Career profiles of Black adult male substance abuse felons using Holland's theory RIASEC.pdf

PROJECT DEMONSTRATING EXCELLENCE

Career Profiles>&f Blade Admit Male Substance Abusev Felons Using Holland's Theory "MIASEC

fey

Carolyn Brown Shrewsbury

Submitted in partial fulfillment of the Requirements for the Degree of

Doctor of Philosophy with a concentration in Clinical Psychology

May 13,2007

Core Faculty Advisors Lawrence J, Ryan, Ph,B.

Union Institute & University Cincinnati, Ohio

UMI Number: 3326015

Copyright 2008 by

Shrewsbury, Carolyn Brown

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Acknowledgements

Jerry, my husband, you have again proven that patience really is a virtue.

I'm grateful for the patience and understanding you have shown, over the last 44 years of

our marriage. You have demonstrated amazing tolerance, especially during the long

process of completing my doctoral degree. Dr. Ronald Klein, my friend and mentor

made it possible to finish my degree. You encouraged me to reach out for what I

believed was an impossible dream. You have been there from the beginning, through

many protracted challenges when I was ready to give up. You and Jerry have always had

more faith in me than I had for myself. Dr. Larry Ryan, you were the one person from

Union Institute and University that accepted the responsibility to pick up all the

disjointed pieces of my program, and put them together, which resulted in the

culmination of my graduation as a Clinical Psychologist. Jerry, Dr. Klein, and Dr. Ryan,

you have performed "above the call of duty," for which I am truly grateful. Dr. Norman

Kane, you have always been there whenever your help was needed, as a friend,

committee member, and later as a supervisor. This goal could never have been reached

without the encouragement and inspiration of my children and their partners, Lorajean,

Brian, and Barbara. There has also been the help of my grandchildren; Brandon,

Meredith, Lauren, Derek, Adam, Kellen, Abby, Laura, Hayley, and Drake. Special thanks

goes to my mother-in-law, Adeline Shrewsbury, who at 95 demonstrates the importance

of living each day that God gives us to the fullest.

In Memory of

Dr. Noel Markwell, (1st. Core) Dr. Chuck Sells 2nd Core

Ruth and Earl Brown (my parents), and Edmond Shrewsbury (my father-in-law)

Abstract

Project Demonstrating Excellence (Dissertation)

Career Profiles of Black Adult Male Substance Abuse Felons Using

Holland's Theory "RIASEC" Classification: A post facto study.

The researcher employed an ex post facto design that was guided by past and

present theoretical and empirical data and by specific research hypotheses. Thus, the

research hypotheses were derived from logical and empirical findings. The study

participants were Black males from a Mid-Atlantic inner city correctional treatment

facility, including substance abuse felons with a history of criminal recidivism.

Participants were from the prison substance abuse treatment program and inmates that

could not read or write did not participate. Six psychosocial instruments were employed

for test differences six groups of inmates classified according to the Holland RIASEC

theory. Each participant was classified using the Holland single letter code of

identification to divide the population into the six groups. The SDS indicated that there

were no Investigative [I] single letter codes in the population; therefore, only five groups

were tested. The instruments used were the Structured Clinical Interview, Holland's Self-

Directed Search, Career Attitudes and Strategies Inventory, verbal sub-tests (information,

comprehension, vocabulary, and similarities) of the Wechsler Adult Intelligence Scale R

(VICS), Rorschach Inkblot Method, and the Millon Clinical Inventory-II. A scale was

developed for this population to evaluate the quality of career development and quantity

of work experience the inmates had participated within the community. Through the use

of several expert judges the specific continuum of classification (numerical values) for

each group was established. The psychosocial variables were examined to determine if

they could significantly differentiate between the groups under investigation. The results

indicated that the sample had varied career personalities. The largest HSLC group was

Social (68) and the smallest was Investigative (0). A large majority of the sample fell in

the below average range of verbal (VCIS) intelligence and were ambient in their

decision-making skills. The Egocentricity Index varied according to HSLC. The MCMI-

II Cluster "B" (DSM-R) indicated that antisocial, compulsive personality, anxiety, and

thought disorder had a positive relationship with the population and HSLC. The CASI

scales demonstrated that the inmates had a dominant work style and good job satisfaction

in their jobs, even though most had no work history. The Quality and Quantity of Work

the inmates reported indicated satisfaction with both the low Quality and Quantity of

Work experience. The data were discussed in terms of potential problems for vocational

counseling and making changes in the attitude of work in the community

TABLE OF CONTENTS

Page

CHAPTER I. THE PROBLEM 1

Introduction 1

Assumptions 6

Definitions and Operational Terms 8

Delimitation 10

Reasons for Research 12

CHAPTER II REVIEW OF THE LITERATURE 14

The Impact of IQ and Education on Career Development 14

Career Development in "at risk" Populations 17

The Value of Vocational Inventories in Career

Development and Maturity 21

Job Satisfaction 26

Psychological Disorders and Its Impact on

Career Development 3 0

Substance Abuse Leading to Criminal Behavior and Recidivism—* 39

Race, Sex, and Test Bias 46

Literature Review Integration 49

CHAPTER III METHODOLOGY 51

Design of the Study 51

Population 52

IV

Sample 52

Procedures and Techniques 52

Instrumentation 58

Hypotheses 61

Data Collection 63

Statistical Treatment 64

Significance of the Study 66

Limitations 67

CHAPTER IV RESULTS OF THE STUDY 69

Section 1- Research hypothesis related to HSLC classification 70

Section 2- Research hypothesis related to (VICS) IQ levels 75

Section 3- Research hypotheses related to Rorschach Ink Blot Method (EB and Egocentricity Index HSLC classifications 81

Section 4- Research hypotheses related to HSLC and the scales according to the MCMI-II 87

Section 5- Research hypotheses related to CASI sub-tests and predicting HSLC classifications 101

Section 6- Research hypotheses related to the CASI and predicting Quality and Quantity of Work 103

Section 7- Research hypotheses related the HSLC Classification to the CASI Sub-test and Job Satisfaction and Quality and Quantity of Work within the community 105

Section 8- Summary 109

CHAPTER V SUMMARY, CONCLUSIONS, AND RECOMMENDATION— 111

Summary of the Study 111

V

Statement of the Problem 111

Statement of Procedures 112

Research Hypotheses Used 113

Conclusions 114

Area One: The division of inmates into groups classified using Holland's Theory of single letter code career classification (HSLC). 114

Area Two: Intelligence levels within the classified groups according to HSLC. — 118

Area Three: Rorschach EB styles (extratensive, ambitent, introversive) and the prediction ability of the HSLC in the sample. 119

Area Four: The ability of the MCMI-II Personality Clusters (A,B,C) according to the DSM-R, Clinical Personality Patterns, Severe Clinical Pathology, Clinical Syndromes, and Severe Syndromes to predict the HSLC of the classified inmate population. 122

Area Five: The CASI and its relationship with the HSLC in the classified sample. 126

Area Six: The CASI scale Job Satisfaction and its relationship with the Quality and Quantity of Work within the community in the HSLC sample of inmates. 127

Implications 129

Recommendations 131

REFERENCES 133

APPENDIX A — 154

Structured Clinical Interview 155

VI

APPENDIX B 166

Figure 1.1 The divisions in the pie chart equal the number of inmates classified in each of the HSLC 167

APPENDIX-C 168

Figure 2.1 The figure shows that most of the HSLC classified inmates ranged in intelligence level from Borderline (VICS) IQ (70-79) to Average (VISC) IQ (90-109) 169

APPENDIX -D 170

Table 3.1- HSLC classification and correlation with Rorschach EB style of decision-making 171

Figure 3.1- HSLC and Rorschach EB Score 172

APPENDDC -E 173

Table 4.2- HSLC- Realistic Classification on Egocentricity Scale 174

Table.4.3 - HSLC- Artistic Classification on Egocentricity Scale 175

Table 4.4 - HSLC- Social Classification on Egocentricity Scale 175

Table 4.5- HSLC- Enterprising Classification on Egocentricity Scale 177

Table 4.6- HSLC- Conventional Classification on

Egocentricity Scale 178

APPENDIX ~F 179

Figure 4.1- The percentages of HSLC Realistic (R) classification and where the inmates place on the Egocentricity Index. 180

Figure 4.2- The percentages of HSLC Artistic (A) classification and where the inmates place on the Egocentricity Index. 181

vn

Figure 4.3- The percentages of HSLC Social (S) classification and where the inmates place on the Egocentricity Index. 182

Figure 4.4- The percentages of HSLC Enterprising (E) classification and where the inmates place on the Egocentricity Index. 183

Figure 4.5- The percentages of HSLC Conventional (C) classification and where the inmates place on the Egocentricity Index 184

APPENDIX - G-— 185

Table 5.1- Any significant relationship between the HSLC

group and MCMI-II cluster "A" (DSM-R) 186

APPENDIX - H 187

Table 5.2 - Any significant relationship between the HSLC group and MCMI-II cluster "B" (DSM-R) 188

Figure 5.1- The results of the MCMI-II personality scale on the sample population for Antisocial 189

Figure 5.2- Uustrates by symbol and colors the number of Inmates and their level of Antisocial Disorder within their HSLC Classification- — 190

APPENDLX-1 191

Table 5.4- Any significant relationship between the HSLC

group and MCMI-II cluster "C" (DSM-R) 192

APPENDLX- J —- 193

Table 6.1- Any significant relationship between the HSLC group and the Clinical Personality Patterns 194

Figure 6.1- The level of Compulsive personality style within the HSLC sample population. 196

Figure 6.2- Where each of the HSLC classified inmates fell on the Compulsive scale. 197

vm

Table 6.2- Correlation coefficients of MCMI-II Compulsive sub-test and MCMI-II validity scales 198

Table 6.3- The measure of variance that can be explained

by a proposed factor 199

Table 6.4- The "loading" on each factor of the factor 200

APPENDIX- K- 202

Table 8.1- Illustrates and predictability using the MCMI-II Clinical Syndromes to the HSLC 203

Figure 8.1- The graph indicates the Anxiety level

of the HSLC sample population 204

APPENDIX - L 205

Table 9.1- MCMI-II Severe Syndrome and the

relationship with the HSLC 206

APPENDLX-M 207

Table 10.1- The ability of the CASI sub-test Job Satisfaction in predicting with the HSLC classified group 208

Figure 10.1- The graph illustrates the relationship between the CASI Syndromes to the HSLC sub-test Job Satisfaction and the classified HSLC sample 209

Table 10.2- The ability of the CASI sub-test Dominant Style in predicting with the HSLC classified group 210

Figure 10.2- The graph illustrates the relationship between the CASI sub-test Dominate Style and the classified HSLC sample 211

APPENDLX-N-— 212

Table 11.1- The ability to predict the Quality and Quantity of Work within the inmate sample population 213

IX

Figure 11.1- The quality for all HSLC inmates through out each code. 214

APPENDIX-O 215

Table 12.1- CASI sub-test Job Satisfaction scale and its Ability to predict the Quality of Work within the sample Population 216

Figure 12.1- The graph illustrates the predictability in Job Satisfaction and of the Quality of Work 218

Figure 12.2- The graph illustrates the predictability in

Quality of Work and Job Satisfaction 219

APPENDIX-P 220

Table 13.1- The data of Quality and Quantity of Work and Grade Level with the HSLC 221

X

TABLES

Table 1.1 The number of predicted and actual inmates

classified in each of the HSLC. 70

Table 1.2 The expected number of inmates that classified in

each of the HSLC and the actual number the fell into each letter code— 71

Table 1.3 The number of inmates tested using the SDS 72

Table 2.1 The number of inmates that were classified under the

HSLC and the correlation between the HSLC and the inmate's IQ score;—75

Table 2.2 The mean and standard deviation of the (VICS) IQ

(information, comprehension, vocabulary, and similarities) scores

of the inmates classified using HSLC 77

Table 3.1 HSLC classification and correlation with Rorschach

EB style of decision-making 81

(Appendix D) p. 171

Table 4.1 The number of subjects that fell into each category

of the Egocentricity Index 83

Table 4.2 HSLC- Realistic Classification on Egocentricity Scale 83 (Appendix E)p. 174

Table 4.3 HSLC- Artistic Classification on Egocentricity Scale 84 (Appendix E)p. 175

Table 4.4 HSLC- Social Classification on Egocentricity Scale 84 (Appendix E)p.l76

Table 4.5 HSLC- Enterprising Classification on Egocentricity Scale 84 (Appendix E)p.l77

XI

12. Table 4.6 HSLC- Conventional Classification on Egocentricity Scale—85 (Appendix E) p. 178

13. Table 5.1 Any significant relationship between the HSLC

group and MCMI-II cluster "A" (DSM-R) 87

(Appendix G) p. 186


group and MCMI-II cluster "B" (DSM-R) 87 (Appendix H) p. 188

15. Table 5.3 The mean score and standard deviation of the

sub-test Antisocial and cluster "B" 88

16. Table 5.4 Any significant relationship between the HSLC group and MCMI-II cluster "C" (DSM-R) 90

(Appendix I) p 192


group and the Clinical Personality Patterns 91

(Appendix J) p. 194

18. Table 6.2 The correlation of the MCMI-II Compulsive

scale and MCMI-II Validity scale of the MCMI-II 93

(Appendix J) p. 198

19. Table 6.3 The measure of variance that can be explained

by a proposed factor (Appendix J) p. 199

20. Table 6.4 The "loading" on each factor of the factors 94 (Appendix J) p.200

21. Table 6.5 The 2 tail prediction and significance level from the t-test for paired samples: MCMI-II Compulsive and Desirability scale 95

22. Table 6.6 The 2 tail prediction and significance level from the

t-test for paired samples: MCMI-II Compulsive and Disclosure scale 95

23. Table 6.7 The 2 tail prediction and significance level

from the t- scale MCMI-II Compulsive scale and the MCMI-II

Debasement scale 96

24. Table 7.1 Any predictability using the MCMI-II Severe

Personality scale to the HSLC 97

25. Table 8.1 Illustrates and predictability using the MCMI-II Clinical

Syndromes to the HSLC 97

(Appendix K) p.203

26. Table 9.1 MCMI-II Severe Syndrome and the relationship

with the HSLC 99

(Appendix L) p.206

27. Table 10.1 The ability of the CASI sub-test Job Satisfaction

in predicting with the HSLC classified group 101

(Appendix M) p.208

28. Table 10.2 The ability of the CASI sub-test Dominant Style

in predicting with the HSLC classified group 102

(Appendix M) p. 210

29. Table 11.1 The ability to predict the Quality and Quantity of

Work within the inmate sample population 103

(Appendix N) p.213

30. Table 12.1 CASI sub-test Job Satisfaction scale and its

ability to predict the Quality of Work within the sample population 105 (Appendix O) p.21

xiii

31. Table 13.1 Grade Level, Quality of Work, and Quantity

of Work and the relationship with the HSLC 107

(Appendix P) p.221

32. Table 13.2 The t-test for paired samples between the Quantity of

Work is paired with the HSLC sample population 108

XIV

FIGURES

1. Figure 1.1 The divisions in the pie chart equal the number

of inmates classified in each of the HSLC (Appendix B) p. 167

2. Figure 2.1 Indicates that most of the inmates in the HSLC

classification, ranged from Borderline IQ to Average IQ (Appendix C) p. 169

3. Figure 3.1 Demonstrates the percentages of HSLC and the Rorschach

EB scores (Extratensive, ambitent, introversive) (Appendix D) p. 172

4.. Figure 4.1 The percentages of HSLC Realistic (R)

classification and where the inmates place on the Egocentricity

Index (Appendix F) p. 180

5. Figure 4.2 The percentages of HSLC Artistic (A)


Index. (Appendix F) p. 181

6. Figure 4.3 The percentages of HSLC Social (S)



7. Figure 4.4 The percentages of HSLC Enterprising (E)



8. Figure 4.5 The percentages of HSLC Conventional (C)


Index (Appendix F) p.l 84

XV

9. Figure 5.1 The results of the MCMI-II personality

scale on the sample population for Antisocial (Appendix H) p. 189

10. Figure 5.2 Illustrates by symbol and colors the number of

Inmates and their level of Antisocial Disorder within their HSLC

Classification (Appendix H) p. 190

11. Figure 6.1 The level of Compulsive personality style

within the HSLC sample population. (Appendix J) p. 196

12. Figure 6.2 Where each of the HSLC classified inmates

fell on the Compulsive scale. (Appendix J) p. 197

13. Figure 8.1 The graph indicates the Anxiety level of the HSLC

sample population (Appendix K) p.204

14. Figure 10.1 The graph illustrates the relationship between the CASI

Syndromes to the HSLC sub-test Job Satisfaction and the classified

HSLC sample (Appendix M) p.209

15. Figure 10.2 The graph illustrates the relationship between the CASI

sub-test Dominate Style and the classified HSLC sample (Appendix M) p.211

16. Figure 11.1 The graph illustrates the predictability the Quality

of Work and Quality of Work of the HSLC sample (Appendix N) p.214

17. Figure 12.1 The graph illustrates the predictability in Job Satisfaction

and of the Quality of Work (Appendix N) p.218

18. Figure 12.2 The graph illustrates the predictability in Quality of

Work and Job Satisfaction (Appendix N)p.219

XVI

CHAPTER I

THE PROBLEM

Introduction

Research suggests that Holland's Model of Career Assessment attempts to integrate the

three major areas Holland considers important in career assessment: abilities, interests, and

personality characteristics. This model demonstrates that career concerns are psychologically

complicated, just as people are psychologically complex. Career assessments must include

important aspects of a person to determine the appropriateness for particular careers and types

of work: abilities and aptitude, vocational interests, and personality characteristics (Lowman,

1991). Two other important variables include career indecision (Barrett & Tinsley, 1977) and

immaturity (Crites, 1974).

There have also been many psychological theorists who have questioned when the

sense of self develops (Lowman, 1991). Should have the developmental process of sense of

self fail within the individual, it would affect the initial development of the individual's

personality, maturity, aptitude, values, and perception. Added to this, restricted opportunity,

socioeconomic deprivation, stimulus nutriment, cultural differences, racial discrimination,

work attitude, limited education, cognitive deficits, and learning disabilities.

There is a need to confront these problems through an extensive holistic approach. The

individual needs to develop the tools to become an independent and productive individual in

society. Every one needs a sense of self-control over one's own life. A person without the

skills, interest, and understanding of self, has a greater propensity to relapse into the same

patterns that started them in the cycle of substance abuse and criminal behavior from their past.

2

Moreover, career is both a phenomenological and behavioral concept (Lowen, 1991). It is

the link between what a person does and how that person perceives the concept. Career

development and career choices in life are a profoundly important issue in today's society.

Around the middle 70s, Smith (1975) reviewed the research on the career and behavior

of Black Americans and drew the following profile. The profile would include many of our

Black felons in the prison system today who were youths during these years: Smith found the

profile of the Black individual in research studies portrayed as of a vocationally handicapped

person. The average Black American, if one can speak of average individuals of any racial

group, is one who may lack positive work role models. There is not a lifetime commitment to a

career as a way of life and is alienated from the work force. A greater priority is placed on job

security rather than finding self-fulfillment in an occupation. There is a tendency to have a

negative self-image, which fosters identity foreclosure and closes out the self and directions.

His aspirations are high, but his expectations of achieving his desired goals are low.

"Limitations, which are placed upon his occupational mobility by reason of his racial

membership, evidences interests that are more person than thing oriented; and is vocationally

immature" (p. 55).

The Washington Post (Holms & Morin, 2006) published a relevant article that emerged

from a survey with the Henry J. Kaiser Family and Harvard University about being a Black

man in America today. The survey results indicated Black American men today are deeply

divided over the way they see themselves and their country. "In many ways, the outward and

inward struggles of Black men appear to reflect where the nation is on its journey toward racial

equality-unquestionably further along and, yet, at risk of moving backward" (p.l 1). Holms and

Morin report the suicide rate among young Black men has doubled since 1980. One in four

Black men has not worked for at least a year, twice the proportion of male non-Hispanic

Whites or Latinos. Trends suggest a third of Black males born today will spend time in prison.

Black men report that Black men put too little emphasis on education and too much on sports

and sex. They worry that the police will treat them unfairly. "Among Blacks with a college

degree, six in ten have had a family member or someone close to them murdered. They report

too little emphasis on education, their health, their families, and getting ahead at work. More

than half of Black men said that they or a member of their immediate family would get AIDS"

(p.12).

The understanding of a person's work history has further increased over the last decade.

It has demonstrated that most of workers have maintained stable employment. Workers may

change jobs, but they remain in generally the same occupational classification. There are others

whose work history is less successful, unstable, or even chaotic. According to the research of

Costa and McCrae (1980), workers high on openness or neuroticism may be more prone to

change jobs.

Research has also indicated that there emerged a disproportionate use of illegal

narcotics and self-destructive behavior by Black males (Lowman, 1991). Apathy and

hopelessness, generated by low self-esteem, socioeconomic problems, and background

difficulties, have contributed to repeat incarcerations that have seriously impeded career

development (Lowman, 1991).

John Holland believes that careers are an expression of the individual's personality, and

that a comparison of self with occupational perceptions, determines career choice. According

to Holland (1997), there are three variables that effect the development of personality:

intelligence, gender, and social class. Holland's theory is based upon eight basic assumptions

4

(Holland, 1997; Powell & Fritzsche, 1994). The first four of the eight assumptions were

utilized in this research: 1. Most people can be categorized into one of six personality types:

(Realistic [R], Investigative [I], Artistic [A], Social [S], Enterprising [E], or Conventional [C]),

2. There are six model environments, (Realistic, Investigative, Artistic, Social, Enterprising,

and Conventional), 3. People search for environments that will let them exercise their skills

and abilities, express their attitudes and values, and take on agreeable problems and roles, and

4. A person's behavior is determined by an interaction between his or her personality and the

characteristics of their environment.

While it is hypothesized by Roe (as cited in Lowman, 1991) that genetics play some

role in deterniining the field and level of an individual's occupation, the environmental

influence of early childhood experiences is an important determinant of occupation. A child, or

an adolescent, who strives hard to satisfy a high degree of psychological needs and eventually

achieves some success, will also strive hard to meet his or her needs later on in life. The child

whose needs were unmet will be less likely to attain higher occupational levels.

This researcher contends that youths entering the correctional system, especially as

juvenile offenders, never go through the developmental or decision-making stages needed to

make career decisions or to develop career maturity. During the early stages of adolescence,

problems develop in the educational process, social adjustment, and personality development.

Add to this, the environmental influence of childhood experiences, gender, and social class.

These individuals become part of a need-driven, group-survivor lifestyle. Without meaningful

work, basic needs were not met and self- concept was diminished (Maslow, 1968). Without

education and/or vocational training, individuals were limited in the job market. Many went to

the streets to support themselves in any manner possible. Many individuals started or continued

5

criminal behavior with the probability of entering the chain of recidivism in the criminal justice

system, eventually returning to criminal behavior, substance abuse, repeated incarcerations, or

even death.

Toward this end, this researcher retrieved archival data from the administration of the

WAIS-R verbal subtests (information, vocabulary, comprehension, and similarities), the

Rorschach Inkblot Method (RIM), Career Attitudes and Strategies (CASI), Holland's Self-

Directed Search (SDS), and Clinical Structured Interview as a part of a battery used to develop

career profiles and help counsel 178 inmates.

The ultimate goal was to determine if certain selected inventories and techniques used

in counseling inmates, who were administered the above instruments, were effective in

establishing profiles of other inmates. More specifically, the purpose of the academic study

was to examine, using the single code letter of Holland's Theory (RIASEC), the career

development of Black male criminal substance abusers with a varied background of recidivism,

and the significance, if any, among their interests, abilities, personality, and work history in

career development within their community. The purpose of the academic study was also to

investigate the significance, if any, using the single code letter of Holland's Theory (RIASEC)

classification code, regarding the quality and quantity of work experiences with respect to

psychological, sociological, and ability variables, using psychosocial instrumentation.

This researcher hypothesized that there is a clear correlation between sociological,

psychological, and ability variables, according to Holland's (RIASEC) single code of

classification, in the quality and quantity of career development and work behavior of inmates.

Inmates with a higher level quality and quantity of work history within their community will

have significantly better profiles in ability, interest, and personality than those with a lower

6

level of quality and quantity of work history. It was also hypothesized that certain letter codes

of Holland's classification theory would be prone to both higher and lower work behavior.

Moreover, the problem investigated in this study was to systematically and empirically

determine if selected psychosocial variables were capable of differentiating between samples

of Black male substance abuse felons, utilizing Holland's theory (RIASEC) of classifications.

There are significant differences among various classified samples of adult Black male

substance abuse felons with histories of recidivism, regarding the quality and quantity of work

history within their community, as measured by psychosocial instrumentation.

Assumptions

It was this researcher's assumption, as hypothesized below, that psychosocial

instrumentation, combined with career inventories, could help predict the profiles of an

inmate's career development, which could lead to better success concerning work history:

H-l. It was assumed that the expectancy of the number of inmates in each of Holland's

six single letter code groups would be equal.

H-2. It was assumed that inmates whose measured intelligence on the verbal subtests of

the WAIS-R would have certain single letter code scores on the Holland inventory

(RIASEC).

H-3. It was assumed that the inmates' placement in one of Holland's single letter codes

would predict a certain EB style on the Rorschach.

H-4. It was assumed that the Rorschach Egocentricity Index (3r + (2)/R) would provide

an estimate of self- concern, and possibly, self-esteem in predicting the Holland's single

letter code (HSLC).

7

H-5. It was assumed that the Millon Clinical Multiaxial Inventory (MCMI-II), grouped

according to three subtest DSM-III clusters (A, B, C), would be able to predict

Holland's single letter code.

H-6. It was assumed that the Millon Clinical Multiaxical Inventory (MCMI-II), grouped

according to the 10 Clinical Personality Patterns, would be able to predict Holland's

single letter code.


according to Severe Personality Patterns, would be able to predict Holland's single

letter code.


according to Clinical Syndromes, would be able to predict Holland's single letter code.

H-9. It was assumed that the Millon Clinical Multiaxial Inventory (MCMI-II, grouped

accordingly to Severe Syndromes, would be able to predict Holland's single letter code.

H-10. It was assumed that the CASI subtest scales would be able to predict each

Holland's single letter codes.

H-l 1. It was assumed that Holland's single letter code (HSLC) would be able to predict

the Quantity and Quality of Work into one of three levels from the self-reported

employment history gathered on the Structured Clinical Interview.

H-l2. It was assumed that the CASI subtest scale Job Satisfaction would be able to

predict the Quality of Work among the classified group of Holland's single letter code.

H-l3. It was assumed that the Quality and Quantity and Grade Level would be able to

predict Holland's single letter code.

8

The factors explored included: substance abuse, attitudes, obstacles, recidivism,

criminal history, ability, interest, and personality. It should be stressed that these sets of

variables were systematically derived from the literature review as elements to be considered in

the quality and quantity of career development and work behavior within the community.

Definitions and Operational Terms

In order to better understand the various terms that are frequently used in this academic

study, a number of definitions are provided below:

Aptitude - The examiner's potential for learning a specific skill or performing a specific

task. It is usually considered a measure of innate ability that also reflects previous learning.

Ambitent - A coping style in which the emotions of the subject are inconsistent in terms

of their impact on thinking, problem solving, and decision making behaviors.

Career Maturity - A measurement of attitude and involvement with the choice process,

orientation toward work, independence in decision making, preference for but not

interdependent functions.

Debasement - Lowering of character, quality, or worth.

Extratensive - A coping style in which the subject will usually tend to try to intermingle

feelings with thinking, especially during a problem solving or decision-making activities

(Exner, 1993).

Interdomain model of career assessment - Holland's model of career assessment that

aims to integrate the three major areas that Holland considers important in career assessment:

abilities, interests, and personality characteristics.

Intelligence - An individual's potential for learning a specific skill or performing a

specific task. Dictionary definition generally refer to such abilities as the ability to adapt to

9

novel situations, utilize abstract concepts, and/or learn quickly. Psychologists tend to view

intelligence, either as a global mental capacity, or as a number of separate, but not

interdependent functions

Introversive - A coping style in which the subject usually prefers to keep his or her

feelings at a distance, particularly during the problem solving and decision-making.

Occupational Personality Types - Holland's model includes six basic occupational

personality types: Realistic ( R), Investigative ( I ) , Artistic (A), Social (S), Enterprising (E),

and Conventional (C) (Holland, 1985a, 1987, & Lowman, 1987). In essence, the researchers

define the six occupational personality types in this model as encompassing the following

traits:

Realistic - An occupational personality type that includes people who like to work

outdoors.

Investigative - The type of person characterized to have a high, and generally abstract

intelligence, is indifferent to social relationships, and troubled by highly emotional

situations.

Artistic - A person which is creative in orientation, is highly sensitive and emotional,

and may personally experience affective disturbances more than the average person.

Social - People oriented toward working with other people. They are individuals who

tend to be willingly helping by nature.

Enterprising - Individuals oriented toward people, rather than things, and who seek to

control or dominate others.

Conventional - Types of people who function best in a well established

structure and who are skilled at working with detail.

10

Additional terms that are frequently used in this study are defined as:

Personality - Represents a pattern of deeply embedded and broadly exhibited cognitive,

affective, and behavioral traits that persist over an extended period of time (Millon, 1985).

Projective Instrument - An instrument that indirectly measures motives, desires, needs,

or general personality functioning. The subject is asked to respond to ambiguous stimulus, such

as an inkblot, vague paragraph, picture, or open-ended sentences.

Quality of Work - The type of work measured by the degree of training, such

as:unskilled, semi-skilled, and skilled, as defined by the Department of Labor.

Quantity of Work - The length of employment, as measured by the time the inmate has

spent on a job in their community.

Recidivism - A continuing slip or a fall back into a former or worse state after a period

of improvement. It is a return to a negative behavior or activity.

Work - The systematic pursuit of an objective valued by oneself (even if only for

survival) and desired by others. Directed and continuous work requires the expenditure of

effort. It may be compensated (paid work) or uncompensated (volunteer work or an avocation).

The objective may be intrinsic enjoyment of the work itself, the structure given to life by the

work role, the economic support which work makes possible, or the type of leisure which it

facilitates (Super, 1976, p. 20).

Work Values - Based on a constant level of three types: security, affiliation, and

independence. Work values differ among gender, social position, and ethnic background.

Delimitations

This study focused on the six single letter codes (HSLC) classifications of Holland's

Theory (RIASEC) of career personality utilizing a voluntary sample of incarcerated adult

11

Black male substance abusers with a history of recidivism. According to Holland (1999), most

people can be categorized as having one of six personality types. The groups were as follows:

1. Realistic \K]

2. Investigative [I]

3. Artistic [A]

4. Social [S]

5. Enterprising [E]

6. Conventional [C]

There are different levels of congruence between a person and an environment. There

are also degrees of congruence between any two sets of codes. A more precise level of

congruence can be obtained if three letter codes are used, instead of the single letter code.

Holland uses a hexagonal model to explain the amount of relationship between each of the

single letter codes. The hexagon would have Realistic at the top point of the model. This would

be followed clockwise at each point with Investigative, Artistic, Social, Enterprising, and

Conventional. Therefore, if a person had a three-letter code of Conventional, Realistic, and

Enterprising the degree of fit would be high. This is because the three letters of the code are

beside each other on the hexagon. If someone had a three letter code of Investigative,

Conventional, and Social the level of fit or congruence would not be as good, because the

codes are spread around the different sides of the hexagon. Each of the six basic occupational

personality types differs in characteristics.

In this research, the researcher used only the single letter code, on account of the large

amount of data produced from the single letter code and the psychosocial instrumentation. In

terms of generalizability, this study focused on one sample that was tested. Therefore, further

12

generalization? beyond this group must be based on additional research using the same

instruments (updated) with different samples.

