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F 73 This is to certify that the dissertation entitled AN EXAMINATION OF EMPLOYMENT OUTCOMES FOR INDIVIDUALS WITH SPINAL CORD INJURY SERVED BY THE STATE VOCATIONAL REHABILITATION SERVICES PROGRAM BETWEEN 2004 AND 2008 presented by Barbara Schoen has been accepted towards fulfillment of the requirements for the Doctoral degree in Rehabilitation Counselor Education + Major Professor’s Signature 8,420.. IO Date MSU is an Affinnative Action/Equal Opportunity Employer LIBRARY Michigan State Universuy PLACE IN RETURN BOX to remove this checkout from your record. TO AVOID FINES return on or before date due. MAY BE RECALLED with earlier due date if requested. DATE DUE DATE DUE DATE DUE 5/08 KIProj/Acc8Pres/CIRC/Date0ue.indd AN EXAMINATION OF EMPLOYMENT OUTCOMES FOR INDIVIDUALS WITH SPINAL CORD INJURY SERVED BY THE STATE VOCATIONAL REHABILITATION SERVICES PROGRAM BETWEEN 2004 AND 2008 By Barbara Schoen A DISSERTATION Submitted to ' Michigan State University in partial fulfillment of the requirements for the degree of DOCTOR OF PHILOSOPHY Rehabilitation Counselor Education 2010 ABSTRACT AN EXAMINATION OF EMPLOYMENT OUTCOMES FOR INDIVIDUALS WITH SPINAL CORD INJURY SERVED BY THE STATE VOCATIONAL REHABILITATION SERVICES PROGRAM BETWEEN 2004 AND 2008 By Barbara Schoen The purpose of this study was to gain an increased understanding of the demographic, service related and outcome variables that reflect characteristics of customers with a SCI who completed a plan and received services through the public rehabilitation system between 2004 and 2008. This study focuses directly on the 23,135 individuals with an SCI who closed in status 26 or 28 between 2004 and 2008. The analysis used RSA911 data and through the use of statistical methodologies including data mining techniques detected and examined variables suggested to be predictors of employment for this population of study. The majority of study participants were male (65.0%). While on the surface this appears as an over representation of males the opposite is true as males represent over 80.0% of the population of individuals with SCI (NSCISC, 2009) but only 65.0% of study participants. Women had a Slightly better employment outcome on average, with 51.8% of women employed at closure as compared to 49.8% of their male counterparts While White or Asian customers make up 71.1% of customers served, 74.5% achieved a positive employment outcome. Hispanic customers achieved a Slightly higher than average outcome, representing 8.8% of customers served and 9.0% of customers with a positive employment outcome. The reverse is true for African American or Black and All Other Race customers. African American or Black customers comprised 17% of customers and only 13.8% of those employed at closure and finally All Other Races represented 3% of customers and 2.7% of those employed. Chi-square and exhaustive CHAID findings suggest the most significant predictors of employment were level of education attained at closure, cost of purchased services, days from application to closure, the delivery of rehabilitation technology and job placement assistance services and the use of supports at closure. While findings indicate a positive linear relationship between level of education and employment outcome additional study findings suggest that other variables are strong mediators as well. Regardless of education level other factors including cost of purchased services and the number of years from application to closure were found to impact employment outcome as well. Copyright by BARBARA SCHOEN 2010 ACKNOWLEGEMENTS It is a genuine pleasure to thank my advisor and dissertation chair, Dr. Michael Leahy, who has provided great guidance and been a constant source of support through this process. I would also like to thank Dr. Virginia Thielsen who has provided continuous support; her extensive knowledge of the RSA-9ll database allowed for great depth in the analysis. Without Drs. Leahy and Thielsen’s support this dissertation would not have been possible. My final two committee members were excellent sources of support as well. Dr. John Kosciulek provided great insight in the use and value of classification trees and data mining techniques and Dr. Nancy Crewe was a great resource in working with the population of individuals with spinal cord injury. I truly believe I had the dream team in the field of rehabilitation counseling guiding my progress and the overall process which carries great promise for my research but also great responsibility. In addition to my committee members, Alice Meshbane provided guidance as a statistician and was instrumental throughout the development of my dissertation. Dr. Timothy Tansey provided great guidance during the planning stages of my dissertation and Eniko Rak was helpful in providing a critical eye in the later stages. AS Peggy Tabor Millin said, “We never touch people so lightly that we do not leave a trace”. There are many people in my life that have left great traces. First of course is my family and circle of friends who encouraged me when my courage waned. Drs. Denise Tate and Claire Kalpakjian who were instrumental in guiding me toward doctoral studies; and Cynthia Banton, Sandy Zawacki, Dawn Ybarra and many others at AllState who kept me in good hands so that I could pursue and achieve my goals. 1 thank you all. TABLE OF CONTENTS LIST OF TABLES ....................................................................................... viii CHAPTER 1 INTRODUCTION ..................................................................................... 1 Background and Descriptive Epidemiology ............................................... 1 Statement and Significance of Problem .................................................... 2 Purpose of the Study .......................................................................... 5 Definition of Terms .......................................................................... 6 CHAPTER 2 REVIEW OF THE LITEILATURE ................................................................. 8 Demographic Profile of Individuals with SCI ............................................ 9 Agencies Providing Services to Individuals with SCI ................................. 14 Research Investigating Factors Related To the Employment of Individuals with SCI ...................................................................................... l6 Physiological Factors .............................................................. 16 Psychosocial Implications ......................................................... 17 Factors Impacting Post-Injury Employment Outcomes ....................... 19 Education ................................................................... 20 Race ......................................................................... 20 Gender ...................................................................... 22 Assistive Technology ..................................................... 23 CHAPTER 3 METHODOLOGY ................................................................................... 26 Data Source .................................................................................. 26 Study Design ................................................................................. 27 Participants .............................................................................. . ..... 28 Variables ..................................................................................... 29 Dependent Variable ............................................................... 29 Independent Variables ............................................................ 29 Data Analysis .......................................................................................... 32 vi CHAPER 4 RESULTS ............................................................................................. 34 Main Population of Study and Summary of Customers Served ............................... 34 Research Question One: Characteristics, Service and Outcome Variables of Customers with SCI .................................................................................. 36 Research Question One (Part Two): Characteristics, Service and Outcome Variables of Customers with SCI Analysis by Year ............................................. 48 Research Question Two: An Analysis of Outcomes (type of closure) based on Characteristics for this Population ................................................................. 69 Research Question Two (Part Two): An Analysis of Outcomes (type of closure) based on Characteristics for this Population Analysis by Year ................................ 83 Research Question Three (Part One): Predictor Variables Associated with Status 26 or 28 Outcomes for Customers with SCI ............................................. 108 Research Question Three (Part Two) Analysis of Five Year Patterns of Change in Significant Predictor Variables .................................................................... 158 CHAPTER 5 DISCUSSION ....................................................................................... 161 Characteristics of Customers with SCI Served by the VR System and the Significant Changes in Customer Profiles between 2004 and 2008 ....................................... 161 Differences in Outcomes (Type of Closure) based on Characteristics for This Population including Changes in Customer Employment Outcomes over a Five Year Span ....................................................................................... 165 An Analysis of the Allocation and Patterns of Change of Predictor Variables... ...........169 Comparison of Study Findings with Previous Research ....................................... 171 Assumptions and Limitations of the Study ...................................................... 174 Conclusions .......................................................................................... l 75 Implications for Future Research ................................................................. 176 Implication for Rehabilitation Counselors and Policy Directors ............................. 177 APPENDICES ...................................................................................... 179 REFERENCES ..................................................................................... 188 Vii Table 1 Table 2 Table 3 Table 4 Table 5 Table 6 Table 7 Table 8 Table 9 Table 10 Table l 1 Table 12 Table 13 Table 14 Table 15 Table 16 Table 17 Table 18 LIST OF TABLES Customer Intake, Service and Outcome Variables ............................ 31 Descriptive Statistics for Type of Closure by Group ......................... 35 Customer Characteristics at Application ....................................... 37 Education and Employment-Related Characteristics of Customers at Application .......................................................... 39 Customers Supports at Application ............................................. 41 Cost of Goods and Purchased Services ......................................... 42 Number and Percent of SCI Customers Receiving Services ................. 43 Education and Employment-Related Characteristics of Customers at Closure ............................................................... 45 SCI Customer Supports at Closure .............................................. 47 SCI Customer Characteristics by Year .......................................... 49 Level of Education and Employment Characteristics of SCI Customers at Application, by Year ............................................... 51 SCI Customer Supports at Application, by Year .............................. 54 Cost of Goods and Purchased Services by Year ............................... 57 Number and Percent of Customers Receiving Services, by Year ........... 59 Education and Employment-Related Characteristics of SCI Customers at Closure, by Year ................................................... 62 SCI Customer Supports at Closure, by Year ................................... 66 Customer Characteristics by Type of Closure ................................. 70 Level of Education and Employment Characteristics of Customers at Application, by Type of Closure ................................. 73 viii Table 19 Table 20 Table 21 Table 22 Table 23 Table 24 Table 25 Table 26 Table 27 Table 28 Table 29 Table 30 Table 31 Table 32 Table 33 Table 34 Customer Supports at Application, by Type of Closure ...................... 75 Cost of Goods and Purchased Services by Type of Closure .................. 77 Number and Percent of Customers Receiving Services, by Type of Closure .................................................................... 78 Level of Education and Employment Characteristics of Customers at Closure, by Type of Closure ...................................... 80 Customer Supports at Closure, by Type of Closure ........................... 82 Customer Characteristics by Year and Type of Closure ....................... 84 Level of Education and Employment Characteristics of Customers at Application, by Year and Type of Closure ..................... 87 Customer Supports at Application, by Year and Type of Closure .......... 92 Cost of Goods and Purchased Services by Year and Type of Closure. . ....96 Number and Percent of Customers Receiving Services, by Year and Type of Closure ......................................................... 98 Level of Education and Employment Characteristics of SCI Customers at Closure, by Year and Type of Closure ........................ 101 Customer Supports at Closure, by Year and Type of Closure ............. 105 Variables with a Statically Significant Outcome Variance ................ 109 Gains chart (node-by-node) statistics for the 60 end groups ............... 151 SCI Customer Characteristics by Year ....................................... 162 SCI Customer Population Compared to National Averages ............... 163 Figure 1 Figure 2 Figure 3.1 Figure 3.2 Figure 4.1 Figure 4.2 Figure 4.3 Figure 4.4 Figure 4.5 Figure 5.1 Figure 5.2 Figure 5.3 Figure 5.4 Figure 6.1 Figure 6.2 LIST OF FIGURES Vulnerable Population Model ................................................ Partial tree of outcome predictors for customers with No Formal Schooling - Elementary Education Grades 1 thru 8 ............. Partial tree depicting outcome predictors for customers with no high school diploma grades 9 thru 12 (Part 1) ......................... Partial tree depicting outcome predictors for customers with no high school diploma grades 9 thru 12 (Part 2) ......................... Partial tree depicting outcome predictors for customers with Special Ed Cert of Comp or High School Grad Equiv (Part 1).. . . . . . .. Partial tree depicting outcome predictors for customers with Special Ed Cert of Comp or High School Grad Equiv (Part 2) .......... Partial tree depicting outcome predictors for customers with Special Ed Cert of Comp or High School Grad Equiv (Part 3) .......... Partial tree depicting outcome predictors for customers with Special Ed Cert of Comp or High School Grad Equiv (Part 4) .......... Partial tree depicting outcome predictors for customers with Special Ed Cert of Comp or High School Grad Equiv (Part 5) .......... Partial tree depicting outcome predictors for customers with a Post-Secondary Education, no degree (Part 1) ........................... Partial tree depicting outcome predictors for customers with a Post-Secondary Education, no degree (Part 2) ........................... Partial tree depicting outcome predictors for customers with a Post-Secondary Education, no degree (Part 3) ........................... Partial tree depicting outcome predictors for customers with a Post-Secondary Education, no degree (Part 4) ........................... Partial tree depicting outcome predictors for customers with an Associates Degree or Vocational Technician Certificate (Part 1)... . Partial tree depicting outcome predictors for customers with an Associates Degree or Vocational Technician Certificate (Part 2).. . ...... 3 ...113 ...115 ...117 ....119 ..121 I23 125 127 129 131 133 135 137 139 Figure 7.1 Figure 7.2 Figure 7.3 Figure 8.1 Figure 8.2 Figure 8.3 Partial tree depicting outcome predictors for customers with a Bachelors Degree (Part 1) ..................................................... 141 Partial tree depicting outcome predictors for customers with a Bachelors Degree (Part 2) ..................................................... 143 Partial tree depicting outcome predictors for customers with a Bachelors Degree (Part 3) ..................................................... 145 Partial tree depicting outcome predictors for customers with a Masters Degree (Part 1) ....................................................... 147 Partial tree depicting outcome predictors for customers with a Masters Degree (Part 2) ....................................................... 149 Partial tree depicting outcome predictors for customers with a Masters Degree (Part 3)......... ............................................................. 151 xi CHAPTER I Introduction Background and Descriptive Epidemiology Traumatic spinal cord injury (SCI) has been considered one of the most severe and devastating physical impairments (Basso, 2000; Inge, Wehman, Kregel, & Sherron- Target, 1996) as it significantly impacts socialization, employment and quality of life (Dijkers, 2005; Krause & Pickelsimer, 2008; North, 1999). There are several factors that may contribute to the severity of this disability such as the direct physiological and psychosocial implications of SCI, secondary conditions, a lack of direct services, and physical and attitudinal barriers (McKinley, Jackson, Cardenas & DeVivo, 1999; Meyers, Mitra, Walker, Wilber & Allen, 2000; Weaver, Guihan, Pape, Legro, LaVela & Collins, 2001; Wehman, Wilson, Parent, Sherron-Targett, & McKinley, 2000). Approximately 12,000 individuals acquire and survive spinal cord injuries each year. An estimated 259,000 individuals with SCI currently live in the United States (National Spinal Cord Injury Statistical Center [N SCISC], 2009). According to recent statistics, the average age at injury is 40 with the majority being Caucasian (66.1%), male (80.9%), and most frequently injured as a result of a motor vehicle accidents (42.1%) or falls (26.7%) (N SCISC, 2009). While 57.5% are employed at the time of injury, only 1 1.5% are employed one year post injury with just over 35% employed 20 years later (NCSCISC, 2009). In addition, employment figures for individuals with SCI are consistently below the national employment average for all individuals with any disability (reported at 36.0% for 2007) (Meade, Armstrong, Barrett, Ellenbogen, & Jackson, 2006; US. Census Bureau, 2007). Several studies also suggest women and individuals of color with SCI may face additional barriers to employment based on their minority status (Jackson, et al., 2006; Young, et al., 1994). Employment for individuals with SCI is important for a number of reasons. First, employment has been reported to provide identity and impact self-esteem (Rice, Near, & Hunt, 1980; Waters & Moore, 2000). Second, employment can help to accommodate costs often associated with SCI including attendant care, medical supplies and assistive technology (Krause & Terza, 2006). Finally, researchers have suggested that individuals like those with SCI who experience a disparity in resources impacted by employment have an increased vulnerability for increased morbidity and premature death (Aday, 1994; Flaskerud & Winslow, 1998; Krause, DeVivo & Jackson, 2004). Statement and Significance of the Problem Spinal cord injury is categorized as a severe disability statistically associated with lower rates of employment and income (Basso, 2000; Meade, et al., 2006; Wehman et al., 2000). The culmination of these potential disparities creates an amplified risk that place individuals like those with SCI in a state of vulnerability. The vulnerable population model developed by Aday (1993) and F laskerud and Winslow (1998) provides a framework to better understand the collective disparities and the detrimental interrelationships affecting at-risk populations including individuals with SCI. As reflected in Figure 1 this model identifies the core categories as resource availability, relative risk and health status. Resource availability refers to socioeconomic and environmental resources. Relative risk refers to the proportion of individuals with poor health who lack resources and are exposed to risk to those with resources and free from risk. Finally, health status refers to the absence of disease including physical, mental and social well-being (Leight, 2003). Limited Resources Escalates Risk Resource Availability Relative Risk Risk Impacts Poor Health Health Impacts Resources Health Status Figure 1. Vulnerable Population Model This model illustrates a cycle of reciprocity that serves to increase the risk and vulnerability associated with disabilities such as SCI and amplifies the need to understand the relationship between customer demographics and vocational service delivery to determine the effectiveness of and improvement in employment outcomes for customers with SCI. The Rehabilitation Services Administration (RSA) is the federal organization charged with the duty to serve individuals with disabilities (Leahy & Szymanski, 1995) through the provision of funds to state Vocational Rehabilitation (VR) agencies to afford employment-related services for individuals with disabilities (Rehabilitation Services Administration, n.d.). Bruyere & Houtenville suggest that data such as the (RSA-9l I) data collected by state VR services can validate service needs and assess the resultant service impact (2006). In a review of existing research there has been increased attention on the disparities in employment experienced by individuals with SCI; however, there is a lack of research investigating whether improvements in outcomes are being experienced by individuals with SCI served by state VR agencies. A study by Krause & Pickelsimer (2008) examined factors impacting employability for 343 participants with spinal cord injury in 1998 and 2002. However, the population of study was recruited from Midwestern rehabilitation hospitals and a large specialty hospital in the Southeastern United States and did not directly focus on employment services from state VR’s (Krause, et al., 2008). Another study examined employment outcomes for 10,901 persons with spinal cord injury who received services from state VR agencies however the study was limited to fiscal year 2001 (Marinia, Lee, Chan, Chapin, & Romero, 2008). Gilmore, Schuster, Timmons, and Butterworth (2000) used RSA—911 data to perform a longitudinal analysis of trends in VR services from 1985 to 1995 but the population of study was people with mental retardation, cerebral palsy, and epilepsy. One final study used RSA-9ll data to examine the effect of vocational rehabilitation services on employment outcomes but their population of study included three different disability groups (Dutta, Gervey, Chan, Chou & Ditchman, 2008). A review of literature to date suggests that no studies have examined five year service delivery patterns for customers with SCI served by the Rehabilitation Services Administration. Understanding the ongoing effectiveness of supports received by individuals with SCI seeking employment may assist counselors and agencies in providing the most effective resources to maximize outcomes for customers with SCI. Purpose of the Study The purpose of this study was to gain an increased understanding of the demographic, services related and outcome variables that reflect characteristics of customers with a SCI who completed a plan (IPE or Individualized Plan for Employment) and received services through the public rehabilitation system between 2004 and 2008. The analysis used RSA911 data for 2004 through 2008 and through the use of statistical methodologies including data mining techniques detected and examined variables suggested to be predictors of employment for this population of study. The research questions to be addressed in this proposed study are: 1. What are the characteristics of customers with SCI served by the VR system? a. Have the characteristics of customers with SCI served by the VR system changed over the five (5) year span? 2. Are there differences in outcomes (type of closure) based on characteristics for this population and have they changed over the five (5) year span? 3. What are the factors (characteristics and/or services?) associated with positive outcomes for customers with SCI? a. Is there a recognizable pattern displaying an increase in the service provisions most often