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I University

This is to certify that the
dissertation entitled

RELATIONSHIP BETWEEN DEMOGRAPHICS, SERVICES
AND EMPLOYMENT OUTCOME AMONG YOUTH WITH
PSYCHIATRIC DISABILITIES IN THE STATE-FEDERAL

REHABILITATION PROGRAM

presented by
Grace Chidinma Ugwuezi Ukasoanya

has been accepted towards fulﬁllment
of the requirements for the

PhD degree in CEPSE

 

 

 

{LAM

Major Professo'r’s Signature

Qua—AV 1", 2°04

Date

 

MSU is an Afﬁnnative ActiorVEquaI Opportunity Institution

 

— ---n-o-n-----u--I-o-—-.-- -—.—.—.—.--.---.--.----A-~---.-u-

RELATIONSHIP BETWEEN DEMOGRAPHICS, SERVICES AND EMPLOYMENT
OUTCOME AMONG YOUTH WITH PSYCHIATRIC DISABILITIES IN THE
STATE-FEDERAL REHABILITATION PROGRAM

By

Grace Chidinma Ugwuezi Ukasoanya

A DISSERTATION

Submitted to
Michigan State University
in partial fulﬁllment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Counseling, Educational Psychology.
and Special Education

2006

18'

 

ABSTRACT
RELATIONSHIP BETWEEN DEMOGRAPHICS, SERVICES AND EMPLOYMENT

OUTCOME AMONG YOUTH WITH PSYCHIATRIC DISABILITIES IN THE
STATE-FEDERAL REHABILITATION PROGRAM

By J

 

 

Grace Chidinma Ugwuezi Ukasoanya I
There is limited information regarding the vocational rehabilitation (VR) services
provided through the state-federal system to youth VR consumers with psychiatric i
disabilities, their personal background characteristics, and how these impact vocational I

rehabilitation outcomes. The purposes of this study were to: (1) examine personal
background characteristics and types of VR services, (2) model the relationships of these
factors to employment outcome, and (3) assess the influence of secondary psychiatric
disability on employment outcomes among youth VR consumers in the state-federal VR
system. The study sample was youth with primary and secondary disabilities whose cases
were closed during the federal fiscal year 2004 (FY October, 2003 to September 30,
2004). These consumers were either closed successfully or unsuccessfully.

The dependent variable was employment outcome with two levels: (1) successful
employment closure in status 26, and (2) unsuccessful employment closure in status 28.
The ﬁndings indicated that numerous VR service variables were important in explaining
differences in youth VR consumers’ outcomes. In addition, with the exception of gender,
the personal background characteristics of these youth were signiﬁcant explanatory

variables. Secondary psychiatric disability was found to have significant impacts on

employment outcomes. Future research may help to clarify the mechanisms through
which these factors impact employment outcome, and identify additional factors that

could account for differences in employment outcomes of youth VR consumers with

psychiatric disabilities.

 

 

‘5
I U..—

Dedicated with love to my husband Bernard, who has always believed in me. Thank you
for your consistent support and encouragement through so much. To my children
Nwanne, Nne, Kern, and Cindy for their consistent love and support through our long

journey. David, you came to bring the laughter needed for the celebration!

ACKNOWLEDGEMENTS

I would like to thank my academic adviser, Dr. Michael Leahy, for his guidance.
encouragement, and support in completing this research study. I will always be grateful
for your ﬁrm support which motivated me to stand again after I discovered that I could
not access the data needed to support my initial research. Studying under you has given
me the opportunity to become a better scholar, researcher and professional.

I am also thankful to Dr. Kosciulek for his ideas, statistical insights and overall
teaching through this study. Thank you Dr. Maiers for your patience, kind offer of your

time and expertise as I worked through this study. Your statistical insights made the

research process easier. I am grateful to Dr. Crewe for your willingness to work with me.

Thank you for your gracious patience and consideration.
I want to acknowledge special people whose friendship held this work together

through my roughest days. Thank you Ron and Anita for your untiring support and

friendship. Thank you Ron for your willingness to switch roles from being a proof reader,

an intercessor, to a counselor. Thank you Pastor John and Beth, Jeff and Nikky, and Scott

for always supporting with Godly encouragement, laughter and prayers. Thank you Dr.
Hussein for helping me to get to the ﬁnal stage of this project. I appreciated your kind
professional advice. Dr. Chinwe, you are an amazing friend. Thanks for your never-
ending support.

Becky and Dave, I will ever remain grateful to you. You made our existence in

East Lansing a big fun and we always felt like it was home with your family

 

Mama, you deserve a big thank you for this journey. But my tear drops today
speak greater than my words would have. Mama, I will try to keep the ideals. Keep
smiling in God’s presence for I will not let you down. To my siblings Christie, Joan, Ech
and Darlie who stood by me all the way, I say thank you. I owe a debt of gratitude to my
husband Bernard and children who wondered when Mom will ever be done with .
schooling. Thank you for always communicating to me that you always knew that I will
get there.

To my almighty God: You remain Supreme over all my life.

vi

 

 

TABLE OF CONTENTS

LIST OF TABLES ..................................................................................
LIST OF FIGURES...................I .............................................................
CHAPTER 1
INTRODUCTION .................................................................................. 1
Statement ofthe Problem................ ....................................................................... 1
Purpose of the Study ........................................................................... 5
Signiﬁcance of the Problem .................................................................... 5
Research Questions ............................................................................. 9
Assumptions .................................................................................... 1 0
Limitations ...................................................................................... 10
Deﬁnition of Terms ........................................................................... 12
CHAPTER 2
REVIEW OF THE LITERATURE .............................................................. 15
Youth and DlsabllltleSIS
Youth with Psychiatric Disabilities. . . . . . . . . .. .............................................................. 18
Mental Illness and Employment ............................................................................ 23
Factors Associated With Employment Outcomes ......................................... 27
Secondary Disability and Employment Outcomes ........................................ 38
Impact of Secondary Disability .............................................................. 46
CHAPTER 3
METHODOLOGY ................................................................................. 56
Research Design ................................................................................ 57
Research Population ........................................................................... 58
Variables ......................................................................................... 59

vii

 

Data Collection and Procedures ............................................................... 61

Data Analysis ................................................................................... 63
CHAPTER 4
Results ............................................................................................ 70

Review ofMethodology...............................................................................7l

Research Question One76

Research Question Two ........................................................................ 82
Research Question Three ....................................................................... 94
CHAPTER 5
Discussion ....................................................................................... 98
Findings ....................................................................................... 99
Limitations ........................................................................................... 108
Implications ..................................................................................... 1 09
Conclusion ......................................................................................... l 14
APPENDICES ..................................................................................... 1 15
REFERENCES ..................................................................................... 122

viii

 

 

LIST OF TABLES

Table Page
1. Hosmer-Lemeshow Goodness-of-ﬁt Statistics ...................................... 75

2. Frequency and Percentage of Services Provided
and Employment Outcome ............................................................. 79

3. Receipt of VR Services and Employment Outcome ................................. 80
4. Summary of Logistic Regression Analysis for
Services Predicting Employment Outcome Controlling for

Demographics. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81

5. Frequency and Percentage of Source of Primary
Psychiatric Disabilities and Employment Outcome ................................. 84

6. Frequency and Percentage of Race and Employment
Outcome ................................................................................... 86

7. Frequency and Percentage of Public Support Received and
Employment Outcome .................................................................. 88

8. Frequency and Percentage of Education Level
Employment Outcome .................................................................. 90

9. Summary of Logistic Regression for Personal Background
Characteristics and Employment Outcome ........................................... 91

10. Frequency and Percentage of Secondary Psychiatric Disability
and Employment Outcome ........................................................... 96

11. Summary of Logistic Regression Analysis for Impact of
Secondary Psychiatric Disabilities ................................................... 97

ix

 

 

LIST OF FIGURES

1. Deviance Residual for Research Questions One and Two ...................... 120

2. Deviance Residuals for Research Question Three .............................. 121

CHAPTER 1
INTRODUCTION

In order to improve the state-federal vocational rehabilitation (VR) service
program, there is need “to understand the individual, agency, and service variables that
affect performance, as well as the potential interactions between these variables”
(Bruyere et al. 2002 p. 62). Individuals with psychiatric disabilities have continued to
experience higher unsuccessful employment outcomes than other disability groups in the
state-federal VR system (Rutman, I994; Rutman, 1992). Speciﬁcally, the vocational
rehabilitation literature has observed that people with physical disabilities in the state-
federal VR program experience three times more successful closures compared to
individuals with psychiatric disabilities (Marshak, Bostic, & Turton, 1990). This situation
draws attention to a need to expand opportunities that will enhance successful
employment outcomes among this population within the state-federal VR program.

Rehabilitation professionals, practitioners and consumers are in agreement
regarding the need to understand the speciﬁc factors which could account for the high
unsuccessful closure trend among people with psychiatric disabilities (Rutman, 1994;
Buell & Anthony, 1975). An important step to understanding these factors will involve
simultaneously exploring the relationships among speciﬁc rehabilitation services,
personal background characteristics, and employment outcomes.

The importance of focusing such a study on youth populations with psychiatric
disabilities is highlighted by research reports which have noted that the rates of disability
among these youth is increasing (Secondary Conditions Proceedings, 1999). Youth has

been deﬁned in various ways in rehabilitation programs and research depending on the

 

purpose of programs and/or research. In the Transition-Post School Outcomes research
ﬁmded by the Social Security Administration (2000), youth was deﬁned as individuals
between the ages of 12 and 24. The Ofﬁce of Special Education and Rehabilitative
Services (OSERS) deﬁned transition age youth as individuals between the ages of 18 and
25. The VR Longitudinal Study (1999) deﬁned transition youth to include individuals
who are 25 years old or younger. However, for the purpose of this study, the deﬁnition of
youth will be consistent with the RSA-91 1 deﬁnition and will consist of individuals
between the ages of 12.99 to 25.99.

Research reports observe that youth comprise 13.5% of the total state-federal VR
case-load (Hayward & Schmidt-Davis, 2000). Kosciulek and Perkins (2005) observed
that the post-school outcomes for youth with disabilities remain poor despite advances in
education, disability rights policy and increased funding of programs that impact youth.
They indicate that the poor post-school outcomes are reﬂected in continuing dependence
on federal income assistance, high unemployment, and poor community integration.

Despite disability rights policies aimed at enhancing independence and
community integration for youth with disabilities, research indicates that an increasing
number of individuals in this population apply for and stay in the federal income
assistance program such as Supplemental Security Income (881) and Social Security
Disability Insurance (SSDI) each year. Social Security Administration (1999) has noted
more than a hundred percent increase in the proportion of youth recipients of federal
income assistance between 1999 and 2000. Only a minute percentage of this population
leaves the program to return to work (Ross, 1996). Hennesy (1997) noted that almost half

of the individuals on these income assistance programs stop working and depend

completely on the assistance. Regardless of these numbers, studies have observed that
vocational training increases the likelihood that youth with disabilities will not stop work
or remain in the income assistance rolls (Dykacz, 1998).

The rehabilitation literature is consistent regarding the high unemployment rate
among youth with psychiatric disabilities. Compared with youth with other disabilities,
youth with psychiatric disabilities have four times as high an unemployment rate
(Vander-Stoep, Beresford, Weiss, McKnight, Cauce, & Cohen, 2000; Vander Stoep,
1997; Ireys, Salkever, Kolodner, & Bijur, 1996; Vander-Stoep, Taub, Holcomb, 1993;
Se, Duchnowski, Kutash, 1992). Connected to this high risk of unemployment outcomes
among these youth, both community and treatment-based studies have observed that
these youth also have a higher risk of adjudicated delinquency, reliance on public
assistance, and a lack of community support (Stoep et al., 2000). At the same time, the
literature is consistent regarding the fact that youth with psychiatric disabilities share a
similar preference for satisfying work at a liveable wage. In addition, researchers have
observed that employment is a critical determinant of recovery, empowerment and
mitigation of crime among this population (Gioia & Brekke, 2003; Baron & Salzer, 2000;
Becker, Drake, & F arabaugh, 1996).

However, despite the signiﬁcance of poor post-school outcomes among youth
with disabilities, there are few studies documenting the factors which account for these
persistent poor outcomes. More speciﬁcally, there is minimal research, which has
focused on the interrelationships among psychiatric disabilities, vocational rehabilitation
services, personal background factors, and employment outcomes among youth.

Irrespective of the increased emphasis on enhancing improved employment outcomes

among people with psychiatric disabilities, rehabilitation research using the RSA-911

 

data has not focused on determining the speciﬁc factors that could predict employment
outcomes among youth with psychiatric disabilities (Lehman, Clark, Bullis, Rinkin, &
Castellanos, 2002; Halpem, 1985; Wills, 1984).

Current rehabilitation literature has noted the need for research direction
regarding the provision of appropriate services, supports, and post-high school assistance
to meet the educational and career development needs of youth with disabilities. 14‘
Speciﬁcally, there is need for research that will contribute information regarding what
combination of educational and vocational services could promote successful

employment outcomes for youth with disabilities (Kosciulek & Perkins, 2005; Simon,

 

2002). Conducting a study targeted in these areas will contribute to the identiﬁcation of:
(l) the most cost effective vocational rehabilitation methods for serving people with
psychiatric disabilities (Bruyere, Erickson, Vanloy et al. 2002), (2) factors that account
for employment outcome differences among recipients of vocational rehabilitation
services (Walker, 2002), and, (3) the inﬂuence of the interactions among service and
person variables in determining the employment outcome among this population. This
study is designed to contribute a unique and needed youth-with-psychiatric-disabilities-
speciﬁc perspective to existing knowledge in each of these areas. To address the critical
need for current and useful data on the transition to work of youth with disabilities, the
purpose of this study is to identify factors that are useful in distinguishing between
successful and unsuccessful employment outcomes among youth VR consumers with

psychiatric disabilities.

Purpose of Study

The purpose of this study is to identify factors that differentiate successful and
unsuccessful employment outcomes among youth VR consumers with psychiatric
disabilities. Using data on youth VR consumers with psychiatric disabilities drawn from
the ﬁscal year 2004 Rehabilitation Services Administration 911 data ﬁle, logistic
regression will provide data regarding the relationships among psychiatric disabilities,
vocational rehabilitation services, personal background factors, and employment
outcomes among youth in the state-federal VR program. Findings from this study will
provide data useful for guiding future VR research and practice related to the
employment of youth with psychiatric disabilities.

Signiﬁcance of the Problem

The persistent high rate of unemployment among individuals with psychiatric
disabilities highlights the need to determine the factors that predict this trend. There is a
research consensus that the majority of the populations with mental illness desire to work
(Rumrill & Roessler, 1999; Marshak et al., 1990). Such individuals can recover
signiﬁcantly and hold meaningful work when provided with appropriate support.
However, the pervasive negative inﬂuence of mental illness on the employment outcomes
of people in the state-federal VR system has become well established in rehabilitation
literature in the past two decades (Spence, 2000). Despite the acquisition of background
work preparations in some instances, and having eligibility status in the state-federal VR
program, rehabilitation literature is consistent regarding the persistent high rate of
unsuccessful closures among people with psychiatric illness (Anthony, Cohen, & F arhas,

1990; Marshak, 1990). Overall, the employment rate among people with psychiatric

 

disabilities has remained below 30% in the past two decades (Mac-Donald-Wilson,
Rogers, & Anthony, 2001).

When this trend is considered in terms of rehabilitation burden and cost, research
has noted that people with psychiatric disabilities are the second most frequent category
of people served by the state-federal VR system in every state (Garske, 2003; Stoddard,
Jans, Ripples & Kraus, 1998). In addition, they comprise about 20% of the case-load
(Mac-Donald-Wilson, Rogers, & Anthony, 2001 ); have the lowest successful closure
rates compared to other groups with disabilities (Marshak, Bostick & Turton, 1990;
Anthony, 1994); have a low recovery rate, and account for a large portion of private
disability claims and costs (Salkever, Goldman, Purushothaman et al., 2000).

Most of these data represent the trend among the general population of people
with psychiatric disabilities. Limited research has been focused on the unique experiences
of youth populations with psychiatric disabilities who are VR service recipients. The few
studies that have focused on youth have noted a high unemployment rate, which tends to
keep them in the social security assistance system for as long as 27 years after high
school (Davis & Vander Stoep, 1997). In these studies, this high unemployment trend has
mostly been accounted for by the linear inﬂuence of speciﬁc demographic factors or
rehabilitation service programs on the employment outcomes of youth (Davis & Vander-
Stoep, 1997).

There is a strong research suggestion that addressing the inﬂuence of background
factors would maximize the potential of VR programs in improving employment
outcomes among people with psychiatric disabilities. In addition, rehabilitation policy,

research and practice will be improved if more attention is given to the personal

background contexts of rehabilitation service recipients (Wentling, Waight, 1999; Yelin&
Cistemas, 1997; Rogers, Anthony, Cohen, & Davies, 1997; Anthony, 1994). The
importance of these background factors is highlighted by the signiﬁcant inﬂuence which
they exert on employment outcome in general populations of people with and/or without
disabilities (Baron & Salzer, 2002). In addition, investigating the inﬂuence of these
factors is capable of contributing meaningful information to rehabilitation research and
practice regarding the most appropriate VR interventions for various subgroups of people
with psychiatric disabilities (Wewiorski & Fabian, 2004).

Currently, there is sparse literature regarding the extent to which VR services
inﬂuence the employment outcomes of youth with psychiatric disabilities. To date, little
empirical research has been conducted which describes how youth with psychiatric
disabilities fare in the VR system. Very little research attention has been focused on the
VR service factors and processes that predict employment outcomes among these youth.
In the absence of such information, VR service delivery system may run the risk of
continuing with services that only add to the cost of vocational rehabilitation, without
contributing to positive employment outcomes for youth with psychiatric disabilities.
Studies will make stronger contributions to rehabilitation research and practice when they
are designed to simultaneously explore how the interactions among personal background
factors, and VR services, inﬂuence employment outcome among youth recipients of VR
services with primary and secondary psychiatric disabilities.

Research has noted the prevalence of secondary mental disabilities among people
with physical disabilities (Hoffman, Manela, & Schiff, 2003; Moore, F iest-Price &

Alston, 2002; Frey, Szalda-Petree & Traci, 2001; Thurer & Rogers, 1984; & Lipowski,

1975). Research studies, which have investigated the prevalence of secondary conditions
among individuals with physical disabilities, have come up with alarming ﬁndings of
high incidence of secondary psychiatric illness among people disabilities (Mitra, Wilber,
Allen & Walker, 2005; Simeonson, McMillen & Huttington, 2002). It has been observed
that secondary psychiatric disabilities hinder successful employment outcomes among
youth with disabilities (Irey, Salkaver, Kldne, Sci, & Bijur, 1996). Rehabilitation research
from the past two decades is consistent about a 40% occurrence of secondary psychiatric
disabilities among individuals with physical disabilities (Kinney & Coyle, 1992; Turner
et al. 1985; Turner & Rogers, 1984). Based on a longitudinal data collected between 1996
and 2000, Mitra et al. (2005), found high prevalence of secondary psychiatric disabilities
across the three phases of a study of adults recruited mainly from independent living
centers. The implication of these ﬁnding for rehabilitation practice includes a need for
rehabilitation professionals to design and deliver services, which target speciﬁc mental
health issues among individuals with disabilities.

At present, there is limited information regarding the prevalence and inﬂuence of
secondary mental illness among youth with disabilities. The nature and scope of
secondary psychiatric disabilities among youth with disabilities has not been adequately
investigated (Ravesloot, Seekins, & Walsh, 1997). Given the pervasive negative
inﬂuence of psychiatric disabilities on employment outcomes of people in the VR
system, it could be assumed that youth with secondary psychiatric disabilities could
experience less successful employment outcomes than those with only physical
disabilities. This gap in our understanding could be ﬁlled by an empirical study, which

emphasizes the nature, distribution and inﬂuence of secondary mental disability on

 

employment outcomes (White, Bransteter, & Seekins, 2000). This study is designed is to
ﬁll this gap by exploring the extent to which secondary psychiatric disabilities could
impact vocational rehabilitation outcomes among youth VR consumers in the state-
federal VR system.

Research Questions

The following research questions will be examined in this study:

 

E|

1. How are the employment outcomes obtained by youth VR consumers with
psychiatric disabilities associated with the vocational rehabilitation services
they receive while controlling for demographic characteristics?
The types of vocational rehabilitation services received are independent/predictor
variables. These services are dichotomously coded as received or not received.
The dependent/criterion variables are employment outcomes. These were treated as
categorical variables with two levels representing closure with an employment and closure
without an employment.
2. How do personal background characteristics of youth VR consumers with psychiatric
disabilities relate to their employment outcomes?
The predictor variables are personal background characteristics including gender,
race/ethnicity, source of impairment and public assistance at application. The criterion
variable is employment outcome. This was treated as a categorical variable with two
levels representing closure with an employment and closure without an employment.
3. How do the employment outcomes obtained by youth VR consumers with secondary
psychiatric disabilities compare to those of youth rehabilitants with no psychiatric

disabilities?