Reasons for Research

The researcher desires to investigate factors that contribute to the career choices of

Black adult male substance abuse felons. Psychosocial instrumentation was administered to

develop career profiles of the inmates incarcerated at an urban prison treatment facility. One of

the major problems confronting criminal and substance abuse treatment programs has been

recidivism. This pattern of behavior cannot be easily changed. Changes require long-term

retraining, education, and a desire within the individual to make the needed changes to become

a productive member of society.

After many years of working in the educational and counseling fields of the urban

public school system, there does not seem to be the importance of education and career

development instilled in the youth or adult population. Time and time again students drop out

of school by eighth grade and head to the streets with no skill training to be productive

individuals in society. Past research and observation has shown that these youths will find a

path to substance abuse and illegal activities partly as a result of the inability to find

sustainable jobs to support themselves within the community.

Later there was the opportunity to work within the youth and adult prison system in a

large urban city. Most of the population was Black American felons with a long history of

substance abuse and recidivism back into the criminal justice system. Upon release there was

still little hope of finding jobs. Many could not read or write and had extremely limited job

training or career development. Over the years there has been much discussion in research as to

the need to rehabilitate or only punish their behavior through intervention in prison. If a person

13

has extremely limited skills to support him in society and feels disenfranchised from being able

to be a part of the community the individual has to find a way to survive. This will often lead

back to criminal activity and/ or substance abuse.

There is a strong need to carefully place these individuals in programs while in prison

to develop the basic skills and career training needed to survive in the community. Then the

released inmates need to be closely followed with a support group to maximize success.

This research was initiated to develop profiles, using archival data of the sample inmate

population. Holland's RIASEC theory was use to classify the inmates and help establish career

profiles of the inmates. The profiles could be used to give counselors, educators, and

vocational training staff another tool to identify the needs of the inmates

14

CHAPTER II

REVIEW OF THE LITERATURE

The purpose of this chapter is to examine the literature related to the various

psychosocial variables that would clarify what factors were common to the profiles of the

offender sample that would be effective in counseling inmates toward successful career

development and work behavior.

In order to achieve this, this chapter has been divided into the following seven

areas: a) the impact of IQ and education on career development; b) career development in

"at risk" populations; c) the value of vocational inventories in career development and

maturity; d) job satisfaction; e) psychological disorders and its impact on career

development; f) substance abuse leading to criminal behavior and recidivism; and g) race,

sex, and test bias.

The Impact oflQ and Education on Career Development

Weisel (1987) conducted a academic study to develop a single measure that could

be used to identify learning problems. Using the Woodcock-Johnson Psycho-Educational

Battery and The London Procedure, a screening, diagnostic, and teaching guide for adult

learning problems, Weisel developed this "best test." Ninety-eight male prisoners at the

Ohio State Reformatory were tested, and any overlapping results from these two

measures were noted. The overlapping factors from each assessment were used to

produce the "best test," which will serve as a single assessment for classification of

learning problems.

15

Naglieri and Reardon (1993) completed a study which examined the relationship

between phonological decoding and intelligence using the Planning, Attention,

Simultaneous, and Successive (PASS) model of intelligence. Sixty male students between

the ages of seven to fifteen were tested using three planning tasks, three simultaneous

tasks, two attention tasks, and four successive tasks. Half of these students had been

identified as learning disabled by their Ohio school district. The other half was

considered to be "normally achieving." Phonological decoding tests using pseudo-word

reading and word recognition were found to have a possible relationship to intelligence.

This study suggests that for students with learning disabilities, their scores on

phonological coding tasks may be able to predict problems with their successive

processes.

A study conducted by Bestolarides (1993) was to examine the attitudes of

correctional educators toward their inmate learners. The findings demonstrated that the

attitudes of correctional educators seriously impacted the probability of educational

success. Success is defined, by breaking the cycle of recidivism, by providing training,

and instruction to inmate learners. Most of the correctional educators possessed a positive

attitude toward their jobs and showed sensitivity toward inmates with learning

disabilities. Smith (1996) completed a study to assess the dominant perceptual modalities

of functionally illiterate adults in a prison setting. The test used was the Multi-Modal

Paired Associates Learning Test-Revised (MMPALT-II). The sample included both

Black and White learning disabled subjects. Based on the significant differences in

subtests, it was determined that the dominant perceptual modalities of functionally

16

illiterate adults were the interactive, visual, and aural modalities of Black and White

functional illiterates.

According to Neisser, et al (1996), there are several different approaches to

measuring intelligence. The Psychometric Approach to measuring intelligence consists of

tests that are designed to measure the different constructs of intelligence, such as verbal

and spatial abilities. Howard Gardner's theory of "multiple intelligences" uses approaches

that test the whole spectrum of intelligent people, ranging from the brain damaged to the

gifted individual. Gardner also measures musical, bodily kinesthetic abilities, and

personal intelligence. The measures of verbal, spatial, and logical abilities were normally

tested using the Psychometric Approach. Robert Sternberg's theory suggests that

analytical abilities as tested using the first two approaches mentioned, makes-up only one

of three aspects of intelligence. The other two aspects this theory suggests are creative

and practical abilities. Measures based on developmental theories, which tend to focus

more on individuals, can be coupled with psychometric tests to serve as a measure of

intelligence.

Furthermore, there are also studies that focus on the biological make-up of the

brain to study intelligence. While measures of intelligence have not proven to be a stable

indicator of IQ, they have been shown to be a predictor of how well an individual will

perform in school. School attendance correlates with higher scores on intelligence tests.

Not only are students who are more intelligent more likely to graduate onto higher-grade

levels, but attending school also helps students to gain the knowledge and skills necessary

to perform well on psychometric intelligence tests. Biological factors that can have a

negative effect on intelligence scores include prolonged malnutrition in children,

17

exposure to lead, prenatal exposure to alcohol, and complications during child labor.

Additionally, differences in scores on intelligence tests among racial groups may be

attributed to socioeconomic factors and cultural differences. For example, the lower

average economic level of Black Americans versus White Americans, and the culture of

the average American classroom, can attribute to African Americans scoring lower on

intelligence test scores, on average, than do White Americans. However, the reason for

differences in intelligence scores among racial groups has not yet been proven in

research.

Career Development in "At Risk" Populations

Moreault (1992) attempted to find a relationship between family experiences and

career exploration. The hypothesis of this study was that higher levels of self and

environmental exploration would be positively related to positive family relationships,

and adequate levels of psychological separation and attachment. Participants in this study

were 304 undergraduate students who were from "intact families." This study did not find

a relationship between family separation, attachment, and career exploration. Further, the

purpose of a study by Anderson (1994) was to determine the effectiveness of career

assessment programs and career counseling for at-risk youths. By using several different

measurements, it was determined that career assessment programs can be helpful for at-

risk students.

Feigley (1995) studied middle and high school students who attended school in an

area that is at high risk for dropouts. Forty-three students participated in the study and

also participated in the STAR program, which paired the students with a college student

for mentoring and tutoring. Each student was given a questionnaire and the Peirs-Harris

18

Children's Self-Concept Scale before and after their participation in the STAR program.

Each student's school records were also reviewed before and after their participation. This

study looked at the self-esteem, school achievement, school attendance, and behavior of

the participants in relation to their age, race, sex, and initial self-esteem levels. The

findings of this study included an increase in the participants' self-esteem levels, and

decreases in the participants' grade point averages and school attendance after having

participated in the program. There was not a significant difference among race, age, sex,

or initial self-esteem levels in almost all of the areas studied. The only significant

difference found was between different races' anxiety scores. While the anxiety scores of

Hispanic students decreased, White and Black students' scores increased.

Skorupa (1995) attempted to determine if any differences exist between adults

who grew up with an alcoholic parent and adults who did not grow up with an alcoholic

parent in the areas of career indecision, anxiety, and irrational thinking. The participants

in this study were 171 students at a community college. Each participant was given the

Career Decision Scale, My Vocational Situation, the State-Trait Anxiety Inventory, the

Irrational Beliefs Test, and the Children of Alcoholics Screening Test. This study found

no significant differences between both groups of participants in the area of career

indecision. However, the children of alcoholics scored higher on two anxiety subscales

and on two irrational belief subscales. A study by Morrow (1995) further suggests that an

individual's difficulty in career development may be a symptom of problems with

cohesion and adaptability within the individual's family. The findings of this study can be

used to assist school counselors in understanding their students' problems with career

development.

19

An article by Lent and Brown (1996) outlines and explains the social cognitive

career theory (SCCT). There are three processes that provide the framework for SCCT.

The first is how academic and career interests develop, the second is interests that

promote career-relevant choices, and the third is how people attain varying levels of

performance and persistence in their educational and career pursuits. SCCT also indicates

that self-efficacy beliefs, outcome expectations, and personal goals are the things that

people use to form their career experiences (Lent & Brown, 1996). There are several

aspects of an individual's life experiences that provide the framework for their career

choices. From a young age, people are exposed to different activities that will assist them

to discover their talents and interests, and later know what kind of job, they may want to

pursue. During a person's life experiences, they develop personality characteristics that

will also help them in deciding what type of job, they would like to perform. Similarly,

by trying out different jobs, an individual can discover what types of tasks they are good

at and which ones they are less able to succeed well at. All of these things, together, help

individuals in discovering what career paths they want to take. Toward this end, Holmes

and Alexander (1996) conducted a study where 99 attorneys were given the Family

Environment Scale, the Career Beliefs Inventory, and a demographics questionnaire in

order to further examine Krumboltz's theory of social learning. This theory states that

family environment is influential in one's career development and in the formation of

career beliefs by means of social learning (Holmes and Alexander, 1996). Their study

found that there was a positive relationship between achievement orientation of the

family-of-origin and career achievement. Chartrand and Rose (1996) looked at "at risk"

individuals, which included people who, because of political, economic, social, and

20

cultural conditions have limited access to educational and occupational opportunities,

who have not been included in the research on career development. Therefore, the current

research on career development interventions, including social cognitive career theory

(SCCT), has a limited ability to generalize to "at risk" populations. The Chartrand and

Rose (1996) study explored the effects of project PROVE (Preventing Recidivism

through Opportunities in Vocational Education) on a group of female offenders who were

scheduled to be released within the following 6 months. The career development

strategies used in PROVE are based on SCCT and Bandura's informational sources of

self-efficacy beliefs. This developmental program consists of 6major constructs: Person

Inputs and Background, Life Events, Things You Learned, Who You Are, What You

Want to Do, and What You Accomplish. Each of these subjects are based on SCCT

constructs, but are applied in a way that the participants can understand and relate to.

Through PROVE and similar programs developed through the research, "at risk"

individuals, particularly young adolescents, should be able to gain the necessary skills

needed to succeed in the ever-growing and technology-advanced work force.

Hill and Rojewski (1999) examined the work ethic of ninth grade students who

were enrolled in a career pathways class. The students were grouped according to their

at-risk behaviors and gender. This study examined three aspects of the participants' work

ethic. The first aspect was whether there was a difference between the work ethic of

students who were considered to be "at risk," moderately "at risk," or not "at risk." In this

study the researchers defined being "at risk" as individuals who, due to social, economic,

political, or cultural conditions, have limited access to educational and occupational

opportunities. The second aspect was whether there was a difference between males and

21

females' work ethics. The third aspect was whether there was a relationship between

interpersonal skills, initiative, and dependability to work on ethics. Each participant was

given the Occupational Work Ethic Inventory, as well as a Risk Behavior Scale. This

study found statistical differences in work ethic between "at risk," moderately "at risk,"

and not "at risk" individuals, as well as between males and females. The mean scores on

the Occupational Work Ethic Inventory were the highest for the students considered to be

not "at risk," and the scores for students moderately "at risk" were higher than the "at

risk" students. Furthermore, the female students scored higher on the Occupational Work

Ethic Inventory than the male students did. Dependability was the characteristic that

differentiated the students from each other in terms of their "at risk" levels as well as

their gender.

The Value of Vocational Inventories in Career Development and Maturity

Tracey (1992) critiqued a study done by Galassi, Grace, Martin, James, and

Wallace (1992) with regards to career counseling. Tracey commended Galassi, et al. for

a noted distinction between anticipations and preferences in career counseling, as well as

the "generation of content categories" (p. 57). However, Tracey felt that the authors did

not include many important ideas from previous research done. Tracey regarded the use

of an open-ended question format in place of a fixed-format questionnaire as problematic.

The concerns with this type of information gathering include the unlimited types of

responses, as well as problems with interpreting the responses. Furthermore, there was a

high non-response rate for the questions, which Tracey felt had an effect on the validity

of the results. Each participant was also given the opportunity to respond to each item

with as many answers as they deemed necessary, which Tracey believed made the

22

responses "unequally weighted and thus biased" (p. 57). Tracey suggested that combining

some of the categories would make the test more user/reader friendly. Finally, Tracey

criticized the number of statistical tests done, as well as the interpretations.

In a study done by Davenport (1993), participants were students attending one of

two middle schools located in a predominantly black inner-city public school system

(Davenport, 1993). Each participant was given Crites's Career Maturity Inventory

Attitude Scale and Rosenberg's Self-Esteem Scale. The number of vocational exploratory

courses each participant had completed was also noted. In this study, a significant

relationship between the number of courses completed and the scores on the career

maturity scale was not found.

Gottfredson, Jones, and Holland (1993) conducted a study where 725 U.S. Navy

trainees were given the Vocational Preference Inventory and the NEO Personality

Inventory. This study found that social and enterprising vocational preferences of the

participants were related to extraversion. Investigative and artistic preferences of the

participants were related to openness, and conventional preferences of the participants

were related to conscientiousness.

Polk (1993) attempted to find a relationship between home life experiences as an

adolescent, and career decision-making. Participants in this study were three hundred 18

and 19-year-old college students. Each participant completed a series of questionnaires

that measured separation, individuation, and career obstacles. This study found that more

than one relationship exists between variables of the two measures. Martinez (1994), in

order to examine differences in minority students, compared to majority students, in areas

of career development, developed a survey and gave it to 130 college students. The

23

survey was designed to measure the self-assessment, career exploration, decision-making,

self-preparation, job search, and career management. The results from this study

indicated that the minority students surveyed were in need of more help, and were less

prepared than the majority of students.

Finch and Hughes (1994) conducted a study that used Super's Theory of

Vocational Development to examine self-concept and career maturity of high school

students. One hundred thirty-nine students between the tenth and twelfth grades were

grouped according to whether or not they chose vocational technical training, or did not

qualify for vocational training. The Tennessee Self-Concept Scale, the Career Maturity

Inventory, and a General Student Information Survey were used. Compared to students

who chose vocational technical training, those students who did not, had better self-

concept attitudes. However, those in vocational training, or those who were eligible for

vocational training, showed higher levels of career maturity.

A study by Loughead and Middleton (1995) followed a group of inner city youths

through the PRO-100 program. The PRO-100 is a program designed to give young

people in underprivileged areas the skills and experience necessary to be successful in

both the ability to search for a job, and in the job force itself. The program places

individuals in a real-life work environment and provides education, focusing on job

behavior, work-search skills, and in career development. Fifty-eight young people was

tested and observed throughout their participation in the PRO-100 program. The

individuals were tested at the beginning and end of the program using the Career

Maturity Inventory, the Self-Perception Profile for Adolescents, and the Pre-Test for

24

Interns. The individuals were also observed several times during their time with the

program. This program was successful in providing the education and skills necessary for

finding and holding a job.

Finally, Reardon (1999) followed a sophomore minority college student, named

Mandy, through participation in a career planning class. The class was composed of three

main parts: teaching career concepts and applications; exploring social influences on

careers; and advising students in implementing a strategic career plan. Two resources that

Mandy used while in the class were the SDS, which is based on Holland's RIASEC

theory, and the CTI, which is based on CIP theory. Through the use of Holland's

RIASEC theory, Mandy learned that there was a strong congruence between her

aspirations and measured interests. Overall, Mandy found that the career planning class

was helpful in teaching about interests, and how to use those interests in planning a

career.

According to Gottfredson and Jones (1997), the scales of the CASI are an attempt

to broaden the scope of career assessment to include other variables that could include

personal styles and situational variables. This could also include family and gender. The

CASI is used to assess job satisfaction, and work involvement, skill development,

dominant style, career worries, interpersonal abuse, family commitment, risk-taking style,

and geographical barriers. "Generality" ought to enable the counselor or teacher to

generalize behavior, ability, or status across different measurement options. This article

explored the dependability of scores from the CASI by employing techniques from

generalizability theory ( Cronback, Glaser, Nanda, & Rajaratnam, 1972).

25

More recent accounts of the generalizability theory have been provided by

Shavelson, Webb, and Rowley (1989) and Webb, Rowley, and Shavelson (1988). The

conduct rating obtained by a teacher might not be the same as for a parent. The article

examines information about error due to items (lack of homogeneity), and occasions

(instability over time), for this new inventory (Gottredson & Jones, 1997). A sample of

forty members of the clergy volunteered to complete the CASI on two occasions, 6-21

days apart. In general, the correlation was in the expected direction. Alpha's ranged from

.70 to .95 and the retest ranged from .65 to .92. There was very little of the variance

associated with time of measurement. The result for job satisfaction was about 36% due

to individual differences. The rest of the variation comes from something else. The Work

Involvement scale had 2% of variance due to "person-by-occasion interaction," and 34%

due to "item-by-occasion interaction" ( Gottredson & Jones, 1997). On interpersonal

abuse, it appeared that a large amount of variation was due to how different individuals

respond to sensitive questions. The Risk Taking scale had a large variance by item. This

would indicate that the specific items used to assess risk were important. The Job

Satisfaction scale was highly dependable, even when tested on one occasion, but on the

Work Involvement scale, it was determined that this scale must be measured on three

occasions to obtain a respectably high level of generalizability coefficient.

There has often been discussion that sometimes, specialists have not been as

precise as they should have been about whether a construct of interest can be stable over

time (Gottfredson & Jones, 1997). Lent, Brown, and Hackett (1994) stated that an

individual's self-efficacy expectations are important and that careers are subject to change

as learning continues. Gottfredson and Jones (1997) stated that work involvement and

26

skill development change over time. The CASI showed considerable consistency when

assessed over time; however, usually just one test occasion is needed. Work involvement

can be sensitive to work load, and there are differences over how some people see "risk."

These results suggest that job satisfaction is not oblivescent or poorly measured

(Gottfredson,1994).

Job Satisfaction

Lubinski and Benbow (2000) used the Theory of Work Adjustment (TWA) to

demonstrate how TWA concepts and psychometric methods, together, can help facilitate

positive development. Using a multifaceted assessment, focusing on strength, helping

people make choices, and providing a developmental context to help bridge educational

and industrial psychology to develop each individual's psychological growth throughout

their lifetime, this article demonstrates how individual-differences measures, used within

the TWA (Dawis & Lofquist, 1984) framework, can facilitate optimal development of an

individual's talent. The individual-differences tradition sets the stage for using ability and

preference assessments to design the highest learning environment for intellectual

growth. The spread of diversity found in the gifted and talented inidvidual was found in

intellectual and nonintellectual attributes. It is necessary to make curriculums at a level

and pace commensurate with their rate of learning. During the last 20 years, there has

been some agreement regarding the nature and structural organization of cognitive

abilities (Carroll, 1993; Gustatsson & Undheim, 1996), interests (Day & Rounds, 1998;

Holland, 1996), and personality (Goldberg, 1992; McCrae & Costa, 1997) among adult

populations. Gifted students often had remarkable results when placed in an environment

corresponding to their abilities. Holland's (1996) (as cited in Day & Rounds, 1998) robust

27

hexagonal model, used to describe adult vocational interests, can be used with

intellectually gifted adolescents (Lubinski, et al., 1995; Schmidt, et al., 1998). Holland's

RIASEC theory is the dominant model used to outline vocational interests. These

dimensions are mumfaceted, and for many purposes, need to be broken down (Schmidt,

et al., 1998). It is suggested that educational and vocational counseling should start with

an assessment to break down individual differences. Interest profiles can and do change

as we mature; however, there is enough stability and validity to consider them flexible

guideposts (Labinski & Benbow, 2000).

The TWA model is useful for organizing psychometric findings on ability and

interest to produce optimum development (Dawis & Lofquist, 1996). Combining the

TWA with the Radex Scaling of Cognitive Abilities (using radex scaling; Lubinski &

Dawis, 1992; Snow & Lohman, 1989), and Holland's (1996) RAISEC model, we produce

a multidimensional view of the individual. According to TWA (Dawis & Lofquist, 1984;

Lofquist & Dawis, 1991), education and vocational adjustment includes two dimensions

of correspondence: satisfactoriness (competence) and satisfaction (fulfillment).

Competence is determined by the correspondence between abilities and ability

requirements of the environment, and fulfillment determined by the correspondence

between personal needs and rewards provided by the environment. When satisfactoriness

and satisfaction co-occur, the person and the environment are in harmony with one

another. Then, sometimes, people are interested in things that they cannot do and are

competent to do things that they do not like to do. Self-concept, self-efficacy, internal

locus of control, and self-esteem all involve perceptions of self. Self-concept reflects our

28

perceptions of our abilities, skills, and our beliefs about our needs and values. Self-

efficacy indicates the extent to which our abilities are effective. This sets up our locus of

control on how events are at meeting our needs (Dawis, 1996a).

Ackerman (1996) and Ackerman and Heggestad (1997) proposed a model of adult

intellectual development, which places abilities-as-process with personality and interest

dimensions, to conceptualize the acquisition of cognitive content throughout the lifespan.

Ackerman's theory is called PPIK. It integrates intelligence-as- process, personality,

interests, and intelligence-as-knowledge. Interests and personality traits tend to direct the

development of knowledge structures down different paths. To support the model, they

compiled ability-interest, ability-personality, and interest-personality correlates from

other psychological literature on adult populations. Trait complexes were identified:

social, clerical/conventional, science/math, and mtellectual/cultural. The last two trait

complexes are akin to Holland (1996) and R.E. Snow (1991). According to PPIK theory,

academic courses have relatively similar patterns from kindergarten through 12th grade.

During adulthood, individuals mature and are free to make more choices. The choices are

made to conform to an individual's psychological characteristics. The individual's

particular competencies and knowledge structures become dependent on cognitive

abilities, interests, and personality (Bouchard, 1997; Reiss, Neider-Hiser, Hetherington,

and Plomin, 2000; Rowe, 1994; Scarr, 1992,1996). The magnitude of development,

according to both the TWA and PPIK theory, stresses individual differences in

development. Each individual has differences in drive and energy. The labels used to

include capacity for work, industriousness, perseverance, and zeal. There are always

individual differences in the amount of energy that a person is willing to invest in their

29

development (Goff & Acherman, 1992). It would still be interesting to see how far

individual psychological difference can take us (Messick, 1992). According to Lubinski

and Benbow (2000), outstanding achievements are simple results of the highest blends of

normal attributes, the affective, cognitive, and conative taken to extraordinary levels,

which were fostered through supportive environments.

Correspondent learning environments help to promote psychological well-being.

Students who are placed in a positive environment are less likely to experience punishing

events, including boredom. The learning environment may be considered challenging or

boring, depending on the student. That same environment may be motivational to some

and aversive to others. When distress ensues, performance is usually unsatisfactory, and

pain is associated with needs that are not met. Two kinds of psychological pain contribute

to a person's well being. Positive and negative punishment, which come from adverse

stimuli (anxiety), the removal appetitive stimuli (depression), and positive and negative

reinforcement, which is the presence of appetitive stimuli (joy) or the removal of adverse

stimuli (relief). Placing students in a learning environment that is congruent to their

abilities, and interests increases their chance of success. More learning occurs and

motivation builds (Lubinski & Benbow, 2000). Lofquist and Dawis (1991) linked Freud's

"pleasure principle" (peoples' need to avoid pain and achieve gratification) to TWA's

satisfaction and "reality principle" (the demands and requirements of the external world,

or TWA's satisfactoriness). To predict the environments that an individual might be likely

to work and thrive in, you must know what their abilities, capabilities, interests,

30

needs, and motivation are. It is possible that educators "should focus on developing the

capacities to do the same thing a little better every day, or continuous improvement,

which the Japanese call" kaizen" (Secretan, 1997, p. 49).

Psychological Disorders and Its Impact on Career Development

Millon and Everly, Jr. (1985) found that personality means many things to many

people. "Personality development starts in the first year of life, and is a function of

complex interactions of biological experiences, environment factors, and how people

relate to those experiences" Thorndike (1935, p. 9) called this "trial and error" learning.

Pleasurable and un-pleasurable reinforcement teaches the child that the most appropriate

experiences are effective. As the child grows, his behavior becomes more of a habit and

later, the collective process develops into traits. Finally, this behavior becomes

crystallized into preferred patterns of behavior.

Millon (1981) defined personality as a pattern of deeply embedded and broadly

exhibited cognitive, affective, and overt behavioral traits. These traits persist over periods

of time and develop from a complicated biological and environmental matrix. Millon

(1981) referred to the biological foundations of personality development as temperament.

Temperament is basically the biological material with which personality will eventually.

Develop. A person's character is based on the values and customs of the society or

environment in which the individual lives. These behaviors can be traced primary to three

sets of factors: Biological, bioenvironmental, and environmental. Normal versus

abnormal personality patterns is represented along a continuum relating to how one

function or adapts to the social environment, and the fulfillment of self-actualization or

one's potential (Millon, 1981). Abnormality could then be noted by the deficits in these

31

qualities (Millon, 1985). Abnormal or unhealthy personality patterns develop from

adaptive inflexibility, self-defeating behavior, and lack of stability, which results in the

inability to cope in an ever-changing society. Through the act of reinforcement,

individuals learn to pursue behavior that the person derives as pleasurable. Some

individuals are proactive, ambitious and goal-oriented. Others are passive or reactive and

wait for something or someone to provide the stimulus or reinforcement needed to act.

Individuals will fall into four different categories in order to obtain satisfaction:

independent, dependent, ambivalent, and detached (Millon, 1985). The dependent

individual will seek reinforcement from others, the ambivalent will never be sure where

to seek reinforcement, and the independent will find reinforcement and self-satisfaction

from within themselves. The detached individual is unable to achieve reinforcement from

others or self.

Choca, Shanley, and Peterson (1990) studied 235 Blacks and 471 White male

psychiatric inpatients, using the MCMI-II to determine possible racial bias of the test. In

predicting psychopathology for the two races, significant differences were found for all

diagnoses, except for personality disorders. There was a significant difference on 45 of

175 items answered. This suggests possible deficiencies in the cultural-fairness of the

MCMI-II items; however, at the structural level, principal components of factor analyses

of each group resulted in identical factor structures. At the same time, Piedmont,

Sokolove, and Fleming (1990) conducted a study which examined whether performance

on the WAIS-R can be used to discriminate between the taxonomies of personality

disorders. The three classification models used were: the biosocial (Millon, 1969,1981),

the interpersonal (Leary, 1957), and the Diagnostic Manual of Mental Disorders-III-R.

32

The results indicated that the WAIS-R proved most effective with the biosocial Millon

model (1981) demonstrating a robust and clinically meaningful pattern.

Another study by Ahrena, Evans, and Barneff (1990) examined 1,757 male

incarcerated felons, ranging in age between 16 and 71 years of age, to determine

personality, social history, and intellectual characteristics associated with dropping out of

school. The students were compared on the following variables: the Wide Range

Achievement Test (WRAT), the Multidimensional Aptitude Battery (MAB), and the

Millon Clinical Multiaxial Inventory. A significant discriminate function analysis (DFA)

differentiated the three groups on reading level, substance abuse, age, verbal IQ, and

personality factors of dependency and borderline personality. The results indicate the use

of the WRAT and MAB for incarcerated populations. In addition, identify personality

factors to be considered in rehabilitative efforts with felons who have not completed high

school. That same year, McCann (1990) calculated the degree of bias for each of the

personality disorders and clinical syndromes of the MCMI-II. According to the study, the

paranoid personality disorder, somatoform, bipolar, manic thought disorder, and

delusional disorder scales are prone to severe biases. When the test is used to diagnose

bipolar and schizophrenic disorders, they are likely to be grossly underestimated. The

MCMI-II, when used for clinical or research subjects, will result in inaccurate estimates

unless specific adjustments are made.

Bagby, Gillis, and Toner (1991) studied the effectiveness of the three validity

scales from the MCMI-II to detect the validity of fake-good and fake-bad responding.

The sample consisted of 150 college students and 75 psychiatric inpatients. The college

students were asked to take the MCMI-II and respond with fake-bad, fake-good, and

33

honest responses. Two separate discriminate-function analyses with cross-validation were

performed. The rate of successful classification was 76% for the faking bad group versus

the inpatient group, and 72% for the faking good group versus the honest group. Also, in

the same year, Bagby, Gillis, and Toner (1991) administered the MCMI and the

Inventory of Interpersonal Problems (IIP) circumplex scales to 177 outpatients being

treated for alcoholism. The subjects who demonstrated the characteristics of schizoid,

avoidant, and negativistic personality styles reported problems with being too guarded

and distant. Antisocial and paranoid subjects were both guarded and domineering;

narcissistic subjects were domineering; compulsives were too unassertive; histrionics was

both open and domineering; and, dependents were both open and non-assertive. The

results provide a useful heuristic for relating personality styles to interpersonal problems.

Previous research suggests that the interpersonal implications of personality

disorder measures are consistent across different populations. Chronically poor

interpersonal patterns are complementary with maladapted persons or relationships.

Donat, Walters, and Hume (1991) looked at 200 subjects who had been admitted into a

treatment center for substance abuse and given the MCMI measure and the Alcohol Use

Inventory (AUI). The results of different clustering methods were compared to the

MCMI personality scales. Subjects who have been identified by Cluster 1 and Cluster 2

scored lower on the AUI. People represented by Cluster 1 are "strongly motivated by a

sensitivity to and avoidance of disapproval by others" (p. 342). Cluster 2 individuals

place more emphasis on personal aspects, and can appear to others to be self-centered. On

the other hand, subjects who were identified by Clusters 3,4, and 5 scored higher on the

34

AUI. Subjects in Cluster 4 tended to be more critical of themselves and were more likely

to abuse alcohol while by themselves.

Craig and Weinberg (1992) stated that the MCMI-II has been used to assess many

drug abusers over the years. Research indicates that the test is useful to assess the

personality styles of drug abusers. This study indicated that the Clinical Syndrome Scales

present some problems. The Drug Dependence Scale has some difficulty in reliably

detecting drug-addicted individuals who were in treatment. Based on a reliable modal

MCMI-II profile among this population; however, there seems to be several different

clusters subtypes, each with different personality styles. The study found that the

narrative computer reports might over diagnose paranoid disorders, and under diagnose

antisocial disorders in this population.

Moreover, Walsh (1992) investigated whether the Wechsler P>V sign test is a

useful diagnostic tool for predicting delinquent behavior. Some doubt has been placed on

the usefulness of the Wechsler P>V or V>P for predicting delinquency since significant

correlations between it and the MMPI and MCMI have failed to turn up many of the

personality traits. This article argues that an imbalance between the P>V or V-P is a

useful predictor of possible delinquency in juveniles. It appears that once a youth

becomes delinquent, the frequency and severity of the delinquent behavior can be

predicted by the degree of P>V discrepancy.

Chick, Sheaffer, and Goggin (1993) conducted a study which examined the

relationship between elevations on the personality scales of the MCMI and the Diagnostic

and Statistical Manual of Personality Disorders-HI-R. Using the personality symptoms in

the DSM-III-R checklist with 101 adult psychiatric patients, diagnoses were made. These

35

same patients completed the MCMI. The results indicated that only the Schizotypal

scale on the MCMI was related to its respective DSM-III-R personality disorder in the

sample correlation. It was concluded that the MCMI personality disorder scales revealed

overall low sensitivity.