associated with positive outcomes for customers with SCI? Definition of Terms Competitive Employment- As specified by Technical Regulations Circular RSA-TAC- 06-01 the definition to be used by State VR’s in defining competitive employment is the 34 CFR 361.5(b) ( l 1) description of “competitive employment” which defined work to mean: “(i) In the competitive labor market that is performed on a full-time or part-time basis in an integrated setting; and (ii) For which an individual is compensated at or above the minimum wage, but not less than the customary wage and level of benefits paid by the employer for the same or similar work performed by individuals who are not disabled” (2005, p. 3). Rehabilitation Services Administration (RSA): The State-Federal VR agency mandated by the Rehabilitation Act that oversees formula and discretionary grant programs that help individuals with physical, sensory or mental disabilities to obtain employment and live more independently through the provision of such supports as counseling, medical and psychological services, job training and other individualized services. RSA’S major Title 1 grant program provides funds to state vocational rehabilitation (VR) agencies to provide employment-related services for individuals with disabilities, giving priority to individuals who are significantly disabled (RSA, n.d.). Spinal Cord Injury (SCI): A disturbance of the spinal cord that results in loss of sensation and mobility (Palmer, Kriegsman, & Palmer; 2000). SCI is also defined as an acute traumatic lesion of neural elements in the spinal canal that results in temporary or permanent sensory deficit motor deficit, and/or bladder dysfunction (Hedrick, Pape, Heinemann, Ruddell, & Reis; 2006). CHAPTER 2 Review of the Literature A spinal cord injury (SCI) is a multifaceted disability that requires a significant amount of supports and services and affects much more than an individual’s mobility. To live well and barrier free often requires home modifications, accessible transportation, assistive technology and support from others. Many of these supports and services are expensive and may become obsolete or degrade over time creating an environment of continued need for financial funding. For almost a century many of those serving individuals with a disability have purported that employment is an effective method to insure an individual’s self sufficiency. This chapter presents a review of the literature on the return to work related needs and experiences of individuals with SCI. To gain a greater understanding of these needs and experiences, this chapter will specifically review literature related to: (a) factors associated with a spinal cord injury including the current demographic profile of individuals with SCI as well as the physiology of SCI and associated health care and accommodations needs (b) agencies charged with the duty to provide services to and/or study the needs of persons with SCI, (c) a comprehensive review of research investigating factors related to the employment of individuals with SCI, and (d) the need for further analysis of factors associated with the employability of individuals with SCI including an analysis of recent trends associated with the service and employment outcomes of those served through the State Vocational Rehabilitation System. Demographic Profile of Individuals with SC] The National Spinal Cord Injury Statistical Center (NSCISC) estimates that as of 2008 there are approximately 259,000 individuals with SCI living in the United States and of those, more than 80% are male (2009). The average age at the time of injury has recently shifted from 28 years of age in 1979 to 40 years of age in 2005 which may be attributed to many factors including a general increase in longevity and survival rates of older individuals at the scene of the accident (NSCISC, 2009). Also shifts in prevalence by race have occurred between 1979 and 2005; Caucasians decreased by 10% (66.1%) while African Americans nearly doubled (27.1%) and Hispanics saw an increase of 2% (8.1%) (N SCISC, 2009). These changes can partially be attributed to general shifts in population as census data from 1979 and 2008 indicates that aggregate population of whites decreased by almost 5% and African American or Blacks increased by nearly 2%. Changes in Hispanic and Asian populations cannot be determined because 1979 census data combined all other races (US. Census Bureau, 1979; US. Census Bureau, 2008). According to the National Spinal Cord Injury Statistical Center (NSCISC) the occurrence of SCI due to motor vehicle crashes is fairly consistent and accounts for 42.1% of reported SCI cases (2009). The proportion of sports-related injuries has decreased over time while the proportion of injuries due to falls has increased (N SCISC, 2009). In 1980 acts of violence resulted in 13.3% of SCI injuries, a spike between 1990 and 1999 brought the level to 24.8% before declining to it current level (15.1%) since 2005 (N SCISC, 2009). The majority of individuals with SCI (87.1%) return to residential non-institutional homes with just under 6% discharged to nursing homes (NSCISC, 2009). Still shortened hospital stays and scarce resources result in many patients being discharged without adequate self-care training, durable medical equipment, home modifications and community services (Kelly, 2007). Because a spinal cord injury impacts multiple systems including musculoskeletal, circulatory, respiratory and skin, there are significant health maintenance needs and increased risk for secondary conditions including pneumonia, deep venous thrombosis (DVT), pulmonary embolus, pressure ulcers, urinary tract infections, spasticity, autonomic dysrefiexia, renal calculi and fractures (McKinley, et al., 1999; Meyers, et al., 2000). This is an area of particular concern as F laskerud & Winslow (1998) suggest that morbidity may create an ongoing cycle of reciprocity that depletes the availability of resources and increases the risk of morbidity and mortality. Resources at risk include jobs, income and health insurance (Blane, Davey, Smith, & Bartley, 1993). A 1996-1997 Household Survey reported by F laskerud and colleagues, (2002) found low-income families were more likely to report worsening access to health care. Premature mortality is a serious concern for many with SCI. Individuals with tetraplegia or injury to the cervical section of the spine (e. g., neck) acquired at an early age (e.g., 20 years old) may die on average 20 years earlier than those without injury and seven years earlier than those with paraplegia (NSCISC, 2009). A study by Saunders and colleagues (2009) found that certain populations including African American or Blacks, persons younger than 25 or older than 64 years of age, and residents in a rural area were at higher odds for death. Two additional studies suggest a direct correlation between income and mortality. In an evaluation of data from the NSCISC, Krause, Devivo & 10 Jackson (2004) reported that economic self-sufficiency increased the percentage of normal life expectancy more than 13%. A second study found that participants with an income of at least $75,000, “were 4.5 times more likely to have survived over the 6—year period than participants whose annual income was $25,000 or less” (Krause & Terza, 2006, p. 4). Such findings are especially concerning as accommodations addressing mobility impairments are numerous and costly. Durable medical equipment for activities of daily living (ADL) generally include manual and/or power wheelchairs, shower chairs, bed lifts, home and vehicle modifications (Krause & Terza, 2006). Berkowitz and colleagues (1998) reported that home modifications for people with SCI averaged $21,000 (in 1996 dollars) in modifications including constructing ramps (83%), widening doors (57%), and remodeling bathrooms (46%) or other rooms in the house (43%). Accessible and reliable transportation is another significant concern for individuals with SCI (Fletcher, Garasky, & Jensen, 2002). Lack of transportation was identified by Whiteneck and colleagues (2004) as a main barrier for individuals with SCI. In fact the employment rate for people who could drive and had a vehicle adapted for independent driving was 40%, compared with 12% for those who did not (Berkowitz, et al., 1998; Jang, Wang, Wang, 2005). As noted, mobility limitations are significant, but they are only a part of a complex set of needs which signify SCI as a severe disability (Inge, et al., 1996). Injury to the spinal cord at any level most frequently impairs the functioning and emptying of the bladder and bowel; requiring medical and personal assistance for some (Wehman, et al., 2000; Hampton, 2004). Blackwell reported that approximately half of individuals with SCI require some type of personal assistance with daily care (2001). Average estimated 11 annual costs for attendant care exceeded $21,000 (in 1996 dollars) with over half (61%) being paid assistance and the remainder provided by family members or others without direct payment (Berkowitz, et. al., 1998). For an individual injured early in life (e. g. 25 years old) lifetime costs may exceed three million dollars excluding indirect costs such as losses in wages, associated benefits and productivity averaging $64,443 per year in December 2008 dollars (N SCICS, 2009). The totality of these factors has a collective effect that serves to limit an individual’s ability to obtain adequate resources, maximize health and locate and maintain employment. The vulnerable population model developed by Aday (1993), Flaskerud and Winslow (1998) provides a framework to better understand the collective disparities and the detrimental interrelationships affecting at-n'sk populations including individuals with SCI. As reflected earlier this model illustrates a cycle of reciprocity that serves to increase the risk and vulnerability associated with disabilities such as SCI (Figure 1). The first association in the model between resource availability and relative risk suggests limits in resources amplify relative risk, (e.g., exposure to risk factors). Socioeconomic and environmental resources significantly impact an individual’s capacity to circumvent risks and reduce disease and its effect (Aday, 1993; Flaskerud & Winslow, 1998). The model’s second relationship outlines the impact of relative risk on health status. “Increased exposure to risk factors leads to increased morbidity and mortality in a population group. Morbidity and mortality may also impact exposure to risk factors” (Flaskerud & Winslow, 1998, p. 72). The final relationship in the model is between 12 health status and resource availability. From a community perspective morbidity and mortality has a collective effect that may feed back into resource availability and further deplete the availability of resources (F laskerud & Winslow 1998). This explanation postulates that poor health status in turn diminishes socioeconomic and environmental resources social connectedness, employability and associated resources including health insurance (Blane, Davey, Smith, & Bartley, 1993). This model further demonstrates the importance of a secure funding stream for individuals to live well with SCI. Since the establishment of the Smith Fess Act (PL. 236, Civilian Vocational Rehabilitation Act) nearly a century ago society, government and business entities have understood the importance of employment for individuals with disability to maintain self sufficiency and an adequate quality of life (Rubin & Roessler, 2001). The rehabilitation philosophy is based on the “dignity and worth of all people” (Maki & Riggar, 1997, p. 5). Within the framework of this philosophy is the commitment to empower individuals with disabilities by providing them with integrated comprehensive services that foster independence, integration, employability and community and societal inclusion (Jenkins, Patterson & Szymanski, 1992). A twenty year longitudinal study by Crewe found that 84% of the study participants received and reported satisfaction with the employment and education support they had received through their state VR agencies (2000). Addressing factors associated with employment is important for several reasons. In addition to affecting the individuals with disabilities, society at large is affected as well. Unemployment is associated with increased expenditures in unemployment l3 insurance, Supplemental Security Income (881) and Social Security Disability Income (SSDI). In December 2008, over 8.5 million people received Social Security disability benefits as disabled workers, disabled widow(er)s, or disabled adult children (SSA Publication No. 13-11826, 2009). In September 1999, there were nearly 4.9 million workers with disabilities receiving SSDI benefits and an additional 3.6 million working age adults were receiving 881 benefits, a combined total of 8.6 million SSl/SSDI beneficiaries according to Social Security Administration (2000). Agencies Providing Services to Individuals with SCI The National Institute of Disability and Rehabilitation and Research (NIDRR) funded through the National Institute of Health is a key organization charged with research and data collection for individuals with disabilities and has a further focus on the SCI population. Since 1985 they have overseen the Model Spinal Cord Injury Care System, currently administering 14 model systems throughout the country that are charged with supporting model projects aimed at establishing innovative projects for the delivery, demonstration and evaluation of comprehensive medical, vocational and other rehabilitation services to meet the wide range of needs of individuals with spinal cord injuries (http://www.naric.com/research/pd/type.cfm). The Rehabilitation Services Administration (RSA) is the federal organization charged with the duty to serve individuals with disabilities (Leahy & Szymanski, 1995). Funds through the title I formula grant program are made available to state VR agencies to provide employment-related services for individuals with disabilities; priority is given 14 to individuals with significant disabilities (http://www.ed.gov/print/about/offices/list/osers/rsa/about.html). The state VR’s (as mandated by the Rehabilitation Act) collect customer demographic and service provision information annually. Systematic reporting of VR customers through the utilization of the Case Service Reporting System was put into practice and strengthened in response to Vocational Rehabilitation Act Amendments of 1954 and Regulations issued in 1966 (Walls, Misra & Majumder, 2002). The Rehabilitation Act facilitated the further enhancement of SRS-RSA-300 and required the collection and dissemination of periodic statistical data (Posavec & Carey, 1985) that reported on all phases of the rehabilitation process; “from first referral to final closure" (Walls, et al., 2002, p. 4). A new Case Service Report System (Form RSA-911) which replaced the earlier reporting system was approved in 1986 and has continued to change in response to new data reporting and researcher needs (Walls, et al., 2002). The data is compiled, customer identifiers are removed and a text file is made available for research (Wheaton & Kosciulek, 2004). Marinia and colleagues suggest that RSA—911 dataset available through the Rehabilitation Services Administration is one of a few options that, “afford rehabilitation researchers the opportunity to study a full range of predictors discussed in the SCI literature” (2008, p. 2). The raw data is accessible through RSA in Washington DC and can be converted into an SPSS file for analysis. Wheaton and Kosciulek published a paper with conversion guidelines to increase access to and use of the RSA-911 data (2004). 15 Research Investigating Factors Related To the Employment of Individuals with SCI Findings from these national sources as well as more targeted studies have identified a number of factors that appear problematic for customers with SCI. These include physiological factors, psychosocial implications associated with adjustment to SCI, post-injury employment outcomes including factors associated with education, race, gender and disincentives. The need to better understand these components impacting return to work are Vital as research indicates that while 57.5% are employed at the time of injury, only 11.5% are employed one year post injury with just over 35% employed 20 years later (NCSCISC, 2009). As suggested by Mariana and colleagues (2008, p.2) these numbers are “alarmingly low” when in 2007 approximately 79% of non-institutionalized, men and women, without a disability, aged 21 to 64 years, all races, regardless of ethnicity, with all education levels in the United States were employed (Bjelland, Erickson, & Lee, 2008). Physiological Factors Physiological components of SCI must be considered when examining post-injury employment as Berkowitz and colleagues reported a direct correlation between functional status and employment success for individuals with SCI with the likelihood of employment for those requiring assistance being less than half (18%) of their counterparts that did not require assistance (1998). Jang, et al., (2005) and Krause & Anson, (1996) also reported functional limitations as a major barrier to employment. These findings are further supported by Conroy and McKenna (1999) and Berkowitz, O’Leary & Kruse (1998) who reported that post-injury employment was correlated with injury severity. l6 Finally, a study by Smith (2007) investigating unemployment across disability type found that needing help with personal care, particularly routine needs, was more predictive of unemployment than any one condition suggesting that loss of function (fundamental in SCI) is a strong barrier to employment. Kelly recently reported that post injury medical and functional outcomes for individuals with a Violently acquired SCI were poorer than individuals who injuries were acquired in alternative ways (2007). This has direct implications for minority populations as Burnett and colleagues (2002) reported that violence is the primary cause for SCI in minority patients served by the model system. Research suggests perceived health limitations may serve as a barrier to employment as well (Krause & Pickelsimer, 2008; Hampton, 2004). Learning about and adjusting to alternative methods of mobility, proper bowel and bladder and skin care and grooming are important factors to be addressed (Kelly, 2007; Krause & Terza, 2006). As a result early perceived and actual health limits should be assessed and addressed before counselors initiate employment related counseling processes (Krause & Pickelsimer, 2008). Psychosocial Implications Addressing the aforementioned physiological needs of living well with SCI is important for maintaining health; however there are additional factors that must be addressed as well. Wehman reported that, “One of the major issues facing persons with spinal cord injury (SCI) after rehabilitation is the adjustment to a different quality-of-life” (2000, p. 162). Wehman defined that quality-of—life was associated with “meeting individual needs, controlling one's environment, and having the opportunity to make 17 choices” (2000, p. 163). While psychosocial adjustment to SCI varies by the individual, research indicates that it a time-intensive process occurring over years rather than days or months (Devivo & Richards; 1992; Wehman, et al., 2000). Because SCI significantly impairs the functionality of major body systems, it has been suggested that an individual may go through a grieving and adjustment process which may include the five stages of grief proposed by Kubler-Ross (1969) which includes denial, anger, bargaining, depression and acceptance. Though some individuals may pass through all five stages of grief, it should not be considered a mandatory process for adjustment. Early studies by Lawson (1976) and Howell, Fullerton, Harvey, and Klein (1981) failed to demonstrate a direct correlation with depression following SCI. While adjustment to disability eventually occurs for most individuals over time, research has shown that adjustment is a unique process that occurs on an individual continuum (Wehman, et al., 2000; Wortman & Silver, 1989). Several studies suggest that psychological adjustment counseling was found to relate positively to employment outcomes (Marini, et al., 2008; Meade, et. al., 2004). Hampton (2004) found factors that promote quality of life or a sense of well being included perceived social support and self-efficacy. Hampton’s findings for social support were further validated by Krause & Terza (2006) who found that social support or “community inclusion” was positively correlated with post injury quality of life and Kelly (2007) suggested that individuals with SCI particularly those with a violence associated SCI should work to enhance their understanding of community resources. Kelly also reported that an individual’s “coping self—efficacy” is an important factor for recovery as well (2007). Finally, a number of studies have found that employment is an 18 essential component of post injury quality of life (Chapin & Kewman, 2001; Kelly, 2007; Kemp & Vash, 1971; Krause & Anson, 1996). Factors Impacting Post-Injury Employment Outcomes As previously evidenced, employment is important for socioeconomic as well as psychosocial reasons yet a significant body of research has consistently reported low employment rates among people with SCI ranging from 13% to 69% (Krause & Pickelsimer, 2008). It has been reported “Society often defines us by our earning power, the type of work that we do, the regularity with which we are employed, the type of environment that we work in, and our long-term work potential; America is a capitalist society, a country that expects people to be productive in work” (Yasuda, Wehman, Target, Cifu. & West, 2002, p. 177). Still individuals with SCI identified many factors for not working; Targett, Wilson, Wehman, & McKinley (1998) reported these include “a physical inability to perform the same type of work postinjury (60%); poor health, stamina, or endurance (28%); loss of benefits (28%); not feeling physically capable of working (27%); inaccessibility of the workplace (23%); and lack of transportation. Studies indicate those individuals successful in returning to work or finding new employment were most commonly successful in white collar positions as opposed to blue collar jobs or those in the service industry (Berkowitz, et. al, 1998; Meade et al., 2004). White collar positions are more likely to provide health benefits, flexibility in work schedules, accessible workspace and salaries that can help offset transportation costs (Anderson & Vogel, 2002; Krause, 1992). A substantial body of research suggests that factors that impact post-injury employment are further affected by demographic factors 19 that include education, race, gender and time since injury as well as disincentives; these factors will be examined next. Education Level of education was found to have a significant impact on a number of factors associated with return to work. In a study by Krause (1992) 70% of individuals with SCI with a college education were employed as opposed to only 6% of those with less than a high school education. In 1998, Berkowitz and colleagues reported similar findings; over 75% of those with a master’s degree and close to 55% of those with a bachelor’s degree were employed alter SCI. This same report stated less than 15% of those with high school diplomas were employed (Berkowitz, et. al., 1998). The more education a person with SCI has at the time of injury, the more their employment options generally increase as well (Anderson, et. al., 2002). Race Racial inequities in the VR systems have been an ongoing concern. A review by Atkins and Wright in the eighties addressed factors in service disparities from acceptance to closure (1980). Herbert and Martinez (1992) provided similar findings that European Americans had a higher VR acceptance rate and that African Americans and Hispanics were more likely to be found ineligible for VR services than were other minority groups. A significant body of research indicates that race is correlated with employment success (Hess, Ripley, McKinley, & Tewksbury, 2000; DeVivo, & Richards, 1992; Krause, Kewman, DeVivo, et al., 1999; Meade, 2004; Krause, Stemberg, Maides, & Lottes, 1998; Young, etal., 1994) of which many suggest European Americans more likely to become employed than minorities (Yasuda et al., 2002). Still others have found opposite findings 20 (Bellini, 2003; Giesen, Cavenaugh, & Sansing, 2004; Wilson, Alston, Harley & Mitchell, 2002) Research supporting service limitations for minorities are examined first. A recent study by Meade and colleagues who directly examined employment and race for persons with SCI by comparing their pre and post injury employment patterns against general population statistics (2004). Racial disparities which mirrored the general population were found at l, 5, 10, 15, and 20 years after SC 1. The type of job held was generally similar as well (Meade, et al, 2004). This study also found that African Americans generally did poorer post injury than their white counterparts with “lower economic self- sufficiency scores, regardless of employment status, and lower social integration scores among those who were not employed” (Meade, et al., 2004, p 1782). Direct findings from this same study include lower employment rates (50% vs. 73 %) and higher rates of unemployment (37% vs. I 1%) for African Americans (Meade, et al., 2004). When compared with their white counterparts, four percent fewer African Americans were students (4% vs. 10%) and those employed were more likely to be working in less skilled, lower-paying jobs (Meade, et al., 2004). The study also suggested a decreased potential for future employment for African Americans evidenced by a gTOWing gap in student status between employment and education (Meade, et al., 2004). An earlier study found minority participants were 2.8 times less likely to be gainfully en'1l3loyed than their white counterparts (Krause, Stemberg, Maides, & Lottes, 1998). Minority participants also reported a higher occurrence of inability to return to their PreVious occupation (Krause & Anson, 1996). 