowers and vegetables Using math to solve problems Construction and Engineering Health and Science
Architectural drafting Biologist Building contractor Chemistry Building projects Dentist Carpenter Determining the cause of a disease Civil Engineer Examining blood samples under a microscope Designing bridges and roads Medical doctor Industrial arts Paramedic Mechanical drafting Performing scientific experiments Reading a blueprint Watching an open heart operation Woodworking X-ray technician Protective Services
Examining a crime scene Firefighter Learning the proper use of firearms Military training Police officer Private investigator Providing security for a concert Rescuing climbers on a mountain Secret service agent Security guard
Is congruence dead?
149
ARTISTIC SOCIAL Music and Arts Cultural Relations
Drama Bilingual teacher Actor / actress Creating harmony among ethnic groups Art Cultural relations Artist Ethnic studies Cartoonist Helping immigrants adapt to a new culture Illustrator Improving racial understanding Musician Learning about cultural differences Performing in a musical Learning about gender differences Sculptor Working for cultural diversity Singing in a choir Working in international relations Writing and Mass Communications Helping Others
Author of novels Counseling distressed individuals Editing a paper Day-care worker English composition Helping others overcome their difficulties Journalism Providing spiritual counseling Literature School counselor Making a speech School nurse Newspaper reporter Serving as a foster parent Poet Social worker Writing Special education teacher Writing a one-act play Volunteering for community service Teaching and Training
Being a teaching assistant College professor Education High school teacher Instructing people in a new method Leading a discussion group Preparing lesson plans School principal Teaching Training new employees
Is congruence dead?
150
ENTERPRISING CONVENTIONAL Law and Politics Office and Project Management
Debating a political opponent Managing business / office work Discussing politics Office manager Government Project manager Governor of a state Planning and organizing a detailed event Judge Scheduling tasks for a project Lawyer Tracking inventory Political science Using an electronic organizer Politician Using computer spreadsheets Providing legal advice to a client Word processing Persuading a jury Working with new office equipment Business, Sales, and Marketing Working with Computers
Advertising executive Computer programming Computer Programming Business management Computer science Displaying merchandise in a store Constructing a website Earning an income based on commission Fixing computer hardware problems Hotel manager Installing computer software Marketing Managing a computer database Sales Networking computer systems Sales manager Providing technical support Tracking a company’s profits and losses Setting up a new computer Trading stocks Using computer-aided design software
Is congruence dead?
151
Appendix K
Short-Form Minnesota Satisfaction Questionnaire Directions and Items
Excerpt from Directions
Read each statement carefully. Decide how satisfied you feel about the aspect of your job described by the statement. Keeping the statement in mind: - if you feel that your job gives you more than you expected, check the box under “Very Sat.”
(Very Satisfied); - if you feel that your job gives you what you expected, check the box under “Sat.” (Satisfied); - if you cannot make up your mind whether or not the job gives you what you expected, check
the box under “N” (Neither Satisfied nor Dissatisfied); - if you feel that your job gives you less than you expected, check the box under “Dissat.”
Dissatisfied); - if you feel that your job gives you much less than you expected, check the box under “Very
Dissat.” (Very Dissatisfied).
Items by Facet Satisfaction Scale and MSQ Long-Form Scale On my present job, this is how I feel about. . . Very Very Dissat. Dissat. N Sat. Sat. I = Intrinsic Satisfaction Scale E = Extrinsic Satisfaction Scale G = General Satisfaction Scale 1. Being able to keep busy all the time (I, G; Activity) 2. The chance to work alone on the job
(I, G; Independence)
3. The chance to do different things from time to time (I, G; Variety)
4. The chance to be “somebody” in the community
(I, G; Social Status)
5. The way my boss handles his/her workers (E, G; Supervision-human relations)
Is congruence dead?
152
6. The competence of my supervisor in making decisions
(E, G; Supervision-technical)
7. Being able to do things that don’t go against my conscience (I, G; Moral values)
8. The way my job provides for steady employment
(I, G; Security) 9. The chance to do things for other people
(I, G; Social Service) 10. The chance to tell people what to do
(I, G; Authority) 11. The chance to do something that makes use of my abilities
(I, G; Ability utilization) 12. The way company policies are put into practice
(E, G; Company policies and practices) 13. My pay and the amount of work I do
(E, G; Compensation) 14. The chances for advancement on this job
(E, G; Advancement) 15. The freedom to use my own judgment
(I, G; Responsibility) 16. The chance to try my own methods of doing the job
(I, G; Creativity) 17. The working conditions
(G; Working conditions) 18. The way my co-workers get along with each other
(G; Co-workers) 19. The praise I get for doing a good job
(E; Recognition) 20. The feeling of accomplishment I get from the job
(I; Achievement)
Is congruence dead?
153
Short-Answer Items
Today’s Date ____________________ Check One: male female When were you born? _____________ Circle the number of years of schooling you completed:
4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Grade School High School College Graduate or
Professional School What is your present job called? ______________________________________________ What do you do on your present job? __________________________________________ How long have you been on your present job? ____________ years ____________ months What would you call your occupation, your usual line of work? _____________________ How long have you been in this line of work? _____________ years ____________ months
Is congruence dead?