In another study by Bishop (1993), the MCMI-II was used to assess the

personality of 73 adult substance abusers in treatment. The influence of

neuropsychological functioning on personality functioning was evaluated. The past

history of substance abuse did not significantly relate to measures of neuropsychological

or personality functioning. MCMI profile validity was related to verbal and perceptual-

motor functioning. Neuropsychological testing significantly predicted MCMI-II scale

scores, however, not with any consistency. Litman and Cernovsky (1993) also looked at

the MCMI-II. According to this research, a principal component analysis (varimax

rotation) of the MCMI-II's 25 scales yielded 5 factors that accounted for 82% of the total

variance. The five factors included: massive over-reporting of psychological symptoms;

rebellious-antisocial; attempts to present oneself in a socially favorable light; compulsive,

mistrusting, and socially detached; and compulsive-anxious somatoform.

Arboleda and Julio (1994) studied the relationship between inmates' mental health

and criminal behavior, which remains a matter of debate. This study explored the

relationship between mental illness and crime. A principal diagnosis on either Axis I or

Axis II was made in 728 of 1200 inmates. Substance abuse disorders, including alcohol,

were the diagnoses most frequently entered. Factors found to be significantly associated

with mental illness included: education, ethnicity, previous detentions, and previous

forensic assessments. In that same year, Huertas-Valdivia (1994) put in place a

36

psychosocial competence program in the Lleida prison for recidivist adult offenders. The

program was intended to promote the learning of several interpersonal problem-solving

methods, as well as the social skills of inmates. A technique was included for anger

control to avoid the excessive autonomic arousal in the decision-making process. The

program changed social skills, interpersonal skills, cognitive problem solving, values,

education, creative thinking, and emotional control. The most improvement was in the

optional thinking of the inmates, mostly because of the creative thinking technique.

Huertas-Valdiva (1994) concluded with the analysis that the most salient features

implicated the need for psychological intervention at the prison.

Craig, Kuncel, and Olson (1994) completed an investigation where 100 drug

addicts were asked to complete the MCMI-II, so as to avoid the detection of a drug or

alcohol problem. 52% were able to avoid detection. By reducing the number of times the

subjects endorsed the drug and alcohol prototype items, the amount of self-disclosure and

the frequency which the subjects debased themselves, increased the ability to avoid

detection.

Ellason, Ross, Conn, and Fuchs (1995) conducted a study of 96 individuals who

had been diagnosed as having Dissociative Identity Disorder (DID) who were given the

MCMI-II. Several personality disorders, as well as depression and substance abuse, were

identified in the subjects. Around the same time, Lindsay and Widiger (1995) looked at

the controversy in the research regarding sex bias in the diagnosis of personality

disorders. The study used self-reporting inventories, including the Millon Clinical

Multiaxial Inventory-II (Millon, 1987), Minnesota Multiphasic Personality Inventory

(Morey, Waugh, & Blashfield, 1985), Personality Diagnostic Questionnaire-Revised (

37

Hyler & Rieder, 1987), along with the Ben Sex Role Inventory (Ben, 1974), and

Symptom Checklist-90-Revised (Derogatis, 1977). The study included 189 subjects. The

scales completed were the Histrionic, Dependent, Antisocial, and Narcissistic scales from

these inventories. The items were considered for evidence of sex or gender bias. The

basis for comparison failed to correlate with dysfunction, but exhibited sex or gender role

differences. Thirteen items evidenced sex bias. Most were from the Narcissistic scales,

with a few from Histrionic items. The study found that women are more frequently

diagnosed with Histrionic, Dependent, and Borderline personality disorders than are men.

Men were more frequently diagnosed with Antisocial, Obsessive-Compulsive, and

Paranoid personalities than are women (APA, 1987). The controversial issue is whether

the differences reflect an actual difference in the respective frequencies of the personality

disorders, or a bias in the self-report inventories.

Wierzbicki and Goldade (1993) found the Histrionic scale to be more male than

female-typed and the Compulsive scale to be more female-typed. Munley, et al. (1995)

compared the results on the MCMI-II for subjects who had previously been diagnosed as

having Post-Traumatic Stress Disorder (PTSD). This study found similar results for the

MCMI and MCMI-II. Hills (1995) compared two self-report measures of personality

disorders (MMPI-2; Butcher, Dahlstrom, Graham, Telligen, & Kaemmer, 1989; MCMI-

II; Millon, 1987) to a Structured Clinical Interview (SCID-II; Spitzer, et al., 1990)

diagnosis. Subjects included were 150 residential or outpatient volunteer subjects who

were measured across a variable disorder spectrum. The results indicated that the MCMI-

II appeared to be a more sensitive document. The MMPI-2 was more specific; however,

the two self-reported inventories had greater convergence with each other than with the

38

interview measure. All diagnostic results existed at acceptable levels, but the diagnoses

generated by the self-report versus the interview were not interchangeable. Self-report

inventories and structural clinical interviews were both only part of a complete battery

toward consideration of a personality disorder. The MCMI-II appeared more efficient at

identifying disorders when they were actually present. Specificity scores for the MCMI-II

were the highest on the Paranoid scale (91%), Histrionic scale (87%), Obsessive-

Compulsive scale (91%), Antisocial scale (76%), and the Schizotypal scale (84%).

Sensitivity scoring on the MCMI-II resulted in higher scores on the Schizoid (71%),

Antisocial (69%), Borderline (70%), and Passive-Aggressive (88%). Overall, the MCMI-

II and the MMPI-2 retained overall diagnostic ability that could be considered reasonably

accurate, but further investigation with larger samples needs to follow.

A study by Hibbard and Hilsenroth (1995) investigated two projective measures

of object representations; the Concept of the Object on the Rorschach (Rorschach, 1994),

and the Social Cognition and Object Relations Scales (Westen, 1991) were compared.

Intelligence was measured using the Wechsler Adult Intelligence Scale-R ( Wechsler,

1981), and measures of pathology using the Millon Clinical Multiaxial Inventory

(Millon, 1983) and Minnesota Multiphasic Personality Inventory (Hathaway &

McKinley, 1983). Analyses focused on the construct validity of object representations

and the implications of structural and affective aspects of object representations for

psychopathology. The results support the construct validity of object representations and

an affective, but not a cognitive structural linkage between object representations and

pathology. Craig, Bivens, and Olsen (1997) conducted a study which attempted to

compare the MCMI-I and the MCMI-II to the results from the MCMI-III. The MCMI-III

39

has been updated from the previous two measures to include scales for depression and

Post-Traumatic Stress Disorder (PTSD). 441 African American men who were dependent

on heroin, cocaine, or both, were given the MCMI-IH. Out of these participants, 161 were

identified as Cluster 1. In addition to other problems, these patients tend to have problems

with organization and may, therefore, encounter problems with treatment methods. 96

participants were identified as Cluster 2. These patients tend to be self-oriented and less

socially aware, which may be a factor in their substance abuse problems. The result of

this study suggests that results derived from the MCMI-I and the MCMI-II can also be

generalized to the MCMI-III.

A study by Pearson (1998) focused on job and leisure satisfaction, and how they

relate to psychological health. This study also looked at the possible differences between

tiie relationships of blue-collar and white-collar workers' job and leisure satisfaction with

their psychological health. The participants of this study were 189 adult men with full-

time jobs. Each participant was given the Job Descriptive Index, the Leisure Satisfaction

Measure, and the Mental Health Inventory. The results of this study indicated a positive

relationship between job satisfaction and psychological health, and between leisure

satisfaction and psychological health. However, the results did not indicate any

relationship between type of job, in terms of their relationships between job and leisure

satisfactions and psychological health.

Substance Abuse Leading to Criminal Behavior and Recidivism.

Khantzian (1985) proposed a model of substance abuse that states that some drug

dependent persons choose a drug that helps provide relief from specific painful affective

states. Khantzian hypothesized those individuals who abuse heroin because of painful

40

affective states associated with extreme aggression and violence, experienced it as a

victim, perpetrator, or both. Cocaine users selected these drugs due to their stimulant

properties when suffering from depressed moods, or feelings of fatigue and emptiness.

Persons with attention deficit problems, hyperactivity, or volatile mood swings tend to

abuse cocaine due to the paradoxical, calming effects. According to the theory, some

alcoholics self-medicate due to anxiety and depression due to its calming effect.

A study by Wierson (1992) examined the roles of several variables in the

prediction of recidivism for juvenile delinquents. In the Georgia Division of Youth

Services, the recidivism rate was approximately one-third. Crime-related and mental

health variables were entered into discriminate function analyses to determine models for

predicting recidivism. Earlier age at first arrest, and higher severity of crime, significantly

discriminated recidivists from non-recidivists. The presence of a substance abuse disorder

appeared to be a positive prognostic indicator. A separate set of analyses was conducted

by race. The results were qualified by race, whereby differential processes may be

operating for Black versus White youths when considering recidivism.

Motiuk (1993) investigated 510 adult male inmates in order to explore the relative

efficacy of using simple predictors, classification methods, and a combination of

assessment procedures for improving actuarial predictions regarding important

correctional outcomes. The intake assessment and post-release reassessment procedures

were found to have predictive merit in relation to criminal recidivism. The analysis of

variance revealed that treatment in prison was associated with decreased recidivism

among high-risk cases. Office visits and interaction in general recidivism outcome

measures were found to be insignificant in the community. Increasing the frequency of

41

visits between professionals and offenders, without targeting and addressing the relevant

criminogenic needs, was not sufficient enough to reduce post-release recidivism.

Another study conducted by Ducan (1993) hypothesized that recidivists among

juvenile delinquents would exhibit more hostile and aggressive behavior, more antisocial

characteristics and behavior, and have more involvement with illegal drugs. It was also

hypothesized that non-recidivists would show higher academic and intellectual

functioning, more psychological distress, and better adjustment to the current placement.

All the youths in this study were arrested on felony offenses. The results accurately

predicted recidivism in the population of chronic, severe, and juvenile offenders using

classes of behavior, rather than individual variables. A history of antisocial behavior was

shown to be the strongest predictor of recidivism. The residents' adjustment to the

program, intellectual achievement, and psychological distress was found to play only

minor roles in the prediction of recidivism. The inclusion of these variables in the

equation significantly improved the prediction rate.

Around the same time, Major (1993) studied 335 clients who were chemically

dependent recidivists. The study investigated the relationships among drug history and

participation in substance abuse treatment. Factors, including employment history,

medical history, psychological history, demographic variables, and participants'

perception of inmates' drug using behavior, were also included. Each member of the

study filled out a questionnaire developed by Major (1993) called "The Drug and

Recidivism Assessment" (DARA). The DARA consisted of 56 items, separated into

seven subscales, which delineated respondents' history and perceptions. The findings

revealed no significant or unique effect regarding drug history or participation in drug

42

programs on recidivism. Relationships among the various independent variables yielded

generally expected responses confirming clinical experience. For example, it showed the

need for total abstinence with this population. Findings also underscored the need for

employment as a tool for mitigating both chemical and criminal behavior. The study

indicated that any treatment was better than no treatment, but that the treatment needed to

be specifically tailored to the needs of the individual to have any positive effect on

recidivism. Inmates perceived the need for individual external help and their willingness

to participate in treatment within the criminal justice system.

In a separate study, Kincaid (1993) researched at the Classification Center of the

Commonwealth of Kentucky for the purpose of studying inmates' recidivism upon release

and with a five-year follow-up period. The main subject of the study was on the effect of

imprisonment on inmates by examining the recidivism rate, based on the security level of

the institution level in which the inmates were housed prior to release. A further

comparison was made of the inmates' original offense(s) and those offenses that returned

the inmate to incarceration. The findings suggested that as security increased, so did

recidivism. Reducing the security level before releasing a prisoner lowered the rate of

recidivism, A majority of the 184 inmates who participated in the study returned for

technical parole violations and no re-offending patterns emerged.

Additionally, Sannes (1993) investigated the attributional style of males who

demonstrated various degrees of criminality. The first group was non-offenders, the

second group was intermittent offenders, and the third group was recidivists. Each group

consisted often Black and ten White subjects. The Expanded Attributional Style

Questionnaire was use to measure individuals on three attributional dimensions: internal

43

versus external causes, stable versus unstable causes, and global versus specific causes. A

four-point Likert-type scale was used. The results were examined for the effects of the

criminal group, race, and the criminal group by race on the three dimensions of

attributional style. There were no significant differences found in the analyses.

Schinka, Curtiss, and Mulloy (1994) stated that there are traits or symptoms that

separate various groups of drug dependent patients, but not in concordance with self-

medication hypothesis. Hyper-vigilance and suspiciousness are commonly found in

individuals who abuse illegal drugs, either alone or with alcohol. Those who are

poly substance abusers experience a large range of health problems as a function of

exposure to many class drugs. Individuals high on the antisocial scale satisfy the need for

sensation-seeking behavior from the drug marketplace.

Astley (1994) examined the DUI offender from the Problem-Behavior Theory

perspective, attempting to identify factors that contribute to DUI recidivism. There were

three groups: non-DUI alcoholics, first-time offenders, and recidivists. The subjects were

compared on a number of psychosocial and demographic variables. Twelve-scale scores

were reduced to three factors: psychological distress, alcohol problems, and impulsivity

sensation-seeking behavior. The first of the three factors held that the alcoholics and

recidivists had more alcohol problems. The second factor that recidivists would have

more psychological distress did not hold up. In fact, the non-DUI alcoholics had more

psychological problems. The third factor that recidivists would score higher impulsivity

sensation-seeking behavior did not uphold. The non-DUI alcoholics scored the highest

and the recidivists scored the lowest. It was determined that alcohol and psychological

distress contributed the most to group differentiation, and impulsivity sensation-seeking

44

behavior contributed a lesser amount. Alcohol issues must be the primary focus, but other

factors must be integrated for a successful treatment program.

Mossier (1995) studied a group of subjects who had recently been admitted into a

drug treatment center. They assessed the subjects using the Ego Function Assessment,

and compared the test results to the assessments of a group of graduates with no

substance abuse problems. Moreover, the Ego Deficit Model theorizes that substance

abuse arises in individuals who have personality deficiencies. This study found

significant differences between the two groups in the areas of quality of relationships,

self-esteem, control of affects and impulses, and defensive functioning. Those subjects

who were being treated in the drug treatment center were deficient in all of these areas.

Another study by Van De Voorde (1995) was to determine the effectiveness of

The Great Escape Program by examining the relationship between program participation

and membership in the recidivist and non-recidivist groups. The field study also

investigated whether group membership in the recidivist and non-recidivist groups could

be distinguished on the intake interview, group participation, and security level of the

inmates. The conclusion reported that The Great Escape Program was not shown to affect

recidivism. The recidivist group could be predicted at a confidence level that was only

significantly different than by chance assignment. It was recommended that the intake

interview be redesigned.

Andrews (1996) reported that every year in the United States crime increases, and

overcrowding in the prison system becomes a more serious problem. The system is

becoming more responsible for the education of inmates. At the same time, budget cuts

make it more difficult to deliver the service. When a program is designed, it needs to be

45

cost-effective and determine the types of inmates who will benefit most from the

program. This study examined the relationships of GED scores and certain demographic

and offense characteristics of South Carolina adult inmates. The sample included 294

inmates who were administered the GED test during a three-month period. The

characteristics included age, ethnicity, gender, educational achievement, intelligence,

type of offense, recidivists or first-time incarcerated, and length of sentence. There was a

significant positive relationship between the GED and all of the predictive variables, but

no significant relationship between the GED and demographic or offense characteristic

variables. Level of reading was the most significant factor in achievement on the GED.

The study reported that a person who engages in criminal behavior does not necessarily

mean that he or she may not perform well academically.

The same year, Klinger (1996) discussed that legislators from all over the world

have always tried to solve the criminal problem of recidivism. Austrian rules about

recidivism are the strictest in the German-speaking family, but have not served the

rehabilitation process in any better way. Klinger (1996) reported that the phenomenon of

recidivists does not depend on the strictness of the penalties. He found that white collar

crime and similar criminal acts in the economic sector do more harm to the society in

both an economic and moral way than most crimes of recidivists. Klinger (1996) believes

that there needs to be other alternatives to classical forms of punishment and a complete

reorganization of the criminal prosecution system.

In another study, Davis (1996) concluded that recidivists represent a significant

percentage of inmates in the prison system. It is difficult, but necessary, to identify

factors that are related to becoming at risk for this lifestyle. Davis (1996) attempted to

46

examine eighteen variables. The study ultimately considered all eighteen of the variables.

Six of the eighteen variables were able to differentiate between recidivists and non-

recidivists. The variables considered most significant were: the number of property

offenses, number of convictions, number of probation orders, number of criminal code

offenses, number of probation orders, number of custody placements, and constitutional

status.

Finally, around the same time, Hewette (1996) examined a possible relationship

between borderline personality traits and substance abuse problems. Twenty subjects who

had been previously diagnosed as having a substance abuse disorder, were tested

according to their responses for early borderline object relations, contemporary

interpersonal interest, primitive defenses of splitting, and affect functioning. The

responses from these subjects were compared to 20 subjects who were previously

diagnosed as having an adjustment disorder. This study did not find any significant

differences between the two groups on any of the measures. However, both groups did

show symptoms of borderline object relations and defenses.

Race, Sex, and Test Bias

Isralowitz and Singer (1986) examined the relationships, if any, of the

unemployment status of the head of the household on adolescents work values.

Participants in this study were 98 Black adolescents between the ages of 12-17. The

participants were split into one group of adolescents whose head of the household was

unemployed for morethan three years, and another group whose head of the household

was employed for at least one year. The results of this study indicated that the

participants from an unemployed family valued a job that gave them independence as

47

less important than the participants from employed families. Furthermore, males from

unemployed families valued a job that would give them the opportunity to help others as

more important than a job that would take place in a pleasant environment less than

males from employed families. Female participants from unemployed families valued a

job that gave them less independence, and a job that would give them the opportunity to

meet people they like more than females from employed families.

Piedmont, Sokolove, and Fleming (1990) analyzed factors, including the effects

of race (Black and White), education (high school graduate versus less than high school

education), and diagnosis (schizophrenic versus non-schizophrenic), and on the MCMI,

antisocial, avoidant, schizotypal, psychotic thinking, and psychotic delusions scale.

Scores were obtained from 94 Black subjects and 116 Black male psychiatric inpatients.

Special norms for Black and White patients found in the MCMI manual supplement

were used (Millon, 1984). The only significant effect found was that Blacks scored

higher than Whites on the asocial, avoidant, psychotic thinking, and psychotic delusion

scale.

A study by Naidoo (1993) examined D.E. Super's theory of career development

in terms of its ability to generalize to Black American college students. Super's theory

was previously based on research with white males (Naidoo, 1993). Both male and

female Black American students enrolled at a university was tested. His study found that

Super's theory might not be wholly adequate in explaining the career maturity of African

American university students.

Peeler (1996) stated that due to trends in the workforce regarding the types of

occupations typically filled by Black Americans, the Peeler study attempted to determine

48

if, and/or, how much, cultural factors for Black Americans influence their career

choices. This study hypothesized that cultural factors, along with personal factors, would

influence the occupational choices of African Americans.

Hartung, Leong, and Pope (1998) investigated the Career-Development

Assessment and Counseling (C-DAC) model, which combines several different career

development theories into one counseling program. The program is made up of four

steps. The first step involves an initial interview with a career counselor. The second

step involves a series of measures. The instruments used at this step can be determined

by the counselor, but there are five measures that make up the "core" of the C-DAC: The

Salience Inventory, the Adult Career Concerns Inventory, the Career Development

Inventory, the Values Scale, and the Strong Interest Inventory. The third step involves

working to identify their career interests and values. The fourth and final step involves

self-assessments to identify themes and patterns. Naidoo (1993) counseled individuals

using the C-DAC in order to properly identify each subject. Cultural identity is a core

component of the final step. There are four major issues that are involved with fostering

cultural relevance. The first is utilizing a tripartite model of the three human dimensions:

universal, group, and individual. The second is evaluating the individual's level of

acculturation. The third issue is evaluating and incorporating the individual's

individualism or collectivism. The last issue is recognizing the counselor's own

stereotypes and prejudices for different ethnic groups. Counselors can help to identify

individuals based on their personal characteristics, rather than on stereotypes, using a

racial identity interaction assessment. Two cultural-specific assessments that can be used

are the Multicultural Career Counseling Checklist and the Career Counseling Checklist.

Other measures can be used as well in alternate ways, paying attention to cultural issues.

Finally, Lattimore and Borgen (1999) looked at a sample of research participants

from the development of the SSI in 1994. The sample taken was separated into racial

categories, as well as occupational categories. The GOT scales of each participant were

examined, and these results were compared to their occupational separation. This study

found that the GOT scales contributed significantly to the measurement of occupational

separation. In sum, Lattimore and Borgen's (1999) study indicated that the 1994 SSI is

valid for testing African American, Asian American, Caucasian American, Hispanic

American, and Native American individuals.

Literature Review Integration

The existing literature supports the use of the Woodcock Johnson Psycho

Educational Battery for assessing academic difficulties (Weisel, 1987). While some

research questions the value of vocational batteries and vocational development

programs (Davenport, 1993), some instruments like the NEO, CASI, SDS, STAR and

Vocational Preference Inventory show greater promise (Jones and Holland, 1993;

Longhead and Middleton, 1995; Reardon, 1999; Gottfredson and Jones, 1997; Feigley,

1995). A number of studies have concluded that the RIASEC is a valuable framework

for facilitating career choice (Lubinski, etal, 1996; Schmidt, etal, 1998; and Holland,

1996).

The MCMI-II has shown promise in identifying psychological impairment

(Millon, 1969; Millon, 1981; McCann, 1990;Craig and Weinberg, 1992; Hills, 1995).

50

Prior research is consistent in pointing out the impact of psychological impairment on

career development (Millon and Everly, Jr., 1985; Choca, Shanley and Peter son, 1990;

Piedmont, Sokolove, and Fleming, 1990).

Recidivism has been studied from a number of perspectives including age of first

arrest and seriousness of the crime (Wierson, 1992), the presence of antisocial behaviors

(Duncan, 1993), chemical dependency (Major, 1993). A few studies have focused on

Black-Americans and factors of work values and personality characteristics (Singer,

1986; Piedmont, Sokolove, and Fleming, 1990; Peeler, 1996).

There is indeed a gap in the literature. Most existing studies deal with educational

and career development conducted at high school and college levels. No vocational

development studies exist with inmate populations. Focused research has not been

completed specifically with the Black American inmate population to discern the most

effective means for conducting educational and career assessments.

It is the purpose of the current study to begin to fill the gap in the literature by

conducting research that will utilize specific psychosocial instrumentation to develop

career profiles from a sample of urban Black American male substance abuse felons.

The data will be useful to counselors and educators as they prepare inmates for

appropriate vocational training. The generation of this data will also ultimately reduce

the testing and assessment time needed with this population. If Black American inmates

are ever to return to society, more research is needed to identify factors that will

facilitate their vocational and career development. The current study will make a

contribution to that effort.

51

CHAPTER III

METHODOLOGY

Design of the Study

The research design that was used in this study was ex-post facto. According to

Kerlinger (1973):

. . . [e]x-post facto research is systematic empirical inquiry in which the scientist

does not have direct control of the independent variables because their

manifestations have already occurred, or because they are inherently not

manipulable. Inferences about relations among variables are made, without direct

intervention, from concomitant variations of independent and dependent variables

(p. 379).

Another distinction that is made about ex-post facto research is that it contains an

attribute or assigned variable, which can only demonstrate relationship—not causation.

Concerning research design, Klein (1976) stated true experimental design, and only true

experimental design, can demonstrate causation. Therefore, no causal statement can be

made about ex-post facto research.

The three major weaknesses in conducting a study using ex-post facto research

are presented below:

. . . (1) the inability to manipulate independent variables, (2) the lack of power to

randomize, and (3) the risk of control ( Kerlinger, 1973, p. 390).

Even though this study was ex-post facto in nature, it was guided by hypotheses

and by past and present theoretical and empirical data. Kerlinger (1973) believed that

52

when a study is guided by alternative hypotheses with predictions, then the resultant data

of such a study is more valid (p. 391).

Population

This study was an ex-post facto research project utilizing psychosocial data

gathered by the researcher or past data already collected by a licensed psychologist. The

inmate population was comprised of Black males from an urban, Mid-Atlantic

correctional institution, with a history of criminal recidivism, and substance abuse. The

inmates of the correctional facility were volunteers in the substance abuse treatment

program. The inmates had demonstrated an interest in making changes in their lives.

Participants of the study were required to complete the test battery as part of the

acceptance criteria for the treatment program. Only Black male inmates were selected for

this study because of the disproportionate large population within the facility where the

investigation transpired.

Sample

The population sampled included Black males ranging in age from 21 though 55

years old. All had previous juvenile and/or adult adjudications. The inmates were

incarcerated in a long-term (over one year) residential treatment program in a large

metropolitan location.

Procedures

This researcher tested, interviewed, and explored the files of inmates incarcerated

in a correctional treatment facility in a large metropolitan area. Of these inmates, 178

were selected for this study and placed into classified groups using Holland's Theory

53

(RIASEC) single code of classification. The following criteria were utilized as set forth

below.

The researcher administered Holland's Self-Directed Search (SDS) to each of the

inmates volunteering for the treatment program at the facility. The data used was already

found in existing data derived from the archived files. According to the results of the

search, each inmate was classified, according to Holland's one letter code R, I, A, S, E, or

C representing one of the six personality types: Realistic, Investigative, Artistic, Social,

Enterprising, or Conventional.

Each of the groups was tested in specific areas of concerns. Data were gathered

from both self-report and socio-psychometric testing. One area of concern included

ability and aptitude testing. Vocational training and educational information were self-

reported. The inmates' verbal intelligence level was obtained using subtests (information,

comprehension, vocabulary, and similarities) from the (VICS) Wechsler Adult

Intelligence Scale-II (WAIS-R). Vocational interests included: career personality, career

interests, skill ability, job satisfaction, work involvement, interpersonal abuse, dominant

style, and risk-taking behavior, which were obtained through the use of Holland's Self-

Directed Search (SDS), as well as Holland's and Gottfredson's Career Attitudes and

Strategies Inventory (CASI). Personality and psychological characteristics were

measured using the following instruments: Rorschach Inkblot Method (RIM) and the

Millon Clinical Multiaxial Inventory-II (MCMI-II). This information was then recorded

and analyzed as to the correlation and interrelation of the six groups assigned to each

single letter Holland code (RIASEC).

54

There was a panel of experts set up for determining the quality and quantity of

work among the sample population in the community using ordinal data. The panel

included two licensed Clinical Psychologists and the researcher. The following scale was

determined:

1. The quality of career development.

2. The quantity of work behavior.

Each of the two categories was divided into three groups:

1. Quality of career development - (a) no skill training, (b) semiskilled,

and (c) skilled; and

2. Quantity of work behavior - (a) 0-11 months, (b) lyear-2 years, and (c)

over two years.

Each of the three groups in the quality group was assigned a point value. No

training was given one point, semiskilled, two points, and skilled, three points. Each of

the three groups in the quantity group was assigned a point value. Zero months - one

year were given one point, one year to two years, two points, and over two years three

points. Each subject received one through three points in the quality group and one

through three points in the quantity group, depending on the quality and quantity of

inmate career development skill and work behavior. From this basis, three profile groups

were derived. Through the use of several expert judges (two Ph.D.'s who had worked

extensively with the prison population and the problem of recidivism) and the researcher

an acceptable numerical continuum of ordinal data for classification, using numerical

values, was developed for this specific population to evaluate the quality and quantity of

work in the community. The following test batteries were utilized to establish

55

intelligence, educational, vocational, and personality guidelines. Only the IQ subtests

(VICS) of the Wechsler Adult Intelligence Scale (Information, Comprehension,

Vocabulary, and Similarities) were used for this research. The VICS was the subtests

use by the prison facility where the research was conducted. The scores of these four sub

tests are a rough estimate of the inmates IQ. The four sub-tests are added together and

divided by four.

1. Wechsler Adult Intelligence Scale (VICS):

a. A score below 69 places the functioning level of the subject in the

mentally deficient range of intelligence.

b. A score between 70 and 79 places the functioning level of the subject in

the borderline range of intelligence.

c. A score between 80 and 89 places the functioning level of the subject in

the low average range of intelligence.

d. A score between 90 and 109 places the level of functioning of the

subject in the average range of intelligence.

e. A score between 110 and 119 places the level of functioning of the

subject in the above average range of intelligence.

f. A score between 120 and 129 places the level of functioning of the

subject in the superior range of intelligence.

g. A score of 130 and over places the level of functioning of the subject in

the very superior range of intelligence.

2. Holland's Self-Directed Search (SDS):

a. Each subject was administered the SDS.

56

b. The responses were scored to establish a personality inventory profile

classification of the highest three letter classifications. Then the highest

Holland single letter summary classification (RIASEC) was designated for

the research.

3. Career Attitudes and Strategies Inventory (CASI):

a. The self-reported inventory was administered to each subject.

b. The inventory was then scored to develop a summary about the subject

that reports the subject's thoughts, attitudes, feelings, and approaches to

work and non-work situations, as compared to other adults.

4. Rorschach Inkblot Method (RIM): This projective test was administered to the

subjects to develop psychological profiles of decision-making styles. The

EB ratio was used in the study to indicate the impact on the subject's basic

affect and cognition during the psychological process. The Egocentricity

Index was used to assess the subject's self-perception (Exner, 1993,

Gacona and Reid, 1994). The EB (Erlebnistypus) is a relationship

between two variables, human movement, and the weighted sum of the

chromatic color responses. This ratio provides information on how affect

or cognition impacts on the basic psychological decision-making styles of

the subject. From this ratio, it could be determined if the subject was

extratensive, introversive, or ambitent.

The Egocentricity Index [(3r + (2) (R)] provides a measurement of

self- concern and possibly, self-esteem. If the individual's average on the

index falls above the average range of between > .44, the individual would

tend to be more involved with himself than are most people. If the index

score falls below < .33, it can be assumed, according to Exner (1993), that

the subject's estimate of personal self-worth tends to be quite negative.

5. Millon Clinical Inventory -II (MCMI-II):

The Millon Clinical Inventory-II was used to distinguish psychological

features of the inmates and the correlation as it relates to the inmates'

single letter Holland code. Then the data was used to observe any

significant personality style inter-correlation between each of Holland's

six personality codes.

1. (X) Gauge measures the Disclosure Level of the client. If the raw score

on the X scale is less than 145 or greater than 590, the results are invalid.

The Desirability Gauge (Y) measures the tendency of the client to make a

highly desirable impression. A base rate (BR) score of greater than 75

shows unusual openness in completing inventory and discussions. The (Z)

Debasement Measure (BR) of more than 75 signifies devaluation of self,

with presentation of more difficulties than seen during an objective review

(Millon, 1992).

2. The MCMI-II assesses both ( Axis I) Clinical Syndrome Scales and

(Axis II) Clinical Personality Pattern Scales, according to the DSM-IV.

3. Base rate (BR) scores of 75 were set for all scales at the line above

which scale percentages would correspond to the clinically judged rate for

"presence" of personality or syndrome features. The (BR) scores of 84

58

were set for all scales at the line above, which scale percentages clinically

judged rate for the "prevalence" or most salient personality syndrome

( Millon, 1987). The data from the above psychological variables, derived

from the 175-item inventory, were entered according to each inmate's

single letter classification code established by Holland's Self-Directed

Search (SDS). All subjects were assigned a random identification number

between one (1) and one hundred and seventy-eight (178) to assure

confidentiality during the testing and research.