21 Rubin & Roessler acknowledged that minority populations have been traditionally underserved but suggest attempts for change are being made (2001). Section 107 of the 1992 amendment of the rehabilitation act of 1978 required annual reviews and monitoring of established standards and measures with increased accountability (PL. 102-569) and included factors associated with minority outreach. In the last decade studies which support equitable and increased services to minorities exist. Wilson and colleagues (2002) used binary logistic regression to examine the relationship between vocational rehabilitation (VR) acceptance and race, gender, education, work status at application, and primary source of support at application. When other variables were controlled in the study African Americans were over two times more likely to be accepted for VR services. A study by Bellini (2003) indicated that some improvements have been made in the vocational training rates that favored people of color as well as costs for service. Finally, a study of access of the state-federal vocational rehabilitation (V R) system, Giesen, Cavenaugh, & Sansing (2004) found that access percentages were higher for African Americans, lower for Whites and about the same for Hispanic Americans. Finally, it is important to recognize that demographic characteristics do not occur in isolation and factors in addition to race (e. g., level of education) may be impacting employability. Gender The research on women with SCI reflects mixed findings. A significant body of reSearch suggests that women are less likely to be competitively employed than their male counterparts. Young and colleagues reported that men were 50% more likely to be emPloyed (1994). Another study reported that women who were competitively employed 22 generally worked fewer hours than their male counterparts (Krause, et al., 1999). A final study by James, Devivo & Richards reported an increased likelihood for Caucasian men to be competitively employed (1993). However, other studies have shown women to achieve better outcomes than their male counterparts (Krause & Anson, 1996). Researchers suggest that there are a number of interacting variables that influence outcome by gender (e. g., education, type of work, age and level of injury) (Anderson, Dumont, Azzariaa, Le Bourdaisc, & Noreau, 2007; Marini, 2008). Assistive Technology As suggested by the World Health Organization (2001) disability is the relationship between impairments and the environment. Several studies suggest assistive technology (AT) may be used to improve an individual’s functionality by overcoming barriers and improving independence (Dittuno, Stover, Freed & Ahn, 1992; Scherer & Cushman, 2001; Smith, 1996). The improvement in functionality provided by AT has been reported to increase socialization, integration and employment opportunities (H cinemann & Pape, 2002; National Council on Disability, 2005; Pape, Kim, & Weiner, 2002). Looking directly at individuals with SCI, a study by Hedrick and colleagues indicated that assistive technology ownership and use impacted employment success (2006) with a positive correlation between AT use frequency and disability severity potentially suggesting that the use of AT can compensate functional limitations. Those AT instruments of occupational significance were 3.5 times more costly than other devices suggesting the need for cost Sponsorship (Hedrick, et al., 2006). Finally, for the analysis of VR customers it is important to recognize that other AT funders and providers 23 may have independently provided services so the 911 data may not fiIlly reflect a customer’s utilization of adaptive devices. Research Investigating Factors Related T o the Employment of Individuals with SCI While legislative initiatives such as the Americans with Disabilities Act (ADA: PL 101-336) were enacted to assist individuals with disabilities into the workforce, nearly twenty years later substantial work is still left to be done (Yasuda, 2002). Such persistent disparities in employment suggest the potential for modification or reconsideration of traditional interventions to promote effective rehabilitation services and social reintegration (Meade, et. al, 2004). Recently researchers in the field of rehabilitation studies have begun using data mining technologies including classification trees as a method for investigating the impact of intake, process and outcome variables on the of employability of VR customers (Kosciulek, 2004; Marinia, Lee, Chan, Chapin, & Romero, 2008; Rosenthal, Dalton, & Gervey, 2007). Because classification trees are used to predict the membership of cases into a categorical criterion variable (e. g., employment outcome) from their measurement on a predictor variable (e.g., level of education) as well as segment large groups of people into homogeneous subgroups they are well suited for use with the 911 data (Kosciulek, 2004; Rosenthal. et. al., 2007). Rosenthal and colleagues (2007) used a data mining approach to examine the Vocational outcomes of individuals with psychiatric disabilities who received state VR Services in FY 2001. Their study found that job placement services were the most Slgnificant predictor of employment. SSI/SSDI was found to be a disincentive. Race and 24 transportation services appeared to impact employability as well. While an earlier study (Bolton et. al., 2000) reported that job placement services were a key predictor of employment only 33.3% of customers in Rosenthal’s study had received this service (2007). In a separate study Marini and colleagues (2008) used a data mining approach to examine VR service patterns related to successful competitive employment outcomes of persons with SCI. This study also examined customers served in 2001 and found job placement services and work disincentives were key factors in employability as well. Case expenditures (cost of goods and purchased services) were also noted as important as clients receiving above average expenditures had a higher probability for employment. The purpose of this study is to expand on the research by Marini & colleagues examining the effect of demographic variables and rehabilitation services on employment outcomes of persons with SCI with cases closed by state vocational rehabilitation agency settings. This study will expand on the earlier study by examining customers served between 2004 and 2008. Aggregate and five year patterns to investigate factors associated with improvements or changes in customer employment outcomes will be examined, 25 CHAPTER 3 Methodology This study examined characteristics of customers with SCI with cases closed by state vocational rehabilitations (VR) services administered through the Rehabilitation Service Administration (RSA) from fiscal year (FY) 2004 through (FY) 2008. Most directly this study investigated the relationships among customer characteristics, service delivery patterns and vocational rehabilitation outcomes to explore potential barriers to or predictors of employment success. This section describes a) the data source used in the study, b) study design with associated statistical analyses, 0) the characteristics of the participants (customers with SCI who received services), (I) research questions and e) the variables associated with the customer, services and outcomes. Data Source The Rehabilitation Service Administration (RSA) provides vocational rehabilitation services at a state level to individuals with disability and collects customer data on all VR case closures during a fiscal year (Dutta, et al., 2008). The requirements for reporting were expanded in accordance with Rehabilitation Act of 1973 (Koch & Merz, 1995) and consists of extensive information collected at intake, during services, and at closure and includes demographics, type of public support at intake, types of VR services received, and type of closure. The Case Service Report (RSA-911), which is periodically revised, is the document that specifies the data collection and reporting Criterion (Schwanke & Smith 2005) and as such promotes long term program accountability (Walls, et al., 2002). This structure is important as it provides the 26 E3.“ 31 V. 3'" ‘I: SILL.» Iris. luugk i’C‘T‘i‘Im 1'; 1 ' ‘14?th m’lfl‘. ““41“ Rim "5“ c , W15 II" 1.. ,H r‘ . "“ nut Ii:- ‘5 HOE framework for the “assessment of service needs, patterns of use, program outcomes, and efficiency of services offered” (Walls, et al., 2002, p.4). The RSA-911 reporting process provides a means for understanding customers and factors associated with intake, process and outcome. A consolidation and comparison of several years of data specifically analyzing the dynamics of factors associated with outcomes could provide significant guidance for needs assessment, program planning, program evaluation, and policy development activities. Walls and Tseng (2004) further stressed the need to examine multiple outcome related measures to further illustrate and understand customer achievements. To address this need for the population of individuals with SCI this study examined factors including five year patterns related to customer characteristics, types of services received as well as closure related items. Data used in this study was acquired through the Rehabilitation Services Administration within the United States Department of Education Office of Special Education and Rehabilitative Services. Study Design An ex post facto design was used as this type of design is consistently used to Perfortn impact analysis on existing data such as the Rehabilitation Services Administration RSA-911 data and is useful in establishing a relationship between Variables. This study’s design utilizing RSA 911 data fits Kerlinger’s (1986) ex post facto design definition as it employs independent variables that have already occurred and Starts With the observation of a dependent variable. In this study all independent variables Will not be manipulated (as they have already occurred) and the rehabilitation outcome w . . . . as not randomly selected. In addition, because ex-post facto desrgn IS used to 27 understand the relationship or effect between variables (e.g., variable A on variable B) this design meets the parameters for this proposed study (Ary, Cheser, Razavieh, & Sorensen, 2009). Participants This study focuses directly on individuals with an SCI who achieved an employment outcome (status 26) or had services initiated but were not employed (status 28) between 2004 and 2008. The use of five years of customer records is important for two main reasons. First it provides a data set with a larger sample size to allow for statistically significant analyses of variables not possible with a one year sample. Second it provides for an analysis of patterns or differences including changes in customer, service or outcome related factors. To understand patterns of differences in the population of customers with SCI an extensive subset of variables used by RSA to collect customer data were included in this analysis. The criterion for the collection and coding of each variable is specified in RSA ’5 Case Service Report (RSA 91 1). This report is updated periodically to meet RSA ’s collection and reporting demands. The definitions and specifications for variables used in this analysis is specified Case Service Report (RSA-911) PD-06-01 which was approved for use through 2008. An overview of the variables used in this study are sun’llnarized in this chapter. The record layout, a more detailed description of all data elements (variables) collected per customer, with unique identifiers, is provided in Appendix B, 28 Variables Variable or data elements in the Case Service Report (RSA 911) are grouped into 43 categories some of which break down into subsets. For example Data Element 32; Type of Public Support at Closure includes Social Security Disability Income, Worker’s Compensation and General Assistance. A total of 70 variables were used for this analysis. Data elements were organized into three major categories; customer characteristics at application (intake), services received (process) and closure related (outcome) factors. Dependent Variables The dependent variable in this analysis was employment status at closure; only customers who closed with a status 26 or 28 were included in this study. Both status 26 and 28 customers completed a plan and received services. Only status 26 customers closed with an employment outcome. Independent Variables The remaining variables were used in cross tabulations and classification tree as predictor variables to better understand the relationship between customer input, service and outcome variables. All variables used in this study are summarized below and described in more detail in Appendix A. 29 Table 1 Customer Intake, Service and Outcome Variables Customer Characteristics at Application (Intake) Variables Variable Name Variable Name Age @ Application Categories Categories for number of days from application to eligibility Categories for Hours Worked at Application Category for Hourly Wage at Application Employment Status at Application Gender General Assistance (State or local government) Individualized Education Program Level of Education Attained at Application Medicaid Ins Coverage at Application Medicare Ins Coverage at Application Number of service types received? Number of supports at application Private Ins Through Other Mans at Application Private Insurance Through own Employment at Application Public Insurance from Other Sources at Application Race Races (Collapsed) Social Security Disability Insurance (SSDI) Supplemental Security Income (881) for the Aged, Blind or Disabled Type of Closure (Status 26 or 28) Temporary Assistance for Needy Families (TANF) Veterans' Disability Benefits Weekly Earnings at Application Workers' Compensation Year of Service (table continues) 30 Table l (continuecQ. Service/Cost Related (Process) Variables Variable Name Variable Name Assessment Services Received Augmentative Skills Training Services Received Basic Remedial or Literacy Services Received Categories for Cost of Goods and Purchased Services College or University Training Services Received Diagnosis and Treatment Services Received Information and Referral Services Received Interpreter Services Received Job Placement Assistance Services Received Job Readiness Training Services Received Job Search Assistance Services Received Maintenance Services Received Miscellaneous Training Services Received Occupational/Vocational Training Services Received On-the-job Supports Services Received On-the-job Training Received Other Services Received Personal Attendant Services Received Reader Services Received Rehabilitation Technology Services Received Technical Assistance Services Received Transportation Services Received Voc Rehab Counseling and Guidance Services Received (table continues) 31 Table 1 (continued). Closure Related (Outcome) Variables Variable Name Variable Name Categories for # of days from application Previous Closure to closure Categories for Hours Worked at Closure Primary Source of Support at Closure Categories for Weekly Earnings at Private Ins Coverage Through Other Means Closure at Closure Category for Hourly Wage at Closure Private Ins Coverage Through own Employment at Closure Employment Status at Closure Public Insurance from Other Sources at Closure General Assistance (State or local Social Security Disability Insurance (SSDI) government) Medicaid Ins Coverage at Closure Social Security Insurance (88]) Medicare Ins Coverage at Closure Temporary Assistance for Needy Families (TANF) Level of Education Attained at Closure Veterans' Disability Benefits Number of supports at closure Workers' Compensation Other Public Support Employment Outcome (Status 26 or 28) Data Analysis For this study, univariate measures (descriptive statistics) were used to identify frequencies and percentages of the composition of customers with SCI on an aggregate basis and for each fiscal year. Cross tabulations and chi-square analyses were used to assess differences associated with inputs, service and outcome variables in relation to employment outcome and fiscal years of service. Chi-square test for independence was used because of its appropriateness in analyzing the relationship between categorical 32 variables such as gender and race/ethnicity (Bellini & Rumrill, 1999; Gravetter & Wallnau, 2000; Pallant, 2001). For all statistical tests the alpha level was set at .05; a Bonferroni correction was received to correct for the number of statistical tests within each predictor. PASW Statistics 18 Release 18.0.0 with the PASW Decision Trees add- on was used for this analysis. Any missing data was automatically omitted by the data analysis software. Variables with missing cases affected only a small percentage of responses, so collectively a large portion of the data was retained and should not have reduced statistical power (Saunders et al., 2006). Decision tree analysis was used to further explore the factors (characteristics and/or services) that had a statistically significant association with 26 and 28 status outcomes based on chi-square analyses. As suggested by Kosciulek, decision tree analysis was used in this study to augment and not replace more traditional methods of analysis (2004). While the variables selected for the decision tree analysis were chosen because of their statistically significant association with 26 and 28 status outcomes several variables were omitted because of their multi-collinearity (e. g., variables indicative of employment). Variables included and excluded from the data mining process are identified in Chapter 4. 33 CHAPTER FOUR Results The purpose of this study was to gain an increased understanding of customers with spinal cord injury served by the Rehabilitation Services Administration between fiscal years (FYS) 2004 and 2008. Research questions that guided the study were: 1.. What are the characteristics of customers with SCI served by the VR system? a. Have the characteristics of customers with SCI served by the VR system changed over the five (5) year span? 2. Are there differences in outcomes (type of closure) based on characteristics for this population and have they changed over the five (5) year span? 3. What are the factors (characteristics and/or services?) associated with positive outcomes for customers with SCI? a. Is there a recognizable pattern displaying an increase in the service provisions most often associated with positive outcomes for customers with SCI? Population of Stuaj/ and Summary of Customers Served The population of interest for this study were individuals with spinal cord injury (SCI) who received services and had cases closed by the state-federal public vocational rehabilitation system. Participants were drawn from the Rehabilitation Services Administration reporting system (RSA-911 database) for FYS 2004 through 2008. This database is annually collected by RSA and is publicly available. The RSA911 data is suitable to examine relationships among input and process variables and outcomes of VR customers. This database provides demographic, service related and outcome variables 34 that reflect characteristics of consumers and services of the public rehabilitation system. The sample of interest for this study was customers with a SCI who completed a plan (IPE or Individualized Plan for Employment) and received services. The dependent variable for this study was closure status. Status 26 indicates the customer closed with an employment outcome and status 28 indicates that the customer closed without an employment outcome A total of 3,106,3 10 individuals had cases closed between 2004 and 2008. Of this population 34,262 (0.011%) reported SCI as their primary or secondary cause of disability. This study focuses directly on the 23,135 individuals with an SCI who closed in status 26 or 28 between 2004 and 2008. This group of 23,135 represents 0.013% of all public VR customers (N=l ,768,686) who were closed in status 26 or 28 in this timeframe. As reflected in Table 2, customers with SCI are less likely to achieve an employment outcome than the aggregate group of VR customers (without SCI); 50.4% of those with SCI achieved an employment outcome as opposed to 57.9% of the people with all other disabilities combined exiting with status a 26 or 28. Table 2 Descriptive Statistics for Type of Closure by Group No-SCI SCI Type of Closure N % N % Employed 1,024,726 57.9 1 1,660 50.4 Services initiated, not employed 743,960 42.1 1 1,475 49.6 Total 1,768,686 100.0 23,135 100.0 35 The use of five years of customer records is important for two main reasons. First it provides a data set (N = 23,135) with a larger sample size to provide a more reasonable chance of detecting a significant association between the variables being investigated. Second it provides for an analysis of patterns or differences including changes in customer, service or outcome related factors over time. Research Question One This first question examined the characteristics, service and outcome variables of customers with SCI served by the VR system. Findings are illustrated in tables with a narrative summary of distinctive findings Customer Characteristics at Application This first analysis of the study examined customer characteristics at application (Table 3). In terms of gender, the majority of customers with SCI or 65% were male. While this expanded database allowed for higher numbers in many categories, many race/ethnicity categories were too small for valid assessment of statistical significance. In order to address this issue, Asian customers were combined with Whites because of similarity in education levels and employment outcomes. African American became the second race/ethnicity category, Hispanic customers became the third category and Native American, Mixed Races and Pacific Islanders were collapsed into an All Other Races category. The 40 through 49 was the most common age bracket (28.3%) followed by those between 30 through 39 (25.6%) years of age. The next most commonly represented groups were 21 years of age and under which comprised 15.1% of the sample and ages 22-29 which comprised 14.9%. Individuals aged 50-59 represented 13.4% of all 36 individuals with SCI injury who were served and individuals 60 and over represented only 2.7%. The majority of customers served (81.4 %) had no previous closure in the past 36 months and less than seven percent (6.1%) had an Individualized Education Program (IEP), indicating that they received services in accordance with provisions of the Individuals with Disabilities Education Act (RSA Policy Directive, 2008). Table 3 Customer Characteristics at Application N % Gender Male 15,032 65.0 Female 8,103 35.0 Race/Ethnicity Collapsed White/Asian 16,453 71.1 African American or Black 3,941 17.0 Hispanic 697 8.8 All Other Races 2,035 3.0 Age at Application Up to age 21 3,502 15.1 22 to 29 3,446 14.9 30 to 39 5,920 25.6 40 to 49 6,552 28.3 50 to 59 3,092 13.4 60 to 64 407 1.8 Over 64 216 0.9 Previous Closure None in past 36 mos. 18,831 81.4 Customer had a previous closure 4,304 18.6 IEP Yes 1,412 6.1 No 21,723 93.9 37 Education and Employment Related Characteristics at Application Table 4 