154
Appendix L
Professional Organizations and Businesses Corresponding to the Occupational Groups
Table L1
Occupational Group Professional Organizations and Businesess
Accountant Directory of Certified Public Accountants Kennett & Kennett P.C., Roanoke, VA
Attorney
American Bar Association Lawyer Locator Virginia Lawyers Directory
Cranwell, Moore & Emick, PLC, Roanoke, VA
Banker
National Bankers Association SunTrust Banks, Inc., Roanoke, VA
Bank of America, Roanoke, VA First Market Bank, Roanoke, VA
Engineer
National Society of Professional Engineers NIOSH, Cincinnati, OH
Florist
American Academy of Floriculture
Creative Occasions Florals & Fine Gifts, Roanoke, VA Flowers & Things, Inc., Roanoke, VA
Kroger, Roanoke, VA
Forester
USDA Forest Service
Librarian
Public Library Directory
Licensed Practical Nurse
National Federation of Licensed Practical Nurses State of Georgia professional licenses
Carilion Family Medicine, Troutville, VA Asthma & Allergy Center, Roanoke, VA
Medical Technologist American Medical Technologist state societies
Psychologist APA Help Center Psychologist Locator
Real Estate Agents National Association of Realtors® Old Colony Company Realtors®, Morgantown, WV
Howard Hanna Premier Properties, Morgantown, WV
Social Worker
NASW Register of Clinical Social Workers Dr. Lewis Weber & Associates, Charlottesville, VA
Wellspring Family Services, Morgantown, WV
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Appendix M
Introductory Cover Letter Mailed to Potential Participants
[Address]
[Date] Dear [Addressee]: I am a doctoral candidate in the Department of Counseling, Rehabilitation Counseling, and Counseling Psychology in the College of Human Resources and Education at West Virginia University in Morgantown, WV. Currently I am completing my dissertation research under the supervision of my faculty advisor, Roy H. Tunick, Ed.D., CRC. I am writing to ask you to participate in my study. I am interested in finding out whether [occupational group name] like you experience higher levels of job satisfaction when their interests match their job duties. In the envelope you received, you should find the following contents:
• Two copies of the form Consent for Participation in a Study of Work Interests and Job Satisfaction.
• Two questionnaires: the Strong Interest Explorer, and the Minnesota Satisfaction Questionnaire.
• A pre-paid, return envelope.
Please review the Consent for Participation in a Study of Work Interests and Job Satisfaction form. If you decide that you would like to participate in this study, please initial and sign one copy of the form and send it back to me in the return envelope. Keep the other copy and this letter for your records. Complete the two questionnaires that are inside the envelope. You may take them in any order you wish. Please DO NOT put your name on any part of the materials or the envelope. DO NOT score the questionnaires. Please put a signed copy of the Consent for Participation in a Study of Work Interests and Job Satisfaction form and the two completed questionnaires back in the pre-paid envelope, seal it, and return it to me in the mail. Thank you for your considering to participate in my research. Sincerely, Shannon M. Bowles, M.Ed., NCC
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Appendix O
Reminder Letter Mailed to Participants
[Address]
[Date]
Dear [Addressee], I have yet to receive your questionnaire materials regarding whether [occupational group name]
like you experience higher levels of job satisfaction when their interests march their job duties. If
you already have sent them, thank you, and please disregard this letter. If you have not yet sent
them back to me, please consider whether you would like to participate in my dissertation
research. Remember that your decision to participate is completely voluntary, and there is no
penalty for not participating.
Sincerely, Shannon M. Bowles, M.Ed., NCC
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Appendix P
Rules for Resolving Tied SIE Scores
Tie for First-Letter and Second-Letter Positions
The first-letter and second-letter positions are ordered according to the type that is most consistent with the type in the third-letter position.
Tie for Second-Letter and Third Letter Positions
The second-letter and third-letter positions are ordered according to the type that is most consistent with the type in the first-letter position.
Tie for Third-Letter Position
The third-letter position is ordered according to the type that is most consistent with the type in the second-letter position.
Ties of Equal Consistency
Ties of equal consistency are ordered according to their consecutive appearance in the RIASEC order. While it is recognized that this method may seem arbitrary, some decision guideline needs to be in place in the event that ties of equal consistency are incurred.
Ties among More Than Two Positions
Ties among more than two positions are arranged according to which order represents the highest possible degree of consistency between types.
Ties of Equal Consistency among More Than Two Positions
Ties of equal consistency among more than two positions are ordered according to their consecutive appearance in the RIASEC order.
Ties that Cannot Otherwise be Resolved
In the event that ties cannot be resolved with the above consistency and RIASEC order guidelines, decide ties based on the ordering that is most consistent with the occupational group GOT code.
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Appendix Q
Rules for Generating Decision-Derived Holland Codes
Decision Step 1
Identify the T-scores with a value of 60 or higher. Assign the summary code types according to descending T-score values.
Decision Step 2
If no T-scores are at least 60, identify the T-scores with values between 55 and 59. Assign the summary code types according to descending T-score values.
Decision Step 3
If no T-scores are at least 55, identify the T-scores with values between 50 and 54. Assign the summary code types according to descending T-score values.
Decision Step 4
If more that three T-scores can be identified in the previous steps, assign the summary code according to only the three highest values.
Decision Step 5
If no T-scores are at least 50, identify the T-score with the highest value. Assign the summary code according to the type corresponding with the highest value.