Instrumentation

The psychosocial instruments selected for this study were based on the following

considerations: (1) the skill and competence of the testing instruments; (2) the need to be

able to administer a battery of instruments to each incoming inmate in order to make a

gross assessment of the individual's psychological and sociological make-up (more in-

depth evaluation could be obtained through having the offender referred to an outside

source); (3) the need to obtain immediate results (3-5 days) on each inmate in order to be

able to design an individual treatment plan; and (4) employing measurements that have a

satisfactory reliability and validity data on the reference groups known for criminal

activity, substance abuse, mental abnormalities, recidivism, and poor community work

history. This investigator examined a number of instruments that would produce a

collection of test information that would examine important variables, such as

personality, education, intelligence, work history, quality and quantity of work history,

work satisfaction, and career personality. The test battery included: The Structured

59

Clinical Interview (SCI), Self-Directed Search (SDS), Career Attitudes and Strategies

(CASI), Millon Multiaxial Clinical Inventory-II (MCMI-II), Wechsler Adult Intelligence

Scale-Revised (WAIS-R) (VICS), and Rorschach Inkblot Method (RIM) (Exner, 1993).

1. The Structured Clinical Interview (SCI) was developed by Dr. Ronald Klein,

Ph.D., ABPP, and Carolyn Shrewsbury, M.Ed., LCPC, to gather self-reported

information concerning socio-demographic background, criminal history, abuse issues,

medical problems, substance abuse, previous mental health issues, and the general

background of each inmate. The Structured Clinical Interview (SCI) was also designed to

determine if an individual is suffering, or has ever suffered, from a major psychiatric

disorder, such as: antisocial personality, depression, mania, obsessive-compulsive

disorder, schizophrenia, post-traumatic stress disorder (PTSD), panic disorder, phobias,

adjustment disorders, eating disorders, and/or drug and alcohol abuse. The individual's

answers are ultimately indicated on the interview form.

2. Holland's Self-Directed Search (SDS) is a self-administered,

self-scored vocational test. Its approach gives attention to behavior style or personality

type as the major influence in career choice and development. It provides an explicit link

between various personality characteristics and corresponding job titles. There are six

personality types; (a) Realistic [R], (b) Investigative [I], (c) Conventional [C],

(d) Artistic [A], (e) Social [S], or (f) Enterprising [E].

3. The Career Attitudes and Strategies Inventory (CASI) was developed to assess

some common attitudes, feelings, experiences, and obstacles that influence the careers of

employed and unemployed adults. The CASI surveys nine aspects of career or work

60

adaptation; (a) job satisfaction, (b) work involvement, (c) skill development, (d)

dominant style, (e) career worries, (f) interpersonal abuse, (g) family commitment,

(h) risk-taking style, and (i) geographical barriers. The reliability coefficients (alpha)

ranged from .79 to .94.

4. The Wechsler Adult Intelligence Verbal Scale R (WAIS-R,) was used to establish

a basic intelligence level using the verbal comprehension subtests (VICS), vocabulary

(V), information (I), comprehension (C), and similarities (S).

5. The Millon Clinical Inventories-II (MCMI-II) is based on Millon's theory of

personality and psychopathology and coordinated with the multi-axial format and

conceptual terminology of the American Psychiatric Association's DSMIV. The MCMI-

II contains separate norms for racial differences in terms of values, perceptions, and

expectations ( Hamberger & Hastings, 1992). Validity and reliability of the MCMI-II (

Millon, 1992) became an integral part of its development in three major states:

theoretical-substantive, internal-structural, and external-criterion validation. Items were

evaluated on how well the content corresponded with the theory (Millon, 1992). The

internal-structural state was evaluated on how closely they interrelated with the overall

model of psychopathology. The external-criterion validation evaluated the degree each

test scale empirically corresponded to other measures of a disorder or syndrome. Each

validation stage was built on the previous one (Million, 1992). The MCMI-II has also

been utilized in a multitude of other studies to examine and identify character disorders.

6. The Rorschach Inkblot Method (RIM) is a projective test that provides

descriptive information about the psychological characteristics of the subjects. It was first

introduced in 1921 and consists often cards with inkblots. The inkblot test became

61

synonymous with clinical psychology by focusing on assessment and diagnostics (Exner,

1993). Validity and reliability for the Rorschach is attributed to the comprehensiveness in

data collection, initiated by John Exner for more than 30 years. The researcher has chosen

to focus primarily on Exner's (1993) interpretation.

Hypotheses

The statement of the general hypotheses depicts an effort to account for various

psychosocial variables, using the Structured Clinical Interview (SCI), the Wechsler Adult

Intelligence Scale-R (WASI-R) [VICS subtests], Rorschach Inkblot Method (RIM),

Career Attitudes and Strategies Inventory (CASI), Millon Clinical Inventories-II (MCMI-

II), and Holland's Self-Directed Search (SDS), for the purposes of this investigation. The

relationships that were examined between the variables hopefully, shall clarify what

factors were common to the profiles of the offender sample that would be effective in

counseling inmates toward successful career development and work behavior.

The general hypotheses examined in this study are presented below:

(H-l) There will be an equal number of inmates in each of the Holland

single letter code (HSLC) classifications.

(H-2) There are significant differences among the various IQ levels and

the Holland single letter code classifications.

(H-3) The Holland single letter code classifications will predict one of

three EB styles (ambitant, introversive, and extratensive) on the

Rorschach.

(H-4) The Rorschach Egocentricity Index (3r + (2)/R) will predict the

Holland single letter code (HSLC).

62

(H-5) The MCMI-II subtests, grouped according to DSM-IV clusters, will

predict the Holland single letter code classifications.

(Sub-H-5.1) The MCMI-II subtest Cluster "A," when grouped

according to the DSM-TR, will be able to predict the Holland

single letter code.

(Sub-H-5.2) The MCMI-II subtest Cluster "B," when grouped

according to the DSMR-III, will be able to predict the Holland

single letter code.

(Sub-H-5.3) The MCMI-II subtest Cluster "C," when grouped

according to the DSMR-IV, will be able to predict the Holland

single letter code.

(H-6) The MCMI-II 10 Clinical Patterns will predict the Holland single

letter code.

(H-7) The MCMI-II Severe Personality Patterns will predict the Holland

single letter code.

(H-8) The MCMI-II Clinical Syndrome will predict the Holland single

letter code.

(H-9) The MCMI-II Severe Syndrome will predict the Holland single

letter code.

(Sub-H-9.1) The CASI will predict the CASI subtest Job

Satisfaction within the HSLC-tested inmates.

(Sub-H-9.2) The CASI will predict the CASI subtest Dominant

Style within the HSLC-tested inmates.

63

(H-10) The Career Attitudes and Strategies Inventory (CASI) will predict

the CASI subtest scales within the inmate group tested with the Holland

(SDS).

(H-l 1) The Quantity and Quality of Work history in the community will

identify the Holland single letter code classification.

(H-l2) The Career Attitudes and Strategies (CASI) subtest scale Job

Satisfaction can predict the Quality of Work among the classified group of

the Holland single letter code.

(H-l 3) The Quality and Quantity of Work and Grade Level will predict the

classified Holland single letter code.

Data Collection

The study initiated with the classification of each subject's three-letter vocational

personality code collected from Holland's Self-Directed Search (SDS). The data was

recorded and subjects were classified into one of six groups, according to the inmates'

vocational personality single letter code: Realistic [R], Investigative [I], Artistic [A],

Social [S], Enterprising [E], or Conventional [C]. Once this data was retrieved, other test

data was collected from the Wechsler Adult Intelligence Scale-R (WAIS-R verbal

comprehensive subtests VICS), Millon Multiaxial Clinical Inventory-II (MCMI-II),

Rorschach Inkblot Method (RIM), Career Attitudes and Strategies Inventory (CASI), and

the self-reported Structured Clinical Interview (SCI) to establish relevant data as to the

correlation, if any, between the six groups and the inter-correlations within each group.

64

After gathering this information, three profile groups were established, according

to the self-reported quantity of work experience of the inmates and the quality of work, as

established by the afore-described panel of expert judges. The inmates were then placed

back into the six groups, assigned by Holland's single letter code, to analyze any

relationship between the subject's quantity and quality of work history within the

characteristics of the career personality codes (RIASEC).

Statistical Treatment

Data were analyzed by utilizing the SPSS computerized statistical system

software program, using the following statistical techniques: (1) calculating the means,

standard deviations, and percentages; (2) examining the means, medians, modes, standard

deviations, and range of the various psychosocial data collected correlated to Holland's

single letter career personality code (RIASEC); (3) obtaining item, subscale, and total

scale reliabilities through the use of the SPSS computerized statistical system software

program to establish the coefficient of internal consistency; (4) Multiple Linear

Regression (MLR) analysis, which is the general case of the least sum of squares

solution, was used to calculate significant linear relationships between the various groups

under investigation; and using (5) discriminate analysis and the anova two-tailed test.

The means, standard deviations, and percentages were examined through the use

of MLR analysis. The investigator was able to obtain the required means, standard

deviations, and percentages by running the statistical program, without putting in

regression models and F-ratios. Of primary importance in using this information was to

examine the mean raw category scale scores, standard deviations, and percentages of

65

Holland's single letter classification groups. This statistic was used to calculate

significant linear relationships which existed between the various groups within the

study. The selection of MLR by this investigator was based on the following reasons:

1. MLR is the general case of the least square solution. Whatever one can do with

other statistical techniques, such as the r-test, F-test, etc., the researcher can do with

regression analysis. Because the t and F-tests are special cases of the least squares

solution, the use of the more general case (MLR) would also be appropriate (Hinton,

1999).

2. Of primary importance is the ability to write full and restricted models with the

regression procedure that reflects the specific research hypothesis, or questions being

tested. This provides much more flexibility than traditional analysis of statistics.

3. A researcher can use the f-test and F-test with regression analysis,

without confusing them with the research design. For example, one can test the

full model against the restricted model and obtain the F-ratio value, without confounding

the statistics with the design of the study.

4. Using MLR, a researcher can ask questions relating to a large number of

categorical or continuous variables. The questions can relate continuous by continuous,

categorical by categorical, or categorical by continuous. Thus, one can gain additional

degrees of freedom and power with the regression procedure (Hinton, 1999).

5. When carrying out or holding constant certain variables, which are believed to

affect the criterion, the regression procedures make the covariance questions much easier

to calculate and interpret (Kerlinger, 1973).

66

6. The use of MLR can deal with unequal Ns, without having to provide a

correction factor, which must be employed when using traditional analysis of variance

procedures.

7. Chi-Square (X2) is a statistical technique that makes it possible to compare the

observed frequencies expected in different categories or with the actual numbers obtained

to the frequencies expected from the hypothesis.

Because of the above-mentioned reasons, this investigator selected Multiple

Linear Regression (MLR) analysis as the primary statistical procedure for the current

study. The level of statistical significance or confidence level was set, indicating that a

five percent variability in the data were considered to be the result of some influence,

other than chance, and with the one percent level, indicating less chance of error. Based

on the conclusions of the data, this researcher must either confirm or deny the hypothesis

that has been stated. The statistically-based hypothesis or null hypothesis will indicate if

a difference does occur. The null hypothesis will either be accepted or rejected. An

unknown examiner by race seems to limit their disclosure to examiners, particularly the

White examiners who administer the Rorschach test (Frank, 1992).

Significance of the Study

Implications based on this study may be useful to the "helping professional," such

as counselors, educators, vocational specialists, and social workers assisting in the

correctional justice system to reduce the rate of recidivism through career development

and improved work behavior. This research will show what, if any, conclusions can be

drawn that would demonstrate a relationship between any of the assigned variables to

67

career maturity, work values, education, intelligence, interests, abilities, personality

styles, or pathology, and the development of careers and better work behavior among

criminal substance abusers, by utilizing Holland's single classification code. The

development of profiles established through the single letter classification code and the

quality and quantity of work history would determine which psychosocial variables,

between samples of Black male substance abuse felons, could better help professionals in

the prison system to evaluate and develop treatment plans that would better prepare

inmates, upon release, with the skills needed to enter and become productive and

responsible members of the work force.

Limitations of the Study

Limitations of this study may include:

1. Self-reported inventories can be misleading or distorted.

2. Test batteries or inventories have low or limited norms using minority

populations.

3. The validity and readability of self-reported inventories are critically

related to the ability of the subjects' reading and comprehension skills.

4. There is still much debate underlying intelligence separate from

I.Q. scores and the impact of intelligence testing on Black

Americans in forming predictive bias.

5. All subjects volunteered for the program at the correctional

treatment facility, indicating a willingness to make changes in their

lives, therefore, there was no random selection procedure in the

research study.

68

6. The limitations of the researcher's experience in test interpretation,

statistical analysis, and research.

7. Finally, the research study cannot be definitive, but only examine an

aspect of the problem and, in doing so, provide some information and

stimuli for further and more extensive research.

69

CHAPTER IV

RESULTS

Findings of the General Hypotheses:

The statement of the general hypotheses was an effort to account for various

psychosocial variables using the Structured Clinical Interview (Appendix A), WAIS- R

(VICS) subtests, Rorschach Ink Blot Method, CASI, and Holland (SDS) for the purpose of

this investigation. The relationships that were examined between the variables hopefully

would clarify what factors were common to the profiles of the offender sample that

would be effective in counseling inmates toward successful career development and work

behavior in the community.

The findings of the data collected are presented in this chapter. The results of the

study are organized into eight major sections in order to present the results in a clear and

ordered manner. The research findings were examined in the following manner. Section

(1): The research hypothesis H-l related to the inmates classified according to the HSLC.

Section (2): The research hypotheses H-2 tested the individual's IQ score using the verbal

subtests (VICS) of the WASI-II and the relationship according to the inmates HSLC

classification. Section (3): The research hypotheses H-3 and H-4 related to the inmates

HSLC, the EB style of decision making and coping style, and Egocentricity Index related

to the self-esteem. Section (4): The research hypotheses H-5, H-5.1, H-5.2, H-5.3, H-6,

H-7, H-8, H-9, related to the inmate population classified according to the HSLC and

personality patterns according to the MCMI-II (DSM-TR) Personality Clusters, Clinical

70

Personality Pattern, Severe Personality Pathology, Clinical Syndrome, and Severe

Syndrome. Section (5): The research hypothesis H-10 (part 1 and part 2) related to the

CASI subtests in predicting the inmates HSLC. Section (6): The research hypotheses

H-l 1, H-12, H-13 related to the CASI subtests and the quality and quantity of work the

inmate population participated within the community according to their HSLC

classification. Section (7) The CASI subtest, job satisfaction and the quality and quantity

of work among the classified inmates and quality and quantity of work and grade level

within HSLC were evaluated. Section (8): The summarized findings of the research data.

The general hypotheses examined in this study are presented below:

Sectionl

H-l There will be an equal number of inmates in each of Holland's single letter

code classification.

Table 1.1

The Chi Square Test of Independence

Test of Categorical Variables Chi-Square df Significance 57.8935 4 .0001

The chi-square score was 57.8935 and analyzed the observed frequency with the

expected frequencies. This would indicate that the expected number of inmates in each

category was different than the observed frequency. The df indicates that four categories

are free to vary in the analysis. The data was analyzed and assigned an alpha level of .05

and considered significance. The null hypothesis is rejected, and the research hypothesis

is accepted at a significant level of .0001.

71

Table 1.2

Holland's Single Letter Code for Vocational Development

HSLC Holland's Single Letter Code Holland Codes __,

R A S E C

Category

1.00 2.00 3.00 4.00 5.00

Cases Observed 40 14 68 32 15

Expected

33.80 33.80 33.80 33.80 33.80

Residual

6.20 -19.80 34.20 -1.80

-18.80

Percent

24.0 8.0

40.0 19.0 9.0

Table 1.2 reports the expected number of inmates that were classified in each of the

HSLC and the observed number that were actually included in each letter code. The

expected number of inmates that were classified into each of HSLC's was 33.80 inmates.

When the cases were examined, the number of inmates in each of the single letter codes

was not equal. The HSLC group classification of the inmates eliminated the Investigative

( I ) single letter code due to the fact that there were no inmates classified as ( I ) . The

rest of the study deals with only five of HSLC (R, A, S, E, C).

Table 1.3

The Frequency, Percent, and Cumulative Percent of the HSLC

1.00 =R 2.00 =A 3.00 = S 4.00 =E 5.00 =C

Total Missing Cases

Total

Frequency 40 14 68 32 15

169 10

179

Percent 22.3

8.4 38.0 17.9 8.4

95.0 5.0

100.0

Valid Percent 23.5

8.8 40.0 18.8 8.9

100.0

Cumulative Percent 23.5 32.3 72.3 90.9

100.0

72

Table 1.3 and (Figure 1. /-Appendix-B) represent the number of inmates tested using

the SDS. The HSLC classification identified the individual single letter code of each

inmate. The Social [S] HSLC group included 68 inmates, or 40 percent of the inmates

classified. This was 28 more inmates, or 16 percent more inmates than the closest

Realistic [R] code of 40 inmates. The single letter code of Realistic [R] classified group

was followed closely by the Enterprising [E] classified group of 32 inmates or 19 percent

of the population tested. The single letter code of Conventional [C] included 15 inmates

or nine percent of the population. The lowest number of classified inmates placed in the

Artistic [A] single letter code with 14 inmates, or eight percent of the population in the

study. The residual score indicates the difference in the expected score and the observed

score. The Social [S] score was predicted to be 33.80. The actual number of inmates with

the HSLC [S] was 68. This was over two times the number of inmates expected in a

code. The HSLC [S] was highly significant. The chi-square test of independence was

used for testing the hypothesis that was accepted at the .0001 level of significance. The

null hypothesis was rejected, and the research hypotheses accepted.

Most HSLC groups were not within the expected equal frequencies, but the

Investigative [I] classification was not found to include the HSLC for any of the 169

inmates tested. Investigative people have jobs such as laboratory assistants, product

inspectors, and medical technicians. The investigative type of career personality usually

has math and scientific abilities. The individuals like to work alone, and to solve

problems. The [I] type likes to work on ideas more than people or things. People will

describe themselves as logical, curious, exact, wise, careful, independent, quiet, and

73

modest (Holland, 1998). This is not the profile of individuals that we would usually find

in a large inner city prison population.

The largest HSLC classification group was the Social [S] type. The Social group

of career personality is individuals who like social jobs such as a fast-food worker,

counselor, or nurse. This type of personality likes to be around people. The Social (S)

group like to help others with problems and work more with people than things. People

with the [S] type are described as helpful, responsible, warm, cooperative, idealistic,

generous, and friendly (Holland, 1998). Some of these factors can contribute to pitfalls of

group. The Realistic [R]) type likes to work with tools and machines. People often

describe the [R] type as follows; genuine, sensible, humble, practical, natural, shy, and

thrifty (Holland, 1998). Some of the pitfalls with this group can be the lack of ability to

see transfer of skills, and get stuck in one direction rather than trying something new.

The Enterprising group likes to work with people and ideas more than things.

This [E] group likes jobs such as: salesperson, waiter, travel agent, supervisor, and store

manager (Holland, 1998). This group had just one case below the expected 33.8 number

with 32 inmates with this profile. The [E] type usually has leadership and speaking

abilities. Money and politics are areas of interest and they like to influence people. The

[E] type people are usually described as follows: out going, adventurous, energetic,

optimistic, agreeable, sociable, self-confident, and ambitious. The downside

characteristics of this group might act before thinking, move too quickly without

planning, and have problems focusing (Holland, 1998). The researcher would have

expected the most of the [E] group of inmates to fall into this classification. So many of

the interests and characteristics of the [E] group are found in this classified group. If the

74

research had included two HSLC's instead of just the most prominent ones the or three of

the Holland codes, instead of just the most prominent code, the personality type would

probably have given a better prediction of the inmate population.

The Artistic [A] and Conventional [C] groups were almost equal with 14 in the

[A] group and 15 in the [C] group. These two groups fell well below the expected (33.8)

cases per group. Added together, these groups would still be below the expected number

of cases in each group. When examined closely, the characteristics of inmates would not

normally fit into either of the groups. Holland (1998) reported that people who are

Artistic [A] generally like to work on ideas more than with people or things. Type [A]

people usually have artistic skills, enjoy creating original works, and have a good

imagination. The [A] group jobs would be as a musician, dancer, and singer. People

describe this HSLC [A] group as being open, investigative, independent, and original.

The [C] group likes to work indoors and likes to organize things. The [C] type likes to do

conventional jobs such as bookkeeper, secretary, office clerk, and radio dispatcher.

People describe these individuals as being conforming, practical, careful, thrifty,

efficient, orderly, and persistent. Many of these qualities are not usually found among

substance abusers in the prison population. Some inmates in the [A] group have good

artistic skills, like music and certain types of dance, but these areas are hard in which to

make a career. It can place them in a job that is unstable, with high drug availability, and

with late nightclub settings. These jobs would place the inmates with problems in areas of

great temptation. Many inmates see conventional and artistic qualities as feminine, and

look upon these group job profiles as a female job. This population of male offenders see

themselves in outside jobs and hands on skills. There is a need for the offenders to feel

75

conforming, and will connect with groups as followers. The need to fit in will sometimes

leads to short-term impulsive decisions with a low success rate. The pitfalls according to

Holland (1998) of the [A] group, include making impulsive job decisions, negative work

experiences, and having problems focusing. Pitfalls for the [C] group would include,

looking to others for authority, impulsive, rigid, non-assertive, and development of a lot

of stress and anxiety. The HSLC that was the "best fit" for this population was the [S]

Social group of inmate substance abusers.

Section 2

H-2 There is a significant difference among the various WAIS-R subtests

(vocational, information, comprehension, and similarities (VICS) IQ levels and

the Holland single letter code classification (HSLC).

Table 2.1

The Chi Square Test of Independence of Categorical Variables

Chi-Square Test Verbal IQ Category (VICS)

IQ Levels Category Cases Observed Expected Residual

69 & below 7 0 - 7 9 8 0 - 8 9 90 -109 110-119 120-129

Chi-square 117.4734

1.00 2.00 3.00 4.00 5.00 6.00

3 46 56 52 10 2 Total - 169

D. F. = 5

28.17

28.17 28.17 28.17 28.17 28.17

-25.17

17.83 27.83 23.83 18.17

-26. 17

Significance .0001

Table 2.1 shows that there are significant differences among various IQ levels and the

HSLC. The chi-square test of independence was used for testing the hypothesis, which

was accepted at the .0001 level of significance. The null hypothesis was rejected and the

research hypothesis accepted.

The actual number of inmates classified under the HSLC and the correlation

between the HSLC and the inmate's (VICS) IQ score, only the [S] group (27.83) of

inmates was close to expected number of (28.11) of inmates in each group. This group

scored 80 -89 on the WAIS-R IQ (VICS), placing them in the below average range of

intelligence. There were only three inmates that scored 69 and below on the WAIS-R

verbal subtest score (VICS), which placed the inmates in the mentally deficient range of

intelligence. There were only two inmates out of 169 that scored 120-129, which placed

the inmates in the superior range of intelligence. Twenty-seven percent of the inmates

scored between 70-79, that placed the inmates the borderline range of intelligence. Sixty-

two percent of the inmates scored below average on the WAIS-R (VICS), and thirty-eight

percent of the inmates scored above average on the verbal (VISC) subtest IQ. The chi-

square score was 117.4734 and analyzed the observed frequency with the expected

frequencies. This would indicate that the expected number of inmates in each category

was different than the observed frequency. The df indicates that 5 categories are free to

vary in the analysis. The data was analyzed and assigned an alpha level of .0001 and

considered significant. The null hypothesis was rejected and the research hypothesis

accepted.

77

Table2.2

Verbal (VICS) IQ Level of Inmates Classified According to HSLC

Summaries of IQ

For entire population

Value Label

HSLC-R

HSLC-A

HSLC-S

HSLC-E

HSLC-C

By levels of HSLC Variable

Mean 83.7367

Fig.2.1 Code (VICS) IQ Score

1.00

2.00

3.00

4.00

5.00

83.8500

83.4643

85.9301

88.8047

96.7333

Std. 11.4201

Std. Dev.

10.4879

9.0117

10.4229

12.4709

12.8214

Cases 169

Cases

40

14

68

32

15

Total Cases =178 Missing Cases = 9 or 5.1 Pet.

Table 2.2 identifies the mean and standard deviation of the (VICS) IQ (information,

comprehension, vocabulary, and similarities) scores of the inmates classified using

HSLC. There were 169 inmates tested using the WAIS-R (VICS) to establish each

inmate's verbal intelligence level. The scores were placed in the HSLC classification

group that was already established in H-l. The mean intelligence level of the entire

population tested was 83.7367 with a standard deviation of 11.4201. This places the mean

population of inmates tested at an IQ level, which falls into the low average range of

intelligence. The only HSLC group of inmates classified with a mean score in the average

range of intelligence was Conventional [C], with a mean score of 96.7333 and standard

deviation of 12.8214.

Figure 2.1 (Appendix- C) shows that most of the HSLC classified inmates ranged

in intelligence from borderline IQ (70-79) to average IQ (90-109). There were about the

same number in the mentally deficient range as the superior range. Only a few of the

inmates scored in the high average range of intelligence. If you combine the mentally

78

deficient (1.00), the borderline (2.00), and below average (3.00), figure 2 predicts that a

high majority of the inmates are functioning on a below average level of intelligence.

The mean verbal IQ score of the tested population was 83.7 with a standard

deviation of 11.4. It was expected that each letter of the HSLC would contain 27.8

inmates. The [S] group of (68) inmates in the observed IQ cases was more than two

times the expected number of (28.1) in each HSLC. The average mean score of the [S]

group on the verbal IQ was 85.9, and only slightly higher than the group average. This

was also the HSLC [S] group that had over twice the number of inmates classified into

this classification than was expected in each HSLC. The IQ scores in the tested

population fell between 69 (mentally deficient) and 129 (superior). There were two

inmates, which scored between 120-129 (superior range), 10 inmates that scored

betweenl09-l 19 (high average range), and 52 that score between 90-110 (average range).

The remaining inmates were in the below average range. There were 56 that scored

between 80-89 (low average range), 46 between 70-79 in the (borderline range), and

three fell into the mentally deficient range of intelligence. Of 169 inmates tested, using

the verbal subtest of the WASI-R, 105 tested below the average range of intelligence.

The Holland codes [R] and [A] tested at the mean score of 83.8 and 83.4 respectfully in

the tested population. The [E] code was above the mean score with 32 inmates at 88.8.

The highest scoring group on the verbal subtest of the WASI-R was the [C] group with,

fifteen inmates in the average range of 96.7.

According to Lowman (1991) the Realistic [R] intelligence level is usually in the

low average to average range. The [R] group's mean score of 83.8 falls within

79

Lowman's reported characteristics of HSLC. The cognitive style of the [R] group is

concrete. These individuals, according to the MCMI-II avoidant scale, try to avoid

people, and see things in only one way.

The Investigative [I] characteristics place these individuals with a high

intelligence level and a cognitive style as rational and scientific. There were no [I]

individuals in this population. This would be expected in an inner-city substance abuse

prison environment. Statistical information places most of our inner-city population in an

"at risk" category. Many inner city schools are not up to national standards with regard

to updating school facilities, progressive learning material, parent assistance, certified

teachers, and have major discipline problems. The population is at or below the poverty

level. The student graduation rate is low, and dropouts find the way to the streets and

drugs. The streets are where, it is believed by many of the poor urban population, that

there is fast and easy money. Students see individuals that have dropped out of school

making money. The students wonder why completing school or career development is

important, and for many there seems to be no way out. When students stay in school for

eight years or more and still cannot read or perform basic math skills, things look

hopeless. Many inner city young people have no fathers at home, and mothers who are

using drugs or alcohol to escape reality. It is tough to make it in life when a person faces

these kinds of problems.

Lowman (1991) places the Artistic [A] group in the variable IQ level with

divergent thinking and labile affect. The HSLC [A] group tends to live in a fantasy world

of dreams. Individuals have beautiful dreams, and good imaginations. Loners are also

80

found among these individuals. A lot of the [A] types have ideas of making it big, but do

not understand the amount of work and luck it takes to get a job, or make money in these

fields. This researcher finds this classification of jobs as potentially dangerous career

choices. There is a lot of free time, nightlife, drugs, and sex in this occupational field.

The "A" type-classified inmate was found to be very low in the tested population.

Lowman (1991) reports the Social [S] group and the Enterprising [E] group to

have a moderately high intelligence level. In this population there was a large group of

the [S] personality style inmates. These individuals had significantly higher IQ scores

than any other HSLC. The [E] group and the [R] groups had about the same number of

inmates in each HSCL. This researcher found that the mean IQ of both groups fell in the

below average range of intelligence, but the [E] group with a mean score of 88.8 was

closer to the average IQ range. The [E] group (Lowman, 1991) has personality

characteristics of being warm and nurturing, with a cognitive style of logical and rational.

The [E] group in this population would probably be entrepreneur on the streets doing

either distribution of drugs or finding another type of operation to start. The [E] type has

the affect characteristic of being aggressive and controlling. These are the men on the

street or in prison that like to run the operation. This group is interested in money and

ambition. This type of person with prison domination and control, tend to be inclined

toward setting up deals and coning or threatening others to run the operation.

The last group is the Conventional [C] type. Lowman (1991) reports this group

as having low to average intelligence. This research shows the [C] group in this

population having the highest mean IQ score of 96.7. The [C] type tends to be

constrained, withdrawn, and rigid. In this inmate population, when the individual starts

81

something it is likely to be finished. The [C] group would have been the group that would

have been more likely to finish school. This type does not have good self-esteem and

tends to be avoidant and withdrawn from other people. There were only 15 out of one

hundred and sixty nine that were as classified under this HSLC. Many in this group

would be doing clerical jobs around the prison, and considered a little feminine by other

inmates and easily pushed around, the down side qualities of social manipulation. The

Realistic [R] classified group comprised 40 of the tested inmates. This type of

personality likes to work more with things than with people. Realistic types of people like

jobs such as: auto mechanic, carpenter, electrician, cook, and farmer. The next group was

the Social [S] type (Holland, 1998). This group comprised of (68) of the HSLC cases, and

more than twice the predicted number of 28.17. Social types are found to be warm,

supportive, and dependent. They like to work with people rather than things, and are

likely to be teachers, social workers, or prison workers.

Section 3

H-3 The three EB styles of the Rorschach (extratensive, ambitent, and

introversive) will predict the HSLC classification.

HSLC classification and correlation with Rorschach EB style of decision-making

Analysis of Variance EB l=Extratensive 2=Ambitent 3=Introversive

Table 3.1 andFigure3.1 (Appendix-D) demonstrate the mean score and correlation

between HSLC and Rorschach EB decision-making style. The EB style (decision-making

style) of the inmates tested has no significant relationship to the HSLC. The null

hypothesis is accepted and the research hypothesis is rejected.

82

The research produced no correlation with the EB style on the Rorschach and

HSLC. The null hypothesis was accepted and the research hypothesis rejected. However,

this research found some interesting information. The Figure 3 indicates that there are at

least twice the ambitents in this population than extratensive or introversive. The

extratensive and introversive EB styles were almost equal. About 50 percent of the

inmates are ambitent. According to Exner (1993), if the EB fails to indicate a coping

style the person considered ambitent. It is likely that the emotions of the person are both

erratic and ineffective when engaged in problem-solving and decision-making behaviors.

This would indicate that over half of the substance abuse inmates included in the group

sometimes let feelings strongly influence thinking, and the next time with a similar

situation allow their thinking to override with thinking and feeling. The extratensive

group tends to intermingle feelings with thinking especially during problem solving and

decision-making activities. These people will display feelings, and are not careful in

controlling those displays. This population of 75% ambitent or extratensive can be

unpredictable in thinking, impulsive in behavior, and confused in decision-making and

problem solving. The introversive group will keep feelings at a distance. This group can

openly display routine emotion, but usually will try to keep feelings under control and

will try to think things out before action is taken.