The predictor variable is secondary psychiatric disability while the criterion

variable is employment outcome.
Assumption

A major assumption of this study was that the category of psychiatric disabilities
(mental illness) in the RSA-9ll data adequately represents the DSM-IV category for
psychiatric and psychological disorders. This assumption was tenable given that research
(Arondel & Depoutot, 1998, as cited in Matrone, 2003) has noted that the “RSA-911 data
possess the three characteristics of quality data: comparability of statistics, coherence,
and completeness” (p.10). Consistent with extant rehabilitation research (Wheaton,
2002), this study also assumed that the variables under study (vocational rehabilitation
services, personal background characteristics, and employment outcomes) were
comprehensively and appropriately measured in the RSA-911 database.

Limitations and Delimitations

This present research was limited by the research characteristics typical of
archival data. First, the choice of variables will be limited by what is available in the
dataset (Borg, Gall, & Gall, 1993). Second, the operational deﬁnitions of the variables
under study may not be representative of the wider theoretical or clinical deﬁnitions. The
variables were operationalized consistent with the deﬁnitions obtained in the database.
For instance, the deﬁnition of the categories of psychiatric disability used in this study
was broad and encompassing. The variable ‘depression’ was treated as a homogenous
condition in the database. In the future, researchers may need to consider using a more
limited deﬁnition, perhaps one that distinguishes between different classiﬁcations of

psychiatric disabilities and recognizes different characteristics of these disabilities.

10

 

“I

Third, generalizing the ﬁndings of this study may be limited by inherent coding
errors, omissions, and human factor limitations in the recording of data. This study did
not consider the backgrounds of the counselors who recorded the data. It did not account
for the impact of the quality of VR services provided on employment outcomes or the
quality of VR service providers. In addition, it will not attempt any explanations on how
the variables under study are causally linked.

Fourth, this study did not account for the inﬂuence of a number of factors which
could possibly predict successful employment outcomes among youth with psychiatric
disabilities. For example, investigating the inﬂuence of factors such as duration and
intensity of services, access to medical and psychological services, consumer
motivational factors, and the working alliance between consumer and the service
providers will provide a more comprehensive view of the factors that may predict
vocational outcome in the state—federal VR program. These potential predicting factors
were not accounted for in this study. In addition, this study delimits the deﬁnition of
employment outcomes to successful or unsuccessful. Other measures of employment
outcomes were not accounted for. Although the source of referral for youth with
disabilities in the VR program may explain the types of services they receive, this factor
was outside the scope of this study. In addition, the investigation of the inﬂuence of
secondary psychiatric disability on the employment outcomes of youth with disabilities in
the state-federal VR program was exploratory. The sample size of youth with secondary
psychiatric disabilities was 4,006. Although small sample sizes increase standard errors
and negatively impact signiﬁcance testing, this sample size was moderate and therefore

should not be a concern.

ll

 

Deﬁnition of Terms
To avoid possible misunderstanding or misinterpretation, the following
deﬁnitions were used in this study:
M: Youth has been deﬁned in various ways depending on the purpose of programs

and/or research. In the Transition-Post School Outcomes research funded by the Social

 

Security Administration (2000), youth was deﬁned as individuals between the ages of 12 .
and 24. The Ofﬁce of Special Education and rehabilitative Services (OSERS) deﬁned
transition age youth as individuals between the ages of 18 and 25. The VR Longitudinal
Study (1999) deﬁned transition youth to include individuals who are 25 years old or
younger. However, for the purpose of this study, the deﬁnition of youth was consistent
with the RSA-9ll deﬁnition and comprised individuals between the ages of 12.99 to
25.99.

Psychiatric Disabilities: This refers to a health condition characterized by alterations in
thinking, mood, or behavior, or a combination of all three linked to distress and/or
impaired functioning in a person (US Surgeon General, 1999). According to the
American Psychological Association (APA, 1994), the three major categories of
psychiatric disability are schizophrenia, mood disorders, and anxiety disorders. For the
purpose of this study, psychiatric disabilities included depression, schizophrenia, eating
disorder, anxiety, personality disorders, and mental illness not listed elsewhere.
Vocation_al Rehabilitation Services: This refers to three categories of services funded by
the state-federal vocational rehabilitation agencies for the purpose of promoting

consumer employment at closure (RSA, 1988). The services included: assessments,

12

diagnosis/treatment of impairments, vocational rehabilitation counseling and guidance,
college/university training, occupational/vocational training, on-the-job training, job
readiness training, disability related augmentative skills training, miscellaneous training,
job search assistance, job placement assistance, on-the-job supports, transportation
services, maintenance, technical assistance, and ‘other’ services.

Personal background variables: These refer to consumer demographic characteristics
which were recorded at intake. In this study, this included variables that have been found
to have the probability of making signiﬁcant impact on employment outcome of people
with mental illness. These will include race, gender, and public assistance and education
at application.

Public Assistance: In the state-federal VR program, this could encompass different cash
assistance determined by individual’s age, disability, employment or post employment
status. In this study this was deﬁned as Supplemental Security Income (SSI), Social
Security Disability Insurance (SSDI) and Temporary Assistance for Needy Families
(TANF) at application.

Employment Outcome: Although this has many categories in the state-federal VR
program, in this study, this was deﬁned as successful employment or unsuccessful
employment outcome. Successful employment outcome was deﬁned as the outcome
which is achieved when an individual has developed vocational plan, received necessary
goods and services and has been able to maintain employment for at least 90 (J ans,
Stoddard, Kraus, 2004). Unsuccessful employment outcome will denote the outcome that
is achieved when an individual has developed a vocational plan, but has been unable to

complete vocational plan, achieve employment or maintain employment for up to at least

13

90 days.
Physical Disabilities: This included a range of disabilities listed in the RSA-911 database
such as deafness, hearing loss, general physical debilitation, other physical, mobility and
orthopedic, manipulation dexterity, both mobility and manipulation dexterity, and other
orthopedic.
Summary

This study was designed to investigate the inter-relationships among mental
illness, VR services, personal background factors, and employment outcomes among
youth consumers in the state-federal VR system. The central objective was to determine
how the employment outcomes of youth VR consumers with psychiatric disabilities, as
measured by successfully or unsuccessfully employed at closure, are inﬂuenced by their

personal background characteristics and the VR services they receive.

14

CHAPTER 2
REVIEW OF THE LITERATURE

The purpose of this study is to identify factors that differentiate successful and
unsuccessful employment outcomes among youth vocational rehabilitation (VR)
consumers with psychiatric disabilities. Speciﬁcally, the study evaluated the relationships
between the types of VR services provided to youth with psychiatric disabilities in the
state-federal VR program and their employment outcomes. In addition, it evaluated what
socio-demographic characteristics of these youth are associated with their employment
outcomes. Findings from this study will provide data useful for guiding future VR
research and practice related to the employment of youth with psychiatric disabilities.

This chapter describes literature relevant to the research purposes of this study.
This review of literature is presented in three sections: (1) Youth with disabilities, (2)
Mental illness, vocational rehabilitation and employment outcomes among people with
psychiatric disabilities and (3) Secondary disability and employment outcomes among
people with disabilities. At the end of each section, the relevance of the literature to the
current research was discussed.

Youth and Disabilities
According to the Research Triangle Institute (2000), youth with disabilities represent

about 13.5% of all VR consumers and approximately 135,391 persons. Recent research is
in agreement regarding the persistent poor post school outcome for the majority of youth
with disabilities despite advances in education, disability rights policy, the support of
federal mandates and increased funding of programs and initiatives that impact all youth

(Kosciulek & Perkins, 2005, p.3: Gerry, 2002). A 1989 National Longitudinal Transition

15

Study (N LTS) which investigated the post school outcome of youth with disabilities
observed that apart from youth with learning disabilities and speech impairments, youth
with visual, orthopedic, and multiple disabilities had poor employment outcomes
compared to youth without disabilities. Blackorby and Wagner (1996) carried out a
research study on the trends in employment, wages, post secondary education and
residential independence among youth with disabilities during the ﬁrst ﬁve years after
high school. The ﬁndings indicated that the employment outcomes of youth with
disabilities lagged signiﬁcantly behind those of youth in the general population. This is
consistent with prior research which has noted persistent low employment rates for youth
with disabilities after high school (Afﬂeck et al., 1990; D’Amico, 1991).

These comparisons between the employment outcomes of youth with disabilities and
youth in the general population indicate the challenges facing young people with
disabilities. The need to be responsive to these challenges is highlighted by research
observation that employment remains the transition goal most often chosen by youth with
disabilities (Kosciulek & Perkins, 2005). Consequently, this highlights the need for
rehabilitation researchers and practitioners alike to be responsive to the vocational
rehabilitation needs of youth with disabilities. However, current studies which have
studied post-school outcome trends among youth with disabilities have not made any
speciﬁc observations regarding youth with psychiatric disabilities.

Kosciulek and Perkins (2005) have described the post-school adjustment outcomes of
youth with disabilities as characterized by limited salable work skills, low income,
underemployment, and unemployment. Generally, research has attributed this trend to

poor preparation of these youth for life beyond school. Speciﬁcally, research has

16

 

observed that majority of these youth exhibit poor decision making and self advocacy
skills (Chadsky-Ruisch & O’Reilly, 1991; Mithuag, Martin, Agran, & Rusch, 1988). The
result is that these youth are unable to pursue successful transition goals and thereby
continue to be dependent on their families, parents, and public ﬁnancial assistance. This
is in contrast with various legislative mandates affecting youth with disabilities. The
majority of these pieces of legislation were enacted with the purpose of providing easier
access to rehabilitation services thereby enhancing successful post—school outcomes for
youth with disabilities.

Several pieces of legislation have been enacted over the past 25 years to exact
changes in how children and youth with disabilities are educated, prepared for and
involved in meaningful employment. Such legislation includes Education for all
Handicapped Children Act (PL. 94-142), the Carl D. Perkins Vocational Education
Amendments of 1984 (PL. 98-524), Americans with Disabilities Act of 1990 ( PL. 101-
476), the Individuals with Disabilities Education Act(IDEA) Amendments of 1992 (PL.
101-239), the School-to-Work Opportunities Act of 1994 (PL. 103-239), the 1998
Rehabilitation Act Amendments (PL. 105-166), the Workforce Investment Act of 1998
(PL. 105-220), and the Ticket to Work and Work Incentives Improvement Act(P.L. 106-
170) ( Social Security Administration, 2000,p.3). Among these pieces of federal
legislation, the IDEA and the Rehabilitation Amendments of 1992 have mostly targeted
the improvement of educational and vocational opportunities for youth with disabilities.

The IDEA requires the development of an Individualized Education Program
(IEP) which details long term vocational goals and the speciﬁc services needed to

achieve these goals. These goals are carried over to transition service planning, when the

17

 

individual turns 16 (SSA, 2000). The Rehabilitation Amendments of 1992 were intended
to provide easy access to rehabilitation services by bringing together rehabilitation and
education services. The mandate includes the development of an Individualized Written
Rehabilitation Plan (IWRP) for students with disabilities. The goal is to ensure that youth
with disabilities who need help entering the rehabilitation system receive those services
in a timely manner (Senate report 102-357, pp.34).
Vocational Challenges Experienced by Youth with Psychiatric Disabilities

Employment remains a fundamental objective for the majority of individuals with
psychiatric disabilities (Rogers, Walsh, Masotta, & Danley, 1991). Speciﬁcally,
Kosciulek and Perkins (2005) observed that employment is the most often chosen
transition goal among youth with disabilities. In addition to ﬁnancial incentives,
researchers have asserted that the importance of work for individuals with psychiatric
disabilities include assisting in recovery by proving opportunity for social contacts
(Noble, et al. 2001), prevention of recurring hospitalization and reduction of dependence
on public income assistance (Noble, 1998).

Research in the area of employment outcomes among individuals with
psychiatric disabilities has mostly focused on identifying the predictors of employment
for this population. This current focus may be informed by the fact that there is presently
a consensus that psychiatric disabilities compromise employment outcomes for
individuals with psychiatric disabilities. Tsang et al. (2000), in their meta-study on
employment outcomes for individuals with psychiatric disabilities since the ‘80’s
identiﬁed social skills, prior functioning and, work history as valid predictors. Moreover,

psychiatric symptomatology was found to be a signiﬁcant predictor of employment

18

outcome. Ten studies out of the 35 studies reviewed identiﬁed psychiatric
symptomatology as signiﬁcant predictors of employment outcome among individuals
with psychiatric disabilities. The ﬁndings of this study did not explain the typicality or
uniqueness of outcomes among individuals with speciﬁc psychiatric diagnoses such as
anxiety disorders, depressive and other mood disorders, schizophrenia and psychotic
disorders.

Among youth with psychiatric disabilities, presenting a review on how depression
could impact vocational outcome would provide a representative overview of the typical
challenges experienced by youth with psychiatric disabilities in the VR program.
Sammons and Schmidt (2001) have asserted that depression is a common co-existing
disability among individuals diagnosed with other mental disorder. In addition current
rehabilitation research has observed that not less than 30% of individuals who acquire
physical disabilities experience post-injury depression (Heinraich & Tate, 1996;
Kosciulek & Perkins, 2005).

Clinical Descriptions of Depression

Depression has been categorized in different ways to include depressed mood,
depressive syndromes. and depressive disorders. Depressive disorders have been grouped
into two, including major depressive disorder (MDD) and Dysthymia (DD). While MDD
refers to single or recurrent episodes of depression, DD refer to chronic mood disturbance
(McCullough, 2000). According to the Canadian Community Health perspective, based
on the DSM-IV criteria, depressive disorder diagnosis criteria include: a) two weeks or
longer of depressed mood or loss of interest or pleasure and at least ﬁve symptoms

associated with depression which represent a change in function; b) symptoms which

19

cause clinically signiﬁcant distress or impairment in social, occupational or other
important areas of functioning; c) occupational or other symptoms that are not due to the
direct physiological effects of a substance or to a general medical condition; and, d)
symptoms that are not better accounted for by bereavement, symptoms that last more
than two months or symptoms which are characterized by a marked functional
impairment, preoccupation with worthlessness, suicidal ideation or psychomotor
retardation. These conditions are consistent with the World Mental health (WMH) 2000
version of the Composite International Diagnostic Interview (CID). Generally, these
challenges associated with depressive disorders are pervasive, affecting many domains of
daily functioning.

Socially, research evidence is consistent regarding social skills deﬁcits among
individuals with depression. Social skills often encompass development in three essential
domains of behavior: perceptual, cognitive, and performance (Anthony, Ledley &
Heimberg, 2005). Perceptually, due to the poor concentration, withdrawing and negative
oriented behavior associated with depressive symptom, individuals with depressive
symptoms exhibit poor skills in selecting appropriate cues within a social interaction
situation (Anthony et al., 2005). In addition, they also demonstrate difﬁculties in
processing and interpreting these cues outside of their frame of persistent negative
reference. Consequently, the individuals usually develop cyclical negative schema, which
reinforce repeated social negative responses. With this frame of mind, the individual with
depressive disorder continues to focus on himself, while avoiding any social interaction.
It could therefore be justiﬁed to expect that such persistent social negative responses at a

work environment could impede adjustment and job retention.

20

Closely related to this, individuals with depressive disorders tend to have
negative attributions due to the negative schema activated during depression. Flory et al.
(2000) asserted that this activated negative schema, in addition to associated self-focused
tendencies mediate social skill outcomes for this population. Speciﬁcally, research
evidence indicates that individuals with depressive disorders experience threat to self—
worth, lack the capacity to feel enjoyment, exhibit less initiation and less responsiveness
in social interaction, and general difﬁculties in psychosocial ﬁrnctioning (Letters: Dual
Diagnosis, 2001, pp. 7 & 8).These attributes inﬂuence the social behavior of individuals
with DD and to a large extent reduce the social support network available to them.

Understanding the implications of compromised social skills to vocational
rehabilitation outcome is critical. Social skills in vocational rehabilitation for instance
have been categorized into job securing and job-retaining social skills. These categories
of social skills have been associated with overall employability traits, such as
development of supportive social networks, coping with day to day stress, ﬁnding and
holding a job, manifest adjustment and ability to communicate. Studies in this area
indicate that consumers with psychiatric disabilities as well as rehabilitation service
providers are in agreement regarding the importance of social competence for successful
employment (Tsang, 1996 p.24).

More research is currently associating cognitive functioning with different
rehabilitation outcomes (Tsang, 1996). For instance, while social cognition is
increasingly being associated with vocational rehabilitation outcome, research remains in
agreement regarding the impact of neuropsychological impairment on academic and

vocational rehabilitation. There seems to be a consensus regarding the pervasive impact

21

 

of cognitive impairment caused by either depressive disorder and or other psychiatric
disabilities associated with them. However, generalizations based on some of these
ﬁndings are limited by lack of uniformity in the deﬁnition and measurement of cognitive
functioning. Moreover, most of the measures have been designed for measuring

‘general’ psychiatric disabilities. Given the unique manifestations of associated
disabilities among different disability populations, it may be more beneﬁcial to focus on
understanding the factors associated with outcomes among subgroups of populations such
as youth with depression, anxiety disorders, and other mood disorders, schizophrenia and
psychotic disorders in the VR system.

Airaksinen et al. (2004) have observed that different types of depression exert
different effects on memory functioning. In a study investigating cognitive functioning in
younger adults diagnosed with depression, the researchers found that depressive disorders
are associated with episodic memory impairments. Speciﬁcally, their ﬁndings indicate
that major depression and mixed anxiety depressive disorders were associated with
signiﬁcant memory dysfunction in memory tests. Dysthymia was associated with speed
in accomplishing tasks. Although the tests used in the study were not very sensitive, the
study found that individuals with minor depression did not experience any memory
impairments. Moreover, their study did not indicate any verbal ﬂuency impairments.
However, the psychometric prOperties of the instrument used (too long for individuals
with DD), the demographic characteristics of the sample used (high income, highly
educated females), small sample size and high drop out rate of the subjects suggest

caution when making inferences to general populations. Given the place of memory in

22

vocational functioning, there is need for a study which will investigate the impacts of
speciﬁc psychiatric disorders among individuals in the VR program.
Mental Illness, Vocational Rehabilitation and Employment Outcome

This section describes literature relevant to the ﬁrst purpose of this study: the
association between vocational rehabilitation services and employment outcomes among
youth with mental illness. To accomplish this, this section was organized into three sub-
sections: (1) mental health and employment, (2) trends in the associations between VR
services and employment outcomes among people with mental illness, and (3) factors
associated with employment outcomes among people with mental illness in VR. This
section was concluded with a summary of the major ﬁndings and gaps, which suggest
needs for further empirical inquiry. At the end of each sub-section, the relevance of the
literature to the proposed study is discussed.

Mental Health and Employment

Rehabilitation research has consistently acknowledged the relationship between
mental health and work. Work has been observed as a critical component of mental
health (Hoffman, Manela, & Schiff, 2003; Hoge, Toboni, Messer, Bell, Amoroso, &
Orman, 2005), even as mental health has been noted as a critical determinant of work
(Anthony, 1994). This literature was reviewed ﬁrst in order to establish the importance
of the intersections of mental health and employment outcomes. The discussion was
centered on the philosophies of: a) recovery, and, (b) empowerment.
Recovery
The increasing signiﬁcance of recovery in psychiatric rehabilitation research and practice

has resulted in numerous studies reporting claims about its crucial inﬂuence on

23

vocational outcome. The predominant belief that people with psychiatric disabilities
could not recover and lead normal lives has been challenged. Currently, it is believed that
people with psychiatric disabilities have good chances of recovery, accompanied by
indicators such as ﬁnding and retaining meaningful work, maintaining positive social
relationships and participating fully in the community (US Department of Health and
Human Services, 1999). Among all these indicators, work has been noted as a critical
component of recovery (Moxley & Finch, 2003). Research has observed that work
enhances recovery through improved opportunities for positive relationship, decrease of
symptoms and increased well being (Baron, 1995).

The recovery-oriented philosophy of VR service delivery is evident in the 1992
Amendments to the Rehabilitation Act. Based on this piece of legislation, ‘employability’
was changed to ‘employment’. Rehabilitation counselors were mandated to remove
selectivity on eligibility based on type and severity of disability. Thus, people with severe
disabilities became a priority for rehabilitation service (Rubin & Roessler, 2001). In order
to accomplish this, there was need for constant ‘re-engineering’ of the service delivery
system in order to accommodate more people with severe disabilities (Young, 2001).

Vocational rehabilitation effectiveness has been associated with stable mental
health of people with psychiatric disabilities (Anthony et al.1993; Rutman, 1994). The
vocational outcomes, which consumers achieve in VR, are typically related to their
‘clinical gains’ (Ams & Linney, 1993, p.64). Furthermore, within the recovery-service-
delivery paradigm, a major expected outcome is the improvement of the over all well-
being of the individual. Focusing on the unique needs of the individual is central to the

success of this process. Thus, achieving positive employment outcome requires a

24

‘coalescence of mental health and vocational rehabilitation services’. Recent research
has acknowledged the increase in the coalescence of mental health and vocational
rehabilitation in VR service provision to people with psychiatric disabilities in recent
years (Moxley & Finch, 2003).