summarizes customers’ education and employment characteristics at application. Slightly less than 20% of customers (N = 4,430; 19.2%) reported having less than a high school degree equivalency, just over 40% reported high school graduate equivalency, and another 40% reported at least some post secondary education at the time of application for VR services. Employment status at application includes customers who are currently employed in a variety of settings as well as students, interns, trainees and customers who are unemployed. For this study customers considered to be employed at application include customers employed with or without supports, homemakers and individuals who are self employed (n= 3986). Of those customers employed and reporting employment wages (N=3,807) nearly 40% (38.5%) reported hourly earnings of less than $8.50. Another 41.6% of those reporting wages had earnings between $8.50 and $17.49 and the remaining customers (19.9%) earned an hourly wage of $17.50 or above. The largest proportion of the customers who were employed at application reported they worked 36-40 hours per week (44.5% or 1,771). An additional 2.7% reported working 41 or more hours per week. In contrast, 7.7% worked 10 hours or less per week. 38 Table 4 Education and Employment-Related Characteristics of Customers at Application N % Level of Education No formal schooling 40 0.2 Elementary, grades 1-8 594 2.6 Secondary, no diploma 3,548 15.3 Special education completion 248 1.1 High school graduate equiv 9,444 40.8 Post secondary, no degree 4,214 18.2 Associate deg or voc tech 2,347 10.1 Bachelor 1,950 8.4 Masters degree or higher 750 3.2 Employment Status Integrated setting, no supports 3,401 14.7 Extended employment 27 0.1 Self employed 213 0.9 Homemaker 1 80 0.8 Unpaid Family Worker 35 0.2 Employment w/ Supports 192 0.8 Not Employed Secondary 944 4.1 Student Not Employed Other Student 1,020 4.4 Not Employed: Trainee, Intern or 72 0.3 Volunteer Not Employed: Other 17,051 73.7 Hourly Wage (n = 3,807) Up to $6.49 739 19.4 $6.50 to $8.49 726 19.1 $8.50 to $11.49 818 21.5 $11.50 to $17.49 765 20.1 Over $17.50 759 19.9 Hours Worked (n=3,983) 0 179 4.5 1-10 308 7.7 11-20 891 22.4 21-35 725 18.2 36-40 1,771 44.5 41 or more 109 2.7 39 Supports at Application The RSA 911 data includes information about customers’ self-reported primary source of financial support as well as the public support benefits the customer was receiving at the time they applied for services; these are examined next (Table 5). A total of 23,091 participants identified a primary source of support at the time of application. These included public support (40.7%), followed by family and friends (34.2%) and personal income (15.0%). All other sources represented the remaining 10.2%. For those receiving public support benefits at application, over a quarter received SSDI (27.4%; N = 6,326), almost 20% received 881 ( 19.8%; N = 4,574), just under 10% reported receiving Other Public Support at Application (7.9% N =1 ,821). Fewer than 5% received Worker’s Compensation (4.5%; N = 1,046) and less than 3% received TANF (2.1%; N = 490), General Assistance (2.3%; N = 538) and Veteran’s Disability (0.8%; N = 176). A review of the number of supports at application indicated almost 45% of applicants used no supports (44.3%). The majority (47.3%) used one support and fewer than 10% used two or more supports at application (8.3%). Medical Insurance Coverage at Application Fewer than 30% of applicants reported having any type of medical insurance coverage at application. Of those with insurance, the majority reported Medicaid benefits (27.2%; N = 6,249), followed by another 20% who had Private Insurance Coverage through Other Means (19.5%; N = 4,463). Just over 15% of cases received Medicare (16.9%; N = 3,882). Approximately 10% reported Private Insurance through Own Employment at Application (8.6%; N = 1,984) and just under five percent reported having Public Insurance from Other Sources at Application (4.2%; N = 961). 40 Days from Application to Eligibility An analysis of days from application to eligibility indicated the majority (51.8%; N = 11,993) were determined eligible within 30 days. An additional 28.8% (N = 6,671) were determined eligible within 60 days while just under 10% (9.2%; N = 2,128) became eligible between 61 and 90 days from the time of application. Approximately 10.1% (N = 2,343) of the participants took longer than 90 days to achieve eligibility. Table 5 Customers Supports at Application Customer Characteristics Total N n % Primary Support Source at App Personal income 23,091 3,456 l 5.0 Family friends 23,091 7,890 34.2 Public support 23,091 9,389 40.7 Other 23,091 2,356 10.2 Type of Public Support Social Security Disability 23,099 6,326 27.4 881 - Aged, Blind, Disabled 23,094 4,574 19.8 TANF 23,100 490 2.1 Veterans’ Disability 23,098 176 0.8 Workers’ Compensation 23,100 1,046 4.5 Other Public Support 23,100 1,821 7.9 General Assistance 23,100 538 2.3 Type of Medical Insurance Medicaid 22,987 6,249 27.2 Medicare 22,963 3,882 16.9 Other Public Source 22,970 961 4.2 Private via Employment 22,944 1,984 8.6 Private via Other Means 22,941 4,463 19.5 (table continues) 41 Table 5 (continued). Customer Characteristics Total N n % Number of Supports at Application 0 23,089 10,239 44.3 1 23,089 10,917 47.3 2 23,089 1,766 7.6 3 23,089 161 0.7 4 23,089 5 0.0 5 23,089 1 0.0 Days from Application to Eligibility 0-30 23,135 11,993 51.8 31-60 23,135 6,671 28.8 61-90 23,135 2,128 9.2 91 or more 23,135 2,343 10.1 Cost of Goods and Purchased Services An analysis of the cost of purchased goods and services identified that no services were purchased for 7.9% of the customers (Table 6). Approximately twenty percent (19.4%) received goods and services that cost $1,000 or less. For the majority (32.2%) services were purchased for a cost between $1 ,001 and $5,000. An additional 27.7% received services that were purchased at an expense between $5,001 and $20,000. Fewer than 10% (9.5%) received services the price of which was between $20,001 and $50,000. Finally 3.4% of customers received over $50,000 in services. Table 6 Cost of goods and purchased services Cost of Goods and Purchased Services N % 0 (no money spent on services) 1,821 7.9 $1 to $1,000.00 4,488 19.4 $1,001 - $5,000 7,455 32.2 $5,001 - $10,000 3,624 15.7 $10,001- $20,000 2,770 12.0 $20,001 - $50,000 2,193 9.5 $50,001 or more 784 3.4 42 Number and Percent of S C] Customers Receiving Services The RSA data classifies the types of services provided to customers into 22 groups that include various assessment and job related services. The information on services is summarized in Table 7. The two most frequently provided services were Assessments (67.8%; N =15,681), and Vocational Rehabilitation Counseling and Guidance, (61%; N = 14,112). The remaining eight of the top ten services include Diagnosis and Treatment (40.9%; N = 9,462), Transportation (35.7%; N = 8,251), Other (31.0%; N = 7,171), College or University Training (27.8%; n=6,423), Rehabilitation Technology (24.9%; n= 5,759), Job Placement Assistance (24.8%; 5,742), Job Search Assistance (21.0%; N = 4,859) and Maintenance (19.5%; N = 4,513) services. Table 7 Number and Percent of S C 1 Customers Receiving Services n of23,135 %of23,135 Service Receiving Services Receiving Services Assessment 15,681 67.8 Vocational Rehab and Guidance 14,1 12 61.0 Diagnosis and Treatment 9,462 40.9 Transportation 8,25 1 35.7 Other Services Received 7,171 31.0 College or University Training 6,423 27.8 Rehabilitation Technology 5,759 24.9 Job Placement Assistance 5,742 24.8 Job Search Assistance 4,859 21.0 Maintenance Services 4,513 19.5 OccupationaWocational Training 3,797 16.4 Information and Referral Services 3,378 14.6 Miscellaneous Training 3,025 13.1 On-the-job Support 2,110 9.1 Job Readiness Training Services 1,722 7.4 Technical Assistance 1 ,327 5 .7 Augmentative Skills Training 714 3.1 Personal Attendant 594 2.6 43 (Table continues) Table 7 (continued). n of23,135 %of23,135 Service Receiving Services Receiving Services On-the-job Training 493 2.1 Basic Remedial or Literacy 345 1.5 Interpreter Services 1 10 0.5 Reader Services 46 0.2 Customer Characteristics at Closure This next part of the analysis examines factors associated with closure variables including education level, employment outcomes, earnings and wages. Education and Employment-Related Characteristics of Customers at Closure Education and employment related variables at the time of case closure are examined next. Findings are summarized in Table 8. Analyses of. educational level at closure indicate that approximately 17% of individuals with SCI improved their level of education while receiving services (refer to Table 4 for comparison). The population of customers who reported a level of education below a high school graduate equivalency at application declined by 6.6%. There was an additional 10.7% reduction in the number of those who reported a high school graduate equivalency (from 40.8% to 30.1 %). The remaining group reporting some post secondary education grew by over 17%, from 40% to 57.4%. As previously reported just over half of the customers closed with a positive employment outcome (50.4%; N = 11,660). A total of 11,186 individuals reported wages at closure. Of this group, 20.1% reported hourly earnings of less $8.49, as opposed to 38.5% at application. While 41.6% of those working at application reported hourly earnings between $8.50 and $17.49, 62.4% reported this wage at closure. Almost 20 percent (19.9%) of those working at application reported hourly earnings of $17.50, as opposed to only 17.5% at closure. Of 44 the 11,160 customers reporting hours worked at closure, 51.0% worked 36-40 hours, 19.1% percent worked 11-20 hours and 20.4 percent worked 21-35 hours. Fewer than 5% (4.7%) worked 10 hours or less and only 2.5 percent reported working 41 or more hours. Table 8 Education and Employment-Related Characteristics of Customers at Closure N % Level of Education No formal schooling 19 0.1 Elementary, grades 1-8 450 1.9 Secondary, no diploma 2,199 9.5 Special ed completion certificate 237 1.0 High school graduate equivalency 6,957 30.1 Post secondary, no degree 4,958 21.4 Associate deg or voc tech certif 3,868 16.7 Bachelor 3 ,267 14. 1 Masters degree or higher 1,180 5.1 Type of Closure Services initiated, not employed 1 1,475 49.6 Employed 1 1,660 50.4 Hourly Wage Up to $6.49 1,169 10.5 $6.50 to $8.49 1,079 9.6 $8.50 to $11.49 4,323 38.6 $11.50 to $17.49 2,659 23.8 Over $17.50 1,956 17.5 Hours Worked 0 474 4.1 1-10 531 4.6 11-20 2,135 18.3 21-35 2,286 19.6 36-40 5,949 51.0 41 or more 285 2.4 45 SCI Customer Supports at Closure This next section examines the types and number of supports customers received at closure and changes from time at application (Table 9). In evaluating changes in public support from application to closure, the number of individuals with SCI receiving SSDI increased by 4.3%, from 27.3% (N = 6,326) at application to 31.7% (N = 7,237) at closure. The number of 881 recipients remained basically unchanged at closure (20.0%; N = 4,575), compared to 4,574 at application. Customers who reported Other Public Support decreased from 7.9% (N = 1,821) at application to 3.6% (N = 832) at closure. Worker’s Compensation also dropped from 4.5% (N = 1,046) at application to 2.3% (N =524) at closure. TANF decreased from 2.1% (N = 490) to 1.2% (N = 274) as well as General Assistance from 2.3% (N = 538) at application to 1.4% (N = 325) by the time these individuals exited public VR. Finally, the number of Veteran’s Disability benefits recipients dropped slightly from 176 to 145 at closure. In reviewing changes in medical insurance coverage from application to closure several distinctions were found. First, Medicaid increased slightly from 27.2%, (N = 6,249) to 28.2% (N = 6,441) and Medicare increased from 16.9% (N = 3,882) to 21.9% (N = 4,982). Private Insurance through Own Employment increased as well from 8.6% (N =1,984) at application to 18.3% (N = 4,167) at closure. Private Insurance Coverage through Other Means dropped from 19.5% (N = 4,463) to 12.5% (N = 2,847) and Public Insurance from Other Sources dropped slightly as well from 4.2% (N = 961) at application to 3.7% (N = 853). An analysis of days from application to closure indicated that over a third of customers spent four or more years in the VR process (34%; N = 7,869). Just over ten 46 percent (1 1.8%; N = 2,741) spent between three to four years. Those that received two to three years of VR services made up 16.0% of customers (N = 3,712). The second largest group (N = 5,123) received one to two years of service. The final 15% of customers (N = 3,690) received less than one year of services. Table 9 SCI Customer Supports at Closure Characteristic Total N n % Primary Source of Support Personal income 21,83 1 9,956 45.6 Family fiiends 21,831 3,454 15.8 Public support 21,831 7,430 34.0 Other 21,831 991 4.5 Type of Public Support Social Security Disability 22,822 7,237 31.7 881 for Aged, Blind or Disabled 22,825 4,575 20.0 TANF 22,797 274 1.2 Veterans’ Disability Benefits 22,802 145 0.6 Workers’ Compensation 22,802 524 2.3 Other Public Support 22,808 832 3.6 General Assistance 22,801 325 1 .4 Type of Medical Insurance Medicaid 22,809 6,441 28.2 Medicare 22,800 4,982 21.9 Public Insurance from other Source 22,835 853 3.7 Private via Employment 22,751 4,167 18.3 Private via Other Means 22,746 2,847 12.5 Number of Supports at Closure 0 22,773 10,759 47.2 1 22,773 10,304 45.2 2 22,773 1,606 7.1 3 22,773 100 0.4 4 22,773 4 0.0 Days from Application to Closure Less than 1 year 23,135 3,690 15.9 1 year to less than 2 years 23,135 5.123 22.1 2 years to less than 3 years 23,135 3,712 16.0 3 years to less than 4 years 23,135 2,741 1 1.8 Greater than 4 years 23,135 7,869 34.0 47 Research Question I (Part 2): Analysis of Customer Data by Year In order to address research question one, have the characteristics of customers with SCI served by the VR system changed over the five (5) year span, this section of the study examines the results of comparisons performed across the five years studied on the variables pertaining to customer characteristics, services received and employment outcomes. Chi-square analysis was used to determine whether changes over time were statistically significant. Customer Characteristics at Application by Year Table 10 summarizes customer characteristics at application by year. While not statistically significant, there was a 2.2% difference in gender dispersion for FY2008 when 67.2% of the sample was represented by men in comparison to the overall 65% male versus 35% female difference. A chi-square analysis reflected no statistically significant associations between race and fiscal year. Age at application was found to be associated to the year of closure, )(2 (24, N =23,135) =673.83, p < 0.0005. Years 2004 and 2006 experienced the greatest variability on this customer characteristic. While the percentage of customers younger than 21 at application was 15.1% there was a low peak of 10.8% in 2004 and a high peak of 26.4% in 2006. A converse variation in distribution occurred within the 30 to 39 age category with a high peak of 28.8% in 2004 and a low peak of 19.9% in 2006. There was a rise in the percentage of students who had an IEP between 2004 (4.7%) and 2008 (7.4%), x" (4, N: 23,135) = 38.38 p < .0005. 48 88. v m eesseecseefia. E g. 3 as 3 SN 3 8m 5. :2 mange: e2 :34. 98 we? 93 83. 9.8 one; «:3 we.“ massages: so 8?“ R3 84.... RS. 23 . mm: 0.8 22 98 N; 0.2 es SN 08 ”.2 e8 23838033 8: now 83 OS :3 m: sea 32 use New 33 £88 358 5282 8am $3. 5.4 R? “a.“ 2386 325$ 3 R .3 mm 2 em 3 G 2 3 $35 3 we 2 am 3 m 3 mm 2 am $28 4.2 gm 3: 8e 22 em :2 am we me $93 92 83 EN we; 38 as; men 83 3m 83 $99. 32 «8 EN 33 we am new 83 was 35 393. 3; an 2: 8m 2; me on a? 02 82. 398 we: 4.2m 2.: e2 ....em $3 4.2 ms 2: :e Queens 83 $3. 83. a? 23 . nausea? a ewe. 3 o: 3 N2 2“ ma 2 m2 2” NE 550 as :2 e2 22 3 34 3 5 3 NS Essa n: we 3: 02 e2 3 92 w; 9: 83 x858 genegseae. wee sea a: 33 ~.:. Ea one mom 2: $3 833823 83 $3 5% R3 8% 8am mam was New 5} 4.2 $3 2.2 $5 4.2 33 038e,,” Se 33 wee “23 93 $3 0% Ea 3e omen 2e: 83 33. 34.4 28.4 23 Base ,2. e ,2. e ,2. e s e s e 2 2 2 2 2 woom Boom eoom meow eoom can» 2a noeflxmuoES‘U $58.30 NOW. 2 055. 49 Education and Employment Related Characteristics at Application by Year This next section examines education and employment-related characteristics of customers at application (Table 11). Level of education of these customers showed a statistically significant difference between 2004 and 2008, x2 (32, N= 23,135) = 159.42, p < .0005. There was a 6.5% decline in the percentage of customers with high school graduate equivalency. Conversely there was an approximate 6% increase in the proportion of customers with an associate degree or higher level of academic training. A chi—square analysis indicated statistically significant changes across the years in employment status at application as well, X2 (36, N = 23,135) = 89.74, p < .0005. There was a consistent increase in the percentage of customers who reported employment without supports in an integrated setting at application from 13.4% 2004 to 16.5% in 2008. Conversely the proportion of those not employed for other reasons experienced a 3.7% decline during this same time period. Customer’s hourly wage at application also experienced statistically significant changes from 2004 to 2008, )(2 (16, N = 3,987) = 63.61, p < .0005. The percentage of customers earning under $6.49 an hour declined by almost 10.0% while the percentage of customers earning above $17.50 an hour increased by almost 9.0%. The percentage of customers with hourly earnings $6.50 to $8.49 decreased by 2.7% and the percentage of customers earning $11.50 to $17.49 per hour increased by 2.8%. The associations between number of hours worked and years of exit from public VR services were found to be statistically significant )(2 (20, N = 23,132) = 52.98, p < .0005. Finally there was a 5.8% increase in the number of customers working 36 to 40 hours at application from 2004 to 2008. 50 engage Seat 88. v 2 885mg c8636... 51 0.9 Ea e. K 83 we $2.2 22 $3 35 ME} 822988: 550 to 2 no 2 to a no 3 do : ease. Season: 3 .22 2 a: 3. we 4.4 an 3. EN 383m 25 see 82 wnfiom b.8803 a E 3 a2 3 a: 3 e2 3 EN am SN caeeam see 82 S we 2 e we 2 no an no a means a? games 3 W do w 3 w 3 e .8 S 383 base 285 ed 3 ed 2 S a we am 2 8 eefiaeaom 3 3 mo 2 I 2 mo 3. we ea Basque rem S e 3 a Ne m S a 3 2 aeaeaae eeeeaxm 3: e8 22 «we 3; we 3: m2 4.2 Na access. 8 63235 83 33 50.4 a? new . seam caeieuaam S. 3: 3 O: Q a; ME ME 2 E 5&3 a Base mesa: 2 42 as 84 we an 3 «em 2 23 8&3 Pages 4.: an. M2: e9 2: $4 3 we ed a? 62 00> a wee sesame. 3: 8e 2: 5 fl: an 3: 82 n: :3 Shoe 8 .3883 see 22 3.5 :3. 33 3m 85 was 33 24 5.2 2:3 Ba 323 as: 3 am 3 S 3 3 3 we 3 s 830388 8 38% 2.2 4% we 3e 2.2 5 a: $2 2.2 we 8.2% 8 .baeeoem ed we 3. mm 3 e: 3 5 an s: 3 macaw .5885 no 2 3 e S e S : 3 A masons 358 oz 8% $3. 5% 28.4 new . Seesaw a 223 s e s e s s e s e 2 2 2 2 2 88 88 88 88 38 new» 3 .zoeeoeois B EoEszb 50.0% 85288825 EoEASREM n2: nomueoanmwsso ESQ g _ 033. 88. v 2 08202:. .5235... on E 2.2 a 2 2 3 2 3 mm 28:0 s. 2.5. $2 3... 32 ed. 82 2.2. an 9:. as 8.3 22 m: 3: 3 2.2 E 22 ME 28 2: 3:. SN as 2.8 E as E EN E :2 E 8-: 2 mm 3 on w... 3 S 8 E fl 2; 3 a 2 mm mm mm w... an I. 8 o o? $2 mm» 2m 22 _. Bio? £52 2.9. 02 3.2 m: :2 a: w: 2: oé 02 8.5 H96 ”.8 NS 2.3 m: a: MS 28 N2 32 m: $.22 9 O? a 0.8 o: 28 ...2 EN “2 22 a: :2 E a: a 3 on: 2: cm 2.2 a: mom 3; ma 5 q: a: $3 9 3.3 2.: 2: 3: E 22 o: 3: NE 32 82 $3 9 .5 o: w? E :2 3w _. was,» is: .2. .. 2. .. .2. .. 2 .. .2. .. 2 2. 2 Z 2 88 88 88. 28 38 é.§.§§ : 29d. 52 Customers Supports at Application by Year Table 12 summarizes the analysis of customer supports at application. There were statistically significant changes in customer’s primary source of support at application, X2 (12, N = 23,091) = 67.65, p < .0005. Family and friends as primary sources of support at application decreased from 35.0% in 2004 to 32.5% in 2008. Conversely, the use of public supports at application increased from 39.8% in 2004 to 42.1% in 2008. When analyzing specific types of public supports, a consistent increase was found in the percentage of customers utilizing Social Security disability insurance at application from 23.7% in 2004 to 30.5% in 2008, X2 (4, N = 23,099) = 99.44,p < .0005 and a 1.2% decrease in the use of general assistance at application, )(2 (4, N = 23,100) = 29.65, p < .0005 during the same years. Other public support had an overall reduction from 8.3% in 2004 to 7.8% in 2008 but had a nonlinear variation greater than 2% through the years, with an 8.9% peak in 2005 to a 6.2% low in 2007, 12 (4, N = 23,100) = 23.76, p < .0005. Medicaid insurance coverage increased from 23.8% in 2004 to 31.7% in 2008, X2 (4, N: 22,987) = 89.08, p < .0005. Medicare increased as well from 13.6% in 2004 to 20.3% in 2008 )(2 (4, N: 22,963) = 1 14.45, p < .0005. A chi-square analysis indicated statistically significant changes existed in the number of days from application to eligibility from 2004 to 2008, ){2 (12, N: 23,135) = 71.68, p < .0005. The number of customers determined eligible within 30 days of application increased by 5.3% from 49.6% in 2004 to 54.9% in 2008. Inversely those receiving eligibility after 30 days declined with a 3.0% reduction occurring in the 60-90 days category and a 2.1% reduction occurring in the 91 days or more category. 53 «2222.228 2322 mooo. v 2. camouflage “gowmnmmm... ms man No SN 3. Own 3w wmv m.w $2 .toaasm 235 22:0 mafim omoxu mg}. 28.2 mama ON on Na mm 2.; on NA 2: N.m $2 . 8282342 32280 mafim omof 8.2.2 $6.2 mama NV 02 me at Nd 3: 3. Zn m.m 2m 23323800 .3828)? 32mm omof mg? 28...» mama wd om 9o 3 We mm 5.0 «m ad mm 3:385 .3888» mafim 03.2 mmiv 28.2 omwfi w; on o; 8 a; vw Na :2 EN a2 272.2. mafim omoxy mg}. 38.2 . waww NAN cow mdm 2% M23 Rm NE 9% v.3 mac; 3335 .925 .392. I Hmm mafim £832 Nate 98.2 wowfi mdm $3 adm mmm; Ema own; 22mm EN; Emu com; . 25385 358m Eoom mafim m3...“ «~32 23.2 Sam toqasm 232m .«o 093. 2d Sum Wm 5mm ad mmv 0.: New 2.: who 2050 fig 3m; QNV m3: fiov was; fiwm gm; wdm Nmm.m 2258 252m mdm mmmJ odm mom; mém Sun; 0.? own; 9mm wwo.m $205 2:822 2.3 30 GE owe WE eve 2.3 .22. 2.2 :w 0883 32382 32 one... 83. 83. 8% .2823 2. 830m 585 R. 2 R. 2 Va 2 o\o 2 X 2 2 2 Z 2 Z woom boom coca moom voom .2222“ 3 22.23.2223‘ 22 2.222222% 22282220 NOW 3 033. 54 88. v 2 3836 “502.35.. ow Em vd mum v.2 Ev Q: 9% 2: m3 808 Ho 5 cs cam 56 En md m3 wd $2 0.3 30 ca 9 G m.wm 8: 9mm mag 93 cum; odm N9} odm is; co 8 “m men owo.m m.mm Sfim 0.9 mafia New owim v.3 cmm.~ on 8 o 83 83. a}. a? 2% .255me 8 2282332 Sow mann— o.o o od 0 o.o o o.o o o.o fl m _.o N o.o N o6 fl od o od o 2 m6 mm We 3 ed mm wd ow fio an m Wm mmm Nd mmm fim wmm N8 mmm wd 82 N Y? mme w.wv m3; wév :oN flow paw wdv onwm fl fimv mam; Wmv own; «.3 mom; adv vofim fimv aqm O Na?” M30...V a»? $6.2 mama 2282332 a gonna—m Mo 23:32 03 5. M23 «as .62 gm mg woa New on: 882 550 a? 823.5 Qua 286 m9? fl 3:2 nmwfi 3 min A; an 3 an MS 3. 3 we. avian—am a; mafia Sfim woof 81¢ 232 mmwfi me N2 3» ~w_ ad #2 2.2 gm oé RN 8.50m 0:95 550 mm?“ Boxq o3}. EQV mvwfi mdm m2. ad— 35 WC «2. N2 35 9m _ was .. 88602 vwbfi _ 86 m3? m g 3. mvww b. M m SN; vdm vw: v.3 ZN; 5mm New; w.m~ 3m; . 28622 wwwm @842 23. m fl acw 3&6 8ng 3232 mo 33. ex. 2 2X. 2 X. 2 X. 2 X. 2 Z 2 Z Z 2 moon boom ooom moon voom 22:22.83 2 938. 5 5 Cost of Goods and Purchased Services by Year The cost of goods and purchased services had statistically significant changes between 2004 and 2008,)(2 (24, N= 23,135) = 171 . l 8, p < .0005. As reflected in Table 13 there was an increase in the funding and allocation of services provided to customers during this five year period. There was a consistent decrease in the number of customers receiving funding in all dollar amount categories that were $10,000 or below and an increase in all funding categories above $10,000. 56 88. v 2 0820...... .aomgm... m... 8. .... w: .2 o: ..m ..2 3 E 208.3853 q: 3. 3: 2.... ma 2.... 3 8... 3 8.. 2.853485% 3. E. 2. me. n: 8m 2. cm. ...: N8 ooodmméod; 3.. a S. a 2.2 N: 22 a: 22 28 82.65-8me ...om mm... mom am; 92 :3 mam as; .....m #3 893-82.: 3: a: 2: on. 3: .5. ed. 08 EN 3.3 83mg; 3 3m .1 an E .3 ..w mam 5 mm... o .2. 2 .2. a .2. 2 2. a .2 a 8.3 "2 m8... "2. 5.... "2 28... "2 ma.