Figure 3.1 (Appendix- D) indicated that even though the research hypothesis was not

significant in predicting any correlation between the HSLC and the Rorschach EB score,

there were a larger number of inmates found to be ambitent than was expected by the

83

researcher. Of the 159 inmates given the Rorschach, over 80 inmates were recorded as

ambitent. Introversive and extratensive categories were almost equally divided at 25%

each.

H-4 The Egocentricity Index (3r+(2) /R) of the

Rorschach will predict the HSLC classification.

Table 4.1

The Egocentricity Index of the HSLC classified population:

Subjects

179 with 16 missing=163

HSLC R, S, E, C, A All codes

>.44 Above Average Range

34 inmates

Average Range

69 inmates

<.31 Below Average Range

60 inmates

Table 4.1 indicates the number of subjects that fell into each category of the Rorschach

Egocentricity Index. Thirty-four individuals were classified above (>.44) mean range

which would indicate that they are more involved with him self than are most others. This

would be considered a narcissistic-like feature. Sixty-nine individuals were classified in

the average range. Sixty individuals were classified in the below (<.33)average mean

range, which would indicate that the individual's estimate of himself would tend to be

quite negative.

Table 4.2

HSLC - Realistic Classification on the Egocentricity Index Total = 38 9 (R)>.44

24% 18 ( R ) Average 47%

11(R) 29%

Table 4.2 (Appendix- E) indicates that about the same percentage of individuals

classified as Realistic [R] fall into the low range and the high range of the Egocentricity

Index. The largest percentage falls within the normal range of self-esteem.

84

Table 4.3

HSLC- Artistic Classii TOTAL= 15 3 (A) >.44

20%

ication on the Egocentricity Index 6 (A) Average 40%

6 (A) <.33 40%

Table 4.3— (Appendix- E) reports the percentage of individual's classified as Artistic [A]

according to the HSLC that are above, below, or in the normal range of self-esteem. This

states that 20% of the classified individuals are in the above average range on the

Egocentricity Index, with 40% in the normal index range. The low index range has 40%

of the classified inmates in the low self-esteem group.

HS1 Total = 64

LC - Social Classification on the Egocentricity Index 11(S)>.44 17%

34 (S) Average 53%

19 (S) <.33 30%

Table 4.4 (Appendix- E) indicates that only 17% of the individuals in the classified

Social [S] group are above normal on the Egocentricity Index, and 30% are below the

average. This classification group has the largest percentage in the normal range of self-

esteem.

Table 4.5

HSLC - Enterprising Classification on the Egocentricity Index TOTAL=31 6 (E) >.44

19% 5 (E) Average 16%

20 (E) <.33 65%

Table 4.5 (Appendix- E) indicates that only 16% of the individuals classified as

Enterprising fall into the normal range on the Egocentricity Index, and only 19% on the

above level. The Enterprising classified group with an index level of 65% would

85

indicate that there could be a serious problem with self-esteem among the inmate

population.

Table 4.6

HSLC-TOTAL=15

Conventional Classification on the Ej 5 (C)>.44 33%

6 (C) Average 40%

eccentricity Index 4 (C) <.33 27%

Table 4.6 (Appendix- E) indicates that 33% of the individuals classified as Conventional

fall into the high level of the Egocentricity Index with 40% in the normal index range.

Only 27% of the individuals or four indicate a possible problem with self-esteem.

Figure 4.2 (Appendix -F) indicates that 47%, or almost half of the HSLC Realistic

are in the normal egocentricity range. That 29% of the HSLC Realistic are in the below

average Egocentricity Index range, and that the subjects estimate of self-worth tends to be

quite negative. This group would probably have low self-esteem. The above average

index was 24% in this HSLC Realistic group, therefore the sample HSLC (R) tended to

be more interested in themselves than in others or would seem to have narcissistic-like

features.

Figure 4.3 (Appendix- F) shows that 40% of the HSLC Artistic are in the normal

Egocentricity Index range. It also shows that 40% are also in the below average range.

Therefore, the subject's estimate of self-worth tends to be quite negative. The inmates

would have low self-esteem. The above average index was low (20%) in this Artistic

group, therefore only a few of the sample HSLC (A) population demonstrated a

preoccupation with themselves more than in others, or would seem to have narcissistic-

like features.

Figure 4.4 (Appendix - F) shows that 30% of the HSLC Social is in the normal

Egocentricity Index range. That 53% or over half of the HSLC Social are in the below

average index range, and that the subjects estimate of self-worth tends to be quite

negative. The inmates would probably have low self-esteem. The below average index

range is twice as large in the HSLC (S) then the combined number in the normal and low

range of the index. The above average index was low (17%) in this Social group,

therefore not many of the sample HSLC (S) tended to be more interested in themselves

than in others, or would seem to have narcissistic-like features.

Figure 4.5 (Appendix - F) demonstrates that only 12% of the HSLC

Enterprising are in the normal Egocentricity Index range. That 68% of the HSLC

Enterprising are in the below average index range and that the subjects estimate of self-

worth tends to be quite negative. This group would probably have low self-esteem. The

above average index was lower at 20% in this Enterprising group, therefore the majority

of the sample HSLC (E) tend to be more interested in themselves than in others or would

seem to have narcissistic-like features.

Figure 4.6 (Appendix- F ) demonstrates that 40% of the HSLC Conventional

are in the normal Egocentricity Index range. That 25% of the HSLC Conventional are in

the below average index range, and that the subjects estimate of self-worth tends to be

quite negative. This group would probably have low self-esteem. The above average

index was 35% in this Conventional group, therefore the sample HSLC (C) tended to be

more interested in themselves than in others, or would seem to have narcissistic-like

features.

87

Section 4

H-5 The MCMI- II Clinical Personality subtests, when grouped

according to DSM-IV clusters (A, B, & C) will be able

to predict the HSLC.

Sub H-5.1 The MCMI-II subtest cluster "A", when grouped

according to DSM-IV will be able to predict the HSLC.

Table 5.1

MCMI-II Subtests Cluster "A"

Cluster "A" - Schizoid (MCMISCHZ), Paranoid (MCMIPARA), Schizotypal (MCMISCTY) Variable MCMIPARA MCMISCHZ MCMISCTY

Beta In - .052303 - .112451

.015959

Partial -.052303 -.112451 -.015959

Min Toler 1.000000 1.000000 1.000000

T -.658 -1.423

.201

SigT .5113 .1568 .8413

Table 5.1 ( Appendix- G) Shows no significant relationship between the HSLC group

and MCMI-II cluster "A." The MCMI-II cluster "A," as grouped according to the DSM-

III cannot predict any significant relationship with respect to the dependent variable

HSLC. The null hypothesis is accepted and the research hypothesis is rejected. Cluster

"A" includes: schizoid, paranoid, and schizotypal, which are three of the 10 Clinical

Personality Patterns on the MCMI-II.

Sub H- 5.2 The MCMI- II subtest cluster "B" will be able to predict the HSLC.

Table 5.2

Variable (s) Entered on Step Number 1... .MCMIANTI (Antisocial)

Cluster "B" - Antisocial (MCMIANTI), Borderline (MCMIBDLI), Histrionic (MCMIHID), Narcissistic (MCMINARC)

Continued p. 88

88

Multiple R

.15865 Analysis of Variance

Regression F = 4.07944

R Square

.02517 DF

1

Adjusted R Square

.01900 Sum of Squares

6.25144 Sig. F = .0451

Standard Error

1.23791 Mean of Squares

6.25144

Table 5.2 (Appendix H) represents any significant relationship between the HSLC group

and MCMI-II cluster "B." The Clinical Personality Pattern antisocial of the MCMI-II

cluster "B" was the first predictor variable, when calculating with the stepwise forward

regression. The F distribution score of 4.07944 yielded a significant interaction between

the HSLC group and antisocial personality style. The data was analyzed and found

significant at the .05 level. The null hypothesis was rejected and the research hypothesis

accepted for antisocial. There is also a significant trend of .0877 towards histrionic.

Borderline, narcissistic, and histrionic personality styles in cluster "B" were rejected.

Table 5.3

The Mean Score and Standard Deviation of the Subtest "Antisocial.

Variable

MCMIANTI

Mean

84.75

Std. Dev.

19.81

Minimum

.00

Maximum

121.00

Valid N

163

Label

Antisocial

Table 5.3 (Appendix H) identifies the mean score of the population for the MCMI -II

cluster "B" subtest antisocial as 84.75 with a standard deviation of 19.81.

Figure 5.1 (Appendix -H) graph indicates through the use of symbols and colors

on the right, the raw score of inmates on the MCMI-II. The scaled scores found

antisocial disorder to be high in each of the classified HSLC (1=[R]), (2=[A])5 (3=[S]),

(4=[E]), and (5=[C]). It can be observed that the largest number and highest scores were

classified in the [S] Social group. The [R] Realistic and the [E] Enterprising HSLC were

also high for antisocial disorder. There were not many scores below the scale score

of 75. The graphs, Figure 5.1 and Figure 5.2 (Appendix- H) depicts a different way to

demonstrate how 3 = [S] Social is driving the antisocial disorder, with a high number of

inmates falling in this sub-scale MCMI-II classification. The [R] Realistic group is the

next highest classification with about a third of the inmates.

Multiple regression was used to test multiple variables to find if any correlation

exist. The dependent variable is the HSLC and the independent variables include:

antisocial, borderline, histrionic, and narcissistic from the DSM-IV cluster "B" subtests

of the MCMI-II. The research hypothesis found that the subscale, antisocial disorder, had

a significant interaction at the .05 level of significance. The null hypothesis was rejected

and the research hypotheses accepted. Antisocial personality pattern was found to be a

good fit with the group of HSLC inmates. This is a correlation that the researcher would

expect to see with any inmate population. The mean antisocial score of this test group

was 84.8. A score of 75 is considered, on the Millon to be a presence of personality

disorder, and 85 and above, a strong prevalence of personality disorder. About 45 of the

165 inmates tested were below the 75 point score for mild to moderate personality

disorder. Antisocial personality disorder in adults can be an especially a serious mental

problem. AntisociaPs do not like to follow rules and regulations. Treatment is difficult

with this population. Learning there are consequences for negative behavior is probably

the most effective treatment. These men are in prison because they would not comply

with the rules that govern society.

90

Sub H- 5.3 The MCMI-II subtests cluster "C", when grouped according to the

DSM-IV will be able to predict the HSLC

Table 5.4

MCMI- II Subtests Clusters "C"

Variable (s) Entered on Step Number 1... (MCMICOMP) Compulsive

Cluster "C" - Passive Aggressive (MCMIPAG), Dependent (MCMIDEP), Avoidant (MCMIADVO), Compulsive (MCMICOMP)

Multiple R

.21572 F =

Variable

MCMICOMP

R Square

.04654 7.71151

B

.017583

SE B

.006332

Adjusted R Square

.04050 Signif. F

Beta

.215721

Standard Error

1.22427 .0062

T

2.777

SigT

.0062

Table 5.4 (Appendix-1) demonstrates if there are any significant relationship between

the HSLC group, and MCMI-II cluster "C." The Clinical Personality Pattern

compulsive of the MCMI-II cluster "C" was the first predictor variable when calculating

with the stepwise forward regression. The F distribution score of 7.71151 yielded a

significant interaction between the HSLC group and compulsive personality style. The

data was analyzed and found significant at the .0062 level. The research hypothesis

accepted for compulsive was accepted.

Multiple regression was used to test the remaining variables to find if any

correlation exist. The dependent variable is the HSLC and the remaining independent

variables included cluster "C" from the DSM-TR personality patterns were: avoidant,

dependent, and passive aggressive of the MCMI-II. The research indicated that cluster

91

"C" could not predict any further significant relationship with the HSLC's. The null

hypothesis was accepted and the research hypotheses rejected except for compulsive.

H-6 The MCMI-II10 Clinical Personality Patterns will predict the group HSLC

Table 6.1

MCMI-II Clinical Personality Patterns and any SignificantRelationship with the HSLC Group

Variable (s) Entered on Step Number 1... .MCMICOMP

Clinical Personality Pattern subtests - Schizoid(MCMISCHZ), Avoidant(MCMIADVO), Dependent(MCMIDEP), Compulsive (MCMICOMP) Narcissistic(MCMINARC), Antisocial(MCMIANTI), Aggressive Sadistic(MCMIAGSA), Passive Aggressive(MCMIPAG), Self-Defeating(MCMISFDE), Histrionic (MCMIHIS) F = 7.71151

Variable

MCMICOMP

B

.017583

SE B

.006332

Signif F = .0062

Beta

.215721

T

2.777

SigT

.0062

Table 6.1 (Appendix- J) recorded any significant relationship between the HSLC group

and the Clinical Personality Patterns on the MCMI-II. The Clinical Personality sub-test

for compulsive of the MCMI-II was the first predictor variable when calculating with the

stepwise forward regression. The F distribution score of 7.71151 yielded a significant

interaction between the HSLC group and the Clinical Personality Pattern compulsive.

The data was analyzed and found significant at the .01 level. The null hypothesis was

rejected and the research hypothesis accepted for compulsive, and rejected for schizoid,

avoidant, dependent, histrionic, narcissistic, antisocial, aggressive sadistic, passive

aggressive, and self-defeating. Under H-5.2 the DSM-fV "cluster B" of the MCMI-II,

antisocial was significant at the .05 level, but was not significant when grouped with all

ten of the MCMI-II Clinical Personality Patterns.

92

The Multiple Regression test was used to test multiple variables to find if any

correlation exists. The dependent variable is the HSLC, and the independent variables

included the 10 Clinical Personality Patterns of the MCMI-II. The research hypothesis

found significant interaction at the .05 level of significance for the compulsive scale. The

null hypothesis was rejected and the research hypotheses accepted, but only for

compulsive personality. At first, the compulsive personality did not seem to fit with this

population. After going over different personality patterns of a compulsive, things started

to fall into place. A large group of inmates are in the mild to moderate range of disorder.

This range would place individuals in a dysfunctional area, but in this population the

compulsive personality could be considered a more positive individual style. Every

personality type can have positive and negative characteristics for each individual. The

research would indicate that there were a group of inmates that fell into the personality

style range, while others were in the disorder range, but the total compulsive personality

for the total HSLC group was significant. Some positive behavioral characteristics

include confident, considerate, respectful, intellectual, and highly organized. Some of the

negative behavior characteristics that are found with compulsives would be cheerless,

rigid, cold, driven, impatient, tense controlled, and defiant. In the affect area the positives

are reserved, sympathetic, and steady. The negatives are stronger in this area of affect.

The negatives include being perturbed, tense, resentful, hostile, angry, anxious, and

intense conflicted feelings toward self and others. The research is being driven between

positive and negative characteristics and is significant, but not in any direction.

93

Figure 5.2

(Appendix -H) shows scores running at the serious compulsive disorder level, in the

HSLC [S] Social and [E] Enterprising classifications. Considering the low number of

cases in the [E] code, almost all are above the 75 mild to moderate disorder. The lowest

scores in the compulsive category would be the [A] Artistic group with no scores

above 75.

Figure 6.1 (Appendix -J) indicates that a large number of the inmate's scores are

falling between 55 and 75 on the compulsive subtest of the MCMI-II. According to the

MCMI-II, these scores would only be approaching any significant level of disorder.

There are more inmates above 75 than below 55. The majority of the inmates are neither

to far above or to far below.

Figure 6.2 (Appendix -J) again shows group of HSLC classified [S] falling in the

upper range of compulsive. The classified [R] group of inmates is also falling into this

higher range of the disorder, indicated by where the multiple numbers of marks are

falling on the graph (each dot is an inmate). The classified [C] group is around a MCMI-

II score of 60 and above with no real low scores.

Table 6.2

Correlation Coefficients of MCMIII Compulsive Sub-test (MCMICOMP)

and MCMI-II Validity Scales

Disclosure (MCMIDIS), Desirability (MCMIDESI), and Debasement (MCMIDEB)

MCMIDIS MCMICOMP -.1433 ( 163 ) P= .068

94

MCMIDESI

MCMIDEB

.4037 ( 163 ) P= .000 -.2244 ( 163 ) P= .004

Table 6.2 (Appendix- J ) demonstrates any correlation between the MCMI-II compulsive

scale, MCMI-II validity scale, MCMI-II disclosure scale, and MCMI-II debasement

scale. The disclosure scale correlation coefficients of .068 indicates an approaching

significant positive correlation with the compulsive scale. The MCMI-II desirability scale

and MCMI-II compulsive scale indicates a positive correlation with the MCMI-

compulsive scale of .000. The MCMI-II debasement scale indicates a significant positive

correlation with the compulsive scale of .004..

Table 6.3 (Appendix- J ) measures of the amount of variance that can be explained by a

proposed factor. A factor with an eigenvalue of one can explain as much variance as one

of the original independent variables. Four factors were extracted in the factor analysis:

avoidant, aggressive sadistic, alcohol, and antisocial had eigenvalue of 1 or more.

Avoidant had the largest measure of variance with an eigenvalue of 9.77160. The

percentage of variance of factor 1 avoidant was 39.1 percent. Avoidant, aggressive

sadistic, alcohol, and antisocial had a cumulative percentage of 67 percent.

Table 6.4

Variable-Factor Analysis

How much variance in each of our items can be explained by the four factors we have produced?

Variables Factor 1 Advoidant

Factor 2 Aggressive Sadistic

Factor 3 Alcohol

Factor 4 Antisocial continued p. 94

95

Variable MCMIADVO MCMIAGSA MCMIALCO MCMIANTI

Communality .73368 .67522 .52114 .64902

Factor 1 2 3 4

Eigenvalue 9.77160 3.37993 1.98631 1.61910

PctofVar 39.1 13.4 7.9 6.5

Cum Pet 39.1 52.6 60.6 67.0

Table 6.4 (Appendix -J) demonstrates the "loading" on each of the factors. Factor 1

"loads" on avoidant, borderline .77571, debasement .76566, desirability .91088, drugs

.72983, major depression .76631, passive aggressive .78723, self-defeating .73958, an

d thought disorder .79610. Factor 2 aggressive sadistic "loads" on aggressive sadistic

.53124, desirability .62133, and narcissistic .65882. Factor 3 "loads" on alcohol,

compulsive .59062, debasement .56648, and desirability .56648. Factor 4 "loads" on

antisocial, paranoid .40098, and schizoid .46788.

Table 6.5

t- tests for Paired Samples

MCMI-II Com Variable

MCMICOMP Compulsive

MCMIDESI Desirability Mean

-6.9080

Number of Pairs

163

SD

16.722

pulsive Sea

Corr.

.404

SEof Mean 1.310

le and MC 2-tail sig.

.000

MI-II Desirability Seal Mean

64.4601

71.3681

t-value

-5.27

SD

15.260

15.364

Df

162

e SE of Mean

1.195

1.203

2-tail Sig

.000

Table 6.5 reports the 2-tail prediction and the significance level from the t-test for paired

samples. The number of pairs was 163 from both the MCMI-II compulsive scale and the

MCMI-II desirability scale. The degree to which the scores correlate is .404. The t-value

is negative (-5.27), and the 2-tailed significance is .000. The compulsive scale and the

desirability scale are negatively significant.

Table 6.6

t- tests for Paired Samples

MCMI-II Compulsive Scale and MCMI-II Disclosure Scale

Variable

MCMICOMP Compulsive

MCMIDIS Disclosure

Number of Pairs

163

Corr.

-.143

2-tail sig.

.068

Mean

64.4601

70.6626

SD

15.260

17.963

SEof Mean 1.195

1.407

Paired Differences Mean

-6.2025

SD

25.181

SEof Mean 1.972

t-value

-3.14

Df

162

2-tail Sig

.002

Table 6.6 provides the 2-tail prediction and the significance level from the t-test for

paired samples. The number of pairs was 163 from both the MCMI-II compulsive scale

and the MCMI-II disclosure scale. The degree to which the scores co-relate is -143. The

t-value is negative (-3.14), and the 2-tailed significance is .002. The compulsive scale

and the disclosure scale are negatively significant.

Table 6.7

t- tests for Pared Samples

MCMI-II Compulsive Scale and MCMI-II Debasement Scale

Variable

MCMICOMP Compulsive

MCMIDEB Debasement

Number of Pairs

163

Corr.

-.224

2-tail sig.

.004

Mean

64.4601

55.1350

SD

15.260

16.981

SEof Mean 1.195

1.330

Paired Differences Mean

9.3252

SD

25.249

SEof Mean 1.978

t-value

4.72

Df

162

2-tail Sig

.000

97

Table 6.7 shows the 2-tail prediction and the significance level from the t-test for

paired samples. The number of pairs was 163 from both the MCMI-II compulsive scale

and the MCMI-II debasement scale. The degree to which the scores co-relate is -.224.

The t-value is positive (4.72), and the 2-tailed significance is .000. The compulsive scale

and the debasement scale are positive at the .000 level of significance.

H-7 The MCMI-II Severe Personality Pathology substests will predict HSLC.

Table 7.1

MCMI-II Severe Personality Pathology and any Significant Relationship with the HSLC

Multiple Regression

Equation Number 1. Dependent Variable .... HSLC Block Number 1. Method: Stepwise Criteria Pin .0500 Pout .1000 Schizotypal (MCMISCHZ), Borderline (MCMIBDLI), Paranoid (MCMIPARA)

End Block Number 1 PIN = .050 Limits reached.

Table 7.1 states that the MCMI-II subtests cannot predict Severe Clinical Pathology

from the group HSLC. The null hypothesis is accepted and the research hypothesis

rejected.

H-8 The MCMI-II Clinical Syndrome subtests will predict the HSLC.

Table 8.1

The MCMI-II Clinical Syndrome subtests and the HSLC Multiple Regression

Equation Number 1 Dependent Variable .... HSLC

Variable (s) Entered on Step Number 1... .MCMIANX (Anxiety Disorder)

Clinical Syndrome subtests - Somatoform (MQMISOMS), Bipolar

98

Manic(MCMIBPMA), Dysthymia (MCMIDYST), Alcohol/ Drugs (MCMIALCO) Continued

Multiple R .18229

Analysis of Variance F = 5.43074

R Square .03323 DF

Adjusted R Square .02711

Sum of Squares Signif F = .0210

Standard Error 1.23278

Mean of Squares

Table 8.1 (Appendix K) reports if there is any significant relationship between subtests of

the MCMI-II Clinical Syndromes and the HSLC. The Clinical Syndrome subtest for

anxiety of the MCMI-II was the first predictor variable when calculating with the

stepwise forward regression. The F distribution score of 5.43074 yielded a significant

interaction between the HSLC group and the Clinical Syndrome anxiety. The null

hypothesis was rejected and the research hypothesis accepted for anxiety, and rejected for

the other independent variables; somatoform, bipolar manic, dysthymia, and alcohol/

drug dependence. This research was completed in a substance abuse treatment facility,

where most of the inmates consider themselves in the recovery phrase. Therefore, the

drug and alcohol responses on the MCMI-II are under reported. Most of the inmates

have been off the streets for a long time, and are not facing the reality of the stressors that

they will be placed under when released.

Multiple regression was used to analyze the data that was found to be significant

for the anxiety scale at the .05 level of significance. Anxiety disorders are found at all

levels in every personality pattern. Millon (1985) reports that, "antisocial personality

disorder is characterized by a tendency to impulsively discharge psychological

discomfort." In this study the antisocial scale was a significant variable in the DSM-IV

cluster "B." Compulsive personality was found to be significant in the Millon-II Clinical

Syndromes according to the DSM-IV. Both of these variables are described within the

99

disorder range of having behavioral and affective characteristics of impatience,

aggressiveness, tense control, inflexibility, and defiance. When antisocial and compulsive

are found in the disordered range some, of the characteristics could be similar. Anxiety

disorders according to Millon (1985), are most often found in the avoidant personality.

The avoidant personality pattern was not found significant in the HSLC group tested. The

high anxiety level would indicate situational stress while incarcerated. When the data

was analyzed using the HSLC the results produced anxiety levels from the low range to

the high range in every HSLC. The two single letter codes of [S] and [R] showed the

highest levels of compulsive personality in the disorder range. Anxiety is an individual

issue and can appear in the disorder range when ever the person is not able to cope. Just

as Millon stated, that anxiety is most often found in the avoidant personality. When the

individual tries to avoid dealing with any issue anxiety becomes a problem.

Figure 8.1 (Appendix -K) indicates that all the HSLC have some low-level

anxiety, but not extremely high for any individual classified group of inmates.

H- 9 The MCMI-II Severe Syndrome subtest will predict HSLC.

Table 9.1

The MCMI-II Severe Syndrome subtests and any significant relationship with the HSLC

Variable (s) Entered on Step Number 1... .MCMITHDI(Thought Disorder)

Clinical Syndrome subtests - Thought Disorc (MCMIMJDE), Delusional Disorder (MCM

Multiple R .16001

Analysis of Variance F = 4.15139

R Square .02560 DF

ler (MCMITHDO), Major Depression [DEL) Continued Adjusted R Square

.01943 Sum of Squares Signif F-.0433


Mean of Squares

100

Table 9.1 (Appendix -L) shows the MCMI-II Severe Syndromes subtests and the

relationship with the HSLC. The Severe Syndrome subtest for thought disorder in the

MCMI-II was the first predictor variable when calculating stepwise forward regression.

The F distribution score of 4.15139 yielded a significant interaction between the HSLC

group and the Severe Syndrome thought disorder. The data was analyzed and found

significant at the .05 level. The null hypothesis was rejected and the research hypothesis

accepted for thought disorder, and rejected for major depression, and delusional disorder.

Multiple regression was used to analyze the data. The data was found to be

significant for thought disorder at the .05 level of significance. The other two patterns in

this syndrome pattern were rejected. The null hypothesis was rejected and the research

hypothesis accepted. Thought disorder was found in each HSLC at both high and low

levels. Thought disorder may be the product of the fact that the thinking of these

inmates, and therefore their responding, is affected by their incarceration. The inventory

could be picking up on the behaviors of hyper-vigilance, suspiciousness, and distrust.

Also, biological factors of the inmate play a roll. Inmates with major substance abuse

problems over many years, and the type of drugs abused, would have an impact on the

brain. These inmates were raised in the inner city within dysfunctual families with a low

level of reality testing. Many had poor diets and little medical care. Some started abusing

drugs and or alcohol while still very young children. The substances were around and

were picked up from the homes. Some used with the parent. Most of the inmates do not,

nor cannot, process information effectively. Only a few have had a good education, work

experience, and coping skill. All these factors may contribute to thought disorders in this

population.

101

Section 5

H-10 The Career Attitudes and Strategies Inventory (CASI) will be able to predict

The CASI subtest scales within the inmate group tested with the SDS- HSLC

Hypothesis 10 (Part One)

Table 10.1

CASI in Predicting the CASI Subtest Scales within the HSLC Tested Inmates

Equation Number 1 Dependent Variable .... HSL Variable (s) Entered on Step Number 1....Job Satisfaction (CASIJOBS) Career Worries (CASIWRR), Dominant Style (CASIDOMS), Family Commitment (CASIFAMC), Geographical Barriers (CASIGEBA), Interpersonal Abuse (CASINPER), Risk Taking Style (CASIRIST), Work Involvement (CASIWKI), Skill Development (CASISKDE)

Multiple R .16593

Analysis of Variance Regression

F = 4.69980

R Square .02753

DF 1


Sum of Squares 7.06603 Sig. F = .0316


Mean of Squares 1.50347

Table 10.1 (Appendix- M) reports any significant relationship between the CASI subtest

scales and the quality of work in the HSLC inmates tested. The CASI subtest scale job

satisfaction, was the strongest predictor in the HSLC inmate group. The other CASI

subtest scales (except dominant style- H-10 part II) were not able to predict in the HSLC

inmate group. The F distribution score was 4.69980, which indicated a significant

relationship between the individual CASI subtest scale job satisfaction and the ability to

predict the HSLC inmates. The data was analyzed and found to be significant at the .05

level.

102

Hypotheses 10-Part II

CASI Significant Subtest Scale - 2

Figure 10.2 (Appendix- M ) scatter graph illustrates the significant relationship of

the CASI subtest scale dominant style in the tested inmate population. The classified

inmates have a dominant style, but it does not differ significantly over any specific

HSLC.

Table 10.2


Variable (s) Entered on Step Number 2... .Dominate Style (CASIDOMS) Multiple R

.22363 Analysis of Variance


R Square .05001

DF 2





Table 10.2 (Appendix -M) demonstrates a significant relationship of the CASI subtest

scale dominant style in the HSLC inmate group. CASI subtest scale dominant style and

the ability to predict the HSLC inmates. The data was analyzed and found to be

significant at the .0145 level.

Figure 10.2 (Appendix- M) scatter graph illustrates the significant relationship of

the CASI subtest scale dominant style in the tested inmate population. The classified

inmates have a dominant style, but it does not differ significantly over any specific

HSLC.

The other CASI scale that came up significant was dominant style, which came up

second on the stepwise regression. Dominant style was significant at the .0145 level.

There are a low number of followers. Most of the inmates are take charge sort of persons

and like to tell others what to do. The inmates like power. There is a lack of

103

understanding, or maybe impatience, in working up a career ladder. Most want to be at

the top, but do not have the skills, education, experience or discipline to make it in

community. The prison population as a whole, seem to be career immature. The [S]

group, as always, seems to demonstrate the most negative characteristics. Most choose to

be dominant and controlling. This time the [E] group also wants to be dominant and in

control. The Enterprising inmates were those most likely to be selling drugs or

organizing some type of legal or illegal business venture.

Section 6

H-l 1 The Quality and Quantity of Work in the population tested will identify the HSLC

Table 11.1

Illustrates the data for Quality and Quantity of Work within the HSLC.

Variable (s) Entered on Step Number 1... .Quality of Work (AN) AN= Quality of Work

Multiple R .17171

Analysis of Variance


AM= Quantity of Work R Square .02984 DF

1

Adjusted R Sq. .02367

Sum of Squares

7.66383 Signif F = .0256


Mean of Squares

7.66383

Table 11.1- (Appendix -N) represents a significant relationship between the quality of

work within the HSLC inmate group. The quality of work was able to predict the HSLC

inmate group. The quantity of work among the inmate group was not able to predict the

HSLC. The F distribution score was 5.07323, which indicated a significant interaction

between the HSLC group of inmates and the ability to predict the quality of work the

inmates had participated in the community. The data was analyzed and found to be

significant at the .05 level. The null hypothesis was rejected for the quality of work, and

104

the research hypothesis was accepted for the quality of work. The null hypothesis was

accepted for the quantity of work, and research hypothesis was rejected for the quantity of

work.

Figure 11.1 (Appendix- N) represents each of the HSLC codes had some low, medium, and

high quality of work.

Multiple regression was used to analyze the data. The null hypothesis was

rejected and the research hypothesis was accepted at the .05 level of significance. The

data demonstrated the ability to identify the quality of work in the population, but not the

quantity. The researcher with other professionals in the field set up the following scale to

rate the quality of work experience of each inmate. The inmates with jobs that required no

skills or low skills were designated as " 1 . " The inmates with jobs that required a high

school diploma or General Education Degree (GED) were designated as "2," and inmates

with jobs that required vocational training or college were designated as "3 ." Before

setting up this scale of ordinal data, two expert APA Clinical Psychologists and the

researcher went over the results of the raw data. The information had been collected from

the Clinical Structured Interview (Appendix- A). No consideration was given to legal or

illegal jobs, but most stated the employment reported was legal. According to the

research, a large majority of the inmates reported jobs that required little or no skill

training. There were only a few inmates that held jobs for over two years. Many of the

inmates had completed a GED program while in prison and not been back into the

community to work. Some of the men who had developed substance abuse problems

while in military careers had the best quantity and quality of work experience. The

105

significance of the relationship was negative for quality and quantity of work in the

community.