In short, the individual with mental illness is supported through the process of
getting and retaining a job by a combination of vocational rehabilitation and mental
health supports. Within this model, the rehabilitation service process is more person-
centered than system centered. Therefore, the recovery paradigm of disability suggests a
need to look beyond the physical characteristics of disability to the complex interplay
among physical, psychological, and environmental factors’ (Crimando,2003), in order to
empower the consumer with disabilities in the VR process.

Although the time-limited nature and limited funding for VR may hinder the full
implementation of a recovery-oriented philosophy of service delivery, it is clear that the
current VR system is giving increased attention to the centrality of mental health in
determining the employment outcomes for people with disabilities in the VR system
(Moxley & Finch, 2003). However, the lack of empirical evidence regarding the extent to
which this model of service delivery has enhanced the employment outcomes for people
with psychiatric disabilities precludes this needed conclusion. Yet, there is a consensus
among rehabilitation researchers, practitioners and consumers that mental health support
should be an integral component of vocational rehabilitation.

Empowerment
For the individual with mental illness, the concept of ‘recovery’ is embedded

within the philosophy of empowerment. Empowerment for the consumer with disability

25

has been deﬁned as a psychological sense of personal control, involvement, inﬂuence,
and awareness of options in one’s life (Anthony, 2004). An empowered consumer with
mental illness takes active part in matters that affect his or her life through developed
mastery over his/her symptoms, internal drives and demands of the environment (Spence,
2000; Bolton & Brookings, 1996). Literature is consistent regarding the role of work in
the empowerment of individuals with mental illness. Research has described the domains
of empowerment achieved through employment to include: integration into the
community, provision of social support, and increase in self worth (O’Day & Killen,
2002), thereby enhancing the self-esteem and personal purpose of the individuals (US
Dept of Human Services, 1999; Bell & Lysakrr, 1997).

For youths with psychiatric disability, empowerment and recovery will include:
(1) learning new skills; (2) developing social relationships; (3) making meaningﬁrl
contributions to the community; (4) and making economic gains which could directly or
indirectly impact other positive life outcomes (Carter & Lunsford, 2005; Blackorby &
Wagner 2000p.63). In order to enhance their recovery and promote employment
outcomes among youth with psychiatric disabilities, there is a need to design a
comprehensive transition package with a focus on providing an ongoing array of mental
health and vocational rehabilitation services and supports for them (Hughes & Carter,
2000 p.64). The design and delivery of such comprehensive package need to be informed
by research which identiﬁes how speciﬁc mental disabilities are related to employment

outcomes among people with disabilities.

26

Factors Associated with Employment Outcomes among People with
Psychiatric Disabilities in the VR system

The relationships between mental illness and employment outcomes have
attracted a vast empirical attention in the past two decades. Most of the studies have
focused on identifying the major factors, which are considered signiﬁcant for the
employment outcomes of people with mental illness in the VR system. However,
understanding how these factors interact with VR and employment outcomes among
people with psychiatric disabilities is critical to the design and delivery of effective VR
services. This section will present only literature that is related to the factors that have
consistently been associated with employment outcomes in state-federal VR program
research, especially, using the RSA-9ll data. These will include: (a) clinical symptoms,
(b) VR services, (c) Background factors, and ((1) public assistance received.
Clinical Symptoms

The impact of clinical symptoms on the rehabilitation outcome of people with
psychiatric disabilities has been widely explored. Research ﬁndings identify
complications associated with psychiatric disability symptoms to include limitations in
social competence, personal and symptom management (Corrigan, Rao & Lam, 1999);
challenging emotional, behavioral, cognitive functioning (Fischler & Bond, 1999); low
motivation (Braitman et al. 1995); lack of self awareness (Fabian 1999); and
inappropriate values, attitudes and aspirations regarding work (Rutman, 1994). These
could have negative impacts on the employment outcomes of people with psychiatric
disabilities, even when they possess the basic competencies required for speciﬁc work

(Garske, 1999).

27

Garske (2003) observed that work functions within the overall well-being of the
individual. Consistent with this, Moxley & Finch (2003), observed that ‘employment as
an outcome cannot stand apart from the psychosocial functioning of the individual.
Therefore, rehabilitation counselors need to be conversant in ancillary services such as
health, mental health, and social services, while mental health professionals need to take
the employment needs of recipients seriously’ (p.6). Although some studies have
concluded that clinical symptoms have predictive inﬂuence on employment outcomes
among people with psychiatric disabilities, the bulk of the research data (Mac-Donald-
Wilson, Rogers & Anthony, 2001; Anthony, 1994; Anthony et al., 1990), suggest that
symptoms alone do not predict employment outcomes among this population.

In a review of indicators of vocational outcome among people with mental illness,
Anthony (1994) found no associations between patterns of psychiatric symptoms and
vocational outcome. This is consistent with previous research, which found no signiﬁcant
relationship between psychiatric clinical symptoms and future vocational outcome
(Anthony, Cohen, & Farkas, 1990). These researchers assert that rather than direct
inﬂuence, the complications associated with clinical symptoms have higher probabilities
of impacting employment outcome.

Although, some studies have found a signiﬁcant relationship between symptoms
and employment outcomes among people with psychiatric disabilities, there is an
empirical consensus that these associations are mediated by other personal factors. For
example, in a study of 90 persons in Supported Employment (SE) programs, Fabian
(1992) found that race mediated the relationship between clinical symptoms and outcome

in the VR system. Another study which examined the relationships between psychiatric

28

symptoms and work performance found a minimal association between race and
vocational outcome, mediated by poor role functioning (Massel et al. 1990). Care needs
to be taken while generalizing these ﬁndings given that the subjects for the study were
‘vocationally ready’ clients with clear vocational goals.

Overall, the pattern of ﬁndings from symptom-outcome studies have concluded:
(a) no relationship (e.g MacDonald-Wilson, Rogers, & Anthony, 2001); (b) modest
relationships (Anthony, 1994); and (c) signiﬁcant relationship between symptoms and
outcome (Tsang, Lam & Leung, 2000). Based on a review of literature on psychiatric
symptoms and vocational outcome since the 80’s, (Tsang et al, 2000), there is evidence
that this lack of agreement is accounted for by the unpredictable course of psychiatric
symptoms due to exacerbations, remissions and recurrence (Bell & Lysker, 1995); hidden
heterogeneity of psychiatric symptoms which challenge the reliability of assessment
measures (Harding 1994; ); and few instruments which focus on emotional functioning
related to quality of work (MacDonald-Wilson et al., 2001). Apart from these clinically
related explanations, there is evidence that most of the study designs were correlational
and used only small samples. There is therefore need for research which will investigate
larger samples for greater power and evaluate effect sizes.

Vocational Rehabilitation Services

 

There is a signiﬁcant amount of literature on the inﬂuence of VR services on the
employment outcomes of people with disabilities, which have implications for the VR of
people with mental illness. Most of these works have emphasized the inﬂuence of the

structure of the VR services, the differential impacts of different clusters of VR services,

29

attitude of the VR service providers, the characteristics of people with mental illness and
the design and delivery of VR services in determining employment outcome.

A recent study (Fabian, 1999) observed that the low employment trend among
people with psychiatric disabilities could be accounted for by the deﬁciencies inherent in
the VR services provided for them. There is an indication that the structure of the VR
service delivery may not be suitable for the unique conditions of people with psychiatric
disabilities. For example, the time limited nature of VR service provision is not suitable
for the long-term nature of psychiatric illness. Individuals who come into the VR are
judged ‘rehabilitated’ and their functions are judged ‘restored’ if they are able to keep a
job for 90 days from the date of closure. While the conditions of this population are long
term and recurrent due to the episodic nature of the disability, the VR service design is
inﬂexible, rigidly goal oriented and time limited based on statuses and steps (Garske,
2003). This makes it difﬁcult to respond effectively to the cyclical nature of psychiatric
disability. In response to this, research has recommended: (a) the provision of
individualized services tailored to the unique needs of people with psychiatric disabilities
(Schalock, 2004); (b) re-evaluation of VR service design and outcome expectation to
accommodate the ongoing nature of their needs (Garske, 20003; Hu & Jerrel ,1998); (c)
long term services that will accommodate relapses and slow progress (Bond & Boyer,
1990); and, ((1) access to comprehensive, ongoing services and supports which will
enhance their chances in the job market.

The inﬂuences of different combinations of VR services have been well noted.
Finch and Wheaton (1999) investigated the relationship between VR services and

employment outcomes among people with psychiatric disabilities. The ﬁndings from

30

their study indicated ﬁve major VR service clusters including: (a) counseling, (b)
diagnostic services, (c) direct placement, (d) total job assistance, and (e) comprehensive
services. Using a chi-square analysis, their study found a moderate relationship between
the VR service clusters and employment outcomes among people with psychiatric
disabilities. Psychosocial services such as counseling and diagnostic services had
signiﬁcant positive effects on wages.

Availability of psychosocial services and supports has been identiﬁed as a crucial
factor in the entry and retention of employment among people with psychiatric disability
(Rosenthal and Olsheki, 1999). From a recovery oriented service perspective,
psychosocial supports are needed in order to provide consumers with skills and
knowledge needed to manage their symptoms and control the effects from associated
complications. Psychiatric rehabilitation research is in agreement regarding the need to
provide appropriate and comprehensive psychosocial support and services in order to
take care of some of the major consequences of psychiatric illness including: (1)
impairment, (2) dysfunction, (3) disability, and (4) disadvantage (Blackorby & Wagner
2000; Carter & Lunsford, 2005). From a psychiatric rehabilitation perspective, the goal of
psychosocial support is to ensure that the individual with psychiatric disability can
accomplish the physical, emotional, social, and intellectual skills necessary to live, learn,
and work in a community (Brommet, 2005, p.20).

Other studies have emphasized the inﬂuence of speciﬁc models of vocational
rehabilitation in predicting vocational outcome among people with psychiatric
disabilities. Rehabilitation research has consistently attested to the superior efﬁcacy of

Supported Employment (SE) in enhancing the employment outcomes of people with

31

 

 

psychiatric disabilities (Boardman, Grove, Perkins, & Shepherd, 2003; Corrigan &
Boyle, 2003; Quimby, Drake, & Becker, 2001; Bond, Becker, Drake & Vogler, 1997).
The supported employment (SE) model reﬂects the shift from the traditional ‘train-place’
to the contemporary ‘place train’ rehabilitation philosophy, in which the consumer is
directly placed in a competitive job, with a provision of ongoing support and supervision
(Rubin & Roessler, 2001). Empirical research has variously investigated the efﬁcacy of
the SE among people with psychiatric disabilities.

Crowther, Marshall and Bond (2001) examined 11 randomized controlled
rehabilitation trials. The ﬁndings from their study indicated that supported employment
(SE) was more effective than the pre-vocational practice of ‘train-place’ in enhancing the
chances of people with psychiatric disabilities to get and keep competitive employment.
This ﬁnding is consistent with Bond et al.’s (2001) assertion that SE is an evidence—based
service, which enhances the vocational goals of people with mental illness to a great
extent. Attributing the efﬁcacy of SE to its structure, research has observed that SE
moves people out of clinical set-ups to where they receive consistent ongoing supports
which cover obtaining employment, meeting the demands of the employment, and
resolving challenges which could otherwise act as barriers to work success (Drake, 1998;
Corrigan & Boyle, 2003).

Although the demonstrated efﬁcacy of supported employment (SE) has been
acknowledged by disability advocates, policy makers, and rehabilitation providers,
contemporary models of the SE seem to be more cumbersome than enhancing. An
example of this contemporary model is the Individualized Placement Support (IPS),

which demands a rapid job search, matching on the job skill development, clinical

32

 

treatment and vocational services. Quimby et al. (2001) used an ethnographic research
design to evaluate approaches to vocational services for persons with severe psychiatric
disabilities who could be described as ‘vocationally not-ready’. The study compared the
traditional VR service with the IPS model of SE. The ﬁndings from this study indicate
that the IPS produced more results in terms of achieving successful employment
outcomes, at a big cost. This cost include: (a) the complexity of implementing it, (b)
confusion of roles (e.g. the risk of viewing employers as quasi mental health
professionals), (c) balancing employment with clinical treatment consecutively, (d) skill
deﬁcits for both clinical and technical team, and (e) challenges related to achieving
collaboration between VR staff and clinical team. Based on this, it could be expected that
people who receive the SE services stand better chances of achieving successful
employment outcome, although at a higher ﬁnancial cost.

Other studies have investigated the inﬂuences of VR services on employment
outcomes in terms of the professional characteristics of VR providers. Given that the
unique needs of people with psychiatric disabilities may make the traditional VR service
provision method non-effective, it is logical to assume that the people with psychiatric
disabilities will achieve successﬁrl employment outcome in VR to the extent that the VR
provider is knowledgeable about their needs and the demands of their conditions. Vash
(1981) observed that the unique needs of people with psychiatric disabilities are not being
met as a result of inadequate mental health training among VR counselors. Consistent
with this Chan, Leahy, Chan, Hillburger, et al. (1998) found a need for the extension of
rehabilitation counselor training to include training on the unique needs, demands and

management procedures for people with mental illness.

33

 

 

M

Although much rehabilitation research has investigated the relationships between
background characteristics of people with psychiatric disabilities and their vocational
outcomes, most of the attention has been given to the predictive role of race/ethnicity.
Racial disparities in VR program acceptance and outcome among VR consumers have
been widely noted. A pioneer research on the inﬂuence of race on VR outcome found a
racial disparity in VR outcome (Atkins &Wright, 1980). Consistent with this most of the
research on this issue from the 80’s through early 90’s ( Feist Price, 1995; Dziekan &
Okocha, 1993; Herbert & Marinez, 1992;) conﬁrmed the trend regarding the fact that
European Americans were more likely to be accepted into VR and achieve successful
competitive employment outcome than other minority races. However, research from the
past decade has provided mixed empirical evidence regarding racial disparities in
acceptance and successful outcome in VR. This current body of research has produced
two major categories of evidence: (a) No difference by race, and (b) difference by race,
mediated by other factors. Both of these categories of evidence have been accounted for
by differences in research methodology.

Research from the mid 90’s is consistent regarding the role of research method
and statistical design in accounting for most of racial disparities in VR service receipt and
outcome of the early 80’s. While most of the studies have focused only on two groups
(European Americans and African Americans), others have used statistical methods that
are vulnerable to Type 11 error. For example, most of the studies used chi-square
statistical tool to analyze very large samples. According to Glass and Hopkins (1996),

this could result in ﬁnding signiﬁcance in the absence of any practical signiﬁcance.

34

Moreover, chi-square would not allow for the controlling of other possible confounding
factors.

The difference that statistical methods could make in rehabilitation outcome
trends has been demonstrated by research. Using a symmetrical hypothesis of
homogeneity, Wheaton (1995) found no racial disparities in acceptance rates between
African Americans and European Americans. In a related study, Peterson’s (1996)
ﬁndings indicated a similar result. His ﬁndings indicated that compared with other races, I
both African Americans and European Americans were over-represented in the VR
system. The difference in this result could have been accounted for by different data

analysis methods. Unlike earlier research studies on this topic, Peterson used a within

 

group approach instead of a between group approach in his data analysis.

Other studies have found that race inﬂuence VR outcome through other factors. In
a study designed to investigate the relationships between race, service factors and
rehabilitation outcomes among people with severe mental retardation in the VR system,
Moore, Feist-Price and Alston (2002) found that race and job placement are signiﬁcantly
related to closure status. European Americans were more likely to achieve successﬁrl
closure success compared to African Americans. This ﬁnding is consistent with those
from other recent studies (e. g Moore, 2001a, Moore 2001b). However, the explanations
given for this trend makes this ﬁnding important to rehabilitation research and practice.
Based on the ﬁndings, Moore et al. (2002) propounded a ‘severity-race correlative
theory’, which states that: “As disability status becomes more severe, the counselor’s
level of cultural sensitivity and lack of cultural competencies have a greater possibility of

negatively inﬂuencing the quality of services to consumers who are racial and ethnic

35

 

members of underrepresented groups”(P.165).. However, no causal explanations should
be attempted, given that most of these studies used retrospective data, since they were
based on the RSA-911 archival data. In summary, there is need to investigate race beyond
ethnicity (Warren, Cavenaugh, Giesen, 2004). For the purpose of producing valid
evidence, a study on the inﬂuence of race on VR outcome would need to control for other
inﬂuential background factors, which include gender, source of impairment, race, and
public assistance received (Rogers, Anthony, Cohen, & Davies, 1997; Anthony, 1994).
Public Assistance Services

The trends of poor employment outcomes for people with psychiatric disabilities
have been attributed to the disincentives inherent in the state-federal income assistance
program. Contrary to the expectations from recent rehabilitation legislation, disincentives
inherent in the state-federal rehabilitation system have been identiﬁed as one of the
reasons for low employment trends among people with psychiatric disabilities. The
Americans with Disabilities Act —ADA (1990) mandates non-discrimination, equal rights
and barrier removal in order to promote productivity and integration of people with
disabilities (Rubin & Roessler, 2001). Related to this, the Rehabilitation Services
Administration passed the Workforce Investment Act (WIA, 1998), to enhance the
opportunities of people with disabilities to obtain, maintain, and re-enter the job market,
through the elimination of barriers (Rubin & Roessler, 2001).

The Workforce Investment Act (WIA) mandates “the empowerment of
individuals with disabilities to maximize employment, economic self sufﬁciency,
independence and inclusion into the society. . .through. . .respect for the individual dignity,

personal responsibility, self determination and pursuit of meaningful careers based on

36

informed choice of individuals with disabilities ...... and assisting individuals with
disabilities to obtain employment that is consistent with strengths, resources, priorities,
concerns, abilities and capabilities” (RSA-PD 97-04). This legislation provides funding
for individual training, educational and employment services through the state-federal
VR agencies. In addition, cash incentives are provided through social security programs
(SS1 & SSDI) for people with psychiatric disabilities to encourage their employment
(O’Day & Killen, 2002; SSA, 2001). Yet, the disincentives inherent in these services
have attracted considerable research attention.

The SSDI restrict beneﬁciaries from earning beyond a certain dollar amount
($810 at the time of this study), in order to retain their beneﬁts (SSA, 2001). The 881,
require beneﬁciaries to lose double amount of dollars for each dollar they make beyond
their maximum allowed earning. As a result people with psychiatric disabilities risk the
loss of opportunities for career advancement, productivity and experience constant
anxiety over the possibility of losing money, sustenance and medical beneﬁts. In some
instances, applying the guidelines of the income assistance could imply a high risk of
losing the services and supports needed for the management of psychiatric symptoms, if
the individual has to retain a competitive employment (Baron, 1995). However, more
support for re-entry into employment has been provided by the recent passage of the
Ticket to Work legislation. Yet, overall most of the people with psychiatric disabilities in
the VR system continue to receive only minimum entry-level employment below their
potential, and without any career advancement prospects.

Secondary Disability and Outcomes among People with Disabilities

Rehabilitation literature has consistently demonstrated that secondary disabilities

37

 

 

complicate the severity and life outcomes associated with primary disabilities, especially
when they are related to mental health (see, Institute of Medicine, 1991; Gallagher &
Stewart, 1987). It is not surprising that efforts to reduce or prevent the occurrence of
secondary disabilities have intensiﬁed both in health policy and rehabilitation practice in
recent years. The need to investigate the implications of secondary disability on the
disability and rehabilitation process is important because (a) the incidence of secondary
disabilities are increasing; (b) Secondary disabilities tend to affect domains of
ﬁmctioning needed for attaining successful rehabilitation outcomes; and (c) attention and
information on secondary disabilities is emerging at a rapid rate in various health-related

ﬁelds, creating the need for more awareness of this possible ‘silent barrier’ to successful

 

vocational rehabilitation.

As part of this review, extant literature on the trends and impacts of secondary
mental disability on the rehabilitation process and outcome will be included. This section
will present review on the: (a) conceptual descriptions of secondary disability
(deﬁnitions, components and progression); (b) challenges associated with secondary
disability (general disability and rehabilitation burden); (c) secondary disabilities within
changing paradigms of disability (looking beyond the premise of ‘cure’ and ‘closure
status;); ((1) current awareness about the impact of secondary disability; and (e)
conclusions related to major research ﬁndings about secondary conditions that suggest
research attention.

This review will not go into etiology, causes or prevention of secondary disability.
Discussions will be focused on aspects of research that is signiﬁcant to disability

rehabilitation. Given that there is still very limited research on the impact of secondary

38

psychiatric disabilities on vocational rehabilitation outcomes, the discussions will draw
ﬁom the broad literature from other health-related disciplines and apply them in relevant
ways within a disability rehabilitation context. Consistent with rehabilitation literature on
this topic, this review will use the terms ‘secondary conditions’ and ‘secondary
disabilities’ interchangeably (Wallace et al. 1997).

Conceptual Descriptions of Secondary Disability

Secondary disability is viewed as a condition that is causally related to a disabling
condition and could be pathology, impairment, a functional limitation or an additional
disability (Pope & Tarlov, 1991). Speciﬁcally, secondary disability could be a physical,
mental, or psychosocial (Brandt & Pope, 1997; Pope, 1992; Marge, 1988) condition
associated directly or indirectly with a primary disability. There is an agreement in
literature that categorizing a disability as ‘primary’ or ‘secondary’ refers more to the
sequence of occurrence than the magnitude or severity. In some cases, a secondary
disability may become more debilitating than primary disability (Marge, 1988 p.).