“ "2 88 88 88 88 ..oom 22m» .3 wmumimm. .232232& 222 groom. \o 2.80 m fl 2an 57 Number and Percent ofSCI Customers Receiving Services by Year Table 14 highlights the changes in services received between 2004 and 2008. The rate of delivery of basic remedial and literacy services varied between 2004 and 2008, X2 (4, N= 23,135) = 20.36, p < .0005; 1.1% of customers received services in 2004, with a peak of 2.0% in 2006 with a decline to 1.2% in 2008. The percentage of people receiving diagnosis and treatment services grew in a linear pattern from 39.1% in 2004 to 43.1% in 2007 but decreased to 41.9% in 2008,)(2 (4, N= 23,135) = 25.12, p < .0005. The number of recipients of information and referral services increased from 12.8% in 2004 to 19.4% in 2008, )(2 (4, N= 23,135) = 108.58, p < .0005. The number of job placement assistance recipients grew 3.5% from 22.8% in 2004 to 26.3% in 2008, )(2 (4, N: 23,135) = 26.71, p < .0005. OccupationaWocational services declined by 3.5% from 17.9% in 2004 to 14.4% in 2008,)(2 (4, N: 23,135) = 26.42, p < .0005. On-the-job Supports increased by 3.4% from 7.5% in 2004 to 10.9% in 2008, x2 (4, N = 23,135) = 41.81, p < .0005. On-the-job training declined by just under 1% from 2.8% in 2004 to 1.9% in 2008,)(2 (4, N= 23,135) = 20.38, p < .0005. Other services received increased by 5.0% from 28.6% in 2004 to 33.6% in 2008, )(2 (4, N: 23,135) = 31.39, p < .0005. The number of those who received rehabilitation technology services increased by almost 10% from 20.1% in 2004 to 29.8% in 2008,)(2 (4, N = 23,135) = 151.97,p < .0005. While not significant statistically within the parameters set for this study, the recipients of transportation services increased by 3.7% from 34.1% in 2004 to 37.8% in 2008. 58 0.022.228 0322» wN 002 N.m 0N2 wN mNfi N.N :2 2N NN~ 02002004 320802 9mm. KN; 0.0m 0.ng mNm wNvJ 0. 2 m NmmJ 0.xN 30.2 . .2050 0.2 N0 04 we 0.N mm 0.N 3 0N mm: _. wand. 00.0.0520 0.02 0:. 2.02 “NV 0.0 m0m 0.0 3:. ms 03. _. 202226 900.0520 . 92222.0 v.3 0.2m N62 20 0.2 mmh 0.02 0mm 0.5 504 32008023020202.2000 0.N~ 09. 02 3m N01 0N0 0.2 3.0 0.3 0mm waged. 0200220022 0.02 NNN. 0.3 30 m.0N 000 0.3 $0 0.3 N03 m0om>20m 00202002202 n.0N 0E. N. N 0mm 0.0N m8 0. 2 N 000; 0.0N nNNJ 002807.00. 20.80m 90.. 002.com 0.0 00m 0.0 2 m 3. 2mm «.2. 20m 0.0 00m wEEEH 80200032 002. m0N 000.2 0.0N 000; SN $0; méN mNN; w.NN 02m; 0023392 020220003 00... m0 2 m0 N2 m .0 NN .00 NN 0.0 m m 002.com 200022202: . 002.com 2.2 09 0.2 2.0 0.m _ 30 0.3 NNO 0.2 0? 3.20.232 020 2020820020 0. 2. man; mm... 9.0; N.Nv wow; n.0m 3.0; 2.0mm m 2 m.N . 020220022. 020 mmm02w020 $228.0 0.0N 000 0.mN mm: 0.wN 3N; SN 0:} wNN 3.0; bmfigab 20 0w0=00 . A0885 N; D. 2.2 mm 0.N S 0; N0 2 20 20 3002200“ 060m 02582 fim 0: 0N 2.: EN 0: fim 2m 2 m.m 00N 0506 303202020. ~00 E m.N m00 waN 2.00 0m0.m 2.00 Gm.m 2.00 000.2 02088080. X. 2 ex. 2 R. 2 ex. 2 X. 2 003000M 802.com mow.m HZ $0.2 n2 0N}. n2 $0.... HZ 20% H2 000N 000N 000N m00N 200N 220..“ A0 2003200. M2..>.~000- 0202202020 \0 22002022 222 200.222 3 030.0 59 88. v 2 880.00 28530... 8580 :0 33 2S :3 20 3.0 0.8 800 2% 03.0 08 0202 008082,. 0.2 5: 0.2 we: 03 :3 0mm $5 2.: :00 8008085 2.0 08 an %N 0.0 an 00 000 mm 2 m 8900.02 280580 . $202203. 0.8 ~22 2% $3 02 S 3 0.2 0:; 3m 2:; 80303200 2 n no 2 3 n no 2 2.0 b 3082 X 2 X 2 00 2 “X. 2 X 2 00>m000m 000m>00m 800 "2 $0.0 "2 E} "2 $3. "2 23 "2 008 88 88 88 38 .90300080 2 2000 60 Education and Employment-Related Characteristics of Customers at Closure by Year This next section examines variables pertinent to education and employment at closure (Table 15). A chi-square analysis of level of education at closure indicated statistically significant differences X2 (32, N = 23,135) = 113.04, p < .0005 among the five years studied. The percentage of customers with high school graduate equivalency at the time of case closure decreased from 32.9% in 2004 to 29.4% in 2008. However there was a nonlinear variation greater than 2% through the years with a 28.0% low point noted for 2006. The percentage of customers with bachelor's degrees increased from 12.6 % in 2004 to 15.2 % in 2008. The percentage of customers with master's degree or higher increased from 4.0% in 2004 to 6.1% in 2008. There was an overall increase in employment outcome from 47.8% in 2004 to 50.2% in 2008. However there was a decrease of 1.8% between 2007 and 2008, )(2 (4, N: 23,135) = 24.13, p < .0005. Average hourly wages at closure improved between 2004 and 2008, )(2 ( 16, N= 11,186) = 183.97, p < .0005. A marked, 9.2% decrease was noted in the percentage of customers earnings $6.49 and less an hour, and a 3.8% increase in the percentage of customers earning between $11.50 and $17.49 an hour. Similarly, a 7.6% increase was found in the percentage of customers earning $17.50 or above an hour. A review of the number of hours worked at closure identified a 2.5% increase in the percentage of customers working between 1 l and 20 hours per week, x2 (16, N = 1 1,660) = 94.19, p < .0005. 61 «0.022.228 032C SN 8m 28 02. 0.: an 0.2 00m 2.: 03 8.20030 0.2 5 240 Sn :2 0N0 0.8 Sn 2% am 3.20 902; in E 0.00 E :2 3 2% § 2% 83 3.209030 2 02 2: N: 0.0 we 4.0 on 2: EN $.00 98.00 0.4 a 00 NS 2: 92 0.2 gm 0.: m2 2.00200 33 080 2:.“ 03.0 «$0 . 000% €82 2m 83 2% 02.0 in 02.0 in 920 2% 022 0922080 2% 30; 204 as; 004 :3 0.0... 83 0% 25.0 80208082 83“ $3. 5.4 a? 2% . 2:86 .8 25 3 RN 3 an 2 4mm 3. am 3. 0mm 0:028 020000.023: 02 En 22 80 0.3 20 02 08 0.2 E 800202282 3: 80 02 80 0.: ME 0.: :0 0.2 23 08388 000 3283. 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This first analysis examines the primary source of support at closure. A statistically significant change was noted in the types of supports received between 2004 and 2008, f (12, N: 21,831) = 61 .47, p < .0005. The use of family and friends as support decreased by 3.5% from 17.9% in 2004 to 14.4% in 2008. Conversely the utilization of public supports increased by 3.6% from 32.7% in 2004 to 36.3% in 2008. An examination of distinct types of public supports, it was found that the number of Social Security disability insurance beneficiaries’ increased 5.7% from 28.8% in 2004 to 34.5% in 2008 12 (4, N: 22,822) = 61.69, p < .0005. The percentage of customers using TANF support at closure decreased by 0.8% from 1.7% in 2004 to 0.9% in 2008 X2 (4, N = 22,797) = 20.97, p < .0005. Similarly, the percentage of customers utilizing general assistance at closure decreased by 1.2% from 2.0% in 2004 to 0.8% in 2008, )(2 (4, N = 22,801) = 27.25, p < .0005. The number of those benefiting from Medicaid insurance coverage increased by 3.5% from 26.1% in 2004 to 29.6% in 2008 X2 (4, N= 22,809) = 20.51, p < .0005. Also, Medicare insurance coverage increased as well from 19.1% in 2004 to 23.6% in 2008 X2 (4, N= 22,800) = 59.94, p < .0005. A chi-square analysis indicated a statistically significant difference in the number of supports used by customers contingent on the year of exit, 2004 through 2008 )(2 (16, N = 22,773) = 58.86, p. < .0005. The percentage of customers who received zero supports decreased by over 5% from 49.3% in 2004 to 44.2% in 2008. In contrast, the number of customers who received one support increased slightly with under 5% from 43.3% in 2004 to 48.0% in 2008. 64 This final analysis of this section looks at differences in the amount of time (in years) elapsed between application and closure across these years studied, 2004 through 2008, 12(16, N= 23,135) = 330.71, p < .0005. 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Ex ea 2 X. 2 ea 2 R. 2 ..\e 2 32222226 2 2 2 2 2 883.528 88 Son 88 88 88 222222 E 2231 68 Research Question Two: An analysis of outcomes (type of closure) based on characteristics for this population The second part of this analysis examines differences associated with employment outcomes. The first review is of the aggregate population of all customers served from 2004 through 2008, followed by an examination of changes in outcomes between 2004 and 2008. As previously illustrated (Table 2) during the period between 2004 and 2008 on average 50.4% of customers with SCI achieved employment at closure. Customer Characteristics by Type of Closure This first part looks directly at customer characteristics at application by closure status (Table 17). A chi-square analysis reflected no statistically significant differences in the distribution of employment outcome by gender. However, women had a slightly better employment outcome than men. The percentage of women achieving employment was 51.8% as opposed to 49.6% of men. This next analysis examines employment outcome by race and their statistically significant differences 12 (3, N: 23,126) = 189.79, p. < .0005. White or Asian customers represent 71.1% of customers served yet 74.5% of customers with a positive employment outcome. Hispanics also achieved a higher than average outcome representing 8.8% of customers served yet 9.0% of customers with a positive employment outcome. The reverse is true for African American or Black and All Other Race customers. African American or Black customers comprised 17% of customers and only 13.8% of those employed at closure and finally All Other Races represent 3% of customers and 2.7% of those employed. A chi-square analysis indicated age at application was statistically significant with a higher percentage of older customers achieving positive employment outcomes [2 (6, N = 23,135) = 27.92, p < .0005. The 69 highest percentages of customers achieving a positive employment outcome were those over 64 years old; 63.4% became employed. Over 55% of customers aged 60 to 64% were successful followed by those 50 to 59 (52.0%). Age was not a statistically significant determinant of employment for those 49 and younger; with the percentage of employed varying by less than 2%; from 48.6% to 50.4%. There was no significant difference in the employment outcome of customers without a closure within 36 months or customers who had an IEP. Table 17 Customer Characteristics by Type of Closure Total Unemloyed Employed N n % n % Gender Male 15,032 7,573 50.4 7,459 49.6 Female 8,103 3,902 48.2 4,201 51.8 Race ' White/Asian 16,453 7,767 47.2 8,686 52.8 African American or Black 3,941 2,229 59.1 1,612 40.9 Hispanic 2,035 986 48.5 1,049 51.5 Other 697 385 55.2 312 44.8 Age at Application * Up to age 21 3,502 1,767 50.5 1,735 49.5 22 to 29 3,446 1,772 51.4 1,674 48.6 30 to 39 5,920 2,945 49.7 2,975 50.3 40 to 49 6,552 3,248 49.6 3,304 50.4 50 to 59 3,092 1,483 48.0 1,609 52.0 60 to 64 407 181 44.5 226 55.5 Over 64 216 79 36.6 137 63.4 Previous Closure None in past 36 months 18,831 9,555 50.7 9,276 49.3 IEP Did not have an IEP 21,723 10,764 49.6 10,959 50.4 Had an IEP 1,412 71 1 50.4 701 49.6 *Significant difference p < .0005 Level of Education and Employment Characteristics of Customers at Application, by Type of Closure Table 18 summarizes the outcome related differences associated with education and employment factors at application. There were a number of statistically significant differences in employment outcome based on the education level at application. )(2 (8, N = 23,135) = 725.77, p < .0005. The majority of customers with an Associates degree or higher achieved a positive employment outcome. More than three quarters (77.5%) of customers with a master's degrees and two thirds (68.3%) of customers with a bachelor's degree were employed at closure. Employment status at application also impacted employment outcomes at closure )(2 (9, N = 23,135) = 1,577.55, p < .0005. The majority of customers unemployed at application (N = 7,426) were also unemployed at closure; only 43.6% achieved employment. Over half of students in a secondary setting (54.7%), students in other classifications (51.5%) and unemployed trainee's or interns (52.8%) were employed at closure. The majority of customers employed at application in an integrated setting without supports were still employed at closure (78.3%) as were customers employed in an integrated setting with supports (84.4%) and those who were self-employed (81.7%). These customers were included in this study because they represent almost twenty percent (17.2%) of customers served and researchers, counselors and administrators may benefits from an understanding of the characteristics of this population as well. An examination of demographic factors associated with customers employed at application and closure revealed a number of items for discussion. First race and gender differences were not statistically significant however a higher percentage of Whites and Asians as 71 well as males exited employed. The majority of customers with fewer than three supports at application were also employed at closure. An examination of the services received by customers employed at application was also examined. The largest proportion of customers utilized assessment services (n = 2634), diagnostic and treatment services (n = 1,736), rehabilitation technology services (n = 1,504), transportation services (n = 703), vocational rehabilitation counseling and guidance services (n = 2,010). Only 561 customers received college or university training services; 64.2% were employed at closure. There was a statistically significant and positive linear relationship between hourly wage at application and employment closure )(2 (6, N = 3,987) = 140.94, p < .0005. Over two thirds of customers employed at application were still employed at closure regardless of their hourly wage however the higher the salary at application the higher percentage of employment at closure. Almost 90% (89.1%) of those employed at application earning over $17.50 an hour were still employed at closure. Similarly approximately 80% of those earning between $11.50 and $17.49 an hour (81.6%) and those earning between $8.50 and $11.49 an hour (79.8%) were still employed at closure. The final review in this section examines the differences associated with hours worked at application and employment outcome X2 (5, N = 23,132) = 1,490.44, p < .0005. Consistent with employment status at application, hours worked at application is positively associated with a positive employment outcome at closure. Over 70% of all customers working at least one hour a week were employed at closure. Over 65.0% of those reporting zero hours but working at application (n = 179) were employed at closure. 72 Table 18 Level of Education and Employment Characteristics of Customers at Application, by Type of Closure Total Unemployed Employed N n % n % Level of Education 1‘ No formal schooling 40 23 57.5 17 42.5 Elementary, grades 1-8 594 345 58.1 249 41.9 Secondary, no diploma 3,548 2,125 59.9 1,423 40.1 Special education 248 l 19 48.0 129 52.0 completion High school graduate 9,444 4,981 52.7 4,463 47.3 equivalency Post secondary, no 4,214 2,103 49.9 2,111 50.1 degree Associate deg or voc 2,347 991 42.2 1,356 57.8 tech Bachelor’s degree 1,950 619 31.7 1,331 68.3 Master’s degree or 750 169 22.5 581 77.5 higher Employment Status ' Integrated, no supports 3,401 739 21.7 2,662 78.3 Extended employment 27 9 33.3 18 66.7 Self employed 213 39 18.3 174 81.7 Homemaker 180 61 33.9 1 19 66.1 Unpaid family worker 35 15 42.9 20 57.1 Integrated, with 192 30 15.6 162 84.4 supports Not emp. student in a 944 428 45.3 516 54.7 Secondary setting Not emp. Student other 1,020 495 48.5 525 51.5 Unemployed trainee 72 34 47.2 38 52.8 Other unemployed 17,051 9,625 56.4 7,426 43.6 Hourly Wage ' Up to $6.49 789 267 33.8 522 66.2 $6.50 to $8.49 760 207 27.2 553 72.8 $8.50 to $11.49 853 172 20.2 681 79.8 $11.50 to $17.49 790 145 18.4 645 81.6 Over $17.50 795 87 10.9 708 89.1 73 (table continues) Table 18 (continued). Total Unemployed Employed N n % n % Hours Worked ' O 179 61 34.1 1 18 3.8 1-10 308 85 27.6 223 72.4 11-20 891 229 25.7 662 74.3 21-35 725 166 22.9 559 77.1 36-40 1771 302 17.1 1469 82.9 41 or more 109 25 22.9 84 77.1 *Significant difference p < .0005 Customer Supports at Application, by Type of Closure This next section reviews the difference in closure status in relation to customer supports at application (Table 19). There was a statistically significant difference in employment outcome based on a customer’s primary source of support at app< lication [2 (3, N = 23,091 = 973.96, p < .0005. Almost three quarters (73.3%) of customers with personal income were employed at closure. Only 42.2% of customers who received any type of public support at application were employed at closure. Chi-square analyses indicated a statistically significant difference in the employment outcome for customers utilizing Social Security Disability Insurance )(2 (l, N = 23,099 = 25.40, p < .0005, Social Security Income, Aged, Blind, Disabled 12 (1, N = 23,094 = 489.01, p < .0005; Temporary Assistance to Needy Families X2 (l, N = 23,100 = 22.51, p < .0005 and General Assistance x2 (1, N = 23,10 = 59.12, p.0005. Only 47.4% of SSDI recipients, 41.0% of TANF users, 35.7% of those on SSI, and 35.3% of those on General Assistance achieved an employment outcome. The majority (58.1%) of customers using Medicaid were unemployed at closure 12 (1, N = 22,987 = 256.10, p < .0005. There was no statistically significant difference in those utilizing Medicare and Other Public Source’s; just over 52.0% were employed at closure. Chi square analyses 74 detected statistically significant differences for customers with private insurance via other means (56.4% employed) X2 (1, N = 22,941 = 74.94, p < .0005 and customers with private insurance via employment (73.0% employed) 12 (l, N = 22,944 = 439.09, p < .0005. An evaluation of the number of supports for categories with 50 or more customers indicated a statistically significant and linear relationship between number of supports and employment outcome )(2 (5, (N = 23,089) = 395.37, p < .0005. The majority of customers with no supports were employed whereas as the majority of customers with one or more supports were unemployed at closure. A chi- square analysis of days from application to eligibility and employment reflected a statistically significant difference 1‘? (3, N = 23,135) = 146.24, p < .0005. There was a negative linear relationship as customers with a shorter time between application and eligibility we more likely to achieve employment; 53.9% of customers who achieved eligibility within 30 days or less were employed at closure as opposed to only 42.6% of those who achieved eligibility after 91 or more days. Table 19 Customer Supports at Application, by Type of Closure Total Unemployed Employed N n % n % Primary Source of Support ‘ Personal income 3,456 924 26.7 2,532 73.3 Family friends 7,890 3,939 49.9 3,951 50.1 Public support 9,389 5,423 57.8 3,966 42.2 Other 2,356 1,145 48.6 1,211 51.4 (table continues) 75 Table 19 (continued) 76 Total Unemployed Enylojed N n % n % Type of Public Support Social Security 6,326 3,309 52.3 3,017 47.4 Disability ‘ SSI Aged, Blind, 4,574 2,939 64.3 1,635 35.7 Disabled . TANF ‘ 490 295 60.2 195 41.0 Veterans’ Disability 176 95 54.0 81 46.0 Workers’ 1,046 490 46.8 556 53.2 Compensation General Assistance ’ 538 348 64.7 190 35.3 Other Public Support 1,821 917 50.4 904 49.6 Type of Medical Insurance Medicaid " 6,249 3,632 58.1 2,617 41.9 Medicare 3,882 1,834 47.2 2,048 52.8 Other Public Source 961 457 47.6 504 52.4 Private via 1,984 535 27.0 1,449 73.0 Employment ' Private via Other 4,463 1,947 43.6 2,516 56.4 Means 1' Number of Supports * 0 10,239 4,383 42.8 5,856 57.2 1 10,917 5,686 53.8 5,049 46.2 2 1,766 1,095 62.0 671 38.0 3 161 108 67.1 53 32.9 4 5 1 20.0 4 80.0 5 1 O 0.0 1 100.0 Days from Application to Eligibility " 0 to 30 11,993 5,523 46.1 6,470 53.9 31 to 60 6,671 3,467 52.0 3,204 48.0 61 to 90 2,128 1,139 53.5 989 46.5 91 or more 2,343 1,346 57.4 997 42.6 *Significant difference p < .0005 Cost of Goods and Purchased Services by Type of Closure There is a statistically significant difference in the cost of goods and purchased services and employment outcome x2 (4, N = 23,135) = 1,297.76, p < .0005 (Table 20). Less than 35% of customers who received $1 ,000.00 or less in goods and purchased services achieved employment at closure as opposed to almost 70% of those receiving over $20,000.00. Table 20 Cost of Goods and Purchased Services by Type of Closure Total Unemployed Employed Cost of Goods and N n % n % Purchased Services $0.00 1,821 1,221 67.1 600 32.9 $1.00 to $1,000 4,488 2,942 65.6 1,546 34.4 $1,001 to $5,000 7,455 3,804 51.0 3,651 49.0 $5,001 to $10,000 3,624 1,555 42.9 2,069 57.1 $10,001 to $20,000 2,770 1,005 36.3 1,765 63.7 $20,001 to $50,000 2,193 689 31.4 1,504 68.6 $50,001 or more 784 259 33.0 525 67.0 *Significant difference p < .0005 Number and Percent of Customers Receiving Services, by Type of Closure Of the 22 service categories 1 I appeared to impact employment outcome (Table 21). Almost 70% of customers who received on-the-job training were employed at closure 12 (1, N = 23,135) = 72.53, p < .0005. Nearly two-thirds of customers who received rehabilitation technology were successful as well x2 (1, N = 23,135) = 639.38, p < .0005. Over 60.0% of customers who received job placement assistance {7 (1, N = 23,135) = 556.63,p < .0005, on—the-job-support )(2 (1, N = 23,135) = 118.73, p < .0005 and technical assistance [7 (1, N = 23,135) = 69.29, p < .0005 had a successful 77 employment closure as well. The majority of customers who received job search assistancef (l, N= 23,135) = 225.41, p < .0005, maintenancexz (l, N= 23,135) = 181.03, p < .0005, other services, 12 (1, N = 23,135) = 143.17, p < .0005; information and referral/ (1, N = 23,135) = 14.85,p < .0005,job readiness trainingxz (1, N: 23,135) = 13.42, p < .0005 and vocational rehabilitation and guidance )2 (1, N = 23,135) = 13.96, p < .0005 were employed at closure as well. Table 21 Number and Percent of Customers Receiving Services, by Type of Closure Total Unemployed Employed Services Received N n % n % Assessment 15,681 7,898 50.4 7,783 49.6 Augmentative Skills 714 316 44.3 398 55.7 Basic Remedial/Literacy 345 202 58.6 143 41.4 College or University 6,423 3,289 51.2 3,134 48.8 Diagnosis and Treatment 9,462 4,641 49.0 4,821 51.0 Information and Referral " 3,378 1,572 46.5 1,806 53.5 Interpreter 1 10 52 47.3 58 52.7 Job Placement Assistance * 5,742 2,073 36.1 3,669 63.9 Job Readiness Training " 1,722 781 45.4 941 54.6 Job Search Assistance ‘ 4,859 1,945 40.0 2,914 60.0 Maintenance * 4,513 1,833 40.6 2,680 59.4 Miscellaneous Training 3,025 1,429 47.2 1,596 52.8 Occupational/Vocational 3,797 1,802 47.5 1,995 52.5 On-the-job Support " 2,110 808 38.3 1,302 61.7 On-the-job Training ‘ 493 151 30.6 342 69.4 Other " 7,171 3,136 43.7 4,035 56.3 Personal Attendant 594 282 47.5 3 12 52.5 Reader 46 26 56.5 20 43.5 Rehab Technology " 5,759 2,025 35.2 3,734 64.8 Technical Assistance " 1,327 51 1 38.5 816 61.5 Transportation 8,251 3,970 48.1 4,281 51.9 Voc Rehab & Guidance ' 14,112 6,861 48.6 7,251 51.4 *Significant difference p < .0005 78 Level of Education and Employment Characteristics of Customers at Closure, by Type of Closure Table 22 illustrates the level of education and employment characteristics of customers at closure, by type of closure. Similar to level of education at application a customer’s level of education at closure appeared to influence employment outcome X2 (8, N = 23,135) = 1,844.62, p < .0005. Nearly 80% of customers with a master’s degree or higher, 72.7% of customers with a bachelor’s degree and 61.7% of those with an Associate degree or vocational technology certification were employed at closure. The majority of customers with a post secondary education with no degree or below were unemployed at closure. Hourly wage and hours worked are specific to customers employed at closure so a comparison by type of closure is not possible. 