Scale developed from the raw data information by the experts and the researcher

Quality of Work Scale 1.0 (No job or low skill job) 2.0 (Semi-skilled jobs) 3.0 (Skilledjobs)

Figure 11.1 (Appendix -N) indicates that the quality of work for all HSLC inmates was

equal though out each code. Before setting up this scale the researcher looked over the

raw data from the Clinical Structured Interview on type of employment. No

consideration was given for legal and illegal jobs, but most stated legal employment.

According to the research the large majority of inmates reported jobs that required little

to no skills. There were only a few inmate jobs held for over two years. Many of the

inmates had completed a GED while in prison and had not been in the community to

work. Some of the men who had developed substance abuse problems while in military

careers had the best quality of work. The significance of the relationship was in the

negative direction for quality of work in the community

Section 7

H-12 The CASI subtest scale Job Satisfaction can predict the Quality of Work

among the group of HSLC inmates.

Table 12.1

The individual CASI Subtest scales and Quality of Work

Equation Number 1 Dependent Variable .... Quality of Work (AN)

Variable (s) Entered on Step Number 1... Job Satisfaction (JOBSATR)

106

Career Worries (CASICAWO), Dominant Style (CASIDOMS), Family Commitment (CASIFAMC), Geographical Barriers (CASIGEBA), Interpersonal Abuse (CASINPER), Risk Taking Style (CASIRIST), Skill Development (CASISKDE), Work Involvement (CASIWKI)

Multiple R .22524

Analysis of Variance Regression F = 11.93253

R Square .05073

DF 1



Standard Error .54481


Table 12.1 (Appendix- O) demonstrates a correlation between the CASI subtest scale job

satisfaction and quality of-work. The quality of work scale was established at 1.0 (no or

low skill job), 2.0 (semi-skilled job), and 3.0 (skilled job) by the chosen experts and

researcher. The CASI subtest scale, job satisfaction was able to predict the quality of

work in the HSLC inmate group. The F distribution score was 8.87137, indicated a

significant interaction between the individual CASI subtest scale job satisfaction and the

ability to predict the quality of work the HSLC inmates had participated within the

community. The data was analyzed and found to be significant at the .0007 level,

Figure 12.1 (Appendix - O) indicates the inmates are satisfied with their jobs

even with low skilled jobs.

Multiple regression was used to analyze the data. The null hypothesis was

rejected and the research hypothesis accepted. The CASI subtest can predict the quality

of work at the .01 level of significance. Figures 12.1 and 12.2 (Appendix- N) indicate

that the inmate population tested is satisfied with the jobs they are doing and the quality

or skill level of the work. The inmates seem to have no motivation to improve and are

satisfied with the way things are presently. Low aspirations and no interest on the part of

the inmates to participating in legitimate jobs within the community will continue to lead

to failure.

107

Figure 12.2 (Appendix O) indicates that the quality of work can predict job

satisfaction. The inmates as a group have low quality of work and are satisfied with their

jobs.

H-13 The Quality and Quantity of Work and Grade Level will be able to predict

the HSLC Table 13.1

Illustrates the data of the Quality and Quantity of Work

and Grade Level with the HSLC. Multiple Regression Listwise Deletion of Missing Data Equation Number 1 Dependent Variable .... HSLC Block Number 1. Method: Stepwise Criteria Pin .0500 Pout .1000 AL = Grade Level AM = Quantity of Work AN = Quality of Work Variable (s) Entered on Step Number 1... .Quality of Work (AN)

Multiple R .20871

Analysis of Variance Regression Residual F = 5.60165

R Square .04356 DF 1

167


Sum of Squares 237.58927

5216.93873 Signif F = .0195


Mean of Squares 237.58927 42.41414

Table 13.1 (Appendix- P) reports the grade level, quality of work, and quantity of work

and any significant relationship with the HSLC group. The quantity of work was the only

independent variable that predicted a significant relationship with the HSLC inmate

group. The quality of work and grade level variables was not able to predict the HSLC

inmate group. The F distribution score was 5.60165, which indicated a significant

interaction between the ability to predict the quantity of work the HSLC inmates had

participated while living in the community. The data was analyzed and found to be

significant at the .05 level.

108

Table 13.2

t- Tests for Paired Samples

Variable

AM= Quantity of work HSLC

Number of Pairs

169

Correlation

.160

2-tail significance

.037

Mean

1.6450

40.6095

SD

.759

6.492

SEof Mean

.058

.499 Paired Differences Mean -38.9645

SD 6.414

SE of Mean .493

t-Value -78.97

Df 168

2-tail Sig. .0000

95% CI (-39.939, -37.990)

Table 13.2 reports the relationship between AM (quantity of work) and HSLC group.

When independent variables AN (quality of work), AM (quantity of work), and (AL)

grade level are analyzed to predict HSLC group the AM of the inmates becomes

significant. A confidence interval of 95% of the mean worked out from the sample

indicates that the estimated population mean would fall between the upper and lower

limits for 95% of the sample. The known population is normally distributed from a

random population of inmates. A confidence interval provides an alternative way of

representing the findings because it provides a range of values within which the

confidence of the population lies. The two-tailed significant level is .0000. It is confirmed

that the null hypotheses was rejected for the quantity of work, and accepted for grade

level and quality of work.

Multiple regression was used to analyzes the data, and found that only the

quantity of work was predicted. The null hypothesis was rejected and the research

hypothesis was accepted for quantity of work at the .01 level of significance. The

researcher, with other professionals in the field, set up the following scale to rate the

quantity of work experience of each inmate. The inmates with less than a year of

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employment were designated as "1". The inmates with 1-2 years of employment were

designated as "2," and inmates with over 2 years of employment were designated as "3".

Before setting up this scale the researcher looked over the raw data from the Clinical

Structured Interview on years of work experience. There were few inmates with over

two years of employment. According to the research the majority of inmates reported job

for less than a year.

Section 8

Summary

The researcher found several significant correlations between psychosocial

instruments, interviews, and inventories along with Holland's single letter code (HSLC)

of career classification. The results identified issues that could help counsel inmates in

career development while incarcerated. There was a large amount of data gathered for

this research, and not all could be interpreted in one research project. There is a large

amount of data that could be expanded. This researcher's main interest was to find out

what factors, if any, played a significant role in the lack of career development among

this sample of inmates, and help to identify and address these issues to reduce recidivism.

The results of the study indicated that the sample group of inmates had varied

career personalities. The largest HSLC group being Social (68 inmates) and the smallest

being Investigative (0 inmates). A large majority or the inmate sample function in the

below average verbal (VCIS) range of intelligence and are ambitent in their decision

making skills. The Egocentricity Index varied according to HSLC. The MCMI-II Cluster

"B" (DSM-R) indicated that antisocial, compulsive personality, anxiety, and thought

disorder had a positive relationship with the population and HSLC. The CASI scales

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demonstrated that the inmates had a Dominant work style and good Job Satisfaction in

their jobs, even though most had no work history. The Quality and Quantity of Work the

inmates reported indicated satisfaction with both the low Quality and Quantity of Work

experience.

I l l

CHAPTER V

SUMMARY, CONCLUSIONS, AND RECOMMENDATIONS

The organization of the final chapter is in three major sections. The

summary section of the study includes a brief restatement of the problem, a brief

review of the research procedures, and the research hypotheses. The conclusion section

comprises: (a) the psychological instruments or parts of the instruments that

significantly predict Holland's single letter code within the inmate population tested,

(b) the psychological instruments or parts of the instruments that did not significantly

predict Holland's single letter code, (c) the researcher's perception of the value of

combining psychological and career profiles to counsel Black male substance abusing

felons to be productive in the community. Finally, the implications section includes the

interpretation of the significant research findings suggestions for further research, and

chapter summary.

Summary of the Study

Statement of the Problem

The study examines and determines the capability of selected psycho-social

variables to predict or differentiate samples of Black male substance abuse felons

utilizing Holland's Theory (RIASEC) of single letter codes (HSLC) of classification. The

sub-problem is to investigate significant differences in the quality and quantity of work

history within the inner city community by measuring the past job experiences of Black

male substance felons with histories of recidivism. Because staff personnel are called

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upon to assess both the psychological and sociological information at the screening and

intake level, the researcher believes that the identification and measurement of

psychosocial variables is critical to sound decision-making. Therefore, psychosocial

variables are employed to identify which variables were good discriminators for needs

counseling among the felons. Psychosocial needs are also be addressed to help felons in

career development, skill training to reduce recidivism, and to be productive in the

community.

Statement of Procedures

The researcher employs an ex post facto design guided by past and present

theoretical and empirical data and specific research hypotheses. Thus, the research

hypotheses are derived from empirical findings.

Black males from a Mid-Atlantic inner city correctional treatment facility that

includes substance abuse felons with a history of criminal recidivism. The offenders are

from the prison substance abuse treatment program. Inmates that could not read or write

are not included due to the inability to validate individual test results.

Six psychosocial instruments are employed for testing differences between the

inmates classified into six groups according to the Holland RIASEC theory. Each subject

is classified according to the results of Holland's Self-Directed Search (SDS). The

researcher used the Holland single letter code of identification to divide the population

into the six groups. The SDS indicates that there is no Investigative (I) single letter codes

in the population; therefore, only five groups are tested using the variables from the

psychosocial instruments. The instruments used are the Structured Clinical Interview,

Holland's Self-Directed Search, Career Attitudes and Strategies Inventory, verbal sub-

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tests (information, comprehension, vocabulary, and similarities) of the Wechsler Adult

Intelligence Scale R (VICS), Rorschach Inkblot Method, and the Millon Clinical

Inventory-II. A scale is developed for this population to evaluate the quality of inmates'

career development and quantity of work experience within the community. Through the

use of several expert judges the specific continuum of classification (numerical values)

for each group is established. The psychosocial variables are examined to determine if

they significantly differentiate the groups under investigation.

The Research Hypotheses

Chi-square is used to analyze the categorical variables. Multiple t- tests are used

for correction. Multiple linear regression is based on the generation of regression models

that reflects the specific research questions it explores. In the current study, testing is

extensive and mis reflects in the number of variables for the investigation. In addition a

number of factors (race, sex, age, education, inmate population, substance abuse

treatment, and quality and quantity of work experience) are also included to examine how

they influence the criterion measure.

The criterion variables in the regression models are the variables drawn from the

instruments. The chi-square is used for categorical variables to test for independence and

'good fit'. The predictor variables are the different groups that are investigated. All

research hypotheses that examine group differences are tested at the .05 level of

significance.

The research hypotheses are presented by examining group differences among

the variables found within each instrument. In addition, selected demographic variables

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are also examined. When appropriate, the researcher examines specific interactions

while statistically holding the effect of other variables constant.

Conclusions

This section divides into six major areas of focus. The first area (H-l) of focus

deals with the significant research findings as the findings pertain to the division of the

inmates into groups classified using Holland's Theory of single letter code of career

classification (HSLC). The second area (H-2) of focus deals with the significant research

findings as pertaining to intelligence and the Holland single letter code career

classification. The third area (H-3, H-4) focuses on the significant research findings as

the findings pertain to the Rorschach EB styles and the Egocentricity Index, and the

relationship to the group and the Holland single letter code. The forth area (H-5, H-5.2,

H-5.3, H-5.4, H-6, H-6.2, H-6.3, H-6.4, H-6.5, H-6.6, H-6.7, H-7, H-8, H-9) of focus

deals with the significant research findings as pertaining to the Millon Multiaxial Clinical

Inventory and the groups classified using Holland's Theory (RIASEC) of single letter

career personality classification. The fifth area (H-10 part 1, H-10 part 2) of focus deals

with the significant findings as findings pertain to career attitudes and strategies (CASI)

and the groups classified using Holland's Theory (RIASEC) of single letter career

personality classification. Finally, the sixth area (H-l 1, H-12, H-13) of focus deals with

the significant findings as pertaining to the quality and quantity of work classified and job

satisfaction using Holland's Theory (RIASEC) of single letter career personality

classification.

Area One: The Division of the inmates into groups classified using Holland's

Theory of single letter code career classification.

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The data indicate that the null hypothesis is rejected at the .01 level of

significance when the population of Black substance abuse felons in the treatment

program is given the Holland's Self-Directed Search career inventory. According to the

findings, the groups are not divided equally between each of the single letter codes. Of

the six different factors, the statistical significance between Holland's single letter code

(HSLC) is one of the most important. The analysis of the data eliminates one complete

group in the single letter code. The Investigative (I) single letter code is not found for

any of the 169 inmates that complete the inventory. Therefore, the research is completed

with five instead of six of the single letter code groups. The Investigative single letter

code includes people that are usually found in the math and scientific field. According to

the demographics of this population, the majority of the sample did not complete high

school; others obtained a GED later in life while within the criminal justice system. This

researcher would not expect these results to be any different within other populations.

There is also evidence that career personalities can vary over time. If these same

inmates had had the opportunity, support, and environment to complete school, the

inmate's interests and career goals might have been different. Individuals in any

population must be educated and able to understand these fields in order to have any

realistic career goals in math and science. The inmates are career immature with few

higher-level skills to succeed in the Investigative (I) career field. The group that is the

highest frequency of inmates classified into one single letter code is the Social single

letter code. This group is 40% or 68 of the classified inmates. Considering the research

sample and Holland's Theory, both of these findings can be understood. The Social (S)

group according to Holland would include jobs such as fast food worker, teachers, nurses,

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and counselors. The Social group likes to be with and help others. The inmates do not

have the education to hold many of these higher skill jobs and are likely to have jobs as

fast food workers. This researcher, while working in the prison system with the

substance abuse treatment program observed many inmates wanting to get into the

counseling field in order to help others with problems. NA and AA are based on social

group sharing and previous experiences with NA and AA.

The next highest single letter code with the most frequencies would be Realistic

(R) with 24% or 40 of the inmates in the research group. This is the career personality

style that the researcher expects to see the largest classification of inmates. Realistic

people like jobs such as auto-mechanic, carpenter, electrician, cook, and landscaper.

These types of jobs are "hands on learning" and would probably be held by a majority of

males. Young men like to work on cars. In this inner city population with a large school

dropout rate, the young men view cars as an important status symbol. This is a job that

individuals can do in a neighborhood without any training to make money. There is no

need for a degree or vocational training to work on cars on the street. The men learn

from each other. Some cars are stolen and others are wrecked. Friends and neighbors

who are looking for a cheap repair can help each other. In addition, there seems to be a

lot of inmates who like to cook. This is a job that can be learned in the prison system

along with maintenance jobs. These jobs could be good paying jobs if the individuals go

through a regular business to be hired, but most do the jobs "under the table" so no taxes

or Social Security has to be paid. Inmates do not want any records kept by employers or

the government. The research demonstrates that a quarter of the inmates in this

population like to work with their hands.

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The next highest group of classified inmates fell into the Enterprising (E) group.

The inmates are always trying to make deals and find a way to make big, fast money.

These men understand the rule "easy come easy goes." Inmates have little patience for

working their way up in a regular job. This groups interests are in money and politics.

They organize, influence people, and like to be in control. The Enterprising group was

found to be energetic, self-confident, and ambitious.

The smallest groups classified by the Holland's single letter code were the Artistic

(A) and Conventional (C). Only a small percentage of the inmates are classified in these

categories. Artistic jobs can be found within the field of entertainment or art. This is a

field that young inner city men and women dream of making it in order to become rich

and famous. The other group is professional sports. The men and women see the big

money, cars, and homes, but there are only a few individuals that ever make it to that

level, which requires a strong vision and discipline to go the distance. These inner city

environments are full of drugs, women, fast cars, and wild parties. When the dreams of

greatness are unrealistic and/or ungrounded, the inner city males deal with this harsh

reality and try to escape it through drugs and alcohol. The Conventional (C) group likes

to work indoors and keep things organized. This group likes to work with words and

numbers. This type is usually conforming, careful, and thrifty. The Conventional group

does not have the characteristics that you see in most inmates. This population lives in a

major inner city where there is a lot of crime, drugs, dysfunction families, and high

dropout rate in education.

Everyone needs a support system and education or vocational training if they are

going to succeed in the work community. When individuals cannot read, perform basic

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math, or have some way to provide for themselves in life, survival nature takes over

(Maslow, 1918). This researcher often hears many inmates, who are substance abusers

and street people say the following: "When it gets to hard on the outside, I just commit a

crime to come back to prison. There I know I can have a bed, three meals a day, watch

television, and play cards with my friends." Prison is a way of coping with reality when

you do not have the basic skills needed to succeed in the community (Maslow, 1965).

Some see prison as a safe place. The inmates have the same career personalities that

everyone else has, but tend to develop them along negative paths. The research indicates

that the majority of the classified inmates enjoy some type of social interaction, even

though it is not always cooperative/collaborative.

Area Two: Intelligence Levels within the classified groups according to HSLC

The data indicates there is a significant difference in the intelligence level of the

classified HSLC. The highest mean intelligence level is found in the Conventional inmate

group. Conventional people are usually conforming and careful; these characteristics are

not typically found among many inmates. The research supports this suggestion, as only

15 of the 169 inmates are classified in this group. The group intelligence mean was about

97 or in the middle range of the average range of intelligence. That indicated that 154

inmates have scores in the mentally deficient, borderline, or low average range of

intelligence. Some researchers suggest there is bias on intelligence tests among the Black

population. After administering many intelligence tests with this population, this

researcher believes that it would be difficult to determine test bias. The test scores were

+/- one standard deviation from the mean that allows for a large range of scores within

each intelligence level. The inmates all came from the same inner city school

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environment, all used and/or sold drugs, drank alcohol, and a large majority have not

finished school. Most came from dysfunctional families, low-income backgrounds with

poor nutrition, little medical care, and few opportunities to learn much about the world

around them.

The next group with highest level of intelligence is the Enterprising (E)

individuals followed by the Social (S), Realistic (R), and the Artistic (A). The research

found that the mean intelligence level of the total population tested is in the low average

range of intelligence (80-89). Only one inmate fell into the mentally deficient range and

six into the superior range of intelligence. The borderline, low average, and average

intelligence ranges are equally divided among the balance of the inmates. There are

always a few inmates that are highly intelligent, but they either became involved with

drugs or thought they are smart enough to beat the system. Many of these inmates started

using drugs at a very early age when the brain was not fully developed. There is no way

to know how much damage is done to the brain, or how intelligence or impulse control

are influenced (Amen, 2002,2003). Making more positive choices in life would certainly

have improved the chance of a higher individual intelligence score.

Area Three- Rorschach EB Styles (Extratensive, Ambitent, Introversive) and the

Egocentricity Index in Prediction Ability of the Holland Single Letter Code in the

Sample Population.

The data indicates that the variables did not predict the Rorschach EB styles and

the Holland single letter code for the research sample. However, the results produced

some valuable information. When the entire sample is examined as a group the tested

sample indicates twice as many EB ambitent style than either the extratensive or

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introversive EB styles. This is important information because it shows how erratic

problem-solving and decision-making impacts a person's basic psychological

functioning. This indicates that the coping and decision making styles of 50% of the

inmate population are ineffective and unpredictable. The subjects' emotions and thinking

is inconsistent and unpredictable in relation to problem solving and decision- making

behaviors. Sometimes the subject's thinking may strongly influence their feelings and in

other instances thinking may play a peripheral role. This group is inconsistent with their

thinking-feeling process and can react differently to the same situation at a different point

in time. Compare this to the extratensive group that usually lets feelings influence their

behavior and you have a large group of inmates that react to feelings at the time of

decision-making.

The Egocentricity Index of the Rorschach provides an estimate of self-concern

and self-esteem among the different HSLC classifications. The Realistic (R) group

indicates that 50% of the group fell into the average range on the Egocentricity Index

with less than 20% falling equally into the high and low range. Most of the Realistic (R)

classified group regarded their self-worth equally to that of others. The Social (S)

classified group, almost 60%, have an average of < .31. It can be assumed that the

subjects' estimated their self-worth less favorably when compared to others. According

to Holland's Theory of the Social (S) career personality, this finding would agree with his

research conclusions. Social (S) people like to help others and often give more of

themselves to others. However, according to the Rorschach Egocentricity Index, the

subject's estimated of self-worth tends to be quite negative. Exner and Murillo (1975)

found that a lower than average index appears to favor far more adjustment hazards. This

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researcher would agree with that statement since how can anyone value you if you cannot

value yourself. About 30% of the (S) group is in the average range of self-concern and

self-esteem and 18% in the above average range. The Conventional (C) classified group

is almost evenly divided. The percentage of the average index classified group is 40%,

the high index group is 35%, and the low index classified group is 25%. The

Enterprising (E) classified group was the most unbalanced on the Egocentricity Index.

Those with low scores (<.31) are 70% of the classified (E) group. It can be assumed that

this sample group has a personal worth that tends to be quite negative. This finding would

seem unusual since this is the group Holland reports as aggressive, controlling, logical,

and rational, but this inmate sample does not seem to have much personal worth. These

inmates tend to become aggressive and controlling with others since they do not have

much control over themselves. About 20% are high on the Index and 15% low on the

Index. The Artistic (A) classified group is both at 40% average and 40% low on the index

with high at 20%. This group feels about average or low in their personal worth. Only

20% have exaggerated or inflated qualities or see themselves more favorably as

compared to others. Looking at the whole sample of inmates, a large percentage of the

inmates saw themselves having a low personal self-worth. The next group fell into the

average range of self-worth when compared to others. The lowest group by a large

percentage fell into the high range of self-worth. This is a significant difference in the

way inmates are most likely to be evaluated. Many think of inmates as self-centered, only

thinking of themselves. This raises a point as to whether the inmates are truly

preoccupied with them selves or really dissatisfied with who they are, even though they

give the appearance of high self-esteem.

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Area Four - The Ability of the MCMI-II Personality Clusters (A, B, C according

to the DSM-TR), Clinical Personality Patterns, Severe Clinical Pathology,

Clinical Syndromes, Severe Syndromes to Predict the Holland Single Letter Score

of the classified inmate population.

The data indicates that cluster "B" was significant on the Antisocial scale in

predicting the Holland single letter code of the inmates. This cluster includes: antisocial,

borderline, histrionic, and narcissistic scales. According to Holland, the modal

personality disorders for inmates should be antisocial, narcissistic, and aggressive

sadistic. Of this group, only antisocial and narcissistic are included in the DSM-TR

cluster "B." Antisocial is immediately considered a major personality disorder among

any inmate population. Individuals who do not want to follow the rules and regulations in

society will most likely end up in trouble. The mean score of 85 places the majority of the

inmates in the prevalent disordered range. There are a significant number of inmates

over the base rate 85 and well into the 100-121 range. Only about 15% fell below the 65

range. The scatter graph indicated high levels of antisocial disorder in each of the S, R, A,

E, and C Holland single letter codes. The Artistic code did not have any classified

inmates not in the antisocial personality disorder range. The Artistic type of individual

does not like to conform to others in society. They are individualistic and creative. The

group that drives the high antisocial personality score is the Social factor within the

HSLC.

The DSM-TR cluster group "A" (schizoid, paranoid, and schizotypal) has no

significant relationship with the HSLC or total sample group. There is also no significant

relationship between the DSM-TR cluster group "C" (i.e., passive aggressive,

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compulsive, dependent, and avoidant) and the HSLC or total sample. The only thing the

inmate group avoids is reality and the need to make changes in their lives.

The data indicates a significant relationship between the MCMI-II Clinical

Personality Pattern compulsive and the HSLC inmate group. The mean score of 65 is

within the average range. The Artistic group is below the 65 level and would not be

considered to have a compulsive personality style. The Artistic individual tends to be

creative and not repeat the same behavior, but would rather be original and do things

different each time. The other HSLC groups that have a large number in the compulsive

disorder range from average to presence to pervasive. The inmates in this study are in a

correctional treatment facility for felons with a history of recidivism. They do not seem to

learn from past mistakes. They keep repeating the same maladaptive behavior, probably

due, in large measure to illicit substances and participation in criminal behavior.

According to Millon (1985), the compulsive individual represents a passive version of the

basic ambivalent. On the one hand the individual wants to be assertive and independent

yet on the other hand needs support and guidance. This finding falls in line with

Rorschach EB personality style. The majority of the inmates in the sample are ambitent

and another quarter extroversive. Both decision-making styles either allow emotions to

govern their problem-solving or become erratic.

The researcher ran a Factor Analysis using the MCMI-II compulsive scale against

the MCMI-validity scales (disclosure, debasement, and desirability). The analysis

produces a negative relationship between the disclosure and compulsive scales and the

debasement and the compulsive scale. The desirability scale and compulsive scale

produces a positive relationship at the .40 level of significance. The inmate sample

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wantes to be desirable and make a good impression with others, but continued with their

negative behavior. Changing their behavior produces excessive stress and anxiety.

According to Millon (1985), the compulsive personality style engages in self-criticism

and blames them selves for adversity. Self-doubt, anxiety, and the inability to perform

assigned tasks at work increase the person's feelings of being out of control. Compulsives

have a strong sense of loyalty with those they trust, but are superficial in their

interpersonal relationships and often indecisive. Their structured life patterns are deeply

instilled and produce a lot of anxiety when even small changes are made to their way of

life. They do not like to make mistakes. The research found a significant relationship

between anxiety and the HSLC, the compulsive scale and the HSLC, and the antisocial

scale and HSLC. The inmates like to follow rules, but it is usually their rules they like to

follow. The situation of being in prison produces a lot of anxiety. In addition they are not

in control of their life - food, clothing, support, contact with significant others, etc.

The data indicates that there is no relationship between the MCMI-II Severe

Personality scales (i.e., schizotypal, borderline, and paranoid) and Holland's single letter

code from the inmate population. This finding is consistent with the results of the DSM-

TR cluster "A" results discussed earlier.

The data indicates that there are significant relationships between MCMI-II

Anxiety disorder and the HSLC of the inmates. The other Clinical Syndromes scales

(i.e. somatoform, bipolar, dysthymia, and drugs and alcohol) are not significant. The

MCMI-II seems to under report drugs and alcohol in this known substance abuse sample.

According to Millon (1987), the MCMI-II is a valuable tool to identify alcohol and drug

disorders; however, in this population the disorder has already been identified and

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treatment is on going. The inmate sample spent many years in prison and is now "clean."

They answer the inventory as if the questions are in the present time. Since they are in

treatment, some inmates feel that they are no longer substance abusers. Many believe

that it has been so long since they used drugs and /or alcohol that they are no longer

addicted. They forget that prison is a structured environment and when that structured

environment is removed and they are released the stress of returning to the community is

not easy. The problems they had before this incarceration remain for them to cope with

when they return to the community.

Anxiety is found frequently in compulsives and antisocial personalities. Both

groups like control. Millon (1985) finds that most of the anxiety disorders are

generalized in the compulsive personality. Anxiety is part of their everyday life. They are

in constant fear of life threatening situations, social disapproval, and humiliation.

Disrespect is a trigger for impulsive behavior, especially among the inmate population. If

they find they are losing control of themselves or their environment the disorder becomes

acute, especially within social settings with others observing. Millon (1985) states that

anxiety disorders in the antisocial personality disorder also come from a fear of losing

control and are particularly tied to person, place, or thing. Where the compulsive has

generalized anxiety all the time, antisocial and aggressive personalities react in a more

impulsive manner to the situation. The Social and Realistic HSLC's are highly correlated

with the anxiety disorder scale in the data. These two HSLC's accounted for all of the

significant data.

The data indicates a significant relationship between the MCMI-II thought

disorder scale and the HSLC group in the inmate population. The other Severe Syndrome

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Pattern scales (i.e., major depression and delusional disorder) are not significant. Thought

disorder covers a large group of various diagnoses. A thought disorder could be found in

a depressed person thinking of suicide, someone having recurrent thoughts of a traumatic

event, extreme grandiosity, or even experiencing distress about assigned gender. This

population has some major problems with thinking clearly. For many inmates the drugs

and alcohol influences their ability to think clearly (Amen, 2002,2003). The substances

undoubtedly caused chemical imbalances in the brain that can sometimes be treated with

psychotropic medication and/or therapy (Amen, 2002,2003). This population has been

damaged for many years, possibly since childhood or adolescence. They do not have the

coping skills to succeed in society or the prerequisite employment skills and education to

work. The thought processes of this population are disturbed / distorted in some way.

Area Five - The CASI (Attitudes and Strategies Inventory) and its relationship

with the HSLC group tested.

The data indicates a significant relationship in the CASI job satisfaction and

dominant style scale. There is no relationship in the career worries, family commitment,

geographical barriers, interpersonal abuse, risk taking, work involvement, and skill

development. One of the important findings is that Job Satisfaction was significant in a

population that is in prison with low education, substance abuse, and histories of criminal

recidivism. Either the inmates are satisfied with being in prison and not working in the

community or inmates like participation in criminal activities. The results also indicate

that the inmates have little ambition or aspirations to better themselves in life. Most of the

inmates in each of the HSLC groups are satisfied with their current job and are probably

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not seeking other employment. The broadest range of scores is found in the Social group

with most in the satisfied range, but a large number are not satisfied.

Dominant style is also significant. According to Holland and Gottredson (1994),

this indicates that the inmates would display leadership when necessary. This group likes

power at work. Only about 20 inmates reported that they were usually followers. None of

the HSLC groups indicated that they are followers. The sad part is that they all want

control, yet they are incarcerated in a place that takes away their control. Perhaps this is a

form of compensating for the lack of control in their lives while incarcerated.

Area 6 - The CASI scale Job Satisfaction and its relationship with the Quality and

Quantity of Work within the community in the HSLC group of inmates in the

sample.

The data indicates that only the job satisfaction subscale on the CASI is

significant in predicting the HSLC group of inmates. A scale is developed for this sample

to evaluate the quality of career development and quantity of work experience the

inmates experienced within the community. Through the use of several expert judges, the

specific continuum of classification (numerical values) for each group is established.

Quality of work within the community is assigned one point for no skill requirements

needed, two points for semi-skilled work requiring a GED or high school diploma, and

three points for skilled work requiring vocational training or college. The psychosocial

variables are examined to determine if they could significantly differentiate between the

groups under investigation.

Job Satisfaction predicts the quality of work within the community that the

inmates participate in while not incarcerated. The scatter graph indicates that the majority

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of work done by the inmates in the community is of the low skill level and that they are

satisfied or highly satisfied with their jobs. This correlates with the data found within the

CASI scales that indicates the inmates are satisfied with their jobs; however, not only are

they satisfied with their jobs, they are also satisfied with the quality level of their jobs.

These results produce a special problem in career counseling within this group, as there is

little motivation to make changes in their life. However, their low-level aspirations could

be realistic given other background information.

The data for the last part of the research indicates that when the variables quality

of work, quantity of work, and yade level are used, there is a relationship with the

quantity of work within the HSLC group of inmates. The quantity of work and the quality

of work are low. A scale is developed for this population to evaluate the quantity of work

experience the inmates participate in the community. Quantity of work within the

community is assigned one point for the longest held job. One point is given for 0-6

months, two points for 1 to 2 years, and three points for over two years of work. The

largest quantity of work for all groups is 0-6 months. Many of these inmates dropped out

of school and lack the education and job skills to be productive in the work community.

Others have environmental and social problems that put them at risk for heading in the

wrong direction. Learning disabilities, cognitive development, career immaturity, and

dysfunctional families all contribute to the lack of career development.

Implications

The review of the literature dealing with career development or (lack there of)

reinforces in this research. Society needs an extensive intervention in the schools to

develop career maturity and skill development. This is a large problem in all our schools.