A major conceptual proposition is that secondary disability is not necessarily
symptomatic of other primary disabilities. For example, researchers have described
secondary disability as any preventable physical, mental, and/or social disorders resulting
directly or indirectly from initial disabling conditions, from a health promotion
perspective (Kinne, Patrick, & Lochner, 2004; Krause & Bell, 1999; Lollar, 2002;
Wilber, Mitra, Walker, & Allen 2002; Simeonsson, Bailey, Scandling et al. 1999).
Further within the frame of rehabilitation of children with disabilities, Wallace et al.
(1997) asserted that secondary disability may either manifest at the same time with the

primary condition, or later as the physical or mental sequelae of primary disability

39

condition. Generally, secondary conditions across empirical rehabilitation literature
presuppose the existence of a primary disability, without necessarily being a consequence
of it. Yet, irrespective of the pattern of occurrence, recognizing the speciﬁc level in the
disability process where secondary conditions could complicate the rehabilitation process
will demand the knowledge of the basic components of secondary disability.

From a psychosocial perspective, secondary mental conditions have been
described as including deﬁcits in self-concept, social skills, and emotional problems that
an individual with a primary disability is likely to experience (Wilber, Mitra, Walker, &
Allen 2002p.394; HP 2010). These conditions could predispose the individual to develop
more complicating mental health disorders. Consistent with this view, research (Spence,
2000) has also observed that life-changing primary disabilities are vulnerability factors
for the development of mental disorders. Often, these mental disorders hinder positive
adaptation and successful rehabilitation outcome. In corroboration, other research has
directly identiﬁed domains of mental illness including depression, anxiety, insomnia and
substance abuse as secondary conditions experienced by individuals with physical
disabilities (Kinney & Coyle, 1989; Turner & Wood, 1985). These are psychological risk
factors which could make the individual with disability inactive (Castelnuovo-Tedesco,
1981) or limited in needed interpersonal skills, cognition, and coping skills (Garske,
2003). In addition, these individuals could experience deﬁcits in self awareness and
understanding needed in making vocational choices (Fabian, 1999), and demonstrate poor
vocational role functioning (Spence, 2000; Anthony & Blanch, 1987).

From a community integration perspective, components of secondary conditions

have been described to include health-related economic consequences associated with

40

primary disability, limitations in work and social participation, family or community

 

problems (HP2010; Wilber, Mitra, Walker, & Allen 2002p. 394). Research has

categorized these mental-health related deﬁcits in terms of community ﬁmctioning, such

as family, peer and school disabilities (Ezpleta, Keeler, Alaatin, Costello & Adrian,

2001). From a youth-speciﬁc perspective, the components of these secondary mental

disabilities have been described to include lowered self-esteem, problems in adjustment

to life altering conditions, and heightened sense of dependence on family (Simoensson, .
Sturz, McMillen & Huntington, 2002; Kokkonen, 1995).

Although some of these secondary mental health issues may not be directly
related to primary disabilities, they have the propensity to increase the disability burden,
make the youth vulnerable to poor coping choices like substance abuse, and immobilize
them in the vocational rehabilitation process. Yet, the extent to which secondary mental
disabilities could make a difference in the rehabilitation outcomes of youth with
disabilities in the VR program has not been researched. A speciﬁc question needs to be
answered: To what extent will secondary mental disabilities inﬂuence vocational
rehabilitation outcomes measured by employment status at closure among youth with
disabilities in the VR program?

It is important to note that limited empirical attention has been given to the
relationships among primary disability, secondary conditions and rehabilitation outcome.
The interactions between secondary mental disabilities, vocational rehabilitation (VR),
and rehabilitation outcomes among VR consumers have not been speciﬁcally
investigated. There is no known study, which has focused primarily on the associations

among secondary psychiatric disabilities and rehabilitation outcomes among youth in the

41

VR system. In short, the inﬂuence of secondary conditions on VR outcomes among
people with disabilities has been understudied in rehabilitation research. Although there
is an agreement regarding the occurrence of mental health conditions as complications
associated with various disabilities (Mitra, Wilber, Allen, & Walker, 2005), the few
studies, which have investigated these associations among VR consumers, have only
treated secondary mental illness as an incidental research component (Moore, Feist-Price

& Alston 2002). As a result, this research proposes to address these gaps.

Secondary Conditions within Changing Paradigms of Disability

Emerging rehabilitation and health promotion trends in disability research and
practice have highlighted the need to pay closer attention to secondary conditions.
Changing paradigms of disability, which highlight ‘disablement’, ‘ablement’ and
wellness processes rather than ‘disease’ and ‘cure’ processes, underlie these trends. This
section will present an overview of the relevance of the bio-psychosocial and socio-
ecological perspectives to the secondary disability discourse.

The bio-psycho-social model conceptualizes disability as the function of the
interaction between the individual with disabilities and his or her biological, ecological,
social, and/or cultural environment (Dodge & Pettit, 2003; NIDDR, 1999). Within this
framework, the individual has limitations as well as impairments, which may not be
directly related to the disability. The unit of assessment will be the individual’s medical
condition, as well as his or her functioning in his environment. The implication for
vocational rehabilitation includes the need for holistic interventions guided by over all
quality of life and not merely physical functioning. Such holistic intervention would need

to embrace all determinants of individual well-being, and target the prevention of

42

needless impairment and disability (Rimmer, 1999).

This shift is aimed at enhancing successful rehabilitation outcomes through the
promotion of over-all well-being, recovery, empowerment and ongoing functioning of the
individual with disability. It recognizes secondary psychiatric disabilities as possible
barriers to successﬁrl rehabilitation outcome. Integrating this into the rehabilitation
process implies a contextual approach to disability with emphasis on the provision of
ongoing individualized support in order to reduce or remove secondary disabilities
(Thompson, Craig, Schalock, Tasse, Bryant, Hughes et al., 2003; Luckason, Bothwick-
Duffy, Buntnix, Coultier, Craig et al., 2002).

Although vocational rehabilitation has recorded great success in the area of
community-focused intervention, the consistent neglect of secondary mental health needs
of individuals with physical disabilities and the lack of adequate mental health services
for individuals with primary physical disabilities, have been noted (Rimmer, 1999).
Mechanic and Aiken (1987) provided empirical evidence which supports this
observation. In their study of mental needs of individuals with disabilities, they noted
that mild symptoms of depression and schizophrenia often go unrecognized in the
rehabilitation system. This raises a crucial concern that any neglect of the interference of
associated mental illness in physical disability may be increasing the disability burden, in
terms of high rehabilitation cost and poor rehabilitation outcome.

For instance, failure to recognize the inﬂuence of associated depression on the
vocational outcomes of people with disabilities could increase the probability of
unsuccessful employment outcome. It could also increase the individuals’ vulnerability to

substance abuse and negative coping choices. Neglecting this secondary mental illness

43

will be contrary to the holistic focus of the bio-psychosocial model. The Institute of
Medicine (1991) asserts that such neglect could lead to non-comprehensibility in service
provision. The biopsychosocial model therefore advocates comprehensibility in VR
service provision, reﬂected in continuous, coordinated services which will promote
personal well-being, and enhance the psychological functioning of individuals with
disabilities (Milkowitz, 2004).

The socio-ecological framework of disability sees disability as a social construct
which is largely shaped by the environment and focuses on the interaction between
people and their environment. This framework is tied mostly to the enhancement of
equity in public health delivery. Under a socio-ecological model, disability is
conceptualized as a social issue reﬂected as the product of an ongoing person-
environment interaction, and manifested in the dimensions of body functions,
performance activities, and participation over time (Rune, 2002, p.6). Within this
framework, environment is categorized to include products and technology, natural
environment, supports and relationships, attitudes, and services, systems and policies.

According to (Sameroff & Fiense, 2000; Tate & Pledger, 2003) the emphasis of
this framework consists of enhancing the creation of quality rehabilitation interventions
aimed at improving equal opportunity, economic self-sufficiency and ﬁll] integration for
individuals with disabilities. This focus is consistent with Silverstein’s (2000) four major
goals of federal disability policy, which include (1) full participation; (2) independent
living; (3) economic self-sufﬁciency; and (4) equality of opportunity. Meeting these goals
demand embracing the emerging focus on functional limitations, personal well being,

individualized supports, personal competence and recovery in rehabilitation (Schalock,

44

2004; Schalock, Baker, & Crosser, 2002; Simeonson et al, 2002; Block, Balcazaar &
Keys, 2001). By implication, these require the recognition that reduction or removal of
secondary mental disabilities and enhancing functional capabilities and personal well-
being are major steps to enhancing successful outcomes in different domains of
rehabilitation, especially vocational.

Irrespective of the holistic focus of these contemporary disability paradigms, and
the improvements in intervention, planning, coordination of services, career planning and
development, the rehabilitation ﬁeld has not given adequate recognition to the prospect
that an individual with disability has an ongoing vulnerability to develop secondary
mental disabilities. For the most part, the major focus of rehabilitation has remained the
reduction of the impact of primary disability and the restoration of as much function as
possible (Marge, 1988). Individuals who come into vocational rehabilitation are provided
services, for restoration of physical functions and community integration. Success in the
VR program is often judged by outcome status. For example, while status 28 represents
unsuccessful employment outcome, status 26 is the successful employment status, which
reﬂects holding for at least 90 days after closure. Dropping out of the VR system without
successful closure is often explained by demographic disparities or lack of individual
motivation (Brodsky, 1987; Rimmer, 1999; Tucker, 1984). However, there is the question
of whether there a possibility that the health- related factors of secondary mental illness
could inﬂuence ‘readiness’ and ‘motivation’ to an extent that vocational outcome may be
compromised.

The rehabilitation implications of these models include the need for holistic

services, which provides support for the ‘whole’ individual. The beneﬁt of these

45

emerging views is that intervention could now directly target multiple levels of
disabilities in the same individual in order to enhance the rehabilitation of the individual.
In order to devise holistic interventions that speciﬁcally address the complex needs of
people in the VR system, there is need for research, which will speciﬁcally explore the
roles of secondary mental disabilities in the rehabilitation outcomes of individuals with
disabilities.

Further, there is need to move beyond identifying major markers or indicators of
psychosocial adaptation, to investigating the intra-individual processes which could
mediate or moderate the disability experience and the associated adaptation outcomes
(Livneh, 2001). Changing the delivery system to match the needs of individuals will
beneﬁt from an in-depth understanding how secondary psychiatric disabilities could
inﬂuence rehabilitation outcomes. Given the high vulnerability of youth to mental illness
(HP2001), this research will explore the prevalence of secondary psychiatric disabilities
and how they inﬂuence employment outcomes of youth with disabilities in the VR
program.

Impact of Secondary Disability

The impact of secondary disabilities on the outcomes of individuals with
disabilities has attracted a number of empirical attentions in recent years (Anderson,
Lollar, & Meyers, 2000; Lollar, 1994; Pope, 1992; Seekins, White, Ravesloot et al.,
1999). Most of the awareness regarding the impact of secondary disabilities has been
propagated through public health promotion research, and disability policy. This section
of the literature is reviewed ﬁrst in order to establish the importance of secondary

disabilities as reported from different practice and policy perspectives. The scope of the

46

review will be limited to issues that are relevant to disability rehabilitation. Throughout,
the focus of the discourse will be an exploration of the question: Does secondary
disability matter?

Health Promotion Perspective

 

The goal of preventing secondary conditions has recently emerged as a major item
on the public health agenda (Craig et al, 1997) This emphasis is tied to the fulﬁllment of
essential independent living objectives of full inclusion; participation in all aspects of
society; and, maintenance of well-being for people with disabilities (Brooks, 1984).
Within a health promotion perspective, researchers have recognized that secondary
disabilities contribute most of the disability burden (Rimmer, 1999), overlap with
primary disabilities (Wilber et al, 2002), reduce the quality of life among individuals with
disabilities (Simeonsson et al. 2002), and, possibly account for most of the relapse and
lack of motivation in the rehabilitation system . Speciﬁcally, there has been an increase in
calls for research to prevent or reduce the frequency or severity of secondary conditions
since the late 19803 (White & Seekins, 1999). Linking health promotion with policy, the
Institute of Medicine (1991) argued that if the health conditions related to disability and
its antecedents are not addressed coherently at the policy level, it should not be surprising
that current approaches to rehabilitation could be lacking in comprehensibility,
continuity, and coordination.

This public health perspective raises some questions for vocational rehabilitation
research and practice: (I) do some of our consumers have inherent ‘unrecognized’
disabilities, which could hinder successﬁrl vocational outcome in the VR program? Apart

from the traditionally identiﬁed VR service and socio-demographic predictors of

47

vocational rehabilitation outcome, what are some of the intra-individual factors that could
make most of our consumers (especially youth) unresponsive to intervention? Some of
these issues have been addressed in the broader rehabilitation literature in terms of
increased disability burden associated with secondary disabilities, although with no
speciﬁc reference to the federal and state VR context.

There is an emerging recognition that primary disability no longer constitutes the
major primary barrier to inclusion and participation (WHO, 2001). A consensus remains
that secondary conditions complicate both the primary disability experience and
rehabilitation process. Secondary disabilities are known to increase the severity of an
individual’s disability (WHO, 2001). In agreement, Traci (2002) observed that secondary
mental disabilities could impede on the individual’s participation in essential life
activities, even while receiving ‘appropriate’ rehabilitation intervention. Alluding to the
importance of recognizing the impact of secondary disabilities, Wilber et al. (2002)
asserted that the prevalence of these conditions and the stakes of compromised well being
are always likely to be substantial, especially as more people survive traumas and chronic
illness.

Secondary disabilities have been known to contribute to high cost of rehabilitation
of primary disabilities (Rimmer, 1999). Relapse and poor engagement in the
rehabilitation process are common in cases where the inﬂuence of secondary disability
has not been recognized. Research has observed that a signiﬁcant proportion of health
problems and expenditures for people with disabilities could be accounted for by health
complications associated with secondary conditions (Lollar, 1994; Marge, 1988; Pope &

Tarlov, 1991). These conditions have been known to constitute barriers to engagement in

48

the disability rehabilitation process.

For instance, rehabilitation literature has demonstrated an association between
depression and employment outcome (IOM, 1991). This association has been construed
as both direct and indirect. Directly, depression and primary disability could produce a
synergy, which could lead to vocational dysfunction of the individual. Indirectly,
depression as a secondary condition could interfere with an individual’s functioning and
thereby lead to more negative psychological conditions and consequently, poor
vocational outcomes (Krueger, 1981; Moore et al., 2001). In the same way, there is ample
empirical evidence regarding the associations between substance abuse, rehabilitation
engagement and outcome in the vocational rehabilitation process (Donat & Haverkamp,
2004; Drake, Brunette, & McHugo, 2004; Kelley & Benshoff, 1997). Often, the
implications would be unresponsiveness to, and lack of motivation in the traditional
vocational rehabilitation process, especially when services are solely targeted at
restoration of vocational functions.

Research is in agreement regarding the high tolls of secondary conditions in the
areas of functional limitations, and increase in the level of disability experience
(Ravesloot, Seekins, & Walsh, 1997; Pope & Tavlov, 1991; Graitcer & Maynard, 1990).
Kinne et al. (2004) demonstrated the importance of recognizing the rehabilitation barriers
associated with secondary disabilities when they asserted that “the precision of the
‘secondary’ label is less important than the clear rehabilitation challenge which these
substantial disability-related and preventable disparities pose” (P.445). These barriers
could be more severe when the conditions are psychiatric. Following Rimmer’s (1999)

advocacy on health promotion activities, improving rehabilitation outcomes among

49

individuals with disabilities would entail furthering rehabilitation initiatives, to solely
target the prevention or reduction of secondary mental disabilities. Based on the current
review, it is clear that giving attention to secondary mental conditions will suggest some
re-organizations in the disability rehabilitation system. However, this re-organization will
be a justiﬁed application of the bio-psychosocial paradigm (Engel, 1983), which
highlights the provision of holistic services to improve the well being of individuals with
disabilities.
Secondary Disability Trends

Research studies, which have investigated the prevalence of secondary conditions
among individuals with physical disabilities, have come up with alarming ﬁndings of
high incidence of secondary conditions among people disabilities (Mitra et al., 2005;
Simeonsson et al, 2002; Wilber et al, 2002; Seeking et al, 2001). A surveillance report by
Seekins et al. (1990) indicates that people with disabilities experience as much as 14
secondary conditions associated with their primary disabilities. Consistent with this
report, White, Gutierrez and Seekins (1996) noted that about 83% of Independent Living
center (ILC) consumers reported experiencing one or more secondary conditions within
the past few months. In a related study of adults recruited mainly from ILC, based on a
longitudinal data collected between 1996 and 2000, Mitra et al. (2005), found high
prevalence of secondary psychiatric disabilities across the three phases of the study.
Although most of these studies have focused on physical secondary conditions, there
have been frequent reports of the occurrence of secondary mental health conditions
among individuals with disabilities.

Rehabilitation research from the past two decades is consistent about a 40%

50

occurrence of secondary psychiatric disabilities among individuals with physical
disabilities (Kinney & Coyle, 1992; Turner & Rogers, 1988; Turner et al. 1985).
Consistent with these ﬁndings, Kinne et al. (2004) investigated the prevalence and impact
of secondary conditions among 98 adults with disabilities. However, the questionnaire
items that measured the occurrence of secondary conditions were not speciﬁcally
constructed as a secondary condition measure. They were part of a 2001 Washington
State Behavior Risk Factor Surveillance Survey (BRFSS) of non-institutionalized people
aged 18 years and older. Secondary conditions were operationalized as psychiatric
secondary conditions of depression, and anxiety as well as other fourteen physical
conditions.

The ﬁndings suggested that having a disability predicted having most secondary
conditions. However, age and health status contributed more to psychiatric secondary
disabilities than primary disability. Lack of access to needed service also contributed to
the high occurrence of secondary conditions. Based on these ﬁndings, the researchers
observed that prevention of secondary conditions would require intervening in the
complex relationship among individual risk factors and environmental determinants of
health and quality of life. One implication of these ﬁndings for rehabilitation research and
practice is to understand how and to what extent secondary psychiatric conditions could
inﬂuence outcomes among people with disabilities.

Reporting youth-speciﬁc trends (HP 2010) used the International Classiﬁcation of
Functioning (ICF) disablement framework to present the increased incidence of
secondary disabilities among young people (HP2010: 3). Speciﬁcally, there were about a

33 % increase in activity limitation among girls and a 40% increase among boys with

51

disabilities. According to this report, these individuals who reported activity limitations
reported more days of pain, depression, anxiety, and sleeplessness and fewer days of
vitality than their counterparts who reported less activity limitations.

The rehabilitation implication of this trend is that it may be important to target
activities and services that address all aspects of health and well-being including
preventing secondary psychiatric disabilities (US Dept of State, 2000; Sowers et al,
1995). This is made more salient with the national baseline data indicating that 31% of all
children and adolescents with disabilities were reported to be sad, unhappy and depressed
in 1997 (HP2010) is considered. Consistent with the above discussed rehabilitation
implication, the Healthy People 2010 report clearly mandates the improvement of the
mental health status of young people with disabilities. This is viewed as a method of
removing psychological barriers and enhancing full participation of young people with
disabilities.

Disability Policy

 

A more important dimension of the secondary disability discourse is situated
within the disability policy perspective. There has been an increased emphasis on access
and support for people with disabilities. For instance, the Education for Handicapped
Children (1975, 1986), the IDEA (1991. 97) and the Americans with Disabilities Act -
ADA (1990) all mandate inclusion, participation and choice among individuals with
disabilities. In line with this emphasis, disability policy, practice, research and advocates
have consistently called for more attention towards the prevention of secondary
conditions among individuals with disabilities, in the past decade (HP2010).

Implementing these disability legislations with minimal attention to the removal of

52

rehabilitation barriers caused by secondary mental conditions may jeopardize the
prospects of achieving full inclusion and participation among individuals with
disabilities.

Although these pieces of legislation have contributed to the improvements in the
quality of rehabilitation and accommodation services provided for children and youth
with disabilities, research reports regarding the scarcity of baseline information on health
maintenance of this population remain a source of concern (see, HP2000). Rimmer
(1999) observed that health maintenance objectives for people with disabilities have been
largely ignored. Consistent with this, research (Patrick, 1997; Stuifbergen & Becker,
1994; Brandon, 1985; Brooks, 1984) is in agreement that secondary health conditions for
individuals with disabilities have been neglected. Incidentally, health maintenance among
people with disabilities has come to be regarded as a key predictor of outcomes among
this population.

Unfortunately, full inclusion, participation and improved general well-being for
people with disabilities would not be attainable without addressing the relationships
between the mental health complications associated with disabilities, and rehabilitation
outcomes. In response to these trends, recent research has recommended the inclusion of
the prevention of secondary conditions in rehabilitation service delivery, in order to
improve the well-being and quality of life of people with disabilities (Simeonsson et al,
2002Fuhrer, 1995; Lollar, 1994).