79 Table 22 Level of Education and Employment Characteristics of Customers at Closure, by Type of Closure Total Unemployed Employed N n % n % Level of Education I No formal schooling 19 15 78.9 4 21.1 Elementary, grades 1-8 450 261 58.0 189 42.0 Secondary, no diploma 2,199 1,430 65.0 769 35.0 Special ed completion 237 129 54.4 108 45.6 High school grad equiv 6,957 4,033 58.0 2,924 42.0 Post secondary, no 4,958 2,971 59.9 1,987 40.1 degree Associate deg or voc 3,868 1,481 38.3 2,387 61.7 tech Bachelor’s degree 3,267 908 27.8 2,359 72.7 Master’s degree or 1,180 247 20.9 933 79.1 higher Hourly Wage Up to $6.49 1,169 O 0.0 1,169 100.0 $6.50 to $8.49 1,079 0 0.0 1,079 100.0 $8.50 to $11.49 4,323 0 0.0 4,323 100.0 $11.50 to $17.49 2,659 0 0.0 2,659 100.0 Over $17.50 1,956 0 0.0 1,956 100.0 Hours Worked 0 474 0 0.0 474 100.0 1-10 531 0 0.0 531 100.0 11-20 2,135 0 0.0 2,135 100.0 21-35 2,286 0 0.0 2,286 100.0 36-40 5,949 0 0.0 5,949 100.0 41 or more 285 0 0.0 285 100.0 *Significant difference p < .0005 Customer Supports at Closure, by Type ofClosure This next section examines customer supports at closure (Table 23). There was a notable difference in the primary source of support and employment status at closure [7 (3, N = 21 ,831) = 10,593.04, p < .0005. Over 90% of customers reporting personal income at closure were employed. Just over a quarter of customers with public support at 80 closure and just under 20.0% of customers utilizing other support at closure exited with an employment outcome. Finally only 12.0% of customers relying on family and fiiends at closure were employed. The majority of customer’s utilizing any type of public support was unemployed at closure. Statistically significant differences in closure include the 46.8% of customers employed at closure who received social security disability, )(2 (1, N = 22,822 = 56.06, p < .0005 and the 32.7% of social security income recipients also employed, x2 (1, N = 22,825 = 722.55, p < .0005. Just over a quarter of TANF recipients, 12 (l, N = 22,797 = 73.04, p < .0005 and slightly over a third of those with worker’s compensation, )(2 (l, N = 22,802 = 45.68, p < .0005 and other public support, )(2 (1, N = 22,808 = 93.63, p < .0005 were also employed. Finally only 21.5% of customers who received general assistance at closure were employed, 12 (1, N = 22,801 = 110.38, p < .0005. Three of the five types of medical insurance had a statistically significant difference at closure. As one might expect nearly the entire population of customers with private insurance via employment were employed at closure [7 (l, N = 22,751 = 3,987.37, p < .0005. The majority (57.9%) of customers with private insurance via other means )(2 (1, N = 22,746 = 62.72, p < .0005 were employed at closure as well. Only 39.5% of customers who received Medicaid were employed at closure 12 (1, N = 22,809 = 467.45, p < .0005. A chi-square analysis of the number of supports at closure indicated a statistically significant difference X2 (1, N = 22,773 = 979.16, p < .0005 with fewer supports generally associated with improved employment outcome. Years from application to closure also reflected statistically significant difference f (4, N = 23,135) = 1,042.04, p < .0005 with over 70.0% of customers closed within one year were employed. The majority of customers who were active between 1 and 2 years were also 81 employed at closure. The majority of customers with two or more years from application to closure were less likely to be employed at closure. Table 23 Customer Supports at Closure, by Type of Closure Total Unemployed Employed N n % n % Primary Source of Support ‘ Personal income 9,956 898 9.0 9,058 91.0 Family friends 3,454 3,039 88.0 415 12.0 Public support 7,430 5,436 73.2 1,994 26.8 Other 991 798 80.5 193 19.5 Type of Public Support Social Security 7,237 3,849 53.2 3,388 46.8 Disability ‘ SS1 Aged, Blind, 4,575 3,080 67.3 1,495 32.7 Disabled ‘ TANF ’ 274 206 75.2 68 25.4 Veterans’ Disability 145 83 57.2 62 42.8 Workers’ 524 336 64.1 188 35.9 Compensation ' General Assistance ‘ 325 255 78.5 70 21.5 Other Public Support ‘ 832 549 66.0 283 34.0 Type of Medical Insurance Medicaid ' 6,441 3,899 60.5 2,542 39.5 Medicare 4,982 2,397 48.1 2,585 51.9 Other Public Source 853 388 45.5 465 54.5 Private via 4,167 200 4.8 3,967 95.2 Employment ‘ Private via Other 2,847 1,199 42.1 1,648 57.9 Means ' Number of Supports ’ 0 10,759 4,170 38.8 6,589 61.2 1 10,304 5,982 58.1 4,322 41.9 2 1,606 1,040 64.8 566 35 .2 3 100 77 77.0 23 23.0 4 4 3 75.0 1 25.0 82 (table continues) Table 23 (continued) Total Unemployed Employed N n % n % Years from Application to Closure ' Less than 1 3,690 1,068 28.9 2,622 71.1 1 to less than 2 5,123 2,228 43.5 2,895 56.5 2 to less than 3 3,712 2,029 54.7 1,683 45.3 3 to less than 4 2,741 1,608 58.7 1,133 41.3 4 or more 7,869 4,542 57.7 3,327 42.3 *Significant difference p < .0005 Research Question Two (Part two): An analysis of outcomes (type of closure) based on characteristics for this population Analysis by Year This next section examines customer characteristics by year and type of closure. Because this analysis further examines five-year patterns of customer input, process and outcome variables by employment outcomes, many of the proportions are small (n < 50) and, as a result, changes in percentages are more sensitive. As a result, this analysis will only report on statistically significant differences and linear patterns of change between 2004 and 2008. Customer Characteristics by Year and Type of Closure Table 24 provides a summary of customer characteristics by year and type of closure. A statistically significant difference was found in the distribution of males by year and type of closure [7 (4, N = 15,032) = 24.47, p < .0005. Changes in outcome greater than 2.0% occurred between 2004 and 2005 (3.4% increase) and 2007 and 2008 (3.7% decrease). There were no five year linear patterns of change observed for males or females between 2004 and 2008. No observable linear patterns of change were found in employment outcomes by race as well. While not perfectly linear, in the age at application category, there was a general increase in the percentage of customers aged 40 83 to 49 who achieved an employment outcome. A chi-square analysis detected a statistically significant difference in the employment of customers without an IEP )(2 (4, N = 21,723) = 23.64, p < .0005 with a 3.5% increase between 2004 (47.8%) and 2005 (51.3%). Table 24 Customer Characteristics by Year and Type of Closure Total Unemployed Employed Variable Year N n % n % Gender 2004 3,820 2,035 53.3 1,785 46.7 2005 3,173 1,584 49.9 1,589 50.1 Male ' 2006 2,858 1,403 49.1 1,455 50.9 2007 2,626 1,246 47.4 1,380 52.6 2008 2,555 1,305 51.1 1,250 48.9 2004 2,095 1,052 50.2 1,043 49.8 2005 1,764 813 46.1 951 53.9 Female 2006 1,569 748 47.7 821 52.3 2007 1,427 699 49.0 728 51.0 2008 1,258 590 47.3 658 52.7 Race 2004 4,169 2,071 59.7 2,098 50.3 2005 3,553 1,659 46.7 1,894 53.3 White/Asian 2006 3,152 1,471 46.7 1,681 53.3 2007 2,885 1,308 45.3 1,577 54.7 2008 2,694 1,258 46.7 1,436 53.3 2004 1,003 618 61.6 385 38.4 2005 818 483 59.0 335 41.0 African American or 2006 733 415 56.6 318 43.4 Black 2007 729 419 57.5 310 42.5 2008 658 394 59.9 264 40.1 2004 572 291 50.9 281 49.1 2005 41 1 166 40.4 245 59.6 Hispanic 2006 404 195 48.3 209 51.7 2007 307 144 46.9 163 53.1 2008 341 190 55.7 151 44.3 84 (table continues) Table 24 (continued). Total Unemployed Employed Variable Year N n % n % 2004 162 99 61.1 63 38.9 2005 156 89 57.4 66 42.6 Other 2006 13 8 70 50.7 68 49.3 2007 132 74 56.1 58 43.9 2008 110 53 48.2 57 51.8 Age at Application 2004 641 319 49.8 322 50.2 2005 613 301 49.1 312 50.9 Up to age 21 2006 1,168 605 51.8 563 48.2 2007 556 274 49.3 282 50.7 2008 524 268 51.1 256 48.9 2004 906 502 55.4 404 44.6 2005 739 368 49.8 371 50.2 22 to 29 2006 651 298 45.8 353 54.2 2007 599 305 50.9 294 49.1 2008 551 299 54.3 252 45.7 2004 1,704 867 50.9 837 49.1 2005 1,360 673 49.5 687 50.5 30 to 39 2006 880 433 49.2 447 50.8 2007 1,041 487 46.8 554 53.2 2008 935 485 51.9 450 48.1 2004 1,806 962 53.3 844 46.7 2005 1,497 720 48.1 777 51.9 40 to 49 2006 1,020 494 48.4 526 51.6 2007 1,128 546 48.4 582 51.6 2008 1,101 526 47.8 575 52.2 2004 725 378 52.1 347 47.9 2005 599 286 47.7 313 52.3 50 to 59 2006 579 259 44.7 320 55.3 2007 602 288 47.8 314 52.2 2008 587 272 46.3 315 53.7 2004 89 46 51.7 43 48.3 2005 88 28 43.2 50 56.8 60 to 64 2006 73 26 49.3 37 50.7 2007 89 33 37.1 56 62.9 2008 68 28 41.2 40 58.8 2004 44 13 29.5 31 70.5 2005 41 1 1 26.8 30 73.2 Over 64 2006 56 26 46.4 30 53.6 2007 38 12 31.6 26 68.4 2008 37 17 45.9 20 54.1 (table continues) 85 Table 24 (continued). Total Unemployed Employed Variable Year N n % n % Previous Closure 2004 4,979 2,638 53.0 2,341 47.0 2005 3,947 1,947 49.3 2,000 50.7 None in past 36 2006 3,601 1,809 50.2 1,792 49.8 months 2007 3,241 1,588 49.0 1,653 51.0 2008 3,063 1,573 51.4 1,490 48.6 IEP 2004 5,638 2,942 52.2 2,696 47.8 2005 4,636 2,258 48.7 2,378 51.3 . Did not have an IEP 2006 4,160 2,020 48.6 2,140 51.4 2007 3,768 1,798 47.7 1,970 52.3 2008 3,521 1,746 49.6 1,775 50.4 2004 277 145 52.3 132 47.7 2005 301 139 46.2 162 53.8 Had an IEP 2006 267 131 49.1 136 50.9 2007 285 147 51.6 138 48.4 2008 282 149 52.8 133 47.2 *Significant difference p < .0005 Level of Education and Employment Characteristics of Customers at Application, by Year and Type of Closure This next section presents results on education and employment related characteristics of customers at application, by year and type of closure (Table 25). As noted in the previous section, the consecutive breakdown by category and year has resulted in smaller proportions for some groups so only statistically significant and linear patterns of change over the five years of study will be reported. There were no linear patterns of change associated with level of education at application. In the employment status at application category there was a positive linear relationship in the percentage of Other Unemployed customers employed at closure, with a progressive increase between 86 2004 (41.3%) and 2008 (57.4%). An examination Of the hourly wage and hours worked at application by year and type of employment closure revealed no linear patterns between 2004 and 2008. Table 25 Level of Education and Employment Characteristics of Customers at Application, by Year and Type of Closure Total Unemployed Employed Variable Year N n % n % Level of Education 2004 7 3 42.9 4 57.1 2005 1 1 4 36.4 7 63.6 No formal schooling 2006 6 3 50.0 3 50.0 2007 6 5 83.3 1 16.7 2008 10 8 80.0 2 20.0 2004 184 105 57.1 79 42.9 2005 137 74 54.0 63 46.0 Elementary, grades 1-8 2006 117 65 56.0 51 44.0 2007 82 50 61.0 32 39.0 2008 75 51 68.0 24 32.0 2004 894 566 63.3 328 36.7 2005 744 419 56.3 325 43.7 Secondary, no diploma 2006 697 416 59.7 281 40.3 2007 639 374 58.5 265 41.5 2008 574 360 61.0 224 39.0 2004 61 25 41.0 36 59.0 2005 48 22 45.8 26 54.2 Special ed completion 2006 44 24 54.5 20 45.5 2007 41 21 51.2 20 48.8 2008 54 27 50.0 27 50.0 2004 2,635 1,419 53.9 1,216 46.1 2005 2,091 1,095 52.4 996 47.6 High school grad equiv 2006 1,730 903 52.2 827 47.8 2007 1,544 788 51.0 756 49.0 2008 1,444 776 53.7 668 46.3 2004 1,021 548 53.7 473 46.3 2005 926 450 48.6 476 51.4 Post secondary, no degree 2006 834 389 46.6 445 53.4 2007 734 368 50.0 366 49.9 2008 699 348 49.8 351 50.2 87 (table continues) Table 25 (continued) Total Unemployed Employed Variable Year N n % n % 2004 534 224 41.9 310 58.1 2005 478 197 41.2 281 58.8 Associate deg or voc tech 2006 467 204 43.7 263 56.3 2007 436 182 41.7 254 58.3 2008 432 184 42.6 248 57.4 2004 442 159 36.0 283 64.0 2005 364 102 28.0 262 72.0 Bachelor’s degree 2006 389 121 31.1 268 68.9 2007 401 115 28.7 286 71.3 2008 354 122 34.5 232 65.5 2004 137 38 27.7 99 72.3 2005 138 34 24.6 1.4 75.4 Master’s degree or higher 2006 144 26 18.1 118 81.9 2007 170 42 24.7 128 75.3 2008 161 29 18.0 132 82.0 Employment Status 2004 792 204 25.8 588 74.2 2005 703 146 20.8 557 79.2 Integrated, no supports 2006 628 142 22.6 486 77.4 2007 652 117 17.9 535 82.1 2008 626 130 20.8 496 79.2 2004 7 3 42.9 4 57.1 2005 4 1 25.0 3 75.0 Extended employment 2006 8 3 37.5 5 62.5 2007 4 1 25.0 3 75.0 2008 4 1 25.0 3 75.0 2004 46 7 15.2 39 84.8 2005 44 5 11.4 39 88.6 Self employed 2006 47 11 23.4 36 76.6 2007 37 10 27.0 27 73.0 2008 37 6 15.4 33 84.6 2004 66 22 33.3 44 66.7 2005 39 12 30.8 27 69.2 Homemaker 2006 29 1 1 37.9 1 8 62.1 2007 25 8 32.0 17 68.0 2008 21 8 38.1 13 61.9 2004 10 4 40.0 6 60.0 2005 4 0 0.0 4 100.0 Unpaid family worker 2006 8 6 75.0 2 25.0 2007 8 2 25.0 6 75.0 2008 5 3 60.0 2 40.0 88 (table continues) Table 25 (continued). Total Unemployed Employed Variable Year N n % n % 2004 29 2 6.9 27 93.1 2005 34 5 14.7 29 85.3 Integrated, with supports 2006 35 6 17.1 28 82.9 2007 49 1 1 22.4 38 77.6 2008 45 6 13.3 39 86.7 2004 202 82 40.6 120 59.4 2005 216 103 47.7 113 52.3 Unemployed h.s. student 2006 186 69 37.1 117 62.9 2007 181 90 49.7 91 50.3 2008 159 84 52.8 75 47.2 2004 274 130 47.4 144 52.6 2005 215 115 53.5 100 46.5 Other unemployed student 2006 198 91 46.0 107 54.0 2007 181 84 46.4 97 53.6 2008 152 75 49.3 77 50.7 2004 l 1 5 45.5 6 54,5 2005 14 5 35.7 9 64.3 Unemployed trainee 2006 19 8 42.1 1 1 57.9 2007 13 6 46.2 7 53.8 2008 15 10 66.7 5 33.3 2004 4,478 2,628 58.7 1,850 41.3 2005 3,664 2,005 54.7 1,659 45.3 Other unemployed 2006 3,269 1,465 44.8 1,804 55 .2 2007 2,903 1,287 44.3 1,616 55.7 2008 2,737 1,165 42.6 1,572 57.4 Hourly Wage 2004 208 78 37.5 130 62.5 2005 142 40 28.2 102 71.8 Up to $6.49 2006 146 46 31.5 100 68.5 2007 137 48 35.0 89 65.0 2008 106 34 32.1 72 67.9 2004 182 39 21.4 143 78.6 2005 151 42 27.8 109 72.2 $6.50 to $8.49 2006 144 48 33.3 96 66.7 2007 1 19 29 24.4 90 75.6 2008 130 33 25.4 97 74.6 2004 174 41 23 .6 133 76.4 2005 189 30 15.9 159 84.1 $8.50 to $11.49 2006 155 31 20.0 124 80.0 2007 154 25 16.2 129 83.8 2008 146 31 21.2 115 78.8 89 (table continues) Table 25 (continued). Total Unemployed Employed Variable Year N n % n % 2004 173 37 21.4 136 78.6 2005 162 33 20.4 129 79.6 $11.50 to $17.49 2006 123 21 17.1 102 82.9 2007 145 17 11.7 128 88.3 2008 162 28 17.3 134 82.7 2004 130 18 13.8 112 86.2 2005 137 11 8.0 126 92.0 Over $17.50 2006 143 13 9.1 130 90.9 2007 183 19 10.4 164 89.6 2008 166 16 9.6 150 90.4 Hours Worked 2004 66 22 33.3 44 66.7 2005 39 12 30.8 27 69.2 0 2006 28 1 1 39.3 17 60.7 2007 25 8 32.0 17 68.0 2008 21 8 38.1 13 61.9 2004 72 17 23.6 55 76.4 2005 66 19 28.8 47 71.2 1-10 2006 65 21 32.3 44 67.7 2007 50 13 26.0 37 74.0 2008 55 15 27.3 40 72.7 2004 197 58 29.4 139 70.6 2005 177 38 21.5 139 78.5 1 1-20 2006 171 45 26.3 126 73.7 2007 177 41 23.2 136 76.8 2008 169 47 27.8 122 72.2 2004 187 56 29.9 131 70.1 2005 138 29 21.0 109 79.0 21-35 2006 147 36 24.5 111 75.5 2007 138 30 21.7 108 78.3 2008 115 15 13.0 100 87.0 2004 388 76 19.6 312 80.4 2005 383 65 17.0 318 83.0 36-40 2006 310 53 17.1 257 82.9 2007 344 50 14.5 294 85.5 2008 346 58 16.8 288 83.2 2004 23 6 26.1 17 73.9 2005 16 5 31.3 11 68.8 41 or more 2006 17 4 23.5 13 76.5 2007 29 4 13.8 25 86.2 2008 24 6 25.0 18 75.0 90 Customer Supports at Application, by Year and Type of Closure This next section examines five year patterns associated with customer supports at application by year and type of closure (Table 26). There were no linear patterns Of change for the employment outcome of customer’s who identified a primary source of support at application. In addition, there were no linear patterns in the percent of usage of the types of public support used at application. However, there was a statistically significant difference in the employment outcome of customers receiving Social Security insurance [7 (4, N = 6,326) = 18.31, p < .0005; most directly 3 5.0% increase in customer utilization of Social Security insurance occurred between 2005 and 2006. There were no five-year patterns of change in the either the type of medical insurance or the number of supports used at application. Finally while there were no five-year linear patterns of change associated with days from application to eligibility. However there was a statistically significant change within the five years; most directly there was over a 5% increase in the number of customers achieving eligibility within 30 days between 2004 and 2005 )(2 (4, N = 11,993) = 23.82, p < .0005. There was less than a 2% change between the remaining years (2005 through 2008). 91 Table 26 Customer Supports at Application, by Year and Type of Closure Total UnemploLed Employed Variable Year N n % n % Primary Source of Support 2004 81 1 240 29.6 571 70.4 2005 724 191 26.4 533 73.6 Personal income 2006 640 1 80 28.1 460 71 .9 2007 660 154 23.3 506 76.7 2008 621 159 25.6 462 74.4 2004 2,068 1,067 51.6 1,001 48.4 2005 1,750 823 47.0 927 53.0 Other 2006 1,544 775 50.2 769 49.8 2007 1,295 657 50.7 638 49.3 2008 1,233 617 50.0 616 50.0 2004 2,352 1,425 60.6 927 39.4 2005 1,904 1,109 58.2 795 41.8 Public support 2006 1,798 982 54.6 816 45.4 2007 1,738 970 55.8 768 44.2 2008 1,597 937 58.7 660 41.3 2004 675 346 51.3 329 48.7 2005 542 257 47.4 285 52.6 Family friends 2006 438 207 47.3 231 52.7 2007 357 161 45.1 196 54.9 2008 344 174 50.6 170 49.4 Type of Public Support 2004 1,396 783 56.1 613 43.9 2005 1,251 685 54.8 566 45.2 Social Security 2006 1,270 629 49.5 641 50.5 Disability ‘ 2007 1,252 611 48.8 641 51.2 2008 1,157 601 51.9 556 48.1 2004 1,095 726 66.3 369 33.7 2005 949 604 63.6 345 36.4 881 Aged Blind 2006 877 533 60.8 344 39.2 Disabled 2007 847 547 64.6 300 35.4 2008 806 529 65.6 277 34.4 2004 159 104 65.4 55 34.6 2005 111 61 55.0 50 45.0 TANF 2006 84 49 58.3 35 41.7 2007 66 39 59.1 27 40.9 2008 70 42 60.0 28 40.0 92 (table continues) Table 26 (continued). Total Unemployed Employed Variable Year N n % n % 2004 52 27 51.9 25 48.1 2005 34 17 50.0 17 50.0 Veterans’ Disability 2006 35 18 51.4 17 48.6 2007 24 15 60.0 10 40.0 2008 30 18 60.0 12 40.0 2004 315 164 52.1 151 47.9 2005 21 l 92 43.6 119 56.4 Workers’ 2006 184 73 39.7 1 1 1 60.3 Compensation 2007 176 80 45.5 96 54.5 2008 160 81 50.6 79 49.4 2004 189 130 68.8 59 31.2 2005 109 70 64.2 39 35.8 General Assistance 2006 76 49 64.5 27 35.5 2007 88 57 64.8 31 35 .2 2008 76 42 55.3 34 44.7 2004 487 242 49.7 245 50.3 2005 438 201 25.9 237 54.1 Other Public Support 2006 350 183 52.3 167 47.7 2007 251 131 52.2 120 47.8 2008 295 160 54.2 135 45 .8 Type of Medical Insurance 2004 1,391 859 61.8 532 38.2 2005 1,262 716 56.7 546 43.3 Medicaid 2006 1,21 1 674 55.7 537 44.3 2007 1,184 681 57.5 503 42.5 2008 1,201 702 58.5 499 41.5 2004 792 398 50.3 394 49.7 2005 749 342 45.7 407 54.3 Medicare 2006 774 343 44.3 431 55.7 2007 799 373 46.7 426 53.3 2008 768 378 49.2 390 50.8 2004 231 127 55.0 104 45.0 2005 216 95 44.0 121 56.0 Other Public Source 2006 171 73 42.7 98 57.3 2007 181 90 49.7 91 50.3 2008 162 72 44.4 90 55.6 93 (table continues) Table 26 (continued). Total Unemployed Employed Variable Year N n % n % 2004 496 166 33.5 330 66.5 2005 432 1 14 26.4 318 73.6 Private via 2006 352 85 24.1 267 75.9 Employment 2007 359 82 22.8 277 77.2 2008 345 88 25.5 257 74.5 2004 1,179 548 46.5 631 53.5 2005 908 377 41.5 531 58.5 Private via Other 2006 857 352 41.6 495 58.4 Means 2007 792 321 40.5 471 59.5 2008 737 349 47.4 388 52.6 Number of Supports 2004 2,694 1,229 45 .6 1,465 54.4 2005 2,264 924 40.8 1,340 59.2 0 2006 1,963 871 44.4 1,092 55 .6 2007 1,720 704 40.9 1,016 59.1 2008 1,528 655 41.0 943 59.0 2004 2,760 1,555 56.3 1,205 43.7 2005 2,276 1,237 54.3 1,039 45.7 1 2006 2,071 1,045 50.5 1,026 49.5 2007 1,975 1,013 51.3 962 48.7 2008 1,835 1,018 55.5 817 44.5 2004 401 260 64.8 141 35.2 2005 353 212 60.1 141 39.9 2 2006 358 213 59.5 145 40.5 2007 332 209 63.0 123 37.0 2008 322 201 62.4 671 38.0 2004 39 32 82.1 7 17.9 2005 40 23 57.5 17 42.5 3 2006 28 21 75.0 7 25.0 2007 19 15 78.9 4 21.1 2008 35 17 48.5 18 51.4 2004 0 0 0.0 0 0.0 2005 0 0 0.0 0 0.0 4 2006 1 0 0.0 1 100.0 2007 2 1 50.0 1 50.0 2008 2 0 0.0 2 100.0 94 (table continues) Table 26 (continuecQ. Total Unemployed Employed Variable Year N n % n % 2004 1 0 0.0 1 100.0 2005 0 0 0.0 0 0.0 5 2006 0 0 0.0 0 0.0 2007 0 0 0.0 0 0.0 2008 0 0 0.0 0 0.0 Days from Application to Eligibility 2004 2,936 1,464 49.9 1,472 50.1 2005 2,480 1,103 44.5 1,377 55.5 0 to 30 ‘ 2006 2,329 1,060 45.5 1,269 54.5 2007 2,162 954 44.1 1,208 55.9 2008 2,086 942 45.2 1,144 54.8 2004 1,717 913 53.2 804 46.8 2005 1,432 731 51.0 701 49.0 31 to 60 2006 1,224 608 49.7 616 50.3 2007 1,198 619 51.7 579 48.3 2008 1,100 596 54.2 504 45.8 2004 629 332 52.8 297 47.2 2005 482 263 54.6 219 45.4 61 to 90 2006 413 220 53.3 193 46.7 2007 314 163 51.9 151 48.1 2008 290 161 55.5 129 44.5 2004 633 378 59.7 255 40.3 2005 543 300 55.2 243 44.8 91 or more 2006 461 263 57.0 198 43.0 2007 379 209 55.1 170 44.9 2008 327 196 59.9 131 40.1 *Significant difference p < .0005 Cost of Goods and Purchased Services by Year and Type of Closure Table 27 provides a summary of the cost of goods and purchased services by year and type of closure. While there were no statistically significant changes, there was a funding category that revealed close to a negative linear pattern. There was a 3.7% decrease in the percentage of finding between $10,001 and $20,000. 95 Table 27 Cost of Goods and Purchased Services by Year and Type of Closure Total Unemployed Employed Cost of Goods and Year N n % n % Purchased Services 2004 482 331 68.7 151 31.3 2005 398 257 64.6 141 35.4 0 2006 343 234 68.2 109 31.8 2007 301 194 64.5 107 35.5 2008 297 205 69.0 92 31.0 2004 1,245 859 69.0 386 31.0 2005 936 576 61.5 360 38.5 $1 to $1,000 2006 838 555 66.2 283 33.8 2007 750 481 64.1 269 35.9 2008 719 471 65.5 248 34.5 2004 2,032 1,072 52.8 960 47.2 2005 1,619 810 50.0 809 50.0 $1,001 - $5,000 2006 1,417 694 49.0 723 51.0 2007 1,229 623 50.7 606 49.3 2008 1.158 605 52.2 553 47.8 2004 837 402 42.9 535 57.1 2005 785 343 43.7 442 56.3 $5,001 - $10,000 2006 712 315 44.2 397 55.8 2007 655 268 40.9 387 59.1 2008 535 227 42.4 308 57.6 2004 652 226 34.7 426 65.3 2005 636 227 35.7 409 64.3 $10,001- $20,000 2006 507 178 35.1 329 64.5 2007 498 191 38.4 307 61.6 2008 477 183 38.4 294 61.6 2004 450 157 34.9 293 65.1 2005 409 134 32.8 275 67.2 $20,001 - $50,000 2006 440 124 28.2 316 71.8 2007 442 131 29.6 31 1 70.4 2008 452 143 31.6 309 68.4 2004 l 17 40 34.2 77 65.8 2005 154 50 32.5 104 67.5 $50,0010r more 2006 170 51 30.0 1 19 70.0 2007 178 57 32.0 121 68.0 2008 165 61 37.0 104 63.0 96 Number and Percent of Customers Receiving Services, by Year and Type of Closure This next section provides an overview of the number and percent of customers receiving services, by year and type of closure, and highlights any statistically significant changes and linear patterns of change (Table 28). While there were no observable linear patterns demonstrating a decrease or increase in services from 2004 through 2008 there were statistically significant changes within two of the 22 service types. There were changes in the percentage of customers who received occupational and vocational services and achieved an employment outcome [7 (4, N = 3,797) = 24.97, p < .0005. Specifically, there was a 3.4% increase between 2004 and 2005 and a 7.1% decrease between 2006 and 2007 followed by an additional 4.7% decrease between 2007 and 2008. A chi-square analysis also detected a statistically significant change in vocational rehabilitation counseling and guidance services 2’2 (4, N = 14,112) = 21.16, p < .0005. A 4.3% increase between 2004 and 2005 was the only change greater than 1% that occurred in the provision of vocational rehabilitation counseling and guidance services between 2004 and 2008. 97 Table 28 Number and Percent of Customers Receiving Services, by Year and Type of Closure Total Unemployed Employed Services Received Year N n % n % 2004 4,088 2,156 52.7 1,932 47.3 2005 3,361 1,654 49.2 1,707 50.8 Assessment 2006 3,030 1,532 50.6 1,498 49.4 2007 2,688 1,313 48.8 1,375 51.2 2008 2,514 1,243 49.4 1,271 50.6 2004 209 106 50.7 103 49.3 2005 154 52 33.8 102 66.2 Augmentative Skills 2006 118 49 41.5 69 58.5 2007 117 57 48.7 60 51.3 2008 116 52 44.8 64 55.2 2004 64 44 68.8 20 31.3 2005 92 54 58.7 38 41.3 Basic Remedial/Literacy 2006 87 49 56.3 38 43.7 2007 55 26 47.3 29 52.7 2008 47 29 61.7 18 38.3 2004 1,644 831 50.5 813 49.5 2005 1,416 724 51 .1 692 48.9 College or University 2006 1,239 617 49.8 622 50.2 2007 1,135 583 51.4 552 48.6 2008 989 534 54.0 455 46.0 2004 2,315 1,205 52.1 1,110 47.9 2005 1,941 924 47.6 1,017 52.4 Diagnosis and Treatment 2006 1,868 908 48.6 960 51.4 2007 1,745 834 47.8 91 1 52.2 2008 1,593 770 48.3 823 51.7 2004 758 387 51.1 371 48.9 2005 622 283 45.5 339 54.5 Information and Referral 2006 614 268 43.6 346 56.4 2007 647 293 45.3 354 54.7 2008 737 341 46.3 396 53.7 2004 35 13 37.1 22 62.9 2005 22 13 59.1 9 40.9 Interpreter 2006 22 10 45 .5 1 2 54.5 2007 12 6 50.0 6 50.0 2008 19 10 52.6 9 47.4 2004 1,348 485 36.0 863 64.0 2005 1,223 426 34.8 797 65.2 Job Placement Assistance 2006 1,083 375 34.6 708 65.4 2007 1,088 395 36.3 693 63.7 2008 1,000 392 39.2 608 60.8 98 (table continues) Table 28 (continued). Total Unemployed Employed Variable Year N n % n % 2004 399 190 47.6 209 52.4 2005 364 158 43.4 206 56.6 Job Readiness Training 2006 334 138 41.3 196 58.7 2007 319 141 44.2 178 55.8 2008 306 154 50.3 152 49.7 2004 1,227 504 41.1 723 58.9 2005 1,079 401 37.2 678 62.8 Job Search Assistance 2006 915 364 39.8 551 60.2 2007 859 338 39.3 521 60.7 2008 779 338 43.4 441 56.6 2004 1,102 473 42.9 629 57.1 2005 983 400 40.7 583 59.3 Maintenance 2006 909 364 40.0 545 60.0 2007 797 31 1 39.0 486 61.0 2008 722 285 39.5 437 60.5 2004 754 372 49.3 382 50.7 2005 644 299 46.4 345 53.6 Miscellaneous Training 2006 628 288 45.9 340 54.1 2007 541 251 46.4 290 53.6 2008 458 219 47.8 239 52.2 2004 1,061 501 47.2 560 52.8 2005 836 366 43.8 470 56.2 Occupational/Vocational 2006 73 5 320 43 .5 415 56.5 2007 617 312 50.6 305 49.4 2008 548 303 55.3 245 44.7 2004 446 181 40.6 265 59.4 2005 434 164 37.8 270 62.2 On-the-job Support 2006 393 131 33.3 262 66.7 2007 421 170 40.4 251 59.6 2008 416 162 38.9 254 61.1 2004 168 67 39.9 101 60.1 2005 97 23 23.7 74 76.3 On-the-job Training 2006 88 18 20.5 70 79.5 2007 68 19 27.9 49 72.1 2008 72 24 33.3 48 66.7 2004 1,691 71 1 42.0 980 58.0 2005 1,532 650 42.4 882 57.6 Other 2006 1,428 613 42.9 815 57.1 2007 1,243 569 45 .8 674 54.2 2008 1,277 593 46.4 864 53.6 99 (table continues) Table 28 (continued). Total Unemployed Employed Variable Year N n % n % 2004 122 54 44.3 68 55.7 2005 11 1 55 49.5 56 50.5 Personal Attendant 2006 125 57 45.6 68 54.4 2007 128 60 46.9 68 53.1 2008 108 56 51.9 52 48.1 2004 7 6 85.7 1 14.3 2005 15 10 66.7 5 33.3 Reader 2006 5 2 40.0 3 60.0 2007 12 5 41.7 7 58.3 2008 7 3 42.7 4 57.1 2004 1,188 445 37.5 743 62.5 2005 1,176 401 34.1 775 65.9 Rehab Technology 2006 1,1 10 375 33.8 735 66.2 2007 1,153 409 35.5 744 64.5 2008 1,132 395 34.9 737 65.1 2004 313 131 41.9 182 58.1 2005 288 107 37.2 181 62.8 Technical Assistance 2006 255 84 32.9 171 67.1 2007 239 98 41.0 141 59.0 2008 232 91 39.2 141 60.8 2004 2,017 980 48.6 1,037 51.4 2005 1,745 822 47.1 923 52.9 Transportation 2006 1,614 755 46.8 859 53.2 2007 1,438 693 48.2 745 51.8 2008 1,437 720 50.1 717 49.9 2004 3,539 1,837 51.9 1,702 48.1 2005 3 ,005 1,430 47.6 1,575 52.4 Voc Rehab Counseling/ 2006 2,713 1,283 47.3 1,430 52.7 Guidance ‘ 2007 2,531 1,191 47.1 1,340 52.9 2008 2,324 1,120 48.2 1,204 51.8 *Significant difference p < .0005 100 Level of Education and Employment Characteristics of Customers at Closure, by Year and Type of Closure This next section provides an overview of the level of education and employment characteristics of customers at closure, by year and type of closure (Table 29). There were no statistically significant or linear patterns of change associated with level of education by year by type of closure. N 0 statistics were computed for hours worked and hourly wage because employment status is a constant. Table 29 Level of Education and Employment Characteristics of SC] Customers at Closure, by Year and Type of Closure Total Unemployed Employed Variable Year N N % n % Level of Education 2004 2 2 100.0 0 0.0 2005 5 3 60.0 2 40.0 No formal 2006 5 3 60.0 2 40.0 schooling 2007 3 3 100.0 0 0.0 2008 4 4 100.0 0 0.0 2004 138 82 59.4 56 40.6 2005 121 50 49.5 51 50.5 Elementary, grades 2006 85 50 58.8 35 41.2 1-8 2007 67 41 61.2 26 38.8 2008 59 38 64.4 21 35.6 2004 556 376 67.6 180 32.4 2005 471 278 59.0 193 41.0 Secondary, no 2006 424 296 69.8 128 30.2 diploma 2007 406 253 52.3 153 37.7 2008 342 227 66.4 1 15 33.6 2004 45 24 53.3 21 46.6 2005 59 33 55.9 26 44.1 Special education 2006 44 25 56.8 19 43.2 completion 2007 39 21 53.8 18 46.2 2008 50 26 52.0 24 48.0 (table continues) 101 Table 29 (continued). Total Unemployed Employed Variable Year N n % n % 2004 1,947 1,160 59.6 787 40.4 2005 1,499 869 58.0 630 42.0 High school 2006 1,241 717 57.8 524 42.2 graduate equiv. 2007 1,152 646 56.1 506 43.9 2008 1,118 641 57.3 477 42.7 2004 1,262 778 61.6 484 38.4 2005 1,081 648 59.9 433 40.1 Post secondary, 2006 968 556 57.4 512 42.6 no degree 2007 838 496 59.2 342 40.8 2008 809 493 60.9 316 39.1 2004 980 380 38.8 600 61.2 2005 841 305 36.3 536 63.7 Associate deg or 2006 778 297 38.2 481 61.8 voc tech 2007 660 261 39.5 399 60.5 2008 609 238 39.1 371 60.9 2004 747 226 30.3 521 69.7 2005 656 163 24.8 493 75 .2 Bachelor’s degree 2006 648 169 26.1 479 73.9 2007 637 164 25.7 473 74.3 2008 579 186 32.1 393 67.9 2004 238 59 24.8 179 75.2 2005 224 48 21.4 176 78.6 Master’s degree or 2006 234 38 16.2 196 83.8 higher 2007 251 60 23.9 191 76.1 2008 233 42 18.0 191 82.0 Hourly Wage ‘ 2004 373 0 0.0 373 100.0 2005 305 0 0.0 305 100.0 Up to $6.49 2006 240 0 0.0 240 100.0 2007 162 0 0.0 162 100.0 2008 89 0 0.0 89 100.0 2004 279 0 0.0 279 100.0 2005 230 0 0.0 230 100.0 $6.50 to $8.49 2006 198 0 0.0 198 100.0 2007 212 0 0.0 212 100.0 2008 160 0 0.0 160 100.0 102 (table continues) Table 29 (continued). Total Unemployed Employed Variable Year N n % n % 2004 1,065 0 0.0 1,065 100.0 2005 957 0 0.0 957 100.0 $8.50 to $11.49 2006 842 0 0.0 842 100.0 2007 732 0 0.0 732 100.0 2008 727 0 0.0 727 100.0 2004 589 0 0.0 589 100.0 2005 562 0 0.0 562 100.0 $11.50 to $17.49 2006 528 0 0.0 528 100.0 2007 503 0 0.0 503 100.0 2008 477 0 0.0 477 100.0 2004 366 0 0.0 366 100.0 2005 386 0 0.0 386 100.0 Over $17.50 2006 385 0 0.0 385 100.0 2007 426 0 0.0 426 100.0 2008 393 0 0.0 393 100.0 Hours Worked ' 2004 156 0 0.0 156 100.0 2005 100 0 0.0 100 100.0 0 2006 83 0 0.0 83 100.0 2007 73 0 0.0 73 100.0 2008 62 0 0.0 62 100.0 2004 122 0 0.0 122 100.0 2005 119 O 0.0 119 100.0 1-10 2006 100 0 0.0 100 100.0 2007 96 0 0.0 96 100.0 2008 94 0 0.0 94 100.0 2004 476 0 0.0 476 100.0 2005 449 0 0.0 449 100.0 11-20 2006 418 0 0.0 418 100.0 2007 424 0 0.0 424 100.0 2008 368 0 0.0 368 100.0 2004 545 0 0.0 545 100.0 2005 495 0 0.0 495 100.0 21-35 2006 435 0 0.0 435 100.0 2007 419 0 0.0 419 100.0 2008 392 0 0.0 392 100.0 2004 1,456 0 0.0 1,456 100.0 2005 1,321 0 0.0 1,321 100.0 36-40 2006 1,185 0 0.0 1,185 100.0 2007 1,045 0 0.0 1,045 100.0 2008 942 0 0.0 942 100.0 103 (table continues) Table 29 (continued). Total Unemployed Employed Variable Year N n % n % 2004 73 0 0.0 73 100.0 2005 56 0 0.0 56 100.0 41 or more 2006 55 0 0.0 55 100.0 2007 51 0 0.0 51 100.0 2008 50 0 0.0 50 100.0 fiNO statistics were computed because Type of Closure was a constant. Customer Supports at Closure, by Year and Type of Closure This final section examines customer supports at closure, by year and type of closure (Table 30). There was a statistically significant difference between social security disability income by year )(2 (4, N = 7,237) = 29.59, p < .0005. There was a 7.8% increase in the number of customers utilizing social security disability income between 2005 and 2006 and a 3.0% decrease between 2007 and 2008. While not statistically significant, there was a positive linear pattern in the number of customers receiving workers compensation from 27.8% in 2004 to 44.6% in 2008. In an evaluation of the number of supports by year by type of closure there was a statistically significant change in the use of one support )(2 (4, N = 10,304) = 34.33, p < .0005. There was a 12.0% increase in the percentage of customers using one support between 2004 and 2005, a 5.1% increase between 2005 and 2006 and a 4.1% decrease between 2007 and 2008. There was a positive linear pattern in the percentage of customers with two to less than three years from application to closure by year, from 43.6% in 2004 to 47.6% in 2008. Finally there was a statistically significant change in the percentage of customers with three to less than four years from application to closure X2 (4, N = 7,869) = 22.48, p < .0005. There was a 2.2% decrease in percentage of customers between 2006 and 2007. 104 Table 30 Customer Supports at C losure, by Year and Type of Closure Total Unemloyed Employed Variable Year N n % n % Primary Source of Support 2004 2,464 244 9.9 2,220 90.1 2005 2,207 177 8.0 2,030 92.0 Personal income 2006 1,917 177 9.2 1,740 90.8 2007 1,744 154 8.8 1,590 91.2 2008 1,624 146 9.0 1,478 91.0 2004 998 877 87.9 121 12.1 2005 756 661 87.4 95 12.6 Other 2006 654 580 88.7 74 11.3 2007 528 460 87.1 68 12.9 2008 518 461 89.0 _ 57 11.0 2004 1,821 1,379 75.7 ‘ 442 24.3 2005 1,503 1,122 74.7 381 25.3 Public support 2006 1,414 988 69.9 426 30.1 2007 1,389 986 71.0 403 29.0 2008 1,303 961 73.8 342 26.2 2004 281 236 84.0 45 16.0 2005 198 164 82.8 34 17.2 Family friends 2006 198 162 81.8 36 18.2 2007 172 125 72.7 47 27.3 2008 142 111 78.2 31 21.8 Type of Public Support 2004 1,649 932 56.6 717 43.5 2005 1,467 824 56.2 643 43.8 Social Security 2006 1,428 691 48.4 737 51.6 Disability " 2007 1,391 704 50.6 687 49.4 2008 1,302 698 53 .6 604 46.4 2004 1,093 763 69.8 330 30.2 2005 938 625 66.6 313 33.4 SS1 Aged Blind 2006 890 577 64.8 313 35.2 Disabled 2007 853 573 67.2 280 32.8 2008 801 542 67.7 259 32.3 2004 99 73 73.7 26 26.3 2005 57 46 80.7 1 1 19.3 TANF 2006 50 36 72.0 14 28.0 2007 34 23 67.6 1 1 32.4 2008 34 28 82.4 6 17.6 105 (table continues) Table 30 (continued). Total Unemployed Employed Variable Year N n % n % 2004 45 25 55.6 20 44.4 2005 34 17 50.0 17 50.0 Veterans’ Disability 2006 22 14 63.6 8 36.4 2007 24 14 58.3 10 41.7 2008 20 13 65.0 7 35.0 2004 158 114 72.2 44 27.8 2005 90 58 64.4 32 35.6 Workers’ 2006 101 62 61.4 39 38.6 Compensation 2007 92 56 60.9 36 39.1 2008 83 46 55.4 37 44.6 2004 115 98 85.2 17 14.8 2005 76 55 72.4 21 27.6 General Assistance 2006 48 33 68.8 15 31.3 2007 54 43 79.6 1 1 20.4 2008 32 26 81.3 6 18.8 2004 255 168 65.9 87 34.1 2005 163 97 59.5 66 40.5 Other Public Support 2006 159 112 70.4 47 29.6 2007 1 16 69 59.5 47 40.5 2008 139 103 74.1 36 25.9 Type of Medical Insurance V 2004 1,513 953 63.0 560 37.0 2005 1,362 827 60.7 535 39.3 Medicaid 2006 1,291 771 59.7 520 40.3 2007 1,170 686 58.6 484 41.4 2008 1,105 662 59.9 443 40.1 2004 1,105 560 50.7 545 49.3 2005 1,009 471 46.7 538 53.3 Medicare 2006 990 450 45.5 540 54.5 2007 994 474 47.7 520 52.3 2008 884 442 50.0 442 50.0 2004 187 91 48.7 96 51.3 2005 184 91 49.5 93 50.5 Other Public Source 2006 152 65 42.8 87 57.2 2007 177 75 42.4 102 57.6 2008 153 66 43.1 87 56.9 106 (table continues) Table 30 (continued). Total Unemployed Employed Variable Year N n % n % 2004 991 63 6.4 928 93 .6 2005 923 42 4.6 881 95.4 Private via 2006 832 37 4.4 795 95.6 Employment 2007 768 29 3.8 739 96.2 2008 653 29 4.4 624 95.6 2004 816 387 47.4 429 52.6 2005 562 213 37.9 349 62.1 Private via Other 2006 533 207 38.8 326 61.2 Means 2007 482 189 39.2 293 60.8 2008 454 203 44.7 251 55.3 Number of Supports 2004 2,803 1,151 41.0 1,657 59.0 2005 2,443 893 36.6 1,550 63.4 0 2006 2,066 837 40.5 1,229 59.5 2007 1,775 668 37.6 1,107 62.4 2008 1,667 621 37.3 1,046 62.7 2004 2,468 1,521 61.6 947 28.4 2005 2,118 1,260 59.5 858 40.5 1 ’ 2006 1,990 1,083 54.4 907 45.6 2007 1,919 1,052 54.8 867 45.2 2008 1,809 1,066 58.9 743 41.1 2004 393 264 67.2 129 32.8 2005 315 205 65.1 110 34.9 2 2006 320 193 60.3 127 39.7 2007 295 195 66.1 100 33.9 2008 283 183 64.7 100 35.3 2004 29 26 89.7 3 10.3 2005 22 15 68.2 7 31.8 3 2006 22 18 81.8 4 8.2 2007 16 11 68.8 5 31.3 2008 1 1 7 63.6 4 36.4 2004 2 2 100.0 0 0.0 2005 1 0 0.0 1 100.0 4 2006 0 0 0.0 0 0.0 2007 1 1 100.0 0 0.0 2008 0 O 0.0 0 0.0 107 (table continues) Table 30 (continued). Total Unemployed Employed Variable Year N n % n % Years from Application to Closure 2004 790 253 32.0 537 68.0 2005 730 204 17.9 526 72.1 Less than 1 2006 744 229 30.8 515 69.2 2007 699 187 26.8 512 7 3.2 2008 727 195 26.8 532 73.2 2004 1,230 584 47.5 646 52.5 2005 1,064 434 40.8 630 59.2 1 to less than 2 2006 964 419 43.5 545 56.5 2007 967 403 41.7 564 58.3 2008 898 388 43.2 510 56.8 2004 1,164 656 56.4 508 43.6 2005 766 424 55.4 342 44.6 2 to less than 3 2006 673 361 53.6 312 46.4 2007 609 326 53.5 283 46.5 2008 500 262 52.4 238 47.6 2004 912 535 58.7 377 41.3 2005 691 401 58.0 290 42.0 3 to less than 4 " 2006 418 239 57.2 179 42.8 2007 374 222 59.4 152 40.6 2008 346 21 1 61.0 135 39.0 2004 1,819 1,059 58.2 760 41.8 2005 1,686 934 55 .4 752 44.6 4 or more 2006 1,628 903 55.5 725 44.5 2007 1,404 807 57.5 597 42.5 2008 1,332 839 63.0 493 37.0 *Significant difference p < .0005 Research Question Three (Part One): Predictor Variables Associated with Status 26 or 28 Outcomes for Customers with SCI This next section addresses research question 3. To determine the input, service and output factors associated with positive outcomes for customers with SCI exhaustive CHAID was used to build a classification tree. Through the use of a systematic algorithm the strongest relationships between predictors and the outcome variable (status 26 or 28 employment outcome) were identified and organized into a hierarchical framework 108 similar to a tree with branches. A top-down, step-wise approach was utilized; as the predictor variable with the strongest relationship to the outcome variable was presented first, followed by splits or branches that identify the next set of variables with the strongest relation to the outcome variable (nodes). The analysis resulted in a total of three branches with 97 nodes (65 end nodes). PASW Statistics Release 18.0.0 with the PASW Decision Trees add-on was used for this analysis. For all statistical tests the alpha level was 0.05; a Bonferroni correction was utilized to correct for the number of statistical tests within each predictor. The estimated risk is 0.304 with a standard error of 0.003. The correct classification of 65% is a significant improvement over the base rate of 46.1%. The variables considered for inclusion were variables from question two that reflected a statistically significant difference in outcome (Table 31). Table 31 Variables with a Statically Significant Outcome Variance Variables Age at application categories On-the-job supports services received Assessment services received On-the-job training received Categories for number of days from Other services received application to closure Categories for number of days from Private insurance through other means application to eligibility at application Cost of services categories Private insurance through other means at closure Information and referral services Rehabilitation technology services received received (table continues) 109 Table 31 (continued). Variables Job placement assistance services Social security disability insurance at received application Job readiness training services received Social security disability insurance at closure Job search assistance services received Social security insurance (SSI)-aged, blind, disabled at application Level of education attained at SS1-aged, blind, disabled at closure application Level of education attained at closure Technical assistance services received Maintenance services received Temporary assistance for needy families at application Medicaid insurance coverage at Temporary assistance for needy application families at closure Number of supports at application Voc rehab counseling and guidance services received Number of supports at closure Workers compensation at closure Several variables were excluded due to their multi-collinearity with the outcome variables. These variables include Private (medical insurance) via Employment at application and closure, number and percent of SCI customers by type of closure and employment status at application, number and percent of SCI customers by type of closure and hours worked at application, number and percent of SCI customers by type of closure and hourly wage at application, number and percent of SCI customers by type of closure and primary support at closure. 110 Of the 30 predictor variables included in the analysis the six variables selected as the most significant predictors of employment outcome include level of education attained at closure, cost of services categories, categories for # of days from application to closure, rehabilitation technology services received, job placement assistance services received and number of supports at closure. The most significant predictor of employment outcomes was level of education attained at closure. Several sets of figures follow to describe the significant predictors of employment outcome by level of education. 111 Predictor Variables for Customers with an Education Level of Elementary Education grades 1 thru 8 As reflected in Figure 2 of the 469 customers with no formal schooling or an education level of elementary education grades one through eight only 41.2% achieved employment outcome at closure. For this group cost of goods and purchased services was the most important predictor variable. Customers receiving less than $1000 in goods and purchased services were too small in population to allow for further breakdown (n=164). Number of days from application to closure was the next most important predictor for customers who received more than $1000 in goods and purchased services. Spending more in services appeared to increase employment outcomes. The number of days from application to closure also appeared highly impactful for this group. Findings suggest that closing within one year Of application increased almost 50.0%. 112 m E222 2 22028.20 28220022022 22822022205 - wa22oo220m 2228.822 0 Z 222.23 0.208820 20.2 29022022 0803220 .20 002.2. 2022.822 .22 032.2 No2 5o 290.2. mm 2.6 280.2. 2m md 2802. 08002220 080050 08002220 8 222 acioaam em 28 2228262225 2. 22.22 288262225 220202280 2022 2002322280 2022 20022022280 8: £22 2.3 20020222222 m0o2>20m om 26m 6020222222 m0o2>20m w Em 2 22020222222 802.com a 2x. mm 02372 22 2x. vm 022072 22 2x. mm 02872 $00» 2. An 21 £002 m €00» N W l 200.» 2 200.2 22 HV 2 2 2 2 auto .mmndvuegcfno .ooo.ou0=20>-n2 2.3.. 023020 02 2202200222232 802.2 @225 2 mom 22 28.2 - 2.62 2o 286.2 32 wdm 08002220 220E>o2mEm2 wm N. mm 0222002220 2202222022822 02 Nov 20022022280 20: 2002222222 m002>20m 32 22.02 2002202920 82 2202022222 m002>20m 22 e\o a 02572 2 ..\° m 02572 2 _ 822.2 A 21.22U 28.288.222-220 522222182322 .22.... 822.22.. 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The next group represents customers who closed in one but less than two years of application; over two-thirds (66.7%) of those who received job placement services were employed at closure. 114 .22 220% «2 02222 a 002202m 08222222 282200 22322 022 .20 2202228000 22223 0202220208 202 0230220222 088225 3220222020 0022 20222052 2.m 025922 32 9o 2020H mom 0.2 20821 8 We 2020,2l omm 20.2 20209 02228230 0800230 0800250 08002220 om 2.00 30822280 82 m. 2 0 200822280 00 0.3 2220822280 E2 20 2852222220 2202029220 2022 2002029220 2022 200329220 2022 2002022280 2022 m0 m.mm h20020222222 m0o2>20m cum 5% 0020222222 m0o2>20m 0 22.222 0020222222 0002B0m cm 2 03 6020222222 000320m 22 2x. an 02572 22 X. am 022072 22 ..\° 5m 02572 22 $0 on 022072 22033022 20030092 8 Z \ 2203200022 22020032 82 T20 .mflfiuegcméo doodufigd .23 W20 .mmwdmueggéo dooduosgd .23 200200022 0002E0m 0000202mm< 2220222000222 02. 200300022 m0o2>20m 23022222092 22220222502232 mam Wm 2020.2; mam n. 2 2082. m 2 N mdv 0222002220 22202222202qu Nmm fiwm 022200250 2G0E>o2n28m2 m 2 m Eon 2002022280 2022 “22020222222 0002Z0m $2 m.2v 2202029220 2022 0020222222 m0o2>20m 22 .x. 22 02.072 22 X. 222 02572 020022 N VI 200% 2 _ 200% 2 uv mnu220 thm.oo2u020s2om-EU .ooo.ou0=20>-n2 .2230. 020820 02 2202200222232 22202.2 @200 comm 00 2020.2. $0 o. mm 022200230 2220222202952 229.2 ode 2002229220 2022 6020222222 000320m 22 .x. 2203200 22 220.22 «2 :25 a 002.0% 0:82.222. 202200 :wE 0: 22022002622 E0ccou0m “N 02572 115 The next group within this education level is represented in Figure 3.2 and examines customers with more than two years from application to closure. While only 29.4% of those receiving two but less than three years of service were employed at closure 47.4% of those who received $5,000 or more in goods and purchased services were employed at closure. The final group at this level of education had three or more years from application to closure and only 23.6% were employed at closure. Of the subgroup that received job placement services 35.7% were employed. 116 .AN 220222 2 22.2222 a 002202w 0222222222 20022022 22MB 22 .220 222022220000 22223 020222020220 20.2 02802220222 02220022222 w22220222022 0022 20222022 .N.m 0222322 m8 2 2020.2 coo ed 2028. v2 2 no 2020.2 00m «.2 20202. 0222002220 0222002220 0222002220 0222002220 8 2.2 25582280 22: 2.22 22208222280 2.0 E2. 25822280 8 2.20 2208229220 2202202222220 2022 2202202222220 2022 220282222220 22222 2202202222220 2022 2.2 0% 22020222222 m0o2>20m omv w.2w 22020222222 0002E0m o0 cam 22020222222 0002E0m 2mm ms» a22020222222 0002>20m 22 2x. mv 02572 22 2x. 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N2 02572 _ . . 2 020022 02222 20 m l mnu222 www.002n020222202220 ooo.on02220>-22 .232 020022 m vlm20022 N 02220020 02 22022002222270~ 22202.2 @209 - _ mafim md 2020.2. $0 9mm 0222002220 22208220222252 3.0.2 owe 220282222220 28 6020222222 0002E0m 22 2x. 22209200 2N 2.20222 N2 :25 22 0,0220% 0228222222 20222200 22w:— 0: 220220022220 22.202222000m ”N 022072 117 Predictor Variables for Customers with an Education Level including Special Education Certificate of Completion or High School Graduate Equivalency Of the 7,194 customers with an education level including special education certificate of completion (N = 237) or high school graduate equivalency (N = 6,957) only 42.1% achieved an unemployment outcome. These next set of figures will examine what factors and or services impact employment outcomes. As was previously reported for other groups fewer days from application to closure appear to improve outcomes; 66.3% of this group (with less than one year from application to closure) achieved employment. For customers in this group that received over $5,000 in goods and purchased services 92.3% were employed at closure (Figure 4.1). 118 .22 2.20222 >2=22m2 22020 2oo220m 22w222 20 2222200 20 2200 22m 2020022m 22223 220222022220 20.2 2222202220222 0222002220 9222022202. 0022 20222022 .222 022E222 2.22 0.2 2082. 23 0.2 2032. 222 2.2 20202 0222002220 0222002220 0222002220 022 2.22 2882222822 022 2.: 28.22.82.280 82 2.22. 288222280 2002202222220 222 229202222220 2022 2202202222220 2022 22 E 632222222 282.52 :2 2.22 222222222 282.52 222 2.02 002022222 282.52 22 .x. 02. 02572 22 .x. 22. 02372 .2 .x. 3. 02372 _ _ _ _ 208828.22 _ _ 2.8.22l28.22 _ _ 822.22Io _ 2 2 2 $20 .2 22.202u20aa2220 .ooo.ouo=_§-2 .23. 200320m 2202022022222 .20 2200 “VII 022.2 0.2 2062. wa 0:8 0222002220 220§o2afim 2.22 2.22 322.228 28 032222222 28232 22 .x. 2.2 02572 . fl, 210 20222022220222.2220 .08.ou82§-2 23. 20022 2 uv 0.2222020 02 22022002222922 22292 2.209 vm 2 .2. 2. 2 m 280.2. ~mo.m 2.? 0222002220 2220222220222222m2 «2.22 Q? 2202202222220 2022 22020222222 200E0m ll 2 22. 2222223 9 2.5222 beau—«>2522H 30:25.20 262—um gas .3 5522—589 .3 gaugkow Eegugabm EEQQQ 2.“. QEQZ 119 The next group of 1,865 customers is comprised of those with at least one year but not more than two years from application to closure; 49.9% of this aggregate group was employed at closure (Figure 4.2). Funding was important for this group as well. Over two-thirds of customers who received $1,000 or less in funding were unemployed at c losure. In contrast 87.2 of customers who received more than $20,000 were employed at c losure. 120 .222 220222 32222.22 22020 200220m 22w222 20 2222200 .20 2200 20m 2020022m 2.2223 020222022220 20.2 2020222022 0222002220 w22220222022 0022 20222022 .Né 020M222 W 22¢ 22.22 20202. 022 22.2 2020.2. mmn 2.m 2082. NS. 2.m 20202. 0222002220 0222002220 0222002220 0222002220 22 2.22 2882222822 2222 0.02 258222822 2222 2.22 2220522222222 222 2.22 288222822 2202202222220 2022 200232222220 8: 2202202222220 82 2002202222220 292 22 2.22 00202222222002.2202 8 2.22 0320222228252 222 2.02. 6022226228252 222. 2.20 .00222222228252 2 2x. am 022072 22 2x. a. 022072 22 2x. an 02572 22 X. 2.2. 022072 2 2 - ..l 2 2 020222 20 Sodmm ooodmm l 28.92 8on I 28.222 oooJmlo 2 _ b 2 mn222 .ammwomn020s2222220 .ooo.on02220>-22 .232 2002>20m 2202022022222 .20 2200 F m cm. 2 2 .22 2020.2. 2 ma adv 0222002220 2220222220222222m2 21mm 2.22m 2202202222220 2022 6020222222 2002>20m 22 3 m2 022072 10 202.220u22aa2220 .ooo.ou82§-2 .23.. 220022 N v - 20022 2 02222020 02 22022002222922 222022 222022 .20 22 H 2202.0 2.22 2020.2. Nmo.m 2.? 022502220 222022222o222222m2 $2.22 msm 2202202222220 2022 .22020222222 2002222”2 22 2x b09200 ti AN 0 0220 0> 22 0 22 2.2 .22 .2 2 2 222.2 20 2202028220m 2&2: .222 22222202222222.9222 2222.22.22.28 ESQEQESQW ..m 922 121 The third group within this level of education had at least two years but less than three years from application to closure and only 37.8% of this core group achieved employment (Figure 4.3). As with prior groups at this level of education the cost of goods and purchased services was found to be a predictor of employment. Only 25.6% of customers who received $1,000 or less in funding were unemployed at closure as Opposed to customers who received more than $5,000; 61.4% achieved employment. 122 Am 2022 >2=22m2 22026 200220m 22?: 20 2222200 .20 2.200 22m 2020025 22223 220222022220 20.2 2222202220222 0222002220 3220222022 0022 20222022 .3. 020M222 o2m 0.2 2020.2. wow o.N 2020.2. mmv o.m 2020.2. 0222002220 0222002220 0222002220 222 2.22 2222220222822 222 2.22 288222822 2: 2.22 255.202.2822 229202222220 22222 229202222220 2022 220.202.22.220 2022 m2 9mm 60202222222002.220m 22m 98 2202022222 2002>20m 2mm 22.2.2 22020222222 2002>20m 22 2x. mm 02572 22 3 am 022072 22 2x. 2m 02572 2 2 02222 20 Sofia 25on In 28.2% 80.222 l o 2 2 . 2 2n20 .22o.2o2u0§2a-222u .ooo.ou%2§-.2 .23. 2002>20m 2202022022222 .20 2200 h ova .06 20202. $22 wfim 0222002220 2208.202228m 2 2.2. N20 22032222220 2022 20020222222 2002>20m 22 2x. 222 022072 122.222.220u222a2220 dooduezgd .23. 2200.2 m v 200.2 N 02222020 02 2202200222223. 22202.2 2.20m .20 2222 2 . ll 229 2 .2. 2. 2 M 20202. Nmo.m 2.22. 022200225 2208.202228m2 $2.2. 06m 2202222222220 2022. 6020222222 2002>20m 2222/2 22. 22222228 22 A 22 02202232222222 0202222020 200220m 2B2: .22. 22222222222225 .222 83.2.2.2to9 grueswm 38am 2” £52 t 123 This fourth group for analysis is of customers who had a least three but less than four years of time from application to closure (Figure 4.4). For this group only 33.3% achieved employment. Only 25.0% of these customers received job placement assistance services with 51.4% employed. Only 27.4% of the group who did not receive services achieved employment. 124 Av 220.22 >255 20020 2oonom 229: 20 22800 .20 2200 20m 2020025 .2223 02080203 20.2 02802200222 0800225 $503020 00.: 20222022 .21. 0.53.2 SN ad 280.2. 080050 :2 32 28822280 2002022280 202 m2: odv 602222.22 0002>20m a 2x. mm 02572 1 200>2W00y2 L 2b ad 2302. 088250 9: EN 28822280 200.202.22.220 222 32. 0.22 .0333 $2.50 a .x. vm 022072 1 2003022022 2072 _ 2 215.22v .mmmm.mvu020=cm-2220 .ooo.ou0=20>-n2 2.20.4. 000320m 00§m2mm< 2220800022 2202. 2 3w 0. m 280.2. 3m «.mm 08002220 2a08>o2228m2 mam ado 209822280 20: 6020222222 000223 a .x. 5 02572 I20 .Sm.m2ou0§cm-30 .ooc.ou0=20>-n2 ..8< 0200» v v 0200.» M 0222820 8 25228222225 802.2 92.5 .20 22 {Ii va 2 .2. .2 .2 m 2802. ~85 2.? 08830 288>o2aam mm 2 .v Q? 2002022280 8: 22020222222 000320m A/ a .2 v 2.2 £0 23253.... 32.25 32.5 as .5 82202225 .22 33222226 2223.22.22 300% a 0232 125 The final group of customers who closed with special education certificate of completion or high school graduate equivalency was customers who closed after four or more years from application (Figure 4.5). This group reported the lowest overall employment outcome (25.3%). Funding for these customers appeared impactful as well. With 37.6% of customers who received over $10,000 in funding employed and only 14.2% who received $1,000 or less. 126 — Fm Gillan-h BJ‘IIA‘Iluiululirv- :1lulllwluvlw\ Inuliluiuvlu IIIINII . Am 220222 >22222m2 22020 Begum 22w222 20 222280 .20 2200 20m 2020025 2222? 02022230220 20.2 02902220222 022282220 $503022 0022 20222022 .3. 0.532 220202222220 2022 Nmm «do .200202222220002E0m $0 0.2 2082. $0 0.2 203.2 0222002220 02220890 020 0.20 288222280 00 ~00 608222522 2002202222220 2022 ova 22.: 6020222222 m0o2>20m an 0.0 2082 0222002220 02: 0.8 28822080 2002822280 2022 292 odm 602022.82 m0o2>20m 0? 0.0 2082. 0222002220 8 0.: 2820222280 200202222220 8: mom w.mw .20020222222000220m 22 ..\° am 022072 22 2x. mm 02572 22 2x. hm 022072 22 .x cm 02572 A 2 2 2 020222 20 28422; 80.2% I 25.3 ooodm I 28.2% oooJmlo mute .mmvdwu020222002220 .ooo.ou02220>-n2 .2230. m0o2t0m 2000022022222 .20 2000 2 mom; Nw 2020.2. 7 $0 m.mm 022282220 22202222202952 Q. 302 SR 2202202222220 822 6020222222 0002.220m 22 2x. «2 022072 2 E20 .Sm.m2ou02022200-2220 .ooo.ou020>-n2 ..8< 0200.2 .0 AM 0222020 8 28220022222222 22202.2 0.20m .20 u .002.» 2.2m 208.2. mmo.m 2 .90 022802220 222082202qu $2.20 msm 00.822280 2022 602022.82 0002E0m 22 2x0 22209200 3 220.22 2220203223— 0202222020 282—um 2322.2 20 2222022222200 .3 02002222200 22022002232 2020025 2m 022072 Predictor Variables for Customers with an Education Level of Post-Secondary Education, no degree For the 4,958 customers with an education level of post-secondary education, no degree only 40.1% achieved employment at closure. Of this group 67.3% of those who closed in less than one year achieved employment. For the subgroup of customers that received more than $10,000 in funding 96.4% were employed at closure (Figure 5.1). 128 A I .-.-«An V 33.23%: C.- ..2222m222U-u-vvn >--=—u:=.u.uII-1:A- .1. .u-\:2 \ .22 22026 002w022 022 £02200va gaoooméom 0 22223 020222020220 20.2 020202220222 088228 3220222022 0022 20222022 .26 0.222322 02 .20 2082 0222002220 2.2 2.02 28822280 220202222220 2022 N 9m h22020222222 m0o2>20m 22 2x. no 0222272 020222 20. Sod 2 m — 229202222220 22222 no m.m~ a22020222222 m0o2>20m 202 2.2 2082. $2 2.2 20202. 0222002220 0222002220 022 2.02 2582292222 22.2 2.22 222082222822 2202029220 2022 02 2.2. 6020222222 m0o2t0m 22 2x. G och 22 2x. 2222 0222272 ooo.o2m.l 28.22 A E0 .222.20ue§2a-22o 08.222252 .23. 08.2.2 - o m0o2>20m 2200022022222 2o 280 2 0% 5N 2020.2. 29. Sb 0222002220 2220222202228m2 mom 2.? 22022222220 2o22 6020222222 m0o2>20m 22 2x. a2 02572 2 I22 .3wd0mu020222202220 .ooo.ou0=20>-22 .23.. 200.2 2 v 0222820 02 2202200222290. 22202.2 0.200 n wmoé v.2m 208.2. 2.23. 2 2 .9. 0222002220 22205202222252 2 SJ 0.0m 2202222220 2022 22020222222 0002.220m 22 2x. 2203200 22 220.22 002322 22 .2202200222222 2.20222280m2822 22. 022072 129 This next subgroup of customers had more than one year but less than two years of service (Figure 5.2). While the majority of customers were unemployed by a slight margin (49.8%) those who received above $5000 in funding had a notable increase in their likelihood of employment (73.0%). 130 ‘6 ‘I...A‘\ I‘I‘Ll‘l‘.‘ 1“. ‘I‘N‘II‘I I11 .I AN 220.22 002w022 022 .22022002222m 2202222000m-2mo.2 0 22223 22202222220220 20.2 0222202220222 0222002220 m22220222022 0022 2022.202 .N.m 0222922 mm Nd 20292. 32 22.22 2020.2. mum 0.2 2020.2. 2mm 02 20202. 0222002220 0222002220 0222002220 0222002220 on 2.8 252.222.2822 22.2 0.22 285202.280 2222 2.02. 222.222.2822 2: 2.22 2882.22.22.20 220202222220 2022 2202222222220 222 220202222220 2022 2202222222220 2022 m 2.0 .220202222222002E0m mm ofim .22020222222200220m 32 2.2m .22020222222m0o2>20m ova 2&0 .22020222222 m0o2>20m 22 .x. we 022072 22 .x. m2 022072 22 .x. 3 022072 22 .x. me 022072 2 2 i 2 2 020222 20 28.22% ooodmm I 22222.3 022.3 I 22222.22 oooJmIo r 2 2 2 E0 22222220322226 .ooo.on0=2§-.2 .222... 0002.220m 2200022022222 20 280 L 22mm 3. 2020.2. m3. wdv 022502.220 22208.2o222222m2 32. New 22022222220 2022 6020222222 m0o2t0m 22 ..\.2 on 0222272 210 $0.202n200326 .ooc.ou82§-.2 .20.... 0200.2 N v 200.2 2 0222820 02 22022002222270. 2202.2 @2022 H 223.2. v.2m 2020.2. 2mm; 2.222. 0222002220 22202222222222m2 22.0.N mdm 220202222220 82 6020222222 m0o2>20m 22 o\.. 220w0200 2N 220.22 002322 022 .22022002222m— .22022:000m-2mo.2 22. 022072 131 For this next group of customers with a post-secondary education, no degree that had more than two years but less than four years of VR service from application to closure, factors other than goods and purchased services were impactful (Figure 5.3). For this first group, customers with more than two years but less than three years, job placement assistance services were found to be important with almost two-thirds of customers who received services achieved employment at closure. Only 34.3% of customers of those that did not receive services achieved employment. For customers with 3 but less than 4 years of time from application to closure number of supports at closure was reported as impactful. Of the customers with one or more support 75.8% were unemployed at closure. 132 I 4' 7. II o GZL Id la 3: o:=:=.u:=v~ Cunt-.699? leL v. 1 . .- ..: . uL-nA—v 09- An” Am wand oohwoc on 48228332 anoom-2mon2 a £23 E08828 8.2 $306222 088225 3282223 ooh 22222.52 .m.m 059.22 8m 5 290.2. 222 N2 2902 05002220 080330 3 SN 38232225 22222 22.3 3052222812 23202925 8a SN mi. .v02m222a2moo2tom 252022280 Ho: on 2 3% .3328 823% a 2x. bomeU a 2x. aw m.2572 2 808 20 2 2 2 o 1 2H? medmuosscinu .ooo.ono=2m>-m ._.2o< @5820 2a mtoaasm .20 22282272 one ad 280.2, mmm m.mm 0808220 2562202952 53V 5.8 25202an 2022 603222222 832% a 8 NN o2572 2 2292022280 28 on 2.5m 6822222222 moatom 22 :2 2.38. 2% 3 293 0500230 0800230 3 22.8 25832225 2mm 3% “89202822 252022280 Ho: mg 53 .2oo2m222a2moo2tom a X. we o2572 a 2x. be 2572 2 263832 a 252832 202 2 _ . 2n“:V .o¢m.mvno2§2om-2220 .oooduofigi .232 moorcom ooafim2mm< 25882.22 92. mmw o. m 2892, omm, I- .mdlm 0808220 2coE>o2aEm mow Dow 2520295 2022 263222222 moorcom a 2x. 2N «2572 m8?» v v I m In .Ewavmueggéo .ooo.on%2§-2 .23 822820 9 282282222922 82.2 @225 2 9892 m v I N wmmé v. 2 N 2 2802‘ So. 2 2 .ov 0803220 acaciam 2 3& man 26202an 20: 68222222 823% a X bowoumu 3 2.3.5 3.232. o: ...3333— Eac:ouom-2mcmnv 02572 133 Job placement assistance services were also found to be an employment predictor for customers with more than four years of time from application to closure (Figure 5.4). While only 28.4% of this subgroup was employed at closure those receiving job placement services had an improved outcome; 46.0% achieved employment. 134 Av 2.8% 3&3 on acumen—em gaoooméom a 22223 808830 8.2 E80233 08083 92282ro ooh 232.822 in 953.2 T22. Shvoufiscvao .228.on82§-n2 .23. moo2tom oo§m2mm< 25:5an n22. 2%; 9w 280.2. «mm van 080825 23520222232 mmmJ 92> 232022280 2022 63222222222 822% a 2x. mm m.2572 2 It .vvw.ov.mno.as2om-2220 .ooodnoagd ..8< mac» v A 0.8820 3 28228222223. 88.2 @225 waxy v.2N 2892‘ 53.2 2.3 08830 uaoaoaam :3 22m 3322280 28 .3332 scream a 2x. bowouao 22. 2.3.22 352. a: 5:223:32 bauuooomuumcm "v 02372 3m 2 233 2on2 3 2992 088:5 088225 %2 22.3 28582225 8m 3m 28522223 2332.280 20: 25202an 8: $2 3% 62325 scream 222.2 E 63325 8033 q .x. N2. 2372 a .x. E 2.2 32,2332 22222332 82 135 Predictor Variables for Customers with an Education Level of Associates Degree or Vocational Technician Certificate Of the 3,868 customers who closed with an associates degree or vocational technician certificate 61.7% were employed. For this group the number of supports at closure was the next most important predicator. Of the customers who closed without any supports 72.4% were employed (Figure 6.1). Cost of goods and purchased services appeared impactful for this group as well. The customers in this group who received one thousand or less in goods and purchased services were less successfiil; only 53.7% were employed. In contrast 81.0% of customers who received more than $5,000 in goods and purchased services were employed at closure. 136 .22 2.20% 08.002.222.200 .2282. 20820802» .8 00809 0000200022 8 22023 808808 8.2 88022882 08880 828222020 008 2029.52 .26 0.832 80 nm 293 08880 48 020 80822228 209222280 208 mm 2 22.02 880328 m0o2t0m 8 2x0 058 um 2229mm 2002022280 208 ow2 9mm 60802828 m0o2t0m 82 2; 230.2 23. 22.2 233 08880 08880 an ER 052822280 SN SH 808202228 2092022280 208 mom 03 60202828 m0o2t0m mm 02572 a ..\o E. 02572 : a\° an 02572 2 2 253 - 28.2w oooa2mIo 2 2t 2 Nn¢220 .mmnd2 28832002229 .ooo.on0:20>-n2 ..€< 0003.23 200082832 .20 280 23.2 m.w 208.2. m 2 v. 2 Van 08880 280§o2n8m gm 9% 2002022280 88 6082828 m0o2t0m a 2x. 3 02372 2% 63.82%33925 .ooo.ou82§-n2 .23, 0 08820 20 mtommsm .20 802282272 wow.m 5.02 280.2, 2.22th n. 2 c 08880 2808>o2a8m 2wv.2 m.wm 209822280 208 8020.528 832% c 2x. 2.8880 22 20.22 0082.580 .282. 208589» .8 00802. 080208.94 "m 0252 137 For customers who closed using one or more supports only 50.8% were employed at closure (Figure 6.2). The next most important predictor for this group was days from application to closure. Consistent with previous findings customers who closed with a shorter time from application to closure appear more likely to be employed at closure. Of those customers closing within a year of application 74.4% were employed at closure. Only 41.9% of those with more than three but less than four years as VR customers achieved employment. 138 .AN 80% 008222800 .802. 20802000022 8 00800 00820832 80 823 808980 8.2 082022008 08880 8828020 00.8 2028.2 .Nd 0802.2 000 3 2902. 08880 34 0.22. 08820288 20082880 88 Em 2.22m 8088282 0002E0m 8 2X. an 02872 800% v M 800» m 2 mom 2 290.2 400 0.2 293 08880 08880 32 3:. 8062022280 082 0.8 8082022280 2000202880 88 02 2.20 .8828 802200 2.2 0.0m 02882 80250 8 X 2:. 02872 8 .x. F 02872 800% NW 800» N 800% N W I .200» 2 2 2 mumw avado2H0882002220 .ooo.ou0820>-n2 .238 08820 8 8028002222840~ 88.2 @200 2 20082880 88 boo. 2 N.w 208.21 wmm wdm 08880 8088288m2 03 N58 20082880 88 8088282 m0o2t0m : x ,, .3 00oz. , 2n:V 8288208200220 58.228542 .228 2 AM 08820 8 02.88826 8 80228872 2 on 2.2 283 08880 2: 8E 058202880 200202880 88 80 w.mN 80820282 0002Z0m 8 .X. en 02872 000.0 32 288 nwm.N n. 20 08880 8088288m2 28.2 m.wm 20082880 88 8028282 0002Z0m 8 2x. 80880 AN :85 0802220000 8020282002. 20802882» .8 00.8022 0082802 "m 028 Z 8022A 2 V 2 139 Predictor Variables for Customers with an Education Level of Bachelors Degree Of the 3,267 customers who closed with a Bachelors Degree 72.2% were employed at closure. For this group cost of goods and purchased services was the next most important predicator. Figure 7.1 examines the 500 customers who received up to $1000 in goods and purchased services; 49.0% were employed at closure. For these customers the number of supports at closure was the next most important predicator with 63.6% of those customers without supports at closure employed. Only 36.0% of those with one or more supports were employed at closure. [40 .22 820 00.800 0.8202200m 0 523 808280 8.2 88022008 08880 98028020 00.8 22028022 .2. 2. 0822 veN 2.2 208.2. emN o.2 208.2. 08880 08880 3 0.00 288322280 82 0.8 285202.280 20082880 88 20082880 88 oe2 ode 600022282 808m em vem 800020.82 828m 8 2x. S 02872 8 2x. on 02872 0.88“ .8 2 222 2 2 2n”:U «Semngaciao 58.27.8802 .23.. 08820 20 3.888% .8 822882 2 oom N.N 208.2. mVN ode 08880 8088288m2 mmN o. 2 m 20082880 88 602020282 m0o2>8m 8 2x. eN 02872 2 E20 802800832220 68.8382 .228 82220422 333% 2003208 20 280 2 heNfi 2.82 208.2. ommd N.Nb 08880 8088288m2 woo SN 20082880 88 802020282 000230m 8 2x. 2.8880 22 «.85 00.8022 820220022 8 02872 141 The next group to be examined is customers with a Bachelor’s degree who received more than a $1 ,000 but not more than $5,000 in goods and purchased services (Figure 7.2). Over 65.4% of these customers were employed. Days from application to closure was the next more important predictor with shorter service times equating to better outcomes (e.g. 88.8% of those closing within one year). 142 AN 80% 00.000 082022025 0 83 0.208808 82 0882288 08880 82828020 00.8 22028022 .NN 082M222 000 2.2 282. 08880 0220 2.00 8802802 20082880 88 o: e.ev 802022282 0002E0m 8 .x. vw 02872 088 8 800% N 2 82 :2 288 08880 022 0.02 288002.280 20082880 88 e8 o.wN 8028282000288 8 ..\° mm 02872 800% N v I80» 2 2 002 :2 258 08880 002 0.00 088022280 200822280 88 n2 N2 2 602020282 0002E0m 8 2X. No 02872 0122c 00820882002220 08.08032 .23.. 080020 8 82282288402 88.2 00200 r 800% 2 v 2 ooh o.m 208.2. mew wee . 08880 8088288m2 NVN eéN 20082880 88 802020282 0002E0m 8 2x. 5N 02872 2 mnu220 .mw2.oNNu088200-2220 “ooo.ou0820>-22 ..220< ooo.mm-2oo.2m 0002E0m 2000022088 .8 2000 $0.0 2.2.2 I I -- 288 omm.N N.N2. 08880 8088288m2 woo wsN 20082880 88 6028282 0002E0m 8 2x. 88080 2N 0.8.22 00800 820220022 ”e 02872 143 The next group received over $5,001 and up to $10,000 in services with 76.1% achieving employment at closure. For this group the next most important predictor variable was the number of supports at closure. There was a 20.0% difference in employment outcomes between those with and without supports at closure. This final group of customers who closed with a bachelor’s degree received more than $10,000 in funding and had the highest likelihood of employment at closure (81.5%) within this group. Support at closure was found to be an important predictor; almost 20% more customers without support at closure closed employed (Figure 7.3). 144 .20. 80$ 00800 0820800 0 823 808308 8.2 0888082 08880 88028020 008 208.202 .mfi 088.2 000 2.0 2202 000 0.0 2200 2.00 22.2 220.0 02.220330 002032.20 00208220 000 0.: 2880222802 000 2.00 2580202802 022 0.20 2880222802 20082880 88 20082880 88 20082880 88 000 0.2 2200 08880 000 S0 282002.250 20082880 88 000 0.00 022222 082.80 20 0.0 022222 082.50 8 0.00 022222 082300 02. 0.02 022222 08280 8 2x. no 02872 8 2x. no 02872 8 X. en 02872 8 2x. mm 02872 2 2 2 0.2002 .20 2 o 0.208 .20 2 m 2 2 2 2 2.08 .mNeewu08082002220 .ooo.ou0820>-n2 2.20.0. 080020 20 02.88028 8 20028872 2 2H8 .evo.wNu0208200-280 .ooo.on0820>-n2 .23.. 080020 20 02.88825 .8 20228872 owe . 2 5e 2 eN. 2 m. 2 0 08880 80882880 5N m.w2 20082880 88 80208282 0002Z0m 8 022 oN 02872 00212800222228 58.08232 .23. 088 8 2oo.o2m 0002E0m 2000022082 8 280 P o 2 m N.N 208.2. mom 2.en 08880 808820280 8N2 o.mN 20082880 88 60208282 0002B0m 8 2x2 wN 02872 022V 00222008202222-2220 08082.22 .23.. 08.020.28.00 08280 0222.08 .20 280 2 208.2. 20082880 88 80208282 0002E0m 08880 80882880 neNfi 2.202 omm.N N.Nn woo MEN 8 2x. 28800 2m 8020 00.800 820.2000 "e 02872 145 Predictor Variables for Customers with an Education Level of Masters Almost 80% of 1,180 customers with an education level of Masters Degree were employed at closure (Figure 8.1). As with many other groups including customers with a bachelor’s degrees cost of goods and purchased services was an important employment predictor. Even at this higher level of education, limits in funding and supports at closure impact the employability of this group. Less than 40.0% of customers with $1,000 or less in funding and one or more supports at closure were employed at closure. Customers with the similar funding constraints but no supports at closure appear to fare better with 68.6% closing employed. 146 .22 2.8822 008022 0.802002 0 523 80882080 8.2 88022008 088080 820028020 0020 20280.2 .2.w 088202 3 86 208.2. N82 86 208.2. 08880 088080 8 8% 28882850 2 0.00 28822880 20082980 88 200082.280 88 am Wow 800022282 mooEom mm v.2m 800020282 000230m 8 .x. 3 02872 8 .x. 3 02872 088“ .8 2 2.2 2 2 E0 83.21.83-200 58.08288 .2022. 0.88820 20 382283 .8 802852 32 md 2082. 32 m.mm 088080 8088202888 0w v.88 2002202880 88 802020282 000220m 8 8x. cm 02872 «"00 83.888280 58.08288 .2020 08.2700 2228 028080 .20 280 2 32.2 2.m 2089 mmm 2.3 08880 80882029812 $0 800 008.280 28 .0288 3888 8 .x. 28330 22 0.8.22 00.809 0.800002 K 0872 147 This second partial tree represents those customers who received over $1,000 but less than $10,000 in goods and purchased services (Figure 8.2). Over 75.0% of this group was employed at closure. Even at this level of education and cost of goods and purchased services, days from application to closure appears to impact employability. The majority of those with four of more years from application to closure exit unemployed, while 89.4% of those who exit within two years are employed at closure. 148 Am 8022 00800 0802002 .8 202202 8220082022 80 22223 808980 8.2 082022008 080088 82208020 00.8 2022.202 .~.w 082.2 00 0.0 220.2 0880280 om 0.5. 2880202888 2002202980 88 m8 Yam 602022282 0002E0m 8 2x. ma 02872 5 8.22 208.2. 0800280 2 o 2 .2. 28088202932 20022028280 88 on mdm 00208282000228 8 2x0 Na 02872 2 00002 8 A.” 2 2 08002 8 v [08002 N 8 82 0.0 . 2208 088080 0: 0.00 2005202080 2002202880 88 2N 0.222 60208282 0002t0m 8 8x. 28 02872 E0 .8%?280280 08.08288 .2020. 08820 02 8022002222822 882.2 @200 2 2 08002 N v 8002 2 v 2 mom 0. 2 208.2. mum Wm» 088080 8088202885 om Ova 2002028820 88 002022282 302.com 8 .x. 2m 02872 F 0.00 820888380 08.08280 .00. . 08.020.28.20 2288 022228 00 200 2 802.0 2.2m 208.2. Nmoxc. 2.90 088080 2800822028882 $2.8 0.0m 2002028820 88 002022282 0002E0m 8 .x. 28980 2N 2.2022 00.800 0.802002 0 02872 149 This last figure (8.3) reflects the outcome of the 1,180 customers with master’s degrees; the majority (79.1%) of which were employed at closure. As previously seen cost of goods and purchased services and days from application to closure appear impactful. Of customers with more than $10,000 in goods and purchased services and closed within 2 years 99.0% were employed. That number dropped to 80.7% for those with more than four years from application to closure. 150 Am 880 00800 0008002 .8 20312 80280832 80 523 00080880 8.2 08822008 088080 82822202. 00.8 202808 .m.w 08w2...2 8m «.2 2308 088080 2.8 gm “88.82088 2000202888 88 no 002 0088282 m0o2>8m 8 2x. ca 02872 2 080» v A.” 2 82 no 238. 32 0.0 2508. 080022.20 08082.20 23 08 808222080 9: 0.3 08622880 200828880 88 00.202980 88 w 3 .3323 802.com N 0.2 .8805 $0250 a 8. m0 0272 a .x. a 2572 2 080» v v lam?» N 2 E20 .madvuossgéo .oooduoagd .23. 080020 08 802802288».N 888.2 @200 ~ 2 080» N v 80» 2 v 8N0 5N 208.2. 2mm m.ww 080080 8808802885 mm 0.2 2 20082028280 88 6088282 0002E0m a x i 22.2 l mn.220 02226388828280 .ooo.ou082m>-n2 ..8< 088 8 Sod; 0002E0m 200008085 .20 8000 H ow 2 . 2 2 .m 2082. mma 2.02. 088080 80288202982 SN mdm 20082028880 88 6088282 0002>80m 8 X. 88980 Am 0.8.20 00800 0.8882 K. 0872 2 151 As reflected in previous findings and viewed in these partial decision trees, factors can be supportive or obstructive in customer employment outcomes. While some factors seem to be more or less beneficial Marini and colleagues used a gain chart to better understand the “homogeneous ‘end groups’ in the decision tree.” (2008, p. 11). Table 32 provides gain scores (employment rates) and index scores of the 65 homogeneous end groups relative to the employment rate of the overall sample. Groups with a higher index were more successful and alternatively groups with a lower index were less successful. To better understand factors associated with both employment and non-employment outcomes (status 26 or 28) five nodes were more extensively investigated. First three groups that had a higher employment outcome are examined followed by two nodes with a higher population of customers who closed not employed. Table 32 Gains chart (node-by-node) statistics for the 60 end groups % of No. of % of Total No. of Success Gain Index Node Subjects Sample Success Sample 1%) (%l 94 191 0.83% 189 1.62% 98.95% 196.34% 62 56 0.24% 54 0.46% 96.43% 191.33% 95 106 0.46% 98 0.84% 92.45% 183.44% 46 234 1.01% 216 1.85% 92.31% 183.15% 66 55 0.24% 50 0.43% 90.91% 180.38% 87 820 3.54% 739 6.34% 90.12% 178.81% 91 199 0.86% 178 1.53% 89.45% 177.48% 37 65 0.28% 58 0.50% 89.23% 177.05% 82 152 0.66% 135 1.16% 88.82% 176.22% 50 94 0.41% 82 0.70% 87.23% 173.08% 85 295 1.28% 250 2.14% 84.75% 168.15% 33 51 0.22% 43 0.37% 84.31% 167.29% 75 807 3.49% 654 5.61% 81.04% 160.80% 96 327 1.41% 264 2.26% 80.73% 160.19% 61 287 1.24% 220 1.89% 76.66% 152.09% 45 463 2.00% 346 2.97% 74.73% 148.27% 152 (table continues) Table 32 (continued). 0/0 Of No. of % of Total No. of Success Gain Index Node Subjects Sample Success Sample (%) (%) 76 250 1.08% 186 1.60% 74.40% 147.62% 74 703 3.04% 523 4.49% 74.40% 147.61% 65 196 0.85% 143 1.23% 72.96% 144.76% 83 164 0.71% 118 1.01% 71.95% 142.76% 88 728 3.15% 522 4.48% 71.70% 142.27% 49 326 1.41% 230 1.97% 70.55% 139.98% 92 87 0.38% 61 0.52% 70.11% 139.12% 89 102 0.44% 70 0.60% 68.63% 136.17% 39 135 0.58% 90 0.77% 66.67% 132.28% 86 224 0.97% 145 1.24% 64.73% 128.44% 80 236 1.02% 150 1.29% 63.56% 126.11% 68 151 0.65% 95 0.81% 62.91% 124.83% 53 319 1.38% 196 1.68% 61.44% 121.91% 34 92 0.40% 56 0.48% 60.87% 120.77% 77 364 1.57% 219 1.88% 60.16% 119.38% 48 723 3.13% 390 3.34% 53.94% 107.03% 73 451 1.95% 242 2.08% 53.66% 106.47% 84 384 1.66% 205 1.76% 53.39% 105.92% 36 330 1.43% 174 1.49% 52.73% 104.62% 60 283 1.22% 147 1.26% 51.94% 103.06% 55 216 0.93% 111 0.95% 51.39% 101.96% 44 589 2.55% 290 2.49% 49.24% 97.69% 64 378 1.63% 185 1.59% 48.94% 97.11% 78 305 1.32% 149 1.28% 48.85% 96.93% 93 82 0.35% 39 0.33% 47.56% 94.37% 41 1 14 0.49% 54 0.46% 47.37% 93.99% 69 278 1.20% 128 1.10% 46.04% 91.36% 72 346 1.50% 159 1.36% 45.95% 91.18% 79 988 4.27% 414 3.55% 41.90% 83.14% 90 86 0.37% 34 0.29% 39.53% 78.44% 59 564 2.44% 212 1.82% 37.59% 74.58% 81 264 1.14% 95 0.81% 35.98% 71.40% 43 272 1.18% 97 0.83% 35.66% 70.76% 35 162 0.70% 56 0.48% 34.57% 68.59% 67 674 2.91% 231 1.98% 34.27% 68.00% 52 468 2.02% 157 1.35% 33.55% 66.56% 63 361 1.56% 1 15 0.99% 31.86% 63.21% 47 722 3.12% 229 1.96% 31.72% 62.93% 153 (table continues) Table 32 (continued). % of No. of % of Total No. of Success Gain Index Node Subjects Sample Success Sample (%) (%) 38 393 1.70% 123 1.05% 31.30% 62.10% 58 347 1.50% 98 0.84% 28.24% 56.04% 54 679 2.93% 186 1.60% 27.39% 54.35% 51 453 1.96% 116 0.99% 25.61% 50.81% 71 1501 6.49% 365 3.13% 24.32% 48.25% 70 392 1.69% 95 0.81 % 24.23% 48.08% 40 284 1.23% 63 0.54% 22.18% 44.01% 57 539 2.33% 108 0.93% 20.04% 39.76% 42 606 2.62% 110 0.94% 18.15% 36.02% 8 164 0.71% 28 0.24% 17.07% 33.88% 56 458 1.98% 65 0.56% 14.19% 28.16% Group 94: This group represents 191 customers with a Masters degree at closure (Figure 8.3). Nearly everyone in this group achieved employment (n=189). Approximately a third (33.5%) received more than $10,000 up to $20,000 in goods and purchased services, more than half (52.9%) received more than $20,000 up to $50,000 in goods and purchased services and the final 13.6% received $50,000 or more in goods and purchased services. Over 60% achieved closure within two years of application and almost 40% achieved closure in less than one year afier application. The group was predominately male (73.8%), White or Asian (91.1%) and earned over $17.50 an hour (71.2%). An analysis of age at application revealed that just over 25.0% of this group was between 30 and 39 years old, almost 30% were between 40 and 49 years of age and just over 30.0% were between 50 and 59 years of age. For this group, the index score was 196.34% (1 .62/0.83).This index score indicates that the proportion of customers who achieved employment at closure did 96.3% better than the employment rate for the sample. While these 191 customers represent less than 1% of the study population; 99.0% of this group achieved employment 154 at closure. This group’s counterparts (groups/nodes 95 & 96; illustrated in Figure 8.3) who had a longer service period were less successful at outcome. For those receiving services for more than two but less than four years slightly less (92.5%) were employed at closure, and