Many students graduate from high school and have no idea what they want to do in life.

Young people go to school and then graduate thinking that the job market will open up

for them. In reality there are not that many more jobs for high school graduates than for a

student that drop out in eighth grade. High school only provides a basic education and

from there you must start educating and planning for a career. The training could be

vocational, apprenticeship, junior college, military, prep school, or college. In general,

society expects every student to obtain more education. There are many good paying

jobs and careers that take different paths. There will always be individuals who are not

qualified or do not care to acquire more education. Some people, because of lack of

cognitive abilities, learning disabilities, other interests, financial needs, and /or

personality, do not want jobs that involve advanced education. Who are our plumbers,

carpenters, truck drivers, bus drivers, and heavy equipment operators going to be?

This research indicates that we need to reach the young people who drop out of

school before they hit the streets. We need to go back to vocational schools that teach

some young people basic vocational trades. Young people graduating from high school

today have no idea what types of jobs there are within the community. The research

suggests that most of the population in the sample would rather do hands on jobs. These

inmates are going to be difficult to change. It can be done, but it will take a lot of

psychological and career counseling. On the positive side, this researcher is observing

beautiful art work created by individuals who did not have the skills to read or write.

Their talent needs to be reinforced and cultivated.

Most of these Black male substance abuse felons, with long criminal recidivism

records living in the inner city, will find it difficult to make significant changes within the

work community. However, there are some who will and can make it if society keeps

trying to educate them for jobs that will help them feel good and support themselves. It

seems obvious that all prisons should have job-training programs in order to assist felons

returning to society.

When an inmate enters the facility it is important to evaluate their work

experience and job skills. If Holland's Self-Directed Search and Career Attitudes and

Strategies (CASI) are given at the intake evaluation it would help the counselors and

therapists understand a lot about the individuals. We know that most of this population

has Social career personalities, and few are Artistic or Conventional. From the WASI-R

verbal sub-tests we know that most are in the low average range of intelligence. The

Rorschach decision-making and problem-solving style indicates that the majority are

ambitent with the others divided equally between extratensive and introversive. Now the

counselors know that most of this population will react with feelings or in an ambivalent

manner when making decisions or problem solving. The Millon Multiaxial Clinical

Interview indicates that this population is predominately antisocial and compulsive. They

have a high anxiety level and thought disorders. The CASI also indicates that they are

satisfied with their jobs in the community and have a dominant style work personality.

The dominant style personality relates back to the compulsive and antisocial personality

disorders. They want to be in control of themselves and their environment, but this is

contradictory because they keep repeating the same mistakes that take away their

freedom and control. This produces a lot of anxiety, which contributes to the inmates

thinking or thought disorder.

131

When it comes to the quality of work and quantity of work, the inmates in this

sample state that they are satisfied with both. However, the research indicates that a large

majority of the inmates have low quality jobs (low skill range) and low quantity of work

(0-6 months). This indicates that this inmate sample has little desire to improve their level

or quantity of work within the community. This makes the counselor's job a lot harder,

but not impossible. Everyone can make changes in their life. Education is the key to

success. When you stop learning you die inside and outside.

Recommendations

1. The development of better career test batteries to evaluate the prison population.

2. Include more career test batteries into the intake procedure.

3. Utilize a career test-retest battery.

4. Develop a career development education group for improving career maturity.

5. Complete more research on career development in the prison population.

6. Repeat the research with a different prison population such as, women substance

abusers, male and female felons, male and female misdemeanants, and juvenile

offenders.

7. Develop research based on the relationship of career development and recidivism.

8. Repeat parts of the research using two or all three letter codes of the Holland Self-

Directed Search.

9. Develop a more scientific way to evaluate the quality and quantity of work within the

prison population.

10. Compare the relationship of the CASI and the Self-Directed Search.

132

11. Follow the inmates after they finish the program and are discharged to determine the

value of the career development program.

12. Conduct more research on the Self-Directed Search career personality inventory and

its ability to significantly predict psychological personalities with the updated version

of MCMI-III or the MMPI-II.

13. Continue research on the relationship between education and criminal recidivism.

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154

APPENDIX-A

CLINICAL INTERVIEW

155

STRUCTURED CLINICAL INTERVIEW

Ronald Klein, Ph.D, ABPP & Carolyn Shrewsbury, M.Ed. LPC

ID# SEX ETHNICITY

1. WHAT IS YOUR FULL NAME: 2. WHAT IS THE DATE OF YOUR BIRTH? AGE 3. WHAT IS TODAYS DATE? 4. WHAT IS THE NAME OF THIS STATE/DISTRICT? 5. WHAT IS THE NAME OF THIS FACILITY WHERE YOU LIVE?

6.WHAT IS YOUR MARITAL STATUS?

SINGLE MARRIED DIVORCED RELATIONSHIP^). HOW LONG CHILDREN HOW MANY (girls) (boys) AGES _ a) Are you involved in your child/children's life? b) What is your relationship with the mother? c) Age you first became a mother / father

7. HOW FAR DID YOU GO IN SCHOOL? a) Do you have a GED? Date: Age: Where:_ b) Did you ever attend special education or slow learners classes? c) Were you ever held back a grade? What grade?

Why? d) If you did dropped out of school, why? e) Did you have discipline problems at school? f) Do you have any college credits? g) If so, what field of study? h) Did you have any career/work goals while in school? I) If so, what?

8. DID YOU EVER SERVE IN THE MILITARY? Yes No YEARS SERVED: TYPE OF DISCHARGE:

9 WHAT KIND OF WORK ARE YOU TRAINED TO DO?

a) What type of work have you done consistently over time?

b) Did anyone ever talk to you or counsel you about work/career choices?

c) As a child or adolescent, what did you want to be as an adult?

d) What type of work did your parent(s) or guardian do for a living?

156

10. HOW WOULD YOU DESCRIBE YOUR SELF? a) Positive qualities-

b) Negative qualities-

11. WHAT ARE THE REASONS FOR YOU BEING HERE AT THIS FACILITY? SUBSTANCE ABUSE: Substance(s) Age of onset How long How used Abuse or Dependency

CRIMINAL ARRESTS: Did you ever use a weapon? Yes No If yes what type? Was there ever a victim involved? Yes No Injuries JUVENILE: Date Age Charge Convicted Sentenced Yrs Served

ADULT: Date Age Charge Convicted Sentenced Yrs Served

Total years of incarceration:

12. WHO RAISED YOU? _ a) Did you feel loved? b) Where they available? c) Did/do they have drug or alcohol problems? d) Alive / Deceased ? If deceased -Date of death Cause f) Did/do they have criminal problems?

13. DO YOU HAVE ANY BROTHERS AND/OR SISTERS? _ _ (sisters) (ages)_ (brothers) (ages)_

a) Do any of your brothers and/or sisters have drug /alcohol / criminal problems? (If yes explain)

b) Did you live with your brothers and/or sisters?

157

14.WH0 DID YOU FEEL THE CLOSEST TO WHEN YOU WERE GROWING UP?

15. WERE YOU EVER VERBALLY OR EMOTIONALLY ABUSED AS A CHILD OR ADOLESCENT? (Teased, or made fun of both within and/or outside the family)

If so how?

16.WERE YOU EVER PHYSICALLY ABUSED AS A CHILD OR ADOLESCENT?

a) Who was the disciplinarian within the family? b) How was discipline administered?

c) Was the discipline heavy handed or appropriate to the situation?

17. WERE YOU EVER SEXUALLY MOLESTED, ABUSED OR RAPED AS A CHILD OR ADOLESANT ? Explain Abuser Age of abuser Results of abuse

Was any other member of your family abused AS AN ADULT

18. a) IN YOUR LIFETIME, HAVE YOU EVER HAD TWO WEEKS OR MORE DURING WHICH YOU FELT DEPRESSED, SAD OR BLUE? Yes No

b) DURING THAT TWO WEEK PERIOD; DID YOU LOSE INTEREST, PLEASURE, OR ENJOYMENT IN THE THINGS THAT YOU USUALLY CARED ABOUT OR ENJOYED DOING? (Not while you were under the influence of drugs or alcohol) Yes No Dates & Events:

c) IN YOUR LIFE TIME, HAVE YOU HAD TWO YEARS OR MORE WHEN YOU FELT DEPRESSED, SAD, OR BLUE - MOST OF THE TIME OR MORE DAYS THAN NOT - EVEN THOUGH SOMETIMES YOU MIGHT HAVE FELT ALL RIGHT? (Not while you were under the influence of drugs or alcohol) Yes No _ _ _ _ _ Dates & Events:

d) WHILE YOU WERE DEPRESSED, SAD OR BLUE, DID YOU EXPERIENCE ANY OF THE FOLLOWING SYMPTOMS?

Check appetite and sleep patterns regardless 1) Poor appetite: Yes No 2) Overeating: Yes No 3) Did the problem last for 2 weeks? within two years ? 4) Did it result in significant - weight loss weight gain

Not the result of conscious attempt to either gain or lose weight 5) Little or no sleep: Yes No 6) Too much sleep: Yes No 7) Did it happen nearly everyday? (1 wk.) (2 yrs.) 8) Did it happen at various periods of time throughout the years? Yes No 9) Explain sleep patterns: (ex. Bedtime, daytime, naps, trouble falling asleep, trouble

staying asleep)

e) DID YOU FELL FIDGETY, RESTLESS, AGITATED, OR MORE SLOWED DOWN THAN IS NORMAL FOR YOU?

Nearly everyday for that (two week period) Yes No (two year period) Yes No

i) DID YOU HAVE LOW ENERGY, LOSS OF ENERGY OR FATIGUE? Nearly everyday for that (two week period) Yes No A lot of the time within the last (two years) Yes No

g) DID YOU HAVE POOR CONCENTRATION? Yes No DIFFICULITY MAKING DECISIONS? , Yes No INABILITY TO THINK CLEAR? Yes No

h) DID YOU HAVE FEELINGS OF LOW SELF-WORTH Yes No FEELINGS OF WORTHLESSNESS? Yes No FEELINGS OF INADEQUACY? Yes No EXCESSIVE QUILT OVER PAST ACTIVITES, OR SINFULNESS? Yes No

Nearly everyday for that (two week period) Yes No A lot of the time within the last (two years) Yes No

i) DID YOU HAVE EXCESSIVE OR RECURRENT THOUGHTS ABOUT DEATH? Either your own or someone close to you? Yes No AND/OR DID YOU HAVE EXCESSIVE OR RECURRENT THOUGHTS ABOUT SUICIDE - WITH OR WITHOUT A SUICIDE PLAN? Yes No

Nearly every day for a (2) week period: Yes No A lot of tiie time within the last (2) year period: Yes No

Dates & Events:

j) AT ANY TIME WHEN YOU WERE DEPRESSED, SAD OR BLUE, DID YOU EXPERIENCE VISIONS (ex. See things that others around you could not see) Yes No AT ANY TIME DID YOU HEAR VOICES (hear things that others around you could not hear)? Yes No or-HAVE YOU HAD FIXED IDEAS ABOUT SOMEONE OR SOMETHING THAT YOU COULD NOT GET RID OF? Yes No

If yes explain:

Have you had these feelings before you got depressed? Yes No or after you got depressed? Yes No

159

k) DID YOUR DEPRESSION, SADNESS, OR FEELING BLUE OCCUR JUST AFTER SOMEONE CLOSE TO YOU DIED? Yes No

If yes explain: _ ^ _ _ _ _ _ _ _ _ _ ^

1) HAVE YOU HAD FEELINGS OF HOPELESSNESS, NEGATIVE THINKING ABOUT PAST EVENTS A LOT OF THE TIME?

Nearly every day for a (2) week period: Yes No A lot of the time within the last (2) year period: Yes No

If yes explain:

19. a) IN YOUR LIFE TIME, HAS THERE EVER BEEN A PERIOD OF ONE WEEK OR MORE WHEN YOU WERE SO HAPPY, EXCITED, HYPER, OR IRRITABLE THAT YOU GOT INTO TROUBLE - OR - YOUR FAMILY OR FRIENDS WERE CONCERNED OR WORRIED ABOUT YOU MOVING ALONG MUCH TO FAST (ex Like a speedball)? Yes No

If yes explain:

a) A DOCTOR SAID YOU WERE MANIC, (Without being under the influence of illegal drugs and /or alcohol)? Yes No

If yes explain:

b) WHILE HAPPY, EXCITED, HIGH, HYPER, OR IRRITABLE, HAVE YOU EXPERIENCED SOME OF THE FOLLOWING SYMFYOMS:

1) Inflated self-worth -Yes No 2) Exaggerated sensed of yourself-Yes No 3) A belief that you had a special gift or special powers- Yes No . 4) Hardly slept at all or just for a few hours, but still did not feel tired or sleepy -

Yes No 5) More talkative than usual or you talked so much that other people could not get in a

word edgewise or other people could not stop you from talking or others said mat they could not understand you ? - Yes No

6) Thoughts or ideas race through your head so fast that you could not understand them?- Yes No

7) Were you easily distracted and had difficulty concentrating because any little thing going on around you could get you off the track? -Yes _ _ No

8) Increased productivity or goal-directed activity at: Work- Yes No School Yes No Socially- Yes No Sexually-Yes No

9) Excessive involvement in pleasurable activities with lack of concern for the high potential (risk) for the painful consequences? (ex. foolish business investments, buying sprees, reckless driving, more interest in sex than is normal for you)Yes No

10) At any time when your mood was happy, excited, high, hyper, or irritable did you experience: visions (ex. See things that other people around you could not see)

Yes No voices ( ex. Hear things that other people around you could not hear) Yes No or (ex. Have fixed ideas about someone or something that you could not get rid of) Yes No

If yes explain:

160

20. NOW I AM GOING TO ASK YOU ABOUT SOME OTHER TYPES OF EXPERIENCES: a) Did it ever seem that people were talking about you, taking special notice of you following you,

watching you, or spying on you for no particular reason? Yes No If yes explain:

b) Did it ever seem that you were receiving special messages from the T.V., radio, or newspaper - or from the way things were arranged around you? Yes No

If yes explain:

c) Did it ever seem that someone was going out of his/her way to give you a hard time, plotting against you, trying to hurt you, or trying to poison you for no particular reason? Yes No

If yes explain:__

d) Did you ever feel that you were especially important in some way - or - that you had powers to do things that other people couldn't do? Yes - No

If yes explain:

e) Did you ever feel that parts of your body had changed or stopped working? Yes No If yes explain:

f) Did you ever feel that you had committed a crime or done something terrible for which you should be punished? Yes. No

If yes explain:

g) Did you ever believe that someone was controlling what you thought or how you moved against your will? Yes No

If yes explain:

h) Have you ever thought that someone or something could put strange thoughts directly into your mind or could take or steal your thoughts out of your mind? Yes No

If yes explain:

161

i) Have you ever believed you could actually hear what another person was thinking, even though he/she was not speaking, - or believed that others could hear your thoughts, - or someone was reading your mind? Yes No

If yes explain: _ _ _ _ _ _ _ _ _ _ _ _ _ _ ^

j) Have you ever had the experience of seeing something or someone that others who were present could no see: - such as, having a vision while you were completely awake? Yes No

If yes explain:

k) Have you ever had the experience of hearing things that others who were present could not hear -such as voices commenting on what you were doing two or more voices talking or whispering to each other— odd noises or music? Yes No If yes explain:

I) Have you ever been bothered by strange smells around you that nobody else seemed to be able to smell -perhaps even foul odors coming from your body? Yes No

If yes explain: .

m) Have you ever had unusual feelings inside your body - like being touched when no- was there or feeling something moving inside your body - or Strange sensations in your body or on your skin? Yes No

If yes explain: ,

21. IN THE PAST YEAR OR SO, HAVE YOU BEEN PARTICULARLY NERVOUS OR ANXIOUS? Yes No FOR EXAMPLE: DO YOU WORRY A LOT-MOST OF THE TIME-MORE DAYS THAN NOT - ABOUT TERRIBLE THINGS THAT MIGHT HAPPEN - WHICH MAY OR MAY NOT BE REALISTIC? Yes_ No If yes explain:

AT THOSE TIMES - WHEN YOU RE FEELING NERVOUS OR ANXIOUS - DO YOU EXPERIENCE ANY OF THE FOLLOWING SYMPTOMS:

a) MOTOR TENSION: 1) Trembling, twitching, or feeling shaky: Yes No 2) Muscle tension, aches, or soreness: Yes No 3) Restlessness or can't sit still: Yes No 4) Felt tired easily: Yes No

b) AUTONOMIC HYPERACTIVITY 1) Shortness of breath or smothering sensations: Yes No 2) Heart pounds or races: Yes No 3) Sweating or cold, clammy hands: Yes No 4) Dry mouth: Yes No

5) Dizziness or light headedness: Yes No 6) Nausea, diarrhea or other abdominal distress: Yes No 7) Hot Hashes, flashes or chills: Yes No 8) Urinate more often than is usual for you: Yes No 9) Trouble swallowing or a lump in your throat: Yes No

c) VIGILANCE AND SCANNING 1) Feeling keyed up or on edge. Yes No 2) Startled by sudden noises: Yes No 3) Difficulty concentrating or your mind goes blank? Yes No 4) Trouble railing or staying asleep: Yes No 5) Often irritable: Yes No

22. NOW -1 WANT TO ASK YOU ABOUT WHETHER YOU RAVE BEEN BOTHERED BY HAVING UNPLEASANT THOUGHTS, IDEAS, IMPULSES, OR IMAGES THAT DIDN'T MAKE SENSE TO YOU, BUT KEPT COMING BACK TO YOU EVEN WHEN YOU TRIED NOT TO HAVE THEM? (ex. The persistent idea that you might harm someone you loved, even through you really didn't want to? - or Ever been bothered by any other unpleasant and persistent thoughts, ideas, or impulses that your just couldn't get rid of? Yes No If yes, explain:

23. a)WAS THERE ANY THING THAT YOU HAD TO DO OVER AND OVER AGAIN AND COULDN'T RESIST DOING? Like washing your hands again and again or- Checking something several times to make sure you have done it right - or- Going back several times to be sure that you locked a door or turned off the lights. HAVE YOU EVER HAD TO DO SOMETHING LIKE THAT OVER AND OVER AGAIN? Yes No If yes explain:

b) WAS THERE A TIME WHEN YOU ALWAYS HAD TO DO SOMETHING IN A CERTAIN ORDER: - Like getting dressed in a specific order or you had to start all over again if you got the order wrong? Yes No If yes explain:

c) HAS THERE EVER BEEN A PERIOD OF SEVERAL WEEKS WHEN YOU FELT YOU HAD TO COUNT SOMETHING - Like squares in a tile floor and you couldnt resist doing it even when you tried to stop? Yes No If yes explain:

24. SOME PEOPLE HAVE A STRONG FEAR OF SOMETHING OR SOME SITUATION THAT THEY TRY TO AVOID EVEN THOUGH THEY KNOW THERE IS NO REAL DANGER. HAVE YOU EVER HAD A STRONG FEAR OF ANY OF THE FOLLOWING:

a) Heights: Yes No b) Tunnels or bridge: Yes No

163

c) Being in a crowd: Yes No d) Going out of the house alone: Yes No e) Being in closed places: Yes No f) Being alone: Yes No g) Eating in front of people: Yes _ No h) Speaking in front of a small group of people you bow: Yes No i) Speaking to strangers or meeting new people: Yes No j) Storms: Yes No k) Being in. a swimming pool or lake: Yes No 1) Spiders, bugs, mice, snakes, or bats: Yes No

m) Seeing blood or an. injury: Yes No

25 a) HAVE YOU EVER HAD A SPELL OR ATTACK WHEN ALL OF A SUDDEN YOU FELT FRIGHTENED, ANXIOUS, UNCOMFORTABLE, OR VERYUNEASY - IN A SITUATION WHERE MOST PEOPLE AROUND YOU APPEARED RELAXED AND CALM? Yes. No \

If yes explain: \

.IKE' b) HAVE YOU EVER HAD FOUR ATTACKS OR SPELLS LIKE THAT IN A FOUR WEEK PERIOD? Yes No

If yes explain:

c) DURING ONE OF YOUR WORST SPELLS OR ATTACKS - OF SUDDENLY FEELINGFRIGHTENED, ANXIOUS, UNCOMFORTABLE OR UNEASY DID YOU EVER NOTICE THAT YOU HAD ANY OF THE FOLLOWING PROBLEMS:

1) Shortness of breath or smothering sensations: Yes N o 2) Dizziness, unsteady feelings, or faintness: Yes No 3) Heart racing, pounding, or skipping: Yes No 4) Trembling or shaking: Yes No 5) Sweating: Yes No 6) Choking: Yes No 7) Nausea or abdominal distress: Yes. No 8) Things around you seemed unreal - or- you felt detached from your body, or from things around you: Yes No 9) Numbness or tingling sensations: Yes No

10) Hot flashes, flushes or chills: Yes No 11) Tightness, discomfort, or pain in your chest: Yes No 12) Fear of dying: Yes No

If yes explain: 13)Fear of going crazy or doing something uncontrolled: Yes No

If yes explain:

26. NOW I AM GOING TO ASK YOU ABOUT YOUR PHYSICAL HEALTH: a) MEDICATION:

1) Do you presently take any mediations for a physical problem? (Hx behind it): Yes No

If yes explain:

Medication:

2.(Hx behind it): Yes No If yes explain:

Medication

b) GASTROINTESTINAL PROBLEMS: 1) Vomiting: Yes No 2) Stomach or belly pain: Yes No 3) Nausea or Feeling sick to your stomach: Yes No 4) Bloating or gassy feeling: Yes No 5) Diarrhea or loose bowels: Yes No 6) Getting sick from several different foods: Yes No

c) PROBLEMS WITH PAIN: 1) Pain in your arms or legs? Yes No 2) Back pain: Yes No 3) Pain in your joints: Yes No 4) Pain during urination: Yes No 5) Pain anywhere else in your body: Yes No

d) CARDIOPULMONARY DISTRESS: 1) Shortness of breath without exerting yourself: Yes No 2) Heart racing, pounding, or skipping: Yes No 3) Chest pain: Yes No 4) Dizziness: Yes No

e) CONVERSION OF PSEUDONEUROLOGICAL

1) Period of time when you couldn't remember anything about what happened during that time: Yes No

2) Difficulty swallowing: Yes No 3) Loss of voice: Yes No 4) Deafness: Yes No 5) Double vision: Yes No 6) Blurred vision: Yes No 7) Blindness: Yes No 8) Fainting spells or loss of consciousness: Yes No 9) Seizure or convulsion: Yes No 10) Trouble walking: Yes No 11) Muscle weakness or paralysis: Yes No 12) Difficulty urinating or retaining your urine: Yes No

f) PSYCHOSEXUAL SYMPTOMS (Major part or person's life after sexual activity): 1) Burning sensation in sexual organs or rectum: Yes No 2) Sexual indifference (loss of interest in sex): Yes No 3) Pain during intercourse; Yes No 4) Not being able to get an erection: Yes No

165

g) FEMALE REPRODUCTIVE SYMPTOMS (occur more often than the average female): 1) Painful menstruation: Yes No 2) Irregular menstrual periods: Yes No 3) Excessive menstrual bleeding: Yes No 4) Vomiting throughout pregnancy: Yes No

27 DO YOU FEEL SORRY FOR ANYTHING YOU HAVE DONE IN THE PAST"? Yes No. It yes explain:

28 HAVE YOU WANTED TO END YOUR LIFE? Yes No HAVE YOU EVER MADE AN ATTEMPT ON YOUR LIFE? Yes No If yes explain

29. a) HAVE YOU EVER HATED ANOTHER PERSON SO MUCH THAT YOU HAVE THOUGHT ABOUT HURTING THEM?

Yes No OR TAKING THEIR LIFE? Yes No If yes explain:

b) HOW DO YOU USUALLY DEAL WITH YOUR ANGER? (ex. Act-Out, Stuff It- Indirect, Talk It Out)

Explain:

30. HAVE YOU OR ANY MEMBER OF YOUR FAMILY EVER HAD A PSYCHIATRIC/ PSYCHOLOGICAL/ SOCIAL WORKER/ COUNSELOR? Yes No If yes explain:

Note: (Determine the nature of the problem, diagnosis, treating professional, etc.)

31 HAVE YOU EVER BEEN TREATED FOR AN ALCOHOL AND /OR DRUG PROBLEM? Yes No If yes explain:

(Determine if the alcohol/ drug problem was, misuse, abuse, and/or dependency)

NOTES:

166

APPENDIX - B

Figure 1.1

The division of the pie chart equal the number of inmates classified in each HSLC

Figure 1.1

The divisions in the pie chart equal the number of inmates classified in each HSLC:

1.00 = Realistic (R), 2.00 ^Artistic, 3.00 - Social (S), 4.00 = Enterprising (E),

5.00 = Conventional, and the Red area are the missing inmates who were not classified.

5J0

400

3.00

1.00

2.00

Figure 1.1 - Represents the number of inmates tested using the SDS. The HSLC

classification identified the individual single letter code of each inmate.

168

APPENDIX-C

Figure 2.1

The figure shows that most of the HSLC classified inmates ranged in intelligence level from Borderline (VICS) IQ (70-79) to Average (VISC) IQ (90-109).

169

Figure 2.1

HSLC Inmates and Verbal IQ

VerbaMQ

Missing

1.00

2.00

3.00

1= 69 & below;2=70-79;3=S0=89^=90-109^5=110-119;6=120-129

Figure 2.1 shows that most of the HSLC classified inmates ranged in

Intelligence from borderline IQ (70-79) to average IQ (90-109).

170

APPENDIX - D

Table 3.1 HSLC classification and correlation with Rorschach EB style of decisionmaking

Figure 3.1 HSLC and the Rorschach EB Scores

171

Table 3.1

HSLC classification and correlation with Rorschach EB style of decision-making

Analysis of Variance EB l=Extratensive 2=Ambitent 3=Introversive Unique sums of squares All effects entered simultaneously Source of Variation

Main effects HSLC Explained Residual Total 178 cases processed

Sum of Squares

13.163 13.163 13.163 67.781 80.943 19 cases 10.7 percent) missing

DF 28 28 28

130 158

Mean Square .470 .470 .470 .521 .512

F

.902

.902 .902 .521

Sig. of F

.611

.611

.611

Table 3.1 demonstrates the mean score and correlation between HSLC

and Rorschach EB decision-making style.

Figure 3.1 I HSLC and the Rorschach EB Score

Inmates

1= exto, 2 = ambitant, 3=introvert

1= Extratensive - 2= Ambitent 3= Introversive

Figure 3.1 I HSLC and the Rorschach EB Score 1

Figure 3.1 indicated that even though the research hypothesis was not significant in predicting any correlation between the HSLC and the Rorschach EB score, there were a larger number of inmates found to be ambitent than was expected by the researcher

173

APPENDIX-E

The Egocentricity Index of the HSLC classified population:

Extended statistics on the classified inmates

Table 4,2 - The percentage of individual's classified as Realistic (R) according to the

HSLC as above, below, or in the normal range of decision-making and self-esteem

according to the Egocentricity Index.

Table 4.3 - The percentage of individual's classified as Artistic (A) according to the

HSLC that are above, below, or in the normal range of self-esteem.

Table 4.4 -The percentage of individual's classified as Social (S) according to the

HSLC that are either above, below, or in the normal range of self-esteem.

Table 4.5- The percentage of individual's classified as Enterprising (E) according to the

HSLC that are above, below, or in the normal range of self-esteem on the Egocentricity

Index.

Table 4.6- The percentage of individual's classified as Conventional (C) according to the

HSLC that are above, below, or in the normal range of self-esteem according to the

Egocentricity Index

174

Table 4.2 - The percentage of individual's classified as Realistic (R) according to the HSLC as above, below, or in the normal range of decision-making and self-esteem according to the Egocentricity Index.

HSLC R4 R12 R34 R36 R40 R41 R47 R50 R52 R53 R64 R66 R67 R69 R72 R75 R76 R84 R86 R87 R91 R95 R96 R114 R116 R118 R125 R127 R130 R134 R136 R137 R154 R156 R160 R161 R163 R169 TOTAL= 38

3r+(2)R .30 .26 .52 .17 .04 .36 .42 .38 .33 .35 .45 .26 .52 .42 .53 .52 .32 .65 .26 .25 .32 .54 .45 .52 .40 .29 .32 .38 .35 .69 .36 .25 .32 .27 .28 .40 .41 .53

>.44

X

X

X X

X

X

X

X

X 9 24%

NORMAL

X X X X X X

X

X

X

X

X

X X X

X

X

X X

18 47%

<.33 X X

X X

X

X X

X

X

X X

11 29%

175

Table 4.3

Table 4.3- The percentage of indivi HSLC that are above, below, or in ti HSLC Al A25 A27 A37 A61 A90 A99 A106 A110 A120 A128 A138 A139 A152 A153 TOTAL=15

3r+(2)/R .54 .48 .12 .21 .06 .06 .44 .35 .30 .43 .45 .35 .40 .29 .44

dual's classified a; le normal range oi >,44 X X

X

3 20%

5 Artistic (A) according to the 'self-esteem. Normal

X X

X

X X

X 6 40%

<.33

X X X X

X

X

6 40%

Table 4.4

Table 4.4- The percentage of individual's classified as Social (S) according to the HSLC that are either above, below, or in the normal range of self-esteem. HSLC S2 S3 S5 S7 S8 S10 Sl l S13 S14 S16 S17 S19 S20

3r+(2)/R .44 .37 .42 .13 .25 .73 .42 .38 .48 .23 .18 .47 .44

>.44

X

X

X

AVERAGE X X X

X X

X

<.33

X X

X X

Continued

176

HSLC S26 S28 S32 S33 S48 S54 S55 S56 S58 S65 S71 S73 S77 S80 S81 S85 S88 S92 S93 S100 S101 S102

S105 S107 S109 S112 S113 S115 S117 S121 S122 S123 S126

S131 S132

S133 S135 S143 S144 S145 S146 S148 S149 S158

3H-(2)/R .36 .41 .41 .41 .33 .54 .57 .29 .15 .18 .44 .46 .40 .35 .25 .39 .39 .37 .30 .33 .35 .25 .56 .35 .32 .53 .62 .35 .30 .25 .39 .38 .10 .44 .32 .14 .35 .44 .44 .57 .22 .30 .25 .33

>.44

X X

X

X

X X

X

NORMAL X X X X X

X

X X

X X X

X X

X X

X

X X

X X

X X X

X

<.33

X X X

X

X

X

X X

X

X

X X X Continued

177

HSLC

S159 S167 S170 S175 S176 S178 TOTAL=64

3r(2)/R

.43

.18

.32

.07

.33

.32

>.44

11

17%

NORMAL

X

X

X X 34

53%

<.33

X

X

19

30%

Table 4.5

Table 4.4- The percentage of individual's classified as Enterprising (E) according to the HSLC that are above, below, or in the normal range of self-esteem on the Egocentricity Index. HSLC E9 E15 El 8 E21 E22 E23 E29 E38 E43 E46 E51 E57 E59 E74 E79 E83 E89 E94 E97 E98 El 03 Total = 21

3r+(2)/R .54 .43 .00 .20 .18 .23 .15 .12 .30 .42 .52 .22 .43 .14 .27 .06 .42 .17 .16 .50 .63

>.44 X

X

X X 4 19%

NORMAL

X

X

X

X

4 19%

<.33

X X X X X X X

X

X X X

X X

13 62%

178

Table 4.6

Table 4.6~ The percentage of individual's classified as Conventional (C)according to the HSLC that are above, below, or in the normal range of self-esteem according to the Egocentricity Index HSLC C6 C49 C60 C62 C63 C68 C78

cm C119 C124 C150 C151 C157 C162 C168 TOTAL=15

3r+(2)/R .42 .62 .42 .56 .26 .41 .33 .50 .18 .50 .41 .65 .50 .21 .04

>.44

X

X

X

X

X

5 33%

NORMAL X

X

X X

X

X

6 40%

<.33

X

X

X X 4 27%

179

APPENDIX - F

Rorschach EB Scores Introversive -Ambitant - Extratensive

Figure 4.1 EB Score Realistic

Figure 4.2 EB Score Artistic

Figure 4.3 EB Score Social

Figure 4.4 EB Score Enterprising

Figure 4.5 EB Score Conventional

180

Figure 4.1

Percentages Egocentric Index

u u

80

60

40

20

A

-

: B 1

|

• D •

+.45 Normal -.32

Realistic Realistic equals 38

Figure 4.1 indicates that 47%, or almost half of the HSLC Realistic are in the normal

egocentricity range. That 29% of the HSLC (Realistic) are in the below average index

range and that the subjects estimate of self-worth tends to be quite negative. They would

probably have low self-esteem. The above average index was 24% in this HSLC Realistic

group, therefore the sample HSLC (R) tended to be more interested in them than in others

or would seem to have narcissistic-like features.