Summary
This overview of literature has addressed extant literature on the associations

between secondary disabilities and rehabilitation outcomes among people with

53

disabilities. From different theoretical and practice perspectives, literature remains
consistent about the pervasive negative impact of secondary psychiatric disabilities in the
lives of people with various physical disabilities. People with primary disabilities are
often at risk of developing secondary disabilities, which can contribute to negative life
outcomes more than the primary disabilities.

Irrespective of the rehabilitation barriers that are associated with secondary
disabilities, information on secondary psychiatric disabilities among people with
disabilities in the vocational rehabilitation (VR) system remains limited. Speciﬁcally,
there is no study focused directly on the impact of secondary psychiatric disabilities
(SPDs) among transition youth with disabilities in the vocational rehabilitation literature.
Despite the increase in the prevalence of SPDs among people with disabilities, and
continued negative inﬂuence on outcome (Simeonsson et al., 2002), rehabilitation
literature has continued to consider it only as an incidental in research investigations
(Moore et al, 2002).

This lack of attention is unfortunate as research of this type would allow policy
makers and program planners to better understand who we are serving and identify the
psychological barriers that need to be removed in order to enhance vocational
rehabilitation outcomes among consumers. Focusing research attention on secondary
psychiatric conditions may highlight the impact of a signiﬁcant health-related intra-
individual factor which could inﬂuence vocational rehabilitation outcome. In addition, it
could contribute knowledge needed for removal of mental health barriers, which could
impede the VR outcome of youth with disabilities.

As part of investigation of the relationships between mental illness, VR, and

54

employment outcomes among youth in the VR system, this study investigated the
prevalence of secondary psychiatric disabilities among youth with disabilities within the
RSA-911 dataset, and how secondary psychiatric disabilities inﬂuence their vocational

outcomes.

55

CHAPTER 3
METHODOLOGY

This chapter includes the research questions, the research design, a description of
the sample population, the source of data, the independent and dependent variables, and a
discussion of the data analysis used in the study.

This study examined the relationships between the employment outcomes of
youth VR consumers with psychiatric disabilities with the following factors: (1) VR
services which they received and (2) personal background characteristics. To accomplish
these goals, data were obtained from Rehabilitation Services Administration (RSA) 911
dataset on youth with primary and secondary psychiatric disabilities whose cases were
closed during federal ﬁscal year 2004 (FY October, 2003 to September 30, 2004).

Information extracted from this dataset fell under three major categories:
consumer personal background characteristics, VR services obtained, and employment
outcomes. The personal background variables evaluated in this study were: (a) gender,
(b) education level at application, (c) public support received at application, (d)
diagnostic type, and (e) race. Sixteen service variables listed in the RSA 911 data were
included in the analyses. Employment outcome was deﬁned as successful or unsuccessful
employment outcome.

Research Questions
1. How are the employment outcomes obtained by youth VR consumers with
primary psychiatric disabilities associated with the vocational rehabilitation

services they receive while controlling for demographic characteristics?

56

2. How do the personal background characteristics of youth VR consumers with
primary psychiatric disabilities impact their employment outcomes?

3. How do the employment outcomes obtained by youth VR consumers with
secondary psychiatric disabilities compare to those of youth rehabilitants with
non-psychiatric disabilities?

Research Design

This study adopted a correlational research design. The use of this research design
is justiﬁed because the primary intent of this study is to examine relationships between a
set of predictor variables and employment outcomes. A correlational study examines the
extent to which differences in one characteristic or variable are related to differences in
one or more other characteristics or variables. The magnitude of the relationship, which is
expressed in a correlation coefﬁcient, provides the researcher with insights regarding the
theory-based, hypothetical association of variables of interest (Leedy & Orrnrod, 2001).
Correlational design was appropriate as this study required making of predictions on
multiple inﬂuences. It also allowed the analysis of how several background
characteristics and VR services or combinations of VR services inﬂuence employment
outcomes among youth with psychiatric disabilities (Borg, Gall,& Gall, 1993; Cohen &
Cohen, 1983).

An exploratory design was employed to assess the inﬂuence of secondary
psychiatric disability on employment outcomes among youth rehabilitants in the state-
federal VR system. Although research (Campbell & Stanley, 1963) has described
exploratory designs as weak, this design was appropriate given the need to better

understand and measure the differences between the target population (youth with

57

 

It?

iii

IIICII
of 1;

5UCC¢

secondary psychiatric disabilities) and the rest (youth without secondary psychiatric
disabilities). This study considered making comparisons between the two groups an
appropriate starting point in assessing the extent to which the VR system is meeting the
needs of youth with psychiatric disabilities as a secondary diagnosis. Thus, as there is no
prototype in exploratory research, the major goal was to become more familiar with this
subject (Babbie, 1995; Rubbin & Babbie, 1993). This type of assessment can provide
data that could be developed to identify new program and service possibilities. Findings
from this type of empirical investigation may lay groundwork for additional research
(Capella, 2003; Rubin & Barbie, 1993).
Subjects

The population of interest in this study included youth with disabilities who have
received VR services through the state-federal VR program. More speciﬁcally, the
participants in this study included youth VR consumers with psychiatric disabilities
whose cases were closed during the 2004 ﬁscal year (October 1, 2003- September 30,
2004) in one of two following categories: (1) successful employment outcome(status 26)
and (2) unsuccessful employment outcome (status 28). In the RSA-911 database, primary
psychiatric disabilities include anxiety disorders, depression and mood disorders, eating
disorders, personality disorders, mental illness not listed elsewhere, schizophrenia and
other psychotic disorders.

The main criteria for inclusion in the study for the ﬁrst two research questions
included: a) having a primary classiﬁcation of mental illness, (b) being between the ages
of 12.99 and 25.99, (c) having received any VR service and (d) having been closed either

successfully (status 26) or unsuccessfully ( status 28). For research question three, the

58

 

sample included all youth with disabilities, but without primary mental illness, whose
cases were closed during the 2004 ﬁscal year (October 1, 2003- September 30, 2004) in
one of two following categories: (1) successful employment outcome(status 26) and (2)
unsuccessful employment outcome (status 28).

For the purpose of identifying whether or not there are associations between
employment outcome and several demographic and service variables among youth VR
consumers with psychiatric disabilities, data containing youth who have primary
psychiatric disabilities (n=8,419) were extracted from a larger RSA-911 database of all
youth with disabilities in the state and federal VR system (n=74,457). For the purpose of
examining whether or not there are associations between secondary psychiatric
disabilities and employment outcome among youth VR service consumers, data was
extracted from the larger database of all youth with disabilities containing 62,032 youth
with non-mental disabilities, and 4,006 with secondary psychiatric disabilities (after those
with primary psychiatric disabilities had been removed).

Variables

The predictor variables for this study included personal background
characteristics and the VR services received. These variables include factors which had
been identiﬁed by existing research as possible important predictors of employment
outcomes among the general populations of people with disabilities (Capella, 2003;
Moore 2001b; Moore and Scroedel, 2001a; Wilson, 1997). In addition, clinical judgment
was applied in selecting the variables for this study. No signiﬁcant differences in
employment outcomes were found in relation to gender and, therefore, this variable was

not included in the regression model. Levels of personal background variables with very

59

small frequencies were not collapsed together. This was based on psychiatric vocational
rehabilitation research which has observed the need to recognize that “the complex
process of obtaining and sustaining employment may not be uniform across various
demographic and diagnostic subgroups or persons with psychiatric disabilities. As a
result there is call for research which does not assume homogeneity, which explores
subgroup differences, and identiﬁes factors outside the VR service system that may be
relevant in determining the employment success of various demographic subgroups”
(Wewiorski, 2004, p. 19).

Predictor variables

Personal background variables: This consisted of gender, education at application,
race/ethnicity, source of impairment (diagnosis) and public support received at
application. Gender is a dichotomous variable coded as: 1 for male and 2 for females.
Race/ethnicity is a nominal variable with seven levels. This information is recorded based
on the individual’s own identiﬁcation of race and ethnicity from the following six
categories: 1 for White, 2 for Black/Aﬁican American, 3 for American Indian/Alaska
Native, 4 for Asian, 5 for Native Hawaiian/ other Paciﬁc Islander, 6 for Hispanic/Latino
origin or 7 for multiracial.

Source of impairment included: anxiety disorders, personality disorders, eating
disorders, depressive and other mood disorders, schizophrenia and psychotic disorders,
and other mental illness not listed elsewhere.

Public support received was treated as a nominal variable with the following
levels: Supplemental Security Income (SSI), Social Security Disability Income (SSDI)

and Temporary Assistance for Needy Families (TANF).

60

For the purpose of this study, ‘services provided’ was represented as a categorical
variable with 16 levels including: assessments, diagnosis/treatment of impairments,
vocational rehabilitation counseling and guidance, college/university training,
occupational/vocational training, on-the-job training, job readiness training, disability
related augmentative skills training, miscellaneous training, job search assistance, job
placement assistance, on-the-job supports, transportation services, maintenance,
technical assistance, and ‘other services’. All sixteen service variables were included in
the evaluation of all the research questions, given that no prior research has documented
the speciﬁc services which could most correctly predict employment outcomes among
youth with psychiatric disabilities, using the RSA-911 database. In this sense, this aspect
of the study was exploratory. Each of these services was dichotomously coded as
received or not received.

Outcome or Criterion Variable

The outcome or criterion variable chosen for this study was the employment
outcome achieved by youth with psychiatric disabilities in the RSA-911 database. This
was represented as a categorical variable with two levels: successful or unsuccessful
employment outcome. For the purpose of this study, successful employment outcome
(status 26) was coded as 1, while unsuccessful employment outcome (status 28) was
coded as 0.

Data Collection Procedure

This study used the archival data collected by the Rehabilitation Services

Administration (RSA-911) for the federal ﬁscal year 2004. The RSA-911 database is a

reporting system which follows federal guidelines established by the Rehabilitation

61

Services Administration (RSA) to keep comprehensive, standardized information on the
rehabilitation process on all cases closed nationwide in the state-federal VR system, from
ﬁrst referral to ﬁnal closure (Capella, 2003; Moore et al, 2002; Moore, 2002; RSA,
1995). This data is collected every year in all the states. The basic information contained
in this database includes demographic, socioeconomic, and disability information at
referral; information on all types of services received; and outcome information for all
cases closed during the ﬁscal year (Warren et al., 2004). For the purpose of this study,
the speciﬁc categories of information that were extracted from the database included: (a)
VR services obtained; (b) personal background characteristics such as gender,
race/ethnicity, source of impairment and public assistance received; and (c) employment
outcomes achieved (successful or unsuccessful employment).

Based on existing literature, Matrone (2003) has asserted that this database is the
single most reliable data on demographics, services, and outcomes of individuals with
disabilities in the state-federal rehabilitation system. In addition, Wheaton (2002) has
observed that the research utility of this database is increased by the fact that the
consequences of random errors are reduced by the large sample size contained in the
database.

However, this study recognized that the inherent unknown elements of miscoding
or lack of coding that exists with collection and analysis of this type of archival data
could limit the reliability and validity of information obtained from the RSA-911
database. Importantly, this study assumed that this error will be minimized as a result of
RSA-devised cross checks of the data, which are aimed at promoting consistency,

coherence, utility of the data elements, and the validity of measurements derived from

62

these data elements. This involves the use of 18 comparison checks at the time of data
entry (RSA, 1995). In addition, this study anticipated problems related i0 missing data,
which could affect the validity of the ﬁndings. However, the many advantages offered by
the RSA-911 dataset increases its research value. First, the external validity of this study
is increased because the data is collected quickly thus reducing the effect of subject
mortality. Second, this dataset provides the researcher with access to a large
representative sample of youth with disabilities across the nation.

Data Analysis

Data Analysis for Question One

 

Research Question 1. How are the employment outcomes obtained by youth VR
consumers with psychiatric disabilities associated with the vocational rehabilitation
services they receive?

Data Analysis.

The predictor variables in this question were VR services listed in the RSA-911
database. Vocational rehabilitation services was treated as a categorical variable with 16
levels including: assessments, diagnosis/treatment of impairments, vocational
rehabilitation counseling and guidance, college/university training,
occupational/vocational training, on-the-job training, job readiness training, disability
related augmentative skills training, miscellaneous training, job search assistance, job
placement assistance, on-the-job supports, transportation services, maintenance,
technical assistance, and ‘other’ services. All the services were coded as received (1) or
not received (0). The criterion variable for this question was employment outcome. This

was coded as successfully employed (1) or not successﬁrlly employed (0).

63

This analysis was performed using all the youth with a primary diagnosis of
mental illness (n=8419). However, nine cases were missing under the ‘race’ category.
The analysis on race was therefore conducted using 8,140 youth with primary mental
illness who received VR services during the 2004 ﬁscal year. Data analysis consisted of
descriptive and logistic regression analyses. Descriptive analyses yielded data providing
an overview of the population indicating the numbers and proportions of youth VR
consumers with mental illness who were successfully employed or not employed after
receiving VR services. Logistic regression analyses involved several steps including a
selection of signiﬁcant variables, model building, and assessment of the goodness-of-ﬁt
of the ﬁnal model.

The second step involved the selection of signiﬁcant variables for the logistic
model. A stepwise method was used to enter variables into the logistic model. Given the
fact that there is limited existing information on how speciﬁc VR services impact the
employment outcomes of youth with psychiatric disabilities, and in this sense this
research is exploratory, this method was considered most appropriate. Norusis (2000)
considered the stepwise method the most commonly used method for model building,
especially in exploratory research. For the purpose of this study, A stepwise variable
selection is a variable selection method based entirely on the statistical signiﬁcance of
several competing models (Mertler & Vanatta, 2002). This involves a combination of
forward and backward regressions in which the initial regression model contains no
variables except an intercept. Variables are then entered to the model one at a time and
are possibly removed from the model depending on whether or not they render a

statistically signiﬁcant model. These steps are necessary in identifying variables that

64

 

n 2
m u.

 

 

 

 

may not individually inﬂuence outcome but can become signiﬁcant predictors in the
presence of other variables. At the end, a model containing all the signiﬁcant VR service
variables was developed.

The third step involved the veriﬁcation of the importance of the variables within
the model. The criteria for judging signiﬁcance for this study was a chi-square or more
speciﬁcally, the likelihood ratio test (LRT) statistic. Cutoff signiﬁcance levels for
entering and removing variables from the model were set to alpha=0.35, 0.30,
respectively. These high signiﬁcance levels were safeguards against removal of variables
that had marginal statistical signiﬁcance. This procedure was necessary given that the
current investigation was among the ﬁrst studies of youth VR consumers with psychiatric
disabilities using the RSA 911 data set. By using the LRT criteria, a model is reﬁned and
reduced by removing the most non-signiﬁcant variables or interactions from the model.

Odds ratios and their 95% conﬁdence intervals based on the ﬁnal models were
computed. Odds ratios are the ratios of the probability of outcome Y=1-successful
employment, to the probability of outcome Y=2- unsuccessful employment (Mertler &
Vannata, 2002). According to Wright (1995), the odds are one when both outcomes are
equally likely; greater than one when the target event is more likely than the other event;
and less than one when the target event is less likely than the other event.

Data Analysis for Question Two
Research Question 2. How do the personal background characteristics of youth VR
consumers with primary psychiatric disabilities impact their employment outcomes?

The predictor variables for this research question were personal background

characteristics of the youth VR consumers with psychiatric disabilities in the RSA-911

65

 

 

data base for the 2004 ﬁscal year. Personal background characteristics investigated were
gender, education at application, race/ethnicity, source of impairment (diagnosis) and
public assistance received at application. Gender was found to be insigniﬁcant and was
therefore removed during the stepwise procedure. Based on clinical judgment, existing
literature review and descriptive analysis conducted for this study, the race variable
‘white’ was coded as the reference group. Based on clinical recognition of cultural
distinctiveness of different races and the need of the study to investigate the unique
outcomes of different races in the state-federal VR system, this study did not merge any
two different races. The education variable ‘higher education’ (7) was coded as reference
group. The diagnostic variable ‘schizophrenia’ was also coded as reference group. The
criterion variable for this research question was also employment outcome.

Logistic regression was again found appropriate for the investigation of this
research question. A logistic regression model similar to the one constructed for research
question one was considered for this second research objective: examining the
relationships between the various categories of race/ethnicity, education levels, sources of
impairments, public assistance received and employment among youth with psychiatric
disabilities in the state-federal VR system.

Data Analysis for Question Three

Research Question 3. How do the employment outcomes obtained by youth VR
consumers with secondary psychiatric disabilities compare to those of youth rehabilitants
with non-psychiatric disabilities?

The predictor variable used to examine this research question was secondary

psychiatric disabilities. The goal of this research question was to better understand the

66

 

m.

.LO
.,

 

possible impacts of secondary psychiatric disabilities on the employment outcomes of
youth VR consumers. The outcome variable for this research question was employment
outcome.

A logistic regression model similar to the one constructed in the previous sections
was considered for this third research objective: examining the differences in successful
employment outcome between youth with secondary psychiatric disability and the rest of
the youth without mental illness after controlling for personal background and VR service
variables. For this purpose, a new variable named SD was deﬁned with 7 levels:
1=anxiety, 2=depressive and other mood disorders, 3=Eating disorder, 4=Mental Illness
not listed elsewhere, 5=Personality Disorder, 6=Schizophrenia, 7=no mental disability. A
model was ﬁnally ﬁtted containing SD variable and all demographic and service
variables that were included in the models of the previous sections.

Summary

This chapter provided an overview of the research questions, the research design,
a description of the sample population, the source of data, the independent and dependent
variables, and a discussion of the procedure of data analysis used in the study.

At present, there is a dearth of literature regarding the employment outcomes of
youth with psychiatric disabilities in the state-federal VR system. The current study is
among the ﬁrst to investigate the factors that predict employment outcomes among youth
with psychiatric disabilities using the RSA-911 data. The ﬁndings from this study will
have both substantive and methodological contributions. The literature on employment
outcomes among people with psychiatric disabilities mainly has investigated either adult

populations in the VR system or youth in the general rehabilitation system. There is

67

M}
l

 

 

limited research that has speciﬁcally examined the issues of youth with psychiatric
disabilities in the state-federal VR system. Findings from this study will provide evidence
that explains whether employment outcome among youth with psychiatric disabilities is a
function of the absence or presence of needed VR services or personal background
factors. By means of this clariﬁcation, this study hopes to contribute to existing
knowledge which could help policy makers to target VR interventions appropriately,
thereby enhancing employment outcomes for this population. Related outcomes can then
be monitored and measured. In addition, concrete and evidence driven objectives can be
achieved and the overall goals of disability advocacy will be furthered (Institute Of
Medicine, 1991, p.16).

This study also expects to contribute to existing knowledge regarding the process
and outcome of vocational rehabilitation among youth with psychiatric disabilities
(primary and secondary) while controlling for unique personal background characteristics
and VR services received. This will help VR service providers to design and deliver
services, which will be effective in increasing employment outcomes among this
population. In this way, achieving successful employment outcomes and retaining jobs
among youth with psychiatric disabilities would increase, while dropout rates from the
VR system and poor employment outcomes would decrease.

This chapter recognizes the methodological limitations related to the statistical
procedures chosen. For example, research has observed that the stepwise method of
variable selection tend to create ‘noise’ in the data. Although it is regarded as the most
commonly used method for model building in both linear and logistic regression, other

methods of variable entry may prove stronger when all statistical requirements are met

68

 

m

.105

 

 

(Norusis, 2000). In addition, this chapter acknowledges the limitations associated with
the use of secondary data such as miscoding, missing data, and the possible inaccuracy in

data collection.

69

 

 

Chapter 4
RESULTS

The purposes of this study were (1) to examine personal background
characteristics, types of vocational rehabilitation (VR) services provided through the
state-federal VR system to youth with psychiatric disabilities, (2) to model the
relationship of these factors to employment outcome, and (3) to assess the inﬂuence of
secondary psychiatric disability on employment outcomes among youth rehabilitants in
the state-federal VR system. The third purpose was addressed because it was
hypothesized that employment outcomes will differ between youth who had secondary
psychiatric disabilities in addition to their primary disabilities and youth without
secondary psychiatric disabilities when controlling for personal background and VR
services factors.

To accomplish these goals, data were obtained from the Rehabilitation Services
Administration (RSA) 911 dataset on youth with primary and secondary psychiatric
disabilities whose cases were closed during federal ﬁscal year 2004 (FY October, 2003 to
September 30, 2004). Descriptive analyses were used to address the ﬁrst goal of the study
and logistic regression was used to address goals two and three.

The dataset analyzed for the ﬁrst two research questions was extracted from a
larger database of all youth who received VR services during FY 2004 and it contains
8,419 youths who have primary mental illness diagnoses of various classiﬁcations. The
objective was to examine whether statistically signiﬁcant relationships existed between
employment outcome, demographic and service variables among youth VR service

consumers with psychiatric disabilities. The dataset analyzed for the third research

70

 

question was extracted from the larger database of all youth VR consumers (N =74,45 7)
containing 62,032 youth with non-mental diagnoses and 4,006 with secondary psychiatric
disabilities. The objective was to examine whether or not relationships exist between
secondary psychiatric disabilities and employment outcomes among youth VR service
consumers.

Review of Methodology

A correlational design was adopted for the purpose of investigating the
relationships between personal background characteristics, VR services and employment
outcomes among youth with psychiatric disabilities. This design was appropriate given
the ﬂexibility and capacity to evaluate multiple relationships which it offers (Cohen and
Cohen, 1983). Given the exploratory nature of this study, this research design is most
appropriate due to its goal to measure complexities of relationships related to personal
background and VR service factors among youth with psychiatric disabilities. Descriptive
and logistic regression analyses were employed as the statistical means with which to
assess the relationships between the predictors (gender, race/ethnicity, source of
impairment, education, public assistance received and VR services) and criterion variable
(employment outcome).

Logistic regression analyses involved selection of signiﬁcant variables, model
building, and assessment of goodness of ﬁt for the ﬁnal model. Correlation coefﬁcients
were ﬁrst computed. This assisted in determining which variables were entered into the
logistic regression model. A stepwise method was employed to enter all variables of
interest into the regression equation. As there were no a priori hypotheses regarding

which variables would have signiﬁcant associations with the outcome, there was need to

71

use a stepwise variable selection procedure to discriminate between models. The stepwise
method enabled the reduction of the number of variables in an effort to identify a ﬁnal
parsimonious model which is most consistent with the sample data. Based on the results
of a likelihood ratio test (LRT) which is also known as the -210g-likelihood statistic, any
variable with an alpha =0.35, 0.30 was judged signiﬁcant enough for entry into the
logistic equation for this study. This criterion facilitated the reduction and reﬁning of the
regression model by removing the most non-signiﬁcant service variables and interactions.

The variables that were entered into the logistic regression equation based on the
likelihood ratio test were race (seven levels), source of mental illness (six levels), public
support received at application (three levels), education at application (seven levels), and
VR services (16 levels). The VR services included were assessment, diagnosis/treatment,
vocational rehabilitation, college/university training, occupational/vocational training,
on-the-job training, job readiness training, miscellaneous training, job search assistance,
job placement assistance, on-the-job supports, transportation, maintenance services,
technical assistance and ‘other’ services. Employment outcome was deﬁned as successful
or unsuccessful employment resulting in a binary variable. The ﬁnal model contained 70
variables including intercept, l6 VR service variables, 23 levels of personal background
variables and two-way interaction variables.

Two-way interactions were included to explore the extent to which employment
outcomes were impacted when two services were combined. The choice of two-way
interactions between services as opposed to three or higher order of interactions kept the

model simpler and more parsimonious. These variables along with their estimated

72

coefﬁcients, standard errors, chi-square test statistics, and p-values are reported in
Appendix 1.

Odds ratios and their 95% conﬁdence intervals based on the ﬁnal models were
computed. The reporting of conﬁdence intervals has been noted as an effective way of
reporting results. “They are considered the best reporting strategy because they combine
information on location, precision and can often be directly used to infer signiﬁcance
levels” (APA Manual, 2003, p. 22). Only the odds ratios whose 95% conﬁdence interval
did not include 1 were reported. When conﬁdence intervals around the odds ratio include
the value of 1.0, this ﬁnding indicates that a change in the value of the predictor variable
is not associated with a change in the odds ratio of the criterion variable. This variable is
then not considered a useful predictor in the logistic regression model.

Assessing the Goodness-of-ﬁt of the Final Model

The ﬁnal model had a Hosmer—Lemeshow goodness-of-ﬁt chi-square test statistic
of 11.37 with 8 degrees of freedom and p-value=0.18 (Somers’D=0.47). According to
Hosmer and Lemeshow (2000), a p-value that is larger than .05 suggests that the model is
consistent with the data. Therefore, the ﬁnal model was satisfactory and it can be used for
predictive purposes. This conclusion was also supported by using various diagnostic
residual plots. In particular, standardized deviance residuals, plotted against subject index
and against predicted probabilities of successﬁrl employment (See Figure 1 in appendix),
did not indicate a lack-of-ﬁt for the ﬁnal model. In fact, these residuals are well between
+-3 and very few of them are beyond +-2. This rule of thumb is deduced from the fact

that standardized residuals based on large sample sizes would follow standard normal

73

distribution whose numbers would be contained between +3 and -3 with probability
99.7%.

Inﬂuence statistics were examined to determine if there were any highly
inﬂuential observations whose removal from the sample would result in a substantial
change in the estimated coefﬁcients. In particular, the dfbeta statistic (which is essentially
a standardized distance between parameters estimated with and without a particular
observation) were plotted and visually examined. These plots (not reported in this
dissertation as there are 70 of them) did not reveal any inﬂuential observations.

For research question 3, a deviance residual was employed in checking the model.
The Hosmer Lemeshow test is not very reliable when the sample size is large and so this
was considered inappropriate for this research question. The deviance residual did not
indicate outlying observations and therefore suggested that the model is good. The

deviance residual graph is presented in Figure 2 in the appendix.

74

Table 1: Hosmer-Lemeshow Goodness-of—ﬁt Statistic

 

Group Total Employed Not Employed Chi-

Observed Expected Observed Expected Square

 

l 841 115 123.17 726 717.83 11.3707
2 843 168 186.07 675 656.93
3 841 227 233.58 614 607.42
4 842 308 284.95 534 557.05
5 839 370 344.50 469 494.50
6 842 398 405.59 444 436.41
7 842 467 459.34 375 382.66
8 841 513 510.38 328 330.62
9 841 566 570.46 275 270.54
10 838 669 682.81 169 155.19

 

Association of predicted probabilities and observed responses

 

 

Value
Percent Concordant 73.3
Percent Discordant 26.4
Somers’ D 0.469
Gamma 0.470
Degree of Freedom 8.0
Chi— Square 0.1816

 

75

Presentation of Results

This section presents overall descriptive statistics of signiﬁcant personal
background characteristics and VR service variables including gender, source of
impairment, race/ethnicity, public assistance received, education at application, 16 VR
services and employment outcome. Eight thousand, four hundred and nineteen males
(n=4,756, 56.5%) and females (n=3,663, 43.5%) with primary psychiatric disabilities
participated in this study. About half of the sample (n=3,809, 45.2%) were closed with a
successﬁrl employment, and 4,617 (54.8%) were closed without achieving successful
employment outcome.

Research Question 1: How are the employment outcomes obtained by youth VR
consumers with psychiatric disabilities associated with the vocational rehabilitation
services they receive, while controlling for demographic characteristics?

The analysis revealed that there are associations between VR services and
employment outcome. Table 2 presents the distribution of services provided and the
employment outcomes achieved by the youth VR consumers with primary mental illness.
The most frequently received VR services were assessment (66%) and vocational
rehabilitation services (61%). Higher percentages of successful employment outcome
(status 26) were achieved among youth who received on-the-job training (63%) and job
placement services (62%). Lower percentages of successful employment outcome were
achieved among youth who received diagnosis and treatment services (44%) and
technical assistance (34%). Information on the services and distribution of employment

outcomes are summarized in Table 2.

76

ILO'

 

 

 

Chi-square results revealed statistically signiﬁcant associations between

employment outcome and numerous VR service variables. For example, job placement
. 2 , 2
servrcesX (1, n=8419)= 362.19, p<.05; Cramer’s V=.20); Job support servrces, X ( 1,

N=8419)=62.48, p<.05; Cramer’s V=.08); and ‘other services”, X2 (1, N=8419)=39.83,
p<.05; Cramer’s V= .06) demonstrated signiﬁcant relationships with employment
outcome. Since the calculated values are greater than the critical values both at p<.05 and
p<.01, it was concluded that these predictor and criterion variables were signiﬁcantly
related. However, the low values of Cramer’s V (below 1) signify that the associations

between VR services and employment outcome among youth with psychiatric disabilities
2
were weak. Assessment services, X (1, N=8419)=1.72; p<.05; Cramer’s V=.01), and

diagnoses and treatment services, X2 (1,N=8419)=1.17; p=.05; Cramer’s V=.01) showed
weak relationships with employment outcome, suggesting that these predictor variables
and employment outcome are independent. Given that these variables are nominal,
reporting the direction of the relationships was considered irrelevant and therefore only
absolute values were reported (Capella, 2003). Further details on this chi square analysis
are presented on Table 3.

Table 4 presents the regression model with the beta, standard error, Wald statistic,
degrees of freedom, signiﬁcance level, odds ratio and 95% conﬁdence intervals.
Numerous variables were signiﬁcant at the p<.05 level. The odds of successful
employment for those receiving placement services were four times higher than the odds
for those not receiving placement services (OR=4.22; 95% CI= 3.25-5.45). The other
odds ratios can be similarly interpreted for odds ratio and 95% conﬁdence interval values

from Table 4. Most of the results revealed a strong relationship to employment outcome,

77

CHE:

2.01

 

 

suggesting that individuals who received these services had several times more odds of
successful employment outcome than counterparts who did not receive the services. In
contrast, diagnosis and treatment services demonstrated a negative relationship with
employment outcome (OR=0.75; 95% CI=0.66-0.86).

It is important to note that interaction effects found in this study among service
variables were weak and inconsistent with any clinical or theoretical framework. For
example, whereas individuals who received college services had about six times the odds
of successﬁil employment, the odds dropped substantially (0.74) when these individuals
also received vocational training services. The effect of placement services was somehow
delimited for individuals who received ‘other services’ in addition to placement services.
In fact, odds of successful employment after receiving placement services dropped from
4.22 to 2.82 with a conﬁdence interval of (21-388) when ‘other services’ were included
in the analysis. Except for the combination of $81 and maintenance services which
increased the odds of successful employment (OR=8.52; 95% CI =5.89-12.31), none of
the interactions between the 16 VR services evaluated indicated an increase in the odds of
successful employment. Overall, the interaction analysis results did not present enough
clear patterns regarding the relationships between VR services and employment
outcomes. The interaction results were therefore not reported. They are presented in

Appendix 1.

78

Table 2: Frequency, percent of Services Provided and Employment Outcome

 

 

Services Provided Number Percent Employment Outcome
Receiving Receiving % Successful % Unsuccessful

Assessment 5555 66% 46 54

Diagnosis and 2913 34.6% 44 56

Treatment

Vocational 5 194 61 .4% 46 54

Rehabilitation

College Training 2038 24.2% 59 41

Occupational/Vocational 1428 17% 54 46

Training

On-the-Job Training 362 4.3% 63 37

Job Readiness Training 1243 14.8%

Miscellaneous Training 1027 12.2% 51 49

Job Search Assistance 2047 24.3% 57 43

Job Placement 2326 27.6% 62 38

On-the-Job Supports 1222 14.5% 56 44

Transportation 1963 23.3% 47 53

Maintenance 1 093 1 3% 5 7 43

Technical Assistance 209 2.5% 34 66

Other 2102 25% 51 49

 

79

HIE!

A

AC)

 

 

Table 3: Receipt of VR Services and Employment Outcomes

 

 

Variable Df N Percent Chi Cramer V
Receiving Square
Assessment 1 8419 66% 1 .72 .0]
Diagnosis and treatment 1 8419 34.6% 1.17 -.01
Vocational rehabilitation 1 841 9 61 .4% 4.95 .02
College/ University 1 8419 24.2% 204.42 .15
Training
Occupational/Vocational l 8419 1 7% 59.43 .84
On-the-Iob Training 1 8419 4.3% 50.03 .07
Job Readiness Training 1 8419 14.8% 13.56 .04
Miscellaneous 1 8419 12.2% 14.65 .04
Job Placement 1 8419 27.6% 362.19 .20
On-the-job-support 1 8419 14.5% 62.48 .08
‘Other Services’ 1 8419 25% 39.83 .06

 

 

 

 

Table 4: Summary of Logistic Regression Analysis for Services Predicting Employment

Outcomes Controlling for Demographics

 

 

Variable B S.E Wald Df Sig. Odds 95% CI

Ratio
Intercept -0.945 0.216 19.0147 1 .0001 0.388 0.254 0.594
Job Placement -0.945 0.216 19.014 1 .0001 4.2 3.25 5.47
Assistance
College 1.788 0.111 257.072 1 .0001 5.98 4.81 7.44
University TR
Occupational/ 1.023 0.123 69.31 1 1 .0001 2.78 2.16 3.54
Vocational TR
On-the-Job 0.696 0.134 26.718 1 .0001 2.01 1.54 2.61
Support
Maintenance 0.467 0.123 14.302 1 .0001 1.59 1.25 2.03
Job Search 0.784 0.151 26.756 1 .0001 2.19 1.63 2.95
Assistance
Diagnosis/TX -0.283 0.066 18.413 1 .0001 0.75 0.66 0.86
On-the-Job TR 0.602 0.166 13.075 1 .0001 1.83 1.32 2.53
‘Other 0.617 0.089 48.112 1 .0001 1.85 1.56 2.21
Services’
Miscellaneous 0.078 0.165 0.228 1 0.638 2.82 2.05 3.86
TR

 

81

 

HIE:

Lo i

 

 

 

Research Question 2: Employment Outcomes Obtained. by Youth with Psychiatric
Disabilities and Personal Background Factors

The results indicated that personal background factors were associated with the
employment outcome of youth VR consumers with primary psychiatric disabilities.
Source of Impairment

Table 5 displays the frequency and percent of ‘source of impairment’ and
employment outcome. Most youth with primary psychiatric disabilities were diagnosed
with depressive disorders (n=3,195, 38%) and mental illness not listed elsewhere
(n=2,058, 24%). Eating disorder was the least diagnosed (n=25, .30%). Signiﬁcant
differences in employment outcomes were found between groups based on diagnosis.
Higher percentages of unsuccessful employment outcome were found among individuals
with schizophrenia/other psychotic disorders and depressive/mood disorder. On the other
hand, individuals with anxiety disorders and eating disorders obtained the highest
percentages of successful employment outcome.

The logistic regression results indicated that diagnoses impacted the employment
outcome of youth VR consumers. For the purpose of this study, the variable ‘sources of
impairment or diagnosis’ was restricted to anxiety disorders, depressive disorders, mental
illness not listed elsewhere, personality disorders, eating disorders and schizophrenia.
Based on clinical and theoretical judgments, differences were assessed by comparing the
employment outcomes of youth with schizophrenia (reference group) with the other
diagnostic groups. Compared with youth with schizophrenia, youth with anxiety
disorders had 37% more odds of successful employment outcome. In the same way,

youth with personality disorders (OR=1.32; 95% C.I.=1.09-1.59) and eating disorders

82

m
IL

 

(OR=1.27; 95% C.I.=.52-3.11) had substantially more odds of successful employment

outcome compared to youth with schizophrenia. Youth with depressive disorders (OR=
1.09; 95% C.I.= 93-130) and mental illness not listed elsewhere (OR=] .05; 95%

C.I.=.88-l .26) had the least odds of successful employment outcome.

83

 

m

m

 

 

 

Table 5: Frequency and Percent of Source of Primary Psychiatric Disability(PPD)

 

 

Source of Frequency Percent Employment Outcome
Disability % Successful % Unsuccessful
Anxiety 757 9% 50 49

Depression 3 195 37.9% 44 56

Eating Disorder 25 .3% 56 44

Mental Illness 2058 24% 44 56

listed elsewhere

Personality 1489 l 8% 49 5 1
Disorder

Schizophrenia 895 1 1% 43 57
Total 841 9 100%

 

84

Information on race is provided in Table 6. While there were statistically
signiﬁcant differences between the groups in terms of race, these differences were small.
Compared to the race category ‘white’, the odds of successful employment outcome were
less for the youth from the minority races. Compared with the odds of successful
employment outcome for the youth from the white race, the odds of successful
employment outcomes for: a) African American youth were 37% less (OR=.63), b)
Hispanic /Latino were 29% less (OR= .71), c) Native Americans were 54% less
(OR=.46), d) Asians were 51% less (OR=.49), e) Native Hawaiian were 26% less (OR=
.74), and t) multiracial youth were two percent less (OR=.98). This study did not explore

the interface of poverty with race.

85

Table 6: Frequency, Percent of Subject’s Race and Employment Outcome

 

Race Frequency Percent Employment Outcome

%Successful %Unsuccessful

 

White 5751 68% 49 51
Black/African 1525 18% 35 65
American

Native 64 .76% 36 64
American

Asian 77 .92% 43 57
Native 28 .3% 36 64
Hawaiian

Hispanic 873 10.4% 36 64
Multiracial 92 l . 1% 47 53
Total 841 0 1 00%

 

86

ab

0'

L

 

Type of Public Support

Signiﬁcant differences in employment outcome were found in terms of receipt of
public assistance. Youth who received SSI and TANF had less odds of successful
employment outcome than youth who did not receive these public income supports.
Detailed information (including frequency, percent and employment outcomes) for the
types of public assistance received is provided in Table 7.

The youth rehabilitants receiving SSDI had only slightly more odds of successﬁrl

3a.

employment outcome as compared to the youth who did not receive this income support
(OR=1.21; 95% CI. = .79-1.87). In contrast, receipt of SSI and TANF had a substantial

negative relationship with employment outcome. The results indicated that individuals

 

who received SSI had 36% less odds of successful employment outcome (OR=0.64; 95% II
CI=0.52-0.79). Those who received TANF at application had 58% less odds of
successﬁrl employment outcome (OR=0.420; 95% CI =0.22-0.81). Again, this study did

not explore the interface of race and source of public support.

87

Table 7: F requency, Percent of Public Support and Employment Outcome

 

 

Public Support Number Percent Employment Outcome
Receiving Receiving % Successful % Unsuccessful
SS1 987 12% 33 67
SSDI 213 2.5% 39 62
TANF 121 1.4% 26 74 A
Total Receiving 1321 15.9% I

Support

 

88

 

 

 

Education Level at Application

Signiﬁcant differences in employment outcome were found based on education
level. Of all the education levels attained at application, associate degree/vocational
certiﬁcate, and bachelor’s degree and master’s degree (coded as ‘higher education’)
indicated substantially more positive inﬂuence on employment outcome than the others.
Overall, the higher the education levels at application, the greater the odds of successful
employment outcome. Descriptive information on education level at application
(frequency and percentage) and employment outcome is provided in Table 8.

The logistic analyses revealed that education level at application was associated

with employment outcome among youth with psychiatric disabilities in the state-federal

 

VR system. Detailed results of the logistic regression analyses are described in Table 9. I
The results indicated that compared to youth with ‘higher education’ qualiﬁcations, the

odds of successful employment outcome were less for youth with lower level education

qualiﬁcations. Compared with the odds of successful employment outcomes for the youth

with higher education, the odds of successful employment outcome for youth with: (a) no

formal education were 96% less(OR=.04 ), b) elementary education were 97%

less(OR=.03), c) secondary education were 95% less(OR=.05), (1) special education

certiﬁcate were 94% 1ess(OR= .06), e) high school graduate equivalent were 97% less

(OR= .07), 0 post secondary education, no degree were 90% less(OR= .10), and g)

associate degree/vocational certiﬁcate 40% less (OR=.59) times.

89

Table 8: Frequency, Percent of Education Level and Employment Outcome

 

 

 

Education Frequency Percent Employment Outcome

Level % Successful % Unsuccessful

Elementary 3 58 4.3% 3 1 69

Secondary 4913 58.3% 44 56

Special Ed. 759 9% 41 59 1‘
Certiﬁcation

High School 2163 25.7% 49 51

Equivalence

Post-Secondary 168 2% 61 39
Associate 20 .24% 90 1 0

Degree

Higher 19 .23% 100

Education

Total 8419 100%

 

90

Table 9

Summary of Logistic Regression Analysis for Personal Background Characteristics

Impacting Employment Outcome

 

 

 

Variable B S.E. Wald Df Sig. Odds 95% CI
Ratio
Intercept -.945 .216 19.0147 1 .000 .388 .254 .594
African .322 .093 1 1.834 1 .000 .63 .55 .72 ,4
American Vs I]
White
Native -.135 .103 1.698 1 .192 .46 .26 .80
American Vs I‘
White
Asian Vs -.448 .253 3.140 1 .076 .49 .41 1.15
White
Native -.044 .234 .036 1 .084 .74 .31 1.74
Hawaiian Vs
White
Hispanic Vs .020 .379 .002 1 .957 .71 .60 .84

White

91

 

Table 9 Cont’d

Variable B
Intercept -.945
No Formal -.974
Sch. Vs HE
Elementary -1 . 15 7
VS HE

Secondary -.626
Educ Vs HE

Special Educ -.561

Vs HE

High School -.499
Equivalence

Vs White

‘ Post Sec. Educ -.03'l
Vs HE

Associate 1 .609

Degree Vs HE

SE.

.216

.467

.207

.178

.190

.181

.232

.686

Wald

19.0147

4.337

31.244

12.256

8.655

7.596

.018

5.502

92

Df Sig.
l .000
1 .037
1 .000
1 .000
1 .003
1 .005
1 .892
1 .019

Odds

Ratio

.3 88

.04

.03

.05

.06

.07

.10

.53

.254

.00

.00

.00

.01

.01

.01

.04

95% CI.