Figure 4.2

181

Percentage EgOCentricity Index

100

80

60

40

20

Artistic equals 15 inmates Artistic

Figure 4.2 shows that 40% of the HSLC Artistic are in the normal Egocentricity Index

range. It also shows that 40% are also in the below average range. Therefore, the

subject's estimate of self-worth tends to be quite negative. They would have low self-

esteem. The above average index was low (20%) in this Artistic group, therefore only a

few of the sample HSLC (A) population demonstrated a preoccupation with themselves

more than in others or would seem to have narcissistic-like features.

Figure 4.3

182

Percentage Egocentricity Index

100

80

60

40

20

0 Social equals 64 inmates

Social

Figure 4.3 shows that 30% of the HSLC Social are in the normal index range. That 53%

or over half of the HSLC Social are in the below average index range and that the

subjects estimate of self-worth tends to be quite negative. They would probably have low

self-esteem. The below average index range is twice as large in the HSLC (S) then the

combine number in the normal and low range of the index. The above average index was

low (17%) in this Social group, therefore not many of the sample HSLC (S) tended to be

more interested in themselves than in others or would seem to have narcissistic-like

features.

Figure 4.4

Percentage Egocentricity Index

100

Enterprising equals 31 Enterprising

Figure 4.4 demonstrates that only 12% of the HSLC Enterprising are in the normal

range. That 68% of the HSLC Enterprising are in the below average index range and

that the subjects estimate of self-worth tends to be quite negative. They would probably

have low self-esteem. The above average index was lower at 20% in this Enterprising

group, therefore the majority of the sample HSLC (E) tend to be more interested in

themselves than in others or would seem to have narcissistic-like features.

Figure 4.5

184

Percentages

100i

Egocentricity Index

80

60

40

20

0 Conventional

Conventional equals 15 inmates

• >.44 • Normal • <.31

Figure 4.5 demonstrates that 40% of the HSLC Conventional are in the normal

Egocentricity Index range. That 25% of the HSLC Conventional are in the below average

index range and that the subjects estimate of self-worth tends to be quite negative. They

would probably have low self-esteem. The above average index was 35% in this

Conventional group, therefore the sample HSLC (C) tended to be more interested in

themselves than in others or would seem to have narcissistic-like features.

185

APPENDIX-G

Table 5.1

Sub. H5.2- MCMI-II Subtests Cluster "A'

186

Table 5.1

Sub H 5.2 -MCMI-II Subtests Cluster "A"

Multiple Regression

Listwise Deletion of Missing Data


Block Number 1. Method: Stepwise Criteria Pin .0500 Pout .1000

Variable (s) Removed on Step Number 6... (MCMISCHZ) Schizoid

Cluster "A" - Schizoid (MCMISCHZ), Paranoid (MCMIPARA), Schizotypal

(MCMISCTY)

Multiple R

.0000


Regression

Residual

F is undefined

R Square

.0000

DF

0

159

Adjusted R Square

.0000

Sum of Squares

.00000

248.37500

Standard Error

1.24984

Mean Square

.00000

1.56211

Variables not in the equation

Variable

MCMIPARA

MCMISCHZ

MCMISCTY

Beta In

- .052303

- .112451

.015959

Partial

-.052303

-.112451

-.015959

Min Toler

1.000000

1.000000

1.000000

T

-.658

-1.423 .

.201

Sig T

.5113

.1568

.8413

End Block Number 1 All requested variables removec

187

APPENDIX ~H

Sub H-5.2 MCMI-II Subtests Cluster "B" and the HSLC

Table 5.2 represents any significant relationship between the HSLC group

and MCMI-II cluster "B."

Figure 5.1 indicates through the use of symbols and colors on the right

indicate the number of inmates with an antisocial disorder which fell into each of the

classified HSLC (1=R), (2=A), (3=S), (4=E), (5=C).

Figure 5.2 The graphs figure 5.1 and figure 5.2 depicts a different way to

demonstrate how 3.00 (S) Social is driving the antisocial disorder with a high number of

inmates falling in this classification.

188

Table 5.2 represents any significant relationship between the HSLC group

and MCMI-II cluster "B."

Multiple Regression


Equation Number 1 Dependent Variable ....

HSLC


Variable (s) Entered on Step Number 1... .MCMIANTI (Antisocial)

Cluster "B" - Antisocial (MCMIANTI), Borderline (MCMIBDLI),

Histrionic (MCMIHID), Narcissistic (MCMINARC)

Multiple R

.15865


Regression

Residual

F = 4.07944

R Square

.02517

DF

1

158

Adjusted R Square

.01900

Sum of Squares

6.25144

242.12356

Sig. F = .0451

Standard Error

1.23791

Mean of Squares

6.25144

1.53243

Variable

MCMI ANTI (Constant)

B

-.009958

3.655963

Variables in the Equation SEB

.004930

.428919

Beta

-.158649 t

T.

-2.020

8.524

Sig T

.0451

.0000

Variable MCMIBDLI MCMIHIS MCMINARC

Beta In .134723 .144820 .040862

Variables not in the Equation Partial .116923 .135860 .036399

Min Toler .773531 .857928 .773531

T 1.475 1.718 .456

S igT .1422 .0877 .6487

189

Figure 5.1 MCMI-II Scale

0 1

holiand unit code

37.00

36.00

35.00

34.00

33.00

32.00

31.00

moo 29.00

28.00

26.00

23.00

21.00

1=R 2=A 3=S 4=E 5=C RAW SCORES MCMI -II

Figure 5.1 indicates through the use of symbols and colors on the right (raw score)

indicate the number of inmates with an antisocial disorder which fell into each of the

classified HSLC (1=R), (2=A), (3=S), (4=E), (5=C). It can be observed that the largest

number and highest scores were classified in the (S) Social group. The (R) Realistic and

the (E) enterprising HSLC were also high for antisocial disorder. .

190

Figure 5.2 Inmates

m-r i

70-/ \

9D- /

m- /

30- / x \ / v--,_

2fl| / / c \ / n

t Q:.: , , j ^ssmg 1.0G 2.00 3.00 4.00 5.00

Wand unit code

I 1.00 =R 2.00 =A 3.00 =S 4.00 =E 5.00 =C

The graphs in figure 5.1 and figure 5.2 depicts a different way to

demonstrate how 3.00 (S) Social is driving the antisocial disorder with a high number of

inmates falling in this classification. The (R) Realistic group is the next highest

classification with about a third of the inmates.

191

APPENDIX-I

Sub. H -5.3 - MCMI- II Subtests Clusters "C"

Table 5.4

Compulsive

192

Table 5.4

Multiple Regression




Variable (s) Entered on Step Number 1... (MCMICOMP) Compul sive

Cluster "C" - Passive Aggressive (MCMIPAG), Dependent (MCMIDEP), Avoidant

(MCMIADVO), (MCMICOMP)

Multiple R

.21572


Regression

Residual

F -

R Square

.04654

DF

1

158

7.71151

Adjusted R Square

.04050

Sum of Squares

11.55831

248.37500

Signif. F

Standard Error

1.22427

Mean Square

11.49884

1.56211

.0062

Variables in the Equation

Variable

MCMICOMP

(Constant)

B

.017583

1.676449

SE B

.006332

.420392

Beta

.215721

T

2.777

3.988

SigT

.0062

.0001

Variables not in the Equation

Variable

MCMIPAG

MCMIDEP

MCMIADVO

Beta In

-.070783

.056690

-.001101

Partial

-.070857

.057943

-.001079

Min Toler

.955476

.996098

.915777

T

-.890

.727

-.014

Sig T

.3748

.4682

.9892

APPENDIX -J

Table 6.1 MCMI-II Clinical Personality Patterns and any Significant

Relationship with the HSLC Group.

Figure 6.1 A large number of the inmates scores are falling between 55 and 75

on the compulsive subtest of the MCMI-II. According to the MCMI-II these

scores would only be approaching any significant level of disorder.

Figure 6.2 A large again shows group of HSLC classified (S) falling in the upper range

of compulsive.

Table 6.2 Demonstrates any correlation between the MCMI-II compulsive scale and

MCMI-II validity scale, MCMI-II disclosure scale, and MCMI-II debasement

scale.

Table 6.3 Measures of the amount of variance that can be explained by a proposed factor.

Table 6.4 Demonstrates the "loading" on each of the factors.

194

Table 6.1

MCMI-II Clinical Personality Patterns and any Significant

Relationship with the HSLC Group

Multiple Regression




Variable (s) Entered on Step Number 1... .MCMICOMP

Clinical Personality Pattern subtests - Schizoid(MCMISCHZ), Avoidant(MCMIADVO),

Dependent(MCMIDEP), Alcohol (MCMICOMP), Narcissistic(MCMINARC),

Antisocial(MCMIANTI), Aggressive Sadistic(MCMIAGSA), Passive

Aggressive(MCMIPAG), Self-Defeating(MCMISFDE), Histrionic (MCMIHIS)

Multiple R

.21572


Regression

Residual

F = 7.71151

R Square

.04654

DF

1

158

Variab Variable

MCMICOMP (Constant)

B

-.017583 1.676449

Adjusted R Square

.04050

Sum of Squares

11.55831

236.81669

Signif F = .0062

Standard Error

1.22427

Mean of Squares

11.55831

1.49884

es in the Equation SEB

.006332

.420392

Beta

.215721

T

2.777 3.988

Sig T

.0062

.0001 continued

195

Variables not in the Equation Variable MCMISCHZ MCMIADVO MCMIDEP MCMINARC MCMIHIS MCMIANTI MCMIAGSA MCMPAG MCMISFDE

Beta In -.095108 -.001101 .056690 .050056 .091819

-.105957 -.103350 -.070783 .032246

Partial -.097061 -.001079 .057943 .051242 .093345

-.104050 -.105627 -.070857 .031948

Min Toler .993033 .915777 .996098 .999194 .985435 .919444 .995949 .955476 .935906

T -1.222 - .014

.727 - .643

1.175 -1.311 -1.331 -.890 .401

Sig T .2236 .9892 .4682 .5212 .2419 .1918 .1851 .3748 .6893

End Block Number 1 PIN = .050 Limits Reached

196

Figure 6.1 MCMI-II ScaleScore

Std.Etev= 15.26 Mean = 64.5 H = 163.00

25.0 35.Q 45.0 55.0 65.0 75.0 85.0 95.0 105.0 30.0 40.0 50.0 60,0 70.0 80.0 90.0 100.0 110.0

compulsive

(Y- axis) Vertical side of the graph are the number of inmates

(X-axis) Horizontal side of the graph are the range of scores on the MCMI-II Test

Figure 6.1 indicates that a large number of the inmate's scores are falling between 55 and

75 on the compulsive subtest of the MCMI-II. According to the MCMI-

II these scores would only be approaching any significant level of disorder. There are

more inmates above 75 than below 55. The majority of the inmates are neither to far

above or to far below.

197

Figure 6.2

MCMI-II Scale

c o m P y I s i v e

120-1

100-

80-

60-

40-

70

*

•

A

J < 1 • -

» •

i 4 T

i *

»

•-

r • i

» & fr

* • * *

*

1 '

t t

i 1 *

. j

-*

t A «

• * 1 *

I

* •«

m

l

6-

£1

r

m m &

' 0

B

1

39.00

38.00

37.00

36.00

35.00

34.00

33.00

32.00

31.00

30.00

29.00

28.00

26.00

23.00

21.00

holland unit code

1=R 2=A 3=S 4=E 5=C RAW SCORES MCMI-n

MCMI-II

Figure 6.2 again shows group of HSLC classified (S) falling in the upper range

compulsive.

198

Table 6.2

Correlation Coefficients of MCMIII Compulsive Sub-test (MCMICOMP)

and MCMI-II Validity Scales

Disclosure (MCMIDIS), Desirability (MCMIDESI), and Debasement (MCMIDEB)

MCMIDIS

MCMIDESI

MCMIDEB

MCMICOMP

MCMIDIS 1.0000 (163) P = . .1961 (163) P=.012 .6588

( 163 ) P= .000 -.1433 ( 163 ) P=.068

MCMIDESI .1961 ( 163 ) P= .012 1.0000 (163) P =

-.0863 ( 163 ) P= .273 .4037

( 163 ) P=.000

MCMIDEB .6588 ( 163 ) P= .000 -.863 ( 163 ) P= .273 1.0000 (163) .P = -.2244 ( 163 ) P= .004

MCMICOMP -.1433 ( 163 ) P= .068 .4037

( 163 ) P= .000 -.2244 ( 163 ) P= .004 1.0000 (163) P = .

Table 6.2 demonstrates any correlation between the MCMI-II compulsive scale and

MCMI-II validity scale, MCMI-II disclosure scale, and MCMI-II debasement scale.

199

Table 6.3

Principal Component Analysis to Find the Factors Factor Analysis

Analysis number

Extraction

1 List wise deletion of

1 for analysis 1,

cases with missing values

Principal Components Analysis (PC)

Initial Statistics

Variables MCMIADVO MCMIAGGA MCMIALCO MCMIANTI MCMIANX MCMIBDLI MCMIBPMA MCMICOMP MCMIDEB MCMIDEL MCMIDEP MCMIDESI MCMIDIS MCMIDRUG MCMIDYST MCMIHIS MCMMJDE MCMINARC MCMIPAG MCMIPARA MCMISCHZ MCMISCTY MCMISFDE MCMISOMA MCMITHDI PC extracted

Communality 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000 1.00000

4 factors

Factor 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

Eigenvalue 9.77160 3.37993 1.98631 1.61919 .97675 .87649 .84059 .75616 .56508 .53161 .46712 .41390 .37447 .32504 .29945 .26179 .23102 .22192 .21744 .19660 .16758 .15542 .14714 .12005 .09733

PctofVar 39.1 13.5 7.9 6.5 3.9 3.5 3.4 3.0 2.3 2.1 1.9 1.7 1.5 1.3 1.2 1.0 .9 .9 .9 .8 .7 .6 .6 .5 .4

Cum Pet 39.1 52.6 60.6 67.0 70.9 74.4 77.8 80.8 83.1 85.2 87.1 88.7 90.2 91.5 92.7 93.8 94.7 95.6 96.5 97.2 97.9 98.5 99.1 99.6 100.0

Factor Matrix: MCMIADVO .70344 -.48756 -.02372 .0 2383

Table 6.3 measures of the amount of variance that can be explained by a proposed factor.

200

Table 6.4

Variable-Factor Analysis How much variance in each of our items can be explained by the four factors we have produced?

Variables

MCMIAGSA MCMIALCO MCMIANTI MCMIANX MCMIBDLI MCMIBPMA MCMICOMP MCMIDEB MCMIDEL MCMIDEP MCMIDESI MCMIDIS MCMIDRUG MCMIDYST MCMIHIS MCMIMJDE MCMINARC MCMIPAG MCMIPARA MCMISCHZ MCMISCTY MCMISFDE MCMISOMA MCMITHDI

Final Statistics Variable MCMIADVO MCMIAGSA MCMIALCO MCMIANTI MCMIANX MCMIBDLI MCMIBPMA MCMICOMP MCMIDEB

Factor 1 Advoidant

.51303

.59604

.60499

.61665

.77517

.55160 - .23708

.76566

.67586

.22438

.17976

.91089

.72983

.60774

.50430 .76631 .50001 .78723 .63825 .34023 .68642 .73958 .45493 .79610

Communality .73368 .67522 .52114 .64902 .54798 .62920 .53581 .60742 .70564

Factor 2 Aggressive Sadistic

.53124 .11443 .31371

- .39238 .07554 .44153 .26592

- .32729 .21837

-.33197 .62133 .03596 .30849

- .48167 .57587

- .38869 .65882 .00606 .27728

-.44122 -.23829 -.27763

.07195 -.12745

Factor 1 2 3 4

Factor 3 Alcohol

-.32826 -.18025 -.42718 .01867

-.11687 .13226 .59062

-.00586 .28962 .65770 .56648

-.00038 -.28491 .12355 .12286

-.01942 -.10022 -.24038 .25394

-.10903 .21603 .07868 .35124 .113

Eigenvalue 9.77160 3.37993 1.98631 1.61910

91

Factor 4 Antisocial

.14849 -.34683 -.04589 -.11581 -.09457 -.13823 .36285

-.11067 .39208

-.37424 -.13974 .04290

-.22212 -.09974 .46169

-.01931 .27992 .16683 .40098 .46788 .30223

-.19353 -.21754 ,

PctofVar 39.1 13.4 7.9 6.5

t9708

Cum Pet 39.1 52.6 60.6 67.0

Continued

201

MCMIDEL MCMIDEP MCMIDESI MCMIDIS MCMIDRUG MCMIDYST MCMIHIS MCMIMJDE MCMINARC MCMIPAG MCMIPARA MCMISCHZ MCMISCTY MCMISFDE MCMISOMA MCMITHDI MCMIDEB MCMIDEL MCMIDEP MCMIDESI MCMIDIS MCMIDRUG MCMIDYST MCMIHIS MCMIMJDE MCMINARC MCMIPAG MCMIPARA MCMISCHZ MCMISCTY MCMISFDE MCMISOMA MCMITHDI

.74208

.73317

.75880

.83285

.75833

.62657

.81419

.73906

.77245

.70538

.70951

.54123

.66597

.66770

.38283

.70183

.70564

.74208

.73317

.75880

.83285

.75833

.62657

.81419

.73906

.77245

.70538

.70951

.54123

.66597

.66770

.38283

.70183

Table 6.4 demonstrates the "loading" on each of the factors.

APPENDIX - K

Table 8.1 MCMI-II Severe Personality Pathology and any Significant

Relationship with the HSLC

Figure 8.1 MCMHI Anxiety Scale

203

Table 8.1 Multiple Regression




Variable (s) Entered on Step Number 1... .MCMIANX (Anxiety Disorder)

Clinical Syndrome subtests - Somatoform (MCMISOMS), Bipolar

Manic(MCMIBPMA),

Dysthymia (MCMIDYST), Alcohol/ Drugs (MCMIALCO)

Multiple R

.18229


Regression

Residual

F = 5.43074

R Square

.03323

DF

1

158

Adjusted R Square

.02711

Sum of Squares

8.25340

240.12160

Signif F = .0210

Standard Error

1.23278

Mean of Squares

8.25340

1.51976

Variables in the Equation Variable

MCMIANX (Constant)

B

-.008849 3.220828

SEB

.003797

.200499

Beta

-.182290

T

-2.330 16.064

Sig T

.0210

.0000 Variables not in the Equation

Variable Beta In Partial Min Toler .SigX MCMISOMA .016484 -.016154 .928549 -.202 .8398 MCMIBPMA .015004 .014909 .954517 .187 .8520 MCMIDYST .168498 .119564 .486781 1.508 .1333 MCMIALCO .004026 .003866 .891477 .048 .9614 Table 8.1 reports if there is any significant relationship between subtests of the MCMI-II Clinical Syndromes and the HSLC. The Clinical Syndrome subtest for anxiety of the MCMI-II was the first predictor variable when calculating with the stepwise forward regression. Final Statistics

204

Figure 8.1 indicates that all the HSLC have some low-level anxiety, but not

extremely high for any individual classified group of inmates.

Figure 8.1 - MCMI-II Anxiety Scale

a

%

I e t

d f s o r d 6 r

12h

10©-

80-

io-

40-

20-

o-

m c

B

D

a a a u

0

a

S a D 0

& a

8

D 0

a

1

D

a D

a a

D

a

a

a

Q

2

a

a

i B 9 a o

1 a

a I 0

g

B

a

3

D

a

a

0 B

0 8 n

B

0

• B D

4

a 0

: a

0

I

0

5 6

holland unit code

l=R 2=A 3=S 4=E 5=C

Figure 8,1 indicates that all the HSLC have some low-level anxiety, but not

extremely high for any individual classified group of inmates.

205

APPENDIX - L

Table 9.1

The MCMI-II Severe Subtests and any Significant Relationship with the HSLC

206

Table 9.1

The MCMI-II Severe Syndrome subtests and any significant relationship with the HSLC

Multiple Regression




Variable (s) Entered on Step Number 1... .MCMITHDI(Thought Disorder)

Clinical Syndrome subtests - Thought Disorder (MCMITHDO), Major Depression

(MCMIMJDE), Delusional Disorder (MCMIDEL)

Multiple R

.16001


Regression

Residual

F = 4.15139

R Square

.02560

DF

1

158

Adjusted R Square

.01943

Sum of Squares

6.35889

242.01611

Signif F = .0433

Standard Error

1.23764

Mean of Squares

6.35889

1.53175

Variable

MCMITHDO (Constant)

B

-.010760 3.436553


.005281

.321533

Beta

-.160006

T

-2.037 10.688

Sig T

.0433

.0000

Variable MCMIMJDE MCMIDEL

Beta In -.073679 .124531

Variables not in the Equation Partial .054468 .096041

Min Toler .532515 .579561

T .683 1.209

Sig T .4953 .2285

207

APPENDIX-M

Parti

Table 10.1 CASI in Predicting the CASI Subtest Scales within the HSLC.

Figure 10.1 CASI Subtest Scale Relationship with HSLS

Part II

Table 10.2 CASI Significant Subtest Scale -2

Figure 10.2 CASI Subtest Scale

208

Table 10.1

CASI in Predicting the CASI Subtest Scales within the HSLC Tested Inmates

Multiple Regression




Variable (s) Entered on Step Number 1... Job Satisfaction (CASIJOBS)

Career Worries (CASIWRR), Dominant Style (CASIDOMS), Family Commitment (CASIFAMC), Geographical Barriers (CASIGEBA), Interpersonal Abuse (CASINPER), Risk Taking Style (CASIRIST), Work Involvement (CASIWKI), Skill Development (CASISKDE)

Multiple R

.16593


Regression

Residual

F = 4.69980

R Square

.02753

DF

1

168

Adjusted R Square

.02167

Sum of Squares

7.06603

249.57683

Sig. F = .0316

Standard Error

1.22616

Mean of Squares

1.50347

1.50347

Variable

CASIJOBS (Constant)

B

.021723 1.591002

Variables in SEB

.010020

.575395

the Equation Beta

.165929

T

2.168 2.765

Sig T

.0316

.0063

Variable CASICAWO CASIDOMS CASIFAMC CASIGEBA CASINPER CASIRIST CASIWKI CASISKDE

Beta In .078462 .149934

-.047290 .019224 .030974 .053272 .033242

-.022564


-.046041 .019449 .000315 .053970 .033385

-.022151

Min Toler .896308 .999936 .921809 .995388 .920943 .998094 .980850 .937213

T .970

1.976 -.592 .250 .004 .694 .492

-.285

Sig T .3333 .0498 .5546 .8030 .9968 .4885 .6684 .7763

209

Figure 10.1

CASI Subtest Scale

a?

J 0 b

$

a t * i s a c t t 0 n

W i

TO

GO-

50-

40-

30

m

a a

a

D • n

a

a a G a

a a a a a o

Q

i . - _

a

a

a

a a

0 0

•0

s

O

a

i

o a a o

o n 0 o a

©

D • a a o G a o D 0 a a n a

D a o a

a u

p

a

a

a

P

D

D

0 0 a a a 0 D a 0 a a a a

a a

a

p

1 • —

£3 D

0

a D

0

•

a a

0 a

0

i;

6

hoiiand unit code

1= R 2 = A 3 = S 4 = E 5 = C

Figure 10.1 scatter graph reports a significant relationship between the CASI

subtest scale job satisfaction and the HSLC classified inmates and finds that many are

satisfied with their jobs

210

Table 10.2

Multiple Regression




Variable (s) Entered on Step Number 2... .Dominate Style (CASIDOMS)

Multiple R

.22363


Regression

Residual

F = 4.34315

R Square

.05001

DF

2

165

Adjusted R Square

.03850

Sum of Squares

12.83506

243.80779

Sig. F = .0145

Standard Error

1.21558

Mean of Squares

6.47762

1.47762

Variables in the Equation

Variable CASIDOMS CASIJOBS

(Constant)

B

.042054

.021880

.275662

SEB

.021283

.009934

.876654

Beta

.149934

.167132

T

1.976 2.203

.314

Sig T

.0498

.0290

.7536

Variable CASICAWO CASIFAMC CASIGEBA CASINPER CASIRIST CASIWKI CASISKDE

Beta In -.159133 -.036153 .038918 .030974 .050889 .061828

-.116653

Variables not in the Equation Partial .143537

-.035519 .039515 .029946 .052155

.061842 -.103297

Min Toler .772904 .916960 .979363 .888014 .997840 .950413 .744906

T 1.857 -.455 .506 .384 .669 .793

-1.330

S igT .0650 .6496 .6132 .7017 .5045 .4286 .1854

Table 10.2 demonstrates a significant relationship of the CASI subtest scale dominant

style in the HSLC inmate group

211

CASI Subtest Scald Figure 10.2

e 10 0 1

hot f and unit code

1=R 2=A 3=S 4=E 5=C

Figure 10.2 scatter graph illustrates the significant relationship of the CASI subtest scale

dominant style in the tested inmate population. The classified inmates have a dominant

style, but it does not differ significantly over any specific HSLC.

APPENDIX-N

Table 11.1 The data for Quality and Quantity of Work in the

population tested will identify the HSLC

Figure 11.1 The quality for all HSLC inmates was equal at though out each

code.

213

Table 11.1

Illustrates the data for Quality and Quantity of Work within the HSLC.

Multiple Regression




Variable (s) Entered on Step Number 1... .Quality of Work (AN)

AN= Quality of Work

Multiple R

.17171


Regression

Residual

F = 5.07323

AM= Quantity of Work

R Square

.02984

DF

1

167

Adjusted R Sq.

.02367

Sum of Squares

7.66383

252.27700

Signif F = .0256

Standard Error

1.22908

Mean of Squares

7.66383

1.51064

F = 5.07323 Variables in the Equation

Signif F = .0256

Variable

AN (Constant)

B

.382512 2.308179


.169826

.242292

Beta

.171706

T

2.252 9.526

Sig T

.0256

.0000

Variable AM

Beta In -.025228

Variables not in the Equation Partial

-.019287 Min Toler

.56761 T

-.249 S igT .8040

Table 11.1 -A significant relationship between the quality of work within the HSLC

inmate group.

Quality of Work

3.5

3.01

* 2.S-U a I j 2.0-t y

r w 1.(H ° o r k .sj . , _____^ , 1

0 1 2 3 4 5 6 hofland unit cods

1=R 2=A 3-S 4=E 5=C

Quality of Work Scale 1.0 (No job or low skill job) 2.0 (Semi-skilled jobs) 3.0 (Skilledjobs)

Figure 11.1 indicates that the quality for all HSLC inmates was equal at though out each

code.

215

APPENDIX-0

Table 12.1 The Individual CASI Subtest Scales and Quality of Work

Figure 12.1 Quality of Work

Figure 12.2 CASI Subtest Scales and Job Satisfaction

Table 12.1

The individual CASI Subtest scales and Quality of Work

ultiple Regression


Equation Number 1 Dependent Variable .... Quality of Work (AN)

Block Number 1. Method: Stepwise Criteria Pin .0500 Pout. 1000

Variable (s) Entered on Step Number 1... Job Satisfaction (JOBSATR)

Career Worries (CASICAWO), Dominant Style (CASIDOMS), Family Commitment (CASIFAMC), Geographical Barriers (CASIGEBA), Interpersonal Abuse (CASINPER), Risk Taking Style (CASIRIST), Skill Development (CASISKDE), Work Involvement (CASIWKI)

Multiple R

.22524


Regression

Residual

F = 11.93253

R Square

.05073

DF

1

166

Adjusted R Square

.04501

Sum of Squares

2.63317

49.27159

Sig. F = .0007

Standard Error

.54481

Mean of Squares

2.63317

.29628

Variable

CASUOBS (Constant)

B

.013261

.558407


.004452

.255660

Beta

.225235

T

2.978 2.184

Sig T

.0033

.0304

Variable CASICAWO CASIDOMD CASIFAMC CASIGEBA CASINPER CASIRIST

Beta In .051335 .076163

-.095965 -.119869 -.056060

.122780


-.094566 -.122746 -.055217

.125898

Min Toler .999924 .999936 .921809 .995388 .920943 .998094

•

T .678

1.007 -1.220 -1.589

-.710 1.603

S igT .4989 .3153 .2241 .1140 .4785 .1050

Continued

217

CASIWKI CASISKDE

-.036346 .068222

-.036946 .067788

980850 .937213

-.475 .873

.6355 .3841

End Block Number 1 PIN = .050 Limits reached

Table 12.1 demonstrates any correlation CASI subtest scales and Quality of Work.

218

Figure 12.1

Quality of Work

CASI Subtest Scales

3.5i

3.0-

** 2.5 U a ( I 2-0-t y

15-0 f

w to-0 r k J

"

0

1

a

o n a G c L

t

3 n o

C B O O O C B =, C D

3 a a 3 a n o o a c G a a o Q c a s ij

• — 1 r

n n ~<i n

a o r. a a a t: '_

r; a .n n n D a n r

t

LI

.*! n o

20 30 40 50 60 70

job satisaction

Figure 12.1 indicates the inmates are satisfied with their jobs even with low skilled jobs.

219

Figure 12.2

CASI Subtest Scale

Job Satisfaction

8§

Wi

i ml Q

S 50" a t

s a c I 3©-

.5 1.0 15 2.0 2.5 3.0 3.5

qualify of wotte

1.0 = No or low skill jobs 2.0 =Semi-skilled jobs 3.0 = Skilled Jobs

Figure 12.2 indicates that the quality of work can predict job satisfaction. The inmates

as a group have low quality of work and are satisfied with their jobs.

220

APPENDIX - P

Table 13.1

221

Table 13.1

Illustrates the data of the Quality and Quantity of Work

and Grade Level with the HSLC.

Multiple Regression




AL = Grade Level AM = Quantity of Work AN = Quality of Work

Variable (s) Entered on Step Number 1... .Quality of Work (AN)

Multiple R

.20871


Regression

Residual

F = 5.60165

R Square

.04356

DF

1

167

Adjusted R Square

.03578

Sum of Squares

237.58927

5216.93873

Signif F = .0195

Standard Error

6.51261

Mean of Squares

237.58927

42.41414

Variable

AM (Constant)

B

1.822227 2.308179


.769918 1.412962

Beta

.208706

T

2.367 26.453

Sig T

.0195

.0000

Variable AL AN

Beta In .038997

-.032777

Variables not in the Equation Partial

.035124 -.023699

Min Toler .775923 .500002

T .388

-.262

S igT .6985 .7939

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