Lower Upper

.594

.39

.27

.45

 

.48 ‘K

.51

.83

6.81

Table 9 Cont’d
Variable B S.E. Wald Df Sig. Odds 95% CI
Ratio Lower Upper

Intercept -.945 .216 19.0147 1 .000 .388 .254 .594
Anxiety Vs .152 .102 2.219 1 .136 1.37 ’ 1.10 1.70
Schizophrenia

Depression Vs -.068 .085 .646 l .421 1.09 .93 1.30
Schizophrenia

Eating .074 .377 .039 1 .842 1.27 .52 3.11

Disorder Vs

 

Schizophrenia 1.
Mental illness -.109 .089 1.508 1 .219 1.05 .88 1.26
not listed

elsewhere Vs

Schizophrenia

Personality .1 12 .092 1.490 1 .222 1.32 1.09 1.59
Disorder Vs

Schizophrenia

SSI -.443 .103 18.593 1 .000 .64 .52 .79
SSDI .192 .220 .761 1 .382 1.21 .79 1.87
TANF -.868 .332 6.810 1 .009 .42 .56 3.10

93

Research Question 3: Employment outcomes obtained by youth with secondary
psychiatric disabilities compared to those of youth rehabilitants with non-psychiatric
disabilities.

Research question 3 addressed differences in employment outcomes for youth
with secondary psychiatric disabilities and the remainder of the youth without mental
disability in the RSA 911 FY 2004 database. Outcomes of the target population
(n=4,006) were compared with the general population of youth rehabilitants with no
psychiatric diagnoses (n= 62,032). The summary statistics of this group describing
numbers and proportions with/without successful employment are reported in Table 10.
Differences were found based on diagnosis. The major difference was that youth
rehabilitants with no secondary psychiatric disabilities were more likely to achieve
successful employment outcome than those with secondary psychiatric disabilities, with
the exception of youth with eating disorders. Although there were statistically signiﬁcant
differences between the diagnostic groups on employment outcomes, the differences in
percentages were small.

Based on the logistic regression analysis, most of the secondary psychiatric
diagnostic categories demonstrated negative relationships with employment outcome.
The diagnoses of schizophrenia (OR=.45; 95% Cl. =.33-.61), depression (OR=.59; 95%
C.I.= .52-.65), and mental illness not listed elsewhere (OR=.65; 95% C.I.=.56-.75)
demonstrated negative association with employment outcome. The ﬁndings indicated that
youth with schizophrenia as a secondary disability had 55% less odds of successful
employment outcome as compared to the youth without secondary mental illness. In the

same way, youth with depression (40% less) and mental illness not listed elsewhere (35

94

% less) had less odds of successful employment outcome as compared to the youth
without secondary mental illness. Additionally, the ﬁndings suggested that personality
disorders (OR=.72; 95% C.I.=.61-84), and anxiety disorders (OR=.87; 95% C.I.=.72-
l.05) were not signiﬁcant covariates of employment outcome. In contrast youth with
eating disorders (OR=1.25; 95% C.I.=.41-.3.77) as secondary disability demonstrated

25% more odds of successful employment outcome.

 

95

Table 10: Secondary Psychiatric Disability and Employment Outcomes

 

Variable Frequency Percent Employment Outcomes

% unsuccessful % successful

 

Anxiety 507 12.7 46 54
Depression 1568 39.1 57 43
Eating disorder 16 .4% 38 62
MI Not Listed 924 23.1% 51 49
Personality Dis 766 19.1% 51 49
Schizophrenia 225 5.6% 63 37
Total 4006 100% 43 46
SD youth 62032 43 56
Total 66038

 

 

 

96

Table 1 1

Summary of Logistic Regression Analysis for Differences in Employment Outcome for

Youth With and Without Secondary Psychiatric Disabilities

 

 

Variable B S.E. Wald Df Sig. Exp(B) 95% CI
Lower Upper
Intercept -.677 .107 39.894 1 .000
Anxiety/SD .148 .1 19 1.540 1 .214 .873 .720 1.058
Depression/SD -.251 .098 6.576 1 .010 .585 .523 .653
Eating D./SD .508 .483 1.107 1 .292 1.251 .415 3.770
MI Not/SD .145 .105 1.895 1 .168 .650 .564 .751
Persona.Di./SD -.042 .108 .149 1 .699 .721 .618 .842
Schizo./SD -.502 .154 10.583 1 .001 .455 .338 .613

 

97

CHAPTER 5
DISCUSSION

The purpose of this study was to examine the various vocational rehabilitation
services provided through the state-federal Vocational rehabilitation (VR) system to
youth with psychiatric disabilities and the relationships of these services to employment
outcome. In addition, this study examined the impact of personal background
characteristics on the employment outcomes of youth VR consumers with psychiatric
disabilities. Finally this study also evaluated the relationship of secondary psychiatric
disabilities to the employment outcomes of youth VR consumers.

This study addressed the following three research questions:

1. How are the employment outcomes obtained by youth VR consumers with psychiatric
disabilities associated with the vocational rehabilitation services they receive while
controlling for demographic characteristics?

2. How do the personal background characteristics of youth VR consumer with primary
psychiatric disabilities impact their employment outcomes?

3. How do the employment outcomes obtained by youth VR consumers with secondary
psychiatric disabilities compare to those of youth rehabilitants with non-psychiatric
disabilities?

Subjects for this study were obtained from the Rehabilitation Services
Administration (RSA) 911 dataset on youth with primary and secondary psychiatric
disabilities whose cases were closed during federal ﬁscal year 2004 (FY October 2003 to
September, 30, 2004). The predictor variables in this study were the VR services

provided through the state-federal VR system to youth with psychiatric disabilities and

98

their personal background characteristics. The personal background variables evaluated
in this study were: (a) gender, (b) education at application, (0) public support received at
application, ((1) source of impairment, and (e) race. Sixteen VR service variables listed in
the RSA 911 data were included in the analyses. The criterion variable employment
outcome was deﬁned as achieved employment or no employment resulting in a binary
variable.

This study employed correlation as the primary design to evaluate the
relationships between VR services, personal background characteristics, psychiatric
disabilities and employment outcomes. The main criteria for inclusion in the study for the
ﬁrst two research questions included: a) having a primary classiﬁcation of mental illness,
(b) being between the ages of 12.99 and 25.99, (c) having received any VR service and
(d) having been closed either successfully (status 26) or unsuccessfully (status 28). For
research question three, the sample included all youth with disabilities, but without
primary mental illness, whose cases were closed during the 2004 ﬁscal year (October 1,
2003- September 30, 2004) in one of two following categories: (1) successful
employment outcome (status 26) and (2) unsuccessﬁrl employment outcome (status 28).
In total, eight thousand, four hundred and nineteen males (n= 4, 756, 56.5%) and females
(n=3, 663, 43.5%) with primary psychiatric disabilities participated in the ﬁrst two

objectives of this study.

Findings

The ﬁndings of the study indicated that vocational rehabilitation services received
by youth VR consumers are associated with their employment outcome. To the extent

that youth received particular VR services, employment outcome was likely to be

99

successful. In addition, the present study’s results indicated that some personal
background factors outside the VR service system contribute to employment outcomes
among youth VR consumers. Overall, the present study’s ﬁndings raise the important
possibility that some youth VR consumers may not achieve employment outcome (status
26) not only because of the absence of certain VR services, but also due to peculiarities in
their personal background characteristics. The results indicated that there are signiﬁcant
relationships between VR services, personal background characteristics, and employment
outcomes among youth clients. Based on the descriptive analyses, a higher percentage of
youth were closed without an employment outcome (n=4617, 55%) and the rest (n=3 802,

45%) were closed with a ‘successﬁil’ employment outcome.

These results are mirrored in literature which has observed persistent high
unemployment outcomes among the general populations of youth with disabilities
(Kosciulek & Perkins, 2005). Speciﬁcally, research has observed that compared with
youth with other disabilities, youth with psychiatric disabilities have four times as high an
unemployment rate (Vander-Stoep, Beresford, Weiss, McKnight, Cauce, & Cohen, 2000;
vander-Stope , 1997; Salkever, Kolodner, & Bijur, 1996; Vander-Stoep, Taup, Holcomb,
1993; & Se, Duchnowski, Kutah, 1992). However, the results from this study provided
slightly more positive evidence regarding the employment outcomes of people with
psychiatric disabilities. In contrast to research projections of below 30% successful
employment outcome among individuals with psychiatric disabilities, about forty-ﬁve

percent of the subjects in this study achieved a successﬁil employment outcome.

In relation to research question one, ﬁndings revealed that there are associations

between some particular VR services and employment outcomes. The ﬁndings indicated

100

statistically signiﬁcant associations between employment outcomes and numerous VR
services received by youth VR consumers with primary psychiatric disabilities. A
substantially higher percentage of youth VR consumers with psychiatric disabilities were
provided assessment (66%) and vocational rehabilitation (61.4%) services. However,
more successful employment outcomes were recorded among youth who received on-the-
job training (63%) job placement (62%), job-search (57%) and maintenance (57%)

services.

As would be expected, this ﬁnding indicates that services which were provided as
prerequisites for entry into the VR case-load were received more frequently. In this study,
they were related to lower probabilities of successful employment outcome. On the other
hand, VR services which targeted speciﬁc preparations for obtaining and sustaining
employment such as on-the-job training, job placement, and maintenance services were
provided less frequently and were related to higher probabilities of successful
employment outcome. These ﬁndings reﬂect existing research observations that the low
employment trend among people with psychiatric disabilities could be accounted for by
the unavailability of the certain VR services and support required to facilitate successful
employment outcome (Fabian, 1998). These ﬁndings raise a question whether the VR
system is meeting the needs of the youth VR consumers with psychiatric disabilities.
However, caution needs to be exercised in generalizing this ﬁnding. This is because the
methodology of this study can not determine whether receiving a particular VR service
produces a more successful employment outcome or whether youth who already have

certain characteristics are more likely to access speciﬁc services.

101

In relation to research question two, the ﬁndings indicated that the trend of
employment outcome was not uniform across various demographic and diagnostic
subgroups within the population of youth VR consumers with psychiatric disabilities.
Findings revealed that race impacted employment outcomes among youth. Minority
youth with primary psychiatric disabilities had less odds of successful employment
outcome compared to the youth who are whites. This ﬁnding is consistent with extant
research which has suggested that whites achieve more favorable employment outcomes
in the VR system than consumers from minority races (Capella, 2002; F eist-Price, 1995).
However, in this study, other interpretations concerning direction of impact are possible.
Sample size distribution could account for the difference in employment outcome. A
substantial majority of the sample consisted of white youth (68%) followed by African
Americans (18%). With large sample size, most test of signiﬁcance are expected to be
statistically signiﬁcant. This result might be expected as higher frequency in receipt of
service may be associated with higher frequency in employment outcome. However,
based on the descriptive results, the differences in outcome were minimal, with whites
and Asians achieving more. In addition, the direction of association between race and
employment outcome may become different when poverty factors are considered. This

would be a good agenda for further research on youth in the VR system.

Gender was not a signiﬁcant predictor of employment outcome among youth with
psychiatric disabilities. Descriptive data indicated that a larger percentage of youth VR
consumers were males (56.5%). In addition, the ﬁndings indicated that the employment
outcomes were fairly equally split with males comprising 45% and females totaling 46%

of participants who achieved successful employment outcomes. Based on existing

102

literature on populations with psychiatric disabilities, this trend might be unexpected as
literature has been consistent regarding more representation of female consumers in the
VR system (Bromet, 2005). However, regarding employment outcome, research has
continued to provide confounding evidence regarding the association between gender and
vocational rehabilitation outcome. While some studies have observed that males are more
likely to achieve successful employment outcomes than females (Capella, 2002; Cook &
Roussel, 1989), most studies have found no association between gender and employment
outcome (Corrigan, Reedy, Thadani & Ganet, 1995; Razzano & Cook, 1994). The
similarity in employment outcome in terms of gender evidenced by this study raises a
question concerning the uniqueness of the youth VR population. It is important to
investigate at what age gender becomes a discriminating factor in outcomes achieved in

the state-federal VR system.

The ﬁndings revealed that youth clients receiving public income assistance had
less odds of successful employment outcome than clients who did not receive these
services. The results indicated that the receipt of some public support considerably
reduced the odds of successful employment for youth who received SSI (36% less odds)
and TANF (5 8% less odds). This is consistent with research which has noted the
disincentives associated with the receipt of public income assistance. Contrary to policy
projections that cash incentives would be provided for people with disabilities to
encourage their employment, research has consistently noted that the policy surrounding
income assistance has continued to act as a disincentive to competitive employment
(Berkowitz, 1981; Rutman, 1994; Baron, 1995). However, an interesting ﬁnding from

this study was that only sixteen percent of youth with primary psychiatric disabilities

103

received public income assistance. This is contrary to research assertions noting a high
increase in the number of youth recipients of federal income assistance in recent years
(Social Security Administration, 1999). This ﬁnding may suggest that the almost ﬁfty
percent unemployment trends among youth with psychiatric disabilities may not be
substantially accounted for by the disincentives associated with the receipt of public
income support. A possible explanation of this low frequency in the receipt of public
support could be linked to eligibility criteria. Additional research is needed to clarify the
reasons for low frequency in the receipt of public support for youth with primary

psychiatric disorders in the sample studied.

The ﬁndings of this study suggested that source of impairment or diagnoses was
associated with employment outcome among youth VR consumers with psychiatric
disabilities. Given that there is empirical evidence regarding the associations between
psychiatric symptoms and employment outcome in the state-federal VR system in
rehabilitation literature, this study took the next step by providing information which
describes the uniqueness and typicality of employment outcome among youth with
speciﬁc sources of psychiatric disabilities. Based on descriptive analyses, youth with
depressive disorders (3 8%), mental illness not listed elsewhere (24%) and schizophrenia
(11%) represented the highest proportions of youth VR consumers having psychiatric
diagnosis. Based on the descriptive analysis and logistic regression, the diagnostic
categories of depression, schizophrenia and mental illness not listed elsewhere
represented over seventy percent of the overall population and along with personality
disorders had the most negative impacts on employment outcome. These data should be

given serious consideration based on the fact that complications associated with clinical

104

symptoms of these diagnoses have high probabilities of impacting employment outcome.
For example, research has noted that schizophrenia is one of the most disabling mental
disorders. It has been identiﬁed both as an illness and a disability. Research indicates that
vocational rehabilitation has not made any statistically signiﬁcant impact on the
competitive employment of individuals with schizophrenia (Lehman, 1995). Vocational
employment outcome for this group has remained as low as below 25% (Anthony, 1978).
Research has also observed the pervasive negative impact of depression on employment
outcomes (Kosciulek & Perkins, 2005; Anthony, Ledley & Heimberg, 2005; Anthony et

al, 2005).

In addition, based on clinical reasons, this study used statistical analyses to
compare the outcomes of youth with various psychiatric diagnoses to those of youth with
schizophrenia as reference group. Although numerical strength is often a key
consideration when selecting a reference group, schizophrenia was chosen as a reference
group based on clinical and practical reasons related to its recognition as the most
debilitating psychiatric diagnosis in terms of work. According to Lehman (1995),
vocational rehabilitation is yet to make substantial difference in the employment

outcomes of people with schizophrenia.

Disparities were shown for individual diagnostic groups compared with the
reference group. Based on logistic regression analyses, youth with depressive disorders
and mental illness not listed elsewhere had the least odds of successﬁrl employment
outcomes compared with those with schizophrenia. Youth with other psychiatric
diagnostic categories of disability on the average had only minimal odds of achieving

more successful employment outcomes as compared to youth with schizophrenia. This

105

study’s ﬁnding may provide additional insight into the need to provide uniquely designed

services and support for speciﬁc psychiatric diagnostic groups in the VR system.

In relation to education level at application, signiﬁcant impacts on employment
outcome were found. Contrary to research observations that about 46% of individuals
with mental illness did not complete high school (Adler, 1996), over half of the youth in
this study were recorded as having high school education. In comparing education
categories, youth with higher education had the most odds of successful employment
outcome. With the exception of youth with associate degrees, youth with all other
education levels had on average 90% less odds of successful employment outcome. This
is consistent with McNeil’s (2001) observation that the probability of encountering a
disability or limitation is higher for individuals with lower education. This ﬁnding
becomes critical to vocational rehabilitation when considering the fact that while
bachelors and master’s degree holders comprised a mere .23% of the sample, the most
prevalent groups (secondary education and high school equivalence) comprised 58.3%
and 25% respectively. This is not unexpected as psychiatric symptoms have been noted to
derail education goals or postpone education achievement (Bromet, 2005).This ﬁnding
may suggest that the persistent poor post-school outcome for youth with disabilities
observed by research could be accounted for by their educational attainment (Kosciulek
& Perkins, 2005). From the ﬁndings of this study, one issue that is coming across is that
it may be critical to focus more on understanding the diverse nature of youth with
psychiatric disabilities and the factors that determine their education attainment, in order

to design supports that are responsive to their need. In conclusion, although this research

106

question did not seek to evaluate direction of association, it appeared that education level

at application was a critical determining factor in employment outcome.

In relation to research question 3, the ﬁndings revealed that secondary psychiatric
disability was related to employment outcomes among youth VR consumers. Youth VR
consumers without secondary psychiatric disabilities were more likely to achieve
employment outcomes than those without secondary psychiatric disabilities, after

controlling for services received.

The majority of the individuals with secondary psychiatric disabilities had
depression (39%) and mental illness not listed elsewhere (23%). This was followed by
anxiety (12%) and personality disorders (19%). Youth consumers with schizophrenia
(3 7%) and depression (43%) were least likely to achieve successﬁrl employment
outcome, followed by those with personality disorders (49%) and mental illness not listed
elsewhere (49%). Thus, secondary psychiatric diagnosis appeared to play a role in
employment outcome, particularly in groups with depression, schizophrenia and mental
illness not listed elsewhere. It is important to note that most of the secondary psychiatric
disability diagnoses demonstrated a similar pattern of impact on employment outcome as
did primary psychiatric diagnoses in this study. For example, youth with schizophrenia
(40% less likely) and depression (33% less likely) were the least likely to achieve
employment outcomes. This information is critical to VR as research has observed
likelihood to overlook the impact of secondary psychiatric disabilities on the vocational
rehabilitation outcomes of individuals with physical disabilities. Research has continued
to observe the neglect of secondary mental health needs of individuals with physical

disabilities in the rehabilitation system (Rimmer, 1999; Mechanic & Aiken, 1987). This

107

possibility raises a crucial concern that neglecting the interference of secondary
psychiatric disability may increase the disability burden and predispose VR consumers to
unsuccessful employment outcomes. Responding to this concern would suggest a holistic
approach to VR service provision which will target multiple levels of disabilities in the

same individual in order to enhance successful rehabilitation outcomes.

Limitations

The ﬁrst limitation in this study is the use of secondary data. Despite the obvious
beneﬁts of having a large dataset such as the RSA-911, inability to make causal
inferences limited the conclusions that could be drawn from the ﬁndings. Second, the
RSA-911 data set is limited by its retrospective nature. Third, correct coding of
information given by the subjects depended on the expertise of the rehabilitation
counselors. Fourth, the information used as research data were collected more as service
tools than research tools. It is possible that factors not assessed in this study including
personality dispositions, socio-cultural factors, service provider factors or other
dimensions, could account for increased propensity to achieve successful employment

outcome in the state-federal VR system.

The deﬁnitions in this study were broad and consistent with those used by the
Rehabilitation Services Administration (RSA) but inconsistent with the diagnostic criteria
described in the DSM-IV. Interpreting results regarding diagnostic criteria such as
‘mental illness not listed elsewhere’ and depression as a homogenous disorder is a
concern. Analyses and interpretation of ﬁndings will be practically more meaningful

when standardized tools such as DSM-IV are used for diagnoses of the psychiatric

108

 

conditions experienced by individuals in the VR case load. In the future, researchers
should consider more speciﬁc deﬁnitions of psychiatric conditions and perhaps delineate

how each symptomatology inﬂuence vocational rehabilitation outcomes.

The deﬁnition of ‘youth’ and the often complex eligibility criteria for different
services may have created limitations in this study. The changing criteria for public
income assistance eligibility determination when youth turn 18 years may have accounted
for the low frequency in the receipt of income assistance. Therefore, many of the subjects
who were supposed to be receiving services in the FY 2004 database may have been non

eligible. This may limit the generalizability of the ﬁndings.

Implications

While numerous studies have investigated the factors that are associated with the
employment outcomes of general populations of people with psychiatric disabilities, this
study sought to ascertain these factors among youth populations. By understanding the
factors that are related to their employment outcome in the state-federal VR system,
insight is gained regarding possible service and/or support measures for reducing
unsuccessﬁrl employment outcomes among them. Implications of these discovered

relationships follow.

Implications for Practice

First, the association found between numerous VR services and employment
outcomes among youth with disabilities may indicate a need for rehabilitation counselors

to inform youth consumers of the availability of speciﬁc services which research has

109

identiﬁed as positive predictors of successful employment outcome. This is more critical
given the ﬁnding that the services that were received most by youth in the VR system
were not those that were associated with the highest percentage of successful

employment outcome. The rehabilitation counselor may take the responsibility of guiding
the youth consumers in making intelligent decisions by considering clients’ strengths,
weaknesses, and knowledge of services which ‘work best’ for their unique conditions.
This situation highlights the role of the rehabilitation counselor as an advocate and a
career educator. This is consistent with research which has called for vocational
rehabilitation to move beyond providing employment support services to providing career

development services (Roessler & Rumrill, 1999).

 

A second implication that can be drawn from this study involves the need to
develop a range of VR services that will cover the spectrum of psychiatric disabilities.
Since nearly all the psychiatric diagnostic categories examined impacted employment
outcome, it follows that ignoring any of these might jeopardize the probabilities of
successﬁrl outcome for state-federal VR service recipients. Although vocational
rehabilitation counselors are not mandated to have mental health specializations, it has
been suggested that there may be need for a stronger embedding of holistic VR service
delivery with a range of clearly deﬁned mental health partnerships (Boardman et al.,
2003). This may suggest a need for a clear deﬁnition regarding responsibilities for
providing ongoing mental health supports for individuals with psychiatric disabilities in
the state-federal VR system. The minimum preparation required of vocational
rehabilitation counselors in this context would be an understanding of clinical challenges

and realities related to psychiatric disabilities (Chan et al., 1998).

110

The ﬁndings that suggested that the trend of employment outcome was not
uniform across diagnostic and demographic subgroups are critical to VR service design
and delivery. First, this implies that no one model of service is right for everyone.
Research has noted the episodic and cyclical nature of psychiatric disabilities. In addition,
it has been noted that symptomatology may differ among individuals having similar
psychiatric diagnoses. In order to optimize beneﬁts derivable from VR services, there
may be need for consumers with psychiatric disabilities to have ready access to a range of
work and mental health services and support which are relevant to their changing needs.
The challenge for rehabilitation counselor lies in the need to effectively manage the

ongoing range of partnerships with support services such as mental health, occupational

 

health and primary care, to ensure that the needs of the consumers are met within the

existing VR plan.

Implications for Training

The present ﬁndings have implications for counselor education and training. It
may be important for rehabilitation counselor education to incorporate not only mental
health issues, but also the peculiarities of different populations such as youth, into the
curriculum. The importance of understanding the peculiarities of youth with psychiatric
disabilities in the VR system underscores this training need. First, being ‘unemployed
youth with psychiatric disability’ predisposes them to multiple barriers to successful
outcome in the VR system. Often, they may bring a sense of loss of purpose and structure
into the VR system. Unemployment exposes them to the loss of essential traits such as
social identity status, opportunity for activity and involvement, sense of personal

achievement, social contacts and supports, and means of structuring and occupying time,

111

needed for healthy life adjustment (Shepherd, 1989; Rowland & Perkin, 1988). Added to
these are the peculiar challenges posed by clinical symptoms related to their disabilities.
Vocational rehabilitation providers who understand the multiple challenges which youth
with psychiatric disabilities bring into the system may be more likely to provide
frameworks that facilitate and sustain successful employment outcome among this

population. This understanding could be achieved through formal training.

Implications for Research

This study used quantitative method to analyze the archival RSA-911 dataset.
Although the ﬁndings of this study were similar to most studies which had investigated
the predictors of employment outcome in the state-federal VR system among general
populations, the focus on youth highlighted the need for ﬁrrther research using qualitative
method. For example, more meaningful information would be contributed to the VR
system if the subjects were surveyed qualitatively. It would be easier to understand why
only a little percentage (15%) of youth with psychiatric disabilities received public
income assistance in the FY 2004 dataset despite research assertions that youth in the
public income assistance program are increasing geometrically (SSA, 2000). A
qualitative research design may better explain how the unique experiences of youth with
psychiatric disabilities in the VR system relate with their employment outcome. A
qualitative study may be needed to ascertain the perceptions of youth with psychiatric
disabilities regarding access to services they need in order to have successful employment

OUICOITIC.

112

Additional research is needed to examine the extent to which youth with
secondary psychiatric disabilities receive supports and services in the VR system. The
ﬁndings which suggest that secondary psychiatric disabilities impact employment
outcome in similar ways as primary mental disabilities call for further investigations.
There may be need for face-to-face interviews with consumers having primary and
secondary psychiatric disabilities. A crucial question may address the duration and

intensity of services provided to these youth as support for their disabilities.

Given the limitations related to the ‘narrow’ and speciﬁc nature of the information
stored in the RSA-911, there is need for ﬁrrther exploration of how the background

characteristics which youth with psychiatric disabilities bring into the VR system impact

 

their vocational outcomes. For example, further research is needed to explain why only a
negligible percentage of youth (.23%) attained ‘higher education’ despite the ﬁnding that
support the positive contributions of further education on the employment outcome of
youth in the VR system. In addition, further understanding regarding how the interface of

poverty and race impact vocational outcomes is crucial.

Further research which will use more sophisticated statistical method such as
structural equation modeling (SEM) to examine group and across time variations, causal
and longitudinal changes related to employment outcomes among youth with psychiatric
disabilities in the VR system is needed. A developmental approach to research on youth
may be more informative regarding the underlying mechanisms involved in the
interactions among psychiatric symptoms, VR services, demographic characteristics and

employment outcomes among youth with psychiatric disabilities.

113

Conclusion

In summary, the results of this study have demonstrated that VR services received
and personal background characteristics substantially relate to differences in employment
outcomes among youth with psychiatric disabilities. Moreover, while the focus of this
study was on determining the relationships between the predictor variables and
employment outcome, there is every reason to believe that the ﬁndings would make
valuable contributions to holistic service design and delivery. Such design would
integrate VR services, mental health and psychosocial supports and services as standard

state-federal VR intervention.

The ﬁndings of the present study have identiﬁed that some speciﬁc services such
as job placement demonstrated positive relationships with employment outcome. A
relevant ﬁnding of this study was that youth with psychiatric disabilities received less of
the services which had positive association with employment outcomes. This may mean
that this population of consumers may not be receiving the services that are most
beneﬁcial to their employment outcome. In terms of personal background characteristics,
the ﬁndings of this study demonstrated that the employment outcomes of the youth with
psychiatric disabilities are related to the background baggage which they bring into the
VR system. Although research and practice may have little control over these, the
ﬁndings may suggest a need to incorporate clearly deﬁned psychosocial supports in the
service plan. Overall, the ﬁndings indicate that to encourage successful employment
outcomes among youth with psychiatric disabilities, the integration of mental health and

VR service may need to be an ongoing standard intervention.

114

APPENDICES

Appendix 1: Estimated coefﬁcients for the ﬁnal model along with Wald statistics (chi-
square) and their p-values for assessing signiﬁcance of the coefﬁcients for Employment

Outcomes, Demographic Characteristics, and Services Received.

Analysis of Maximum Likelihood Estimates

Standard Wald
Parameter DF Estimated Error Chi-Square P-value
Coefficients

Intercept 1 -0.9452 0.2167 19.0147 <.0001
PLACVERE 1 1.4389 0.1329 117.2326 <.0001
COLGVERE 1 1.7885 0.1116 257.0721 <.0001
OCCVERE 1 1 0237 0.1230 69.3116 <.0001
RACE 1 1 0 3221 0.0936 11.8342 0.0006
RACE 2 1 -0 1350 0.1036 1.6987 0.1925
RACE 3 1 -0 4483 0.2530 3.1403 0.0764
RACE 4 1 -0 0447 0.2349 0.0362 0.8491
RACE 5 1 0 0202 0.3792 0.0028 0.9576
RACE 6 1 -0 0176 0.1121 0.0248 0.8750
SSI 1 -0 4443 0.1030 18.5936 <.0001
JBSUVERE 1 0 6961 0.1347 26.7182 <.0001
EDUCAPP 0 1 -0 9742 0.4678 4.3376 0.0373
EDUCAPP 1 1 -1 1579 0.2072 31.2442 <.0001
EDUCAPP 2 1 -0 6264 0.1789 12.2562 0.0005
EDUCAPP 3 1 -0 5613 0.1908 8.6554 0.0033
EDUCAPP 4 1 -0 4997 0.1813 7.5964 0.0058
EDUCAPP 5 1 -0 0314 0.2320 0.0183 0.8924
EDUCAPP 6 1 1 6095 0.6861 5.5023 0.0190
MAINVERE 1 0 4672 0.1235 14.3022 0.0002
JSCHVERE 1 0 7846 0.1517 26.7561 <.0001
DIAGRE 1 -0 2836 0.0661 18.4136 <.0001
DIAGREPLACVERE 1 0 4240 0.1192 12.6549 0.0004
TANF 1 -0 8683 0.3327 6.8104 0.0091
MIDIS 1 1 0 1527 0.1025 2.2199 0.1362
MIDIS 2 1 -0 0685 0.0852 0.6463 0.4214
MIDIS 3 1 0 0749 0.3771 0.0395 0.8426
MIDIS 4 1 -0 1094 0.0891 1.5087 0.2193
MIDIS 5 1 0 1129 0.0925 1.4906 0.2221
OTJVERE 1 0.6022 0.1665 13.0757 0.0003
0THRVERE 1 0.6174 0.0890 48.1128 <.0001
COLGVEREOTHRVERE 1 -0.8181 0.1383 34.9710 <.0001
PLACVEREOTHRVERE 1 -0.4015 0.1270 9.9976 0.0016
JSCHVEREPLACVERE 1 -0.4784 0.1391 11.8234 0.0006
JSCHVEREMAINVERE 1 -0.3736 0.1696 4.8521 0.0276
COLGVEREJBSUVERE 1 -0.3935 0.2076 3.5930 0.0580
MISCVERE 1 0.0789 0.1651 0.2283 0.6328
TRANVERE 1 -0.1079 0.1083 0.9919 0.3193
COLGVERETRANVERE 1 -0.4598 0.1439 10.2097 0.0014
MISCVERETRANVERE 1 0.5434 0.1726 9.9152 0.0016
SSIMISCVERE 1 -0.5704 0.2255 6.3999 0.0114
OTJVEREMAINVERE 1 -0.9163 0.3754 5.9566 0.0147
TECHVERE 1 -0.1554 0.2166 0.5150 0.4730
COLGVERETECHVERE 1 -0.7872 0.3802 4.2883 0.0384
JBSUVEREMAINVERE 1 -0.3645 0.1890 3.7194 0.0538
VOCVERE 1 0.4127 0.0878 22.1135 <.0001
VOCVERECOLGVERE 1 -0.7141 0.1287 30.7772 <.0001
VOCVEREPLACVERE 1 -0.3873 0.1393 7.7327 0.0054
VOCVEREOCCVERE 1 -0.2925 0.1447 4.0857 0.0432
PLACVEREJBSUVERE 1 -0.3735 0.1480 6.3716 0.0116
VOCVEREJBSUVERE 1 0.3361 0.1457 5.3251 0.0210
OCCVERETRANVERE 1 -0.3136 0.1433 4.7886 0.0286

115

 

Appendix 1 contd.

Parameter DF Estimated Standard Chi-Square P-Value
Coefficients Error

SSDI 1 0.1928 0.2209 0.7617 0.3828
TRANVEREMAINVERE 1 0.3533 0.1520 5.4047 0.0201
MISCVEREOTHRVERE 1 -0.3026 0.1694 3.1899 0.0741
TANFPLACVERE 1 1.1408 0.4981 5.2448 0.0220
JSCHVERETRANVERE 1 -0.4399 0.1596 7.5937 0.0059
PLACVERETRANVERE 1 0.3535 0.1546 5.2305 0.0222
DIAGREOTJVERE 1 0.5722 0.2743 4.3516 0.0370
SSIMAINVERE 1 0.4566 0.2365 3.7266 0.0536
SSIDIAGRE 1 -0.3038 0.1778 2.9177 0.0876
MISCVEREMAINVERE 1 -0.3274 0.2084 2.4688 0.1161
TANFOTHRVERE 1 —0.8324 0.5539 2.2581 0.1329
JBSUVEREOTHRVERE 1 -0.2672 0.1528 3.0582 0.0803
MISCVEREPLACVERE 1 -0.4336 0.1825 5.6451 0.0175
MISCVEREJSCHVERE 1 0.4294 0.1969 4.7537 0.0292
VOCVEREJSCHVERE 1 -0.2751 0.1522 3.2674 0.0707
COLGVEREJSCHVERE 1 0.2984 0.1774 2.8302 0.0925
INFOVERE 1 —0 3379 0.2393 1.9949 0.1578
OTJVEREINFOVERE 1 -0.8598 0.2954 8.4751 0.0036
SSDIINFOVERE 1 -1.5892 0.5859 7.3580 0.0067
PLACVEREINFOVERE 1 0.2035 0.1668 1.4879 0.2225
SSDICOLGVERE 1 —0.9400 0.4439 4.4849 0.0342
VOCVEREINFOVERE 1 0.4167 0.2310 3.2536 0.0713
OCCVEREINFOVERE 1 -0.3678 0.1811 4.1268 0.0422
MISCVEREINFOVERE 1 0.3274 0.2373 1.9038 0.1676
COLGVEREINFOVERE 1 -0.3391 0.1966 2.9769 0.0845
TANFMAINVERE 1 —0.9600 0.6430 2.2290 0.1354
MAINVERETECHVERE 1 2.1667 1.1745 3.4031 0.0651
TECHVEREOTHRVERE 1 -3.1593 1.2298 6.5999 0.0102
PLACVERETECHVERE 1 1.5155 0.8119 3.4841 0.0620
SSDIPLACVERE 1 -0.4805 0.3242 2.1971 0.1383

116

 

Appendix 2: Logistic regression model for the probability of successful employment
Secondary Psychiatric Disability, personal background factors, Services and Employment
Outcomes and their respective p-values based on Wald (chi-square) statistic.

Analysis of Maximum Likelihood Estimates

Standard wald

Parameter DF Estimate Error Chi-Square Pr > ChiSq
Intercept 1 -0.6778 0.1073 39.8948 <.0001
sd 1 1 0.1483 0.1195 1.5408 0.2145
sd 2 1 -0.2519 0.0982 6.5767 0.0103
sd 3 1 0.5086 0.4833 1.1078 0.2926
sd 4 1 -0.1455 0.1057 1.8955 0.1686
sd 5 1 -0.0420 0.1088 0.1491 0.6994
sd 6 1 -0.5021 0.1543 10.5837 0.0011
EDUCAPP 0 1 -0.3352 0.1454 5.3163 0.0211
EDUCAPP 1 1 -0.5428 0.0667 66.3193 <.0001
EDUCAPP 2 1 -0.2174 0.0478 20.6992 <.0001
EDUCAPP 3 1 -0.2114 0.0506 17.4346 <.0001
EDUCAPP 4 1 -0.2221 0.0497 20.0107 <.0001
EDUCAPP 5 1 0.0530 0.0775 0.4685 0.4937
EDUCAPP 6 1 0.5395 0.1941 7.7227 0.0055
RACE 2 1 0.1008 0.0340 8.7763 0.0031
RACE 3 1 -0.3002 0.0810 13.7367 0.0002
RACE 4 1 -0.0487 0.0770 0.4012 0.5265
RACE 5 1 -0.5061 0.1259 16.1547 <.0001
RACE 6 1 0.0295 0.0373 0.6273 0.4283
RACE 7 1 0.2852 0.0797 12.8158 0.0003
SEX 1 -0.1545 0.0175 77.9455 <.0001
SSI 1 -0.7342 0.0249 867.1122 <.0001
TANF 1 -0.4237 0.0892 22.5490 <.0001
SSDI 1 -0.3535 0.0543 42.4095 <.0001
ASSESSRE 1 -0.0392 0.0188 4.3499 0.0370
DIAGRE 1 -0.2868 0.0216 176.6175 <.0001
VOCVERE 1 0.1851 0.0189 95.6070 <.0001
COLGVERE 1 0.7545 0.0232 1061.7450 <.0001
OCCVERE 1 0.5886 0.0262 504.4072 <.0001
OTJVERE 1 0.4243 0.0399 113.0495 <.0001
LITVERE 1 —0.2024 0.0550 13.5486 0.0002
REDYVERE 1 0.3065 0.0255 143.9634 <.0001
MISCVERE 1 0.3154 0.0250 159.6800 <.0001
JSCHVERE 1 0.4548 0.0243 351.1864 <.0001
PLACVERE 1 1.0653 0.0233 2083.2590 <.0001
JBSUVERE 1 0 5500 0.0269 418.0699 <.0001
TRANVERE 1 -0 1220 0.0236 26.7160 <.0001
MAINVERE 1 0 4248 0.0294 209.0479 <.0001
RHABVERE 1 0 0548 0.0490 1.2509 0.2634
READVERE 1 —0 4762 0.1253 14.4436 0.0001
ATNDVERE 1 -0 5551 0.1302 18.1727 <.0001
TECHVERE 1 -0 4334 0.0569 58.0958 <.0001
INFOVERE 1 -0 1077 0.0279 14.8852 0.0001
0THRVERE 1 0 3432 0.0220 242.4383 <.0001

117

Effect

EDUCAPP
EDUCAPP
EDUCAPP
EDUCAPP
EDUCAPP
EDUCAPP
EDUCAPP
RACE
RACE
RACE
RACE
RACE
RACE

SEX

SSI

TANF
SSDI
ASSESSRE
DIAGRE
VOCVERE
COLGVERE
OCCVERE
OTJVERE
LITVERE
REDYVERE
MISCVERE
JSCHVERE
PLACVERE
JBSUVERE
TRANVERE
MAINVERE
RHABVERE
READVERE
ATNDVERE
TECHVERE
INFOVERE
OTHRVERE

VO‘WAWNO‘WBWNHOO‘WAWNH

odds Ratio Estimates
95% Wald

Point

ooooooooooooxrwxrwxrwwxixrxrxrxixr

Estimate
0.

873

0.585

I-‘OOOOI-‘l-“Ol-d!\Jli--*I-‘l-‘Olm'l-‘Nl--'CDCOOOOOOOOOOOCDOOOC)CDCDCDOIHI

.251
.650
.721
.455
.280
.228
.315
.317
.314
.413
.672
.713
.477
.614
.388
.664
.857
.857
.480
.655
.702
.962
.751
.203
.127
.801

118

Confidence Limits
0.720 1.058
0.523 0.653
0.415 3.770
0.564 0.751
0.618 0.842
0.338 0.613
0.160 0.493
0.141 0.369
0.197 0.505
0.198 0.509
0.196 0.503
0.253 0.675
0.357 1.268
0.683 0.744
0.400 0.569
0.520 0.724
0.292 0.516
0.628 0.702
0.721 1.018
0.828 0.887
0.457 0.504
0.550 0.780
0.631 0.781
0.927 0.998
0.720 0.783
1.160 1.249
2.032 2.225
1.711 1.896
1.414 1.653
0.733 0.910
1.292 1.428
1.305 1.440
1.503 1.653
2.772 3.037
1.644 1.827
0.845 0.927
1.444 1.620
0.960 1.163
0.486 0.794
0.445 0.741
0.580 0.725
0.850 0.948
1.350 1.472

Appendix 3: Full Names for Abbreviated Variables in Maximum Likelihood Ratio Tables

Abbreviated

Placvere
Colgvere
OCCvere
Race 1
Race2

Race 3
Race 4
Race 5
Race 6
Race 7
SSI
SSDI

TANF

JBSUvere
Mainvere
JSCHvere
DIAGRE
MIDIS 1
MIDIS 2
MIDIS 3
MIDIS 4

MIDIS 5

MIDIS 6
SD
OTJver
OTHRver
MISCvere
TRANvere
VOCvere
ASSESSre
Litvere
Redyvere

Full Names

Job placement assistance services

College or University training services
Occupational/Vocational training services
White

African American/Black

Native American/Alaska Natives

Asian

Native Hawaiian/ other paciﬁc Islander
Hispanic/ Latino

Multiracial

SSI-aged, blind, disabled at application
Social Security Disability Insurance at
application

Temporary assistance for needy families at
application

On-the-job supports

Maintenance services

Job search assistance services

Diagnosis and treatment services
Anxiety( primary mental illness)
Depression( primary mental illness)
Eating Disorder( primary mental illness)
Mental illness not listed elsewhere(
primary mental illness)

Personality disorder ( primary mental
illness)

Schizophrenia and primary mental illness)
Youth with non-psychiatric disabilities
On-the-job training

Other services

Miscellaneous training services
Transportation services

Voc rehabilitation counseling& Guid.
Assessment services

Basic remedial or literacy services

Job readiness training services

119

Augmere Augmentative skills training services

Rhabvere Rehabilitation technology services
MI Not Mental illness not listed elsewhere
Figure 1

Deviance Residual for Checking Logistic Regression Models for Research Questions One

and Two

 

deviance residul
0
l

 

 

 

I I I I I I

0.0 0.2 0.4 0.6 0.8 1.0

predicted value

120

 

 

 

Figure 2

Deviance Residual for Checking the Logistic Regression Model for Research Question

Three

 

 

 

 

3
+
#1
2'1
I
11
o:
.11
-21
4 4
-3 IT'E l r 1 I - | I l I III I r I I I I T I 1 1 1 1 I I_“l 1 | I l I 1 I TI—IirI
0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0

FstinledROde'lity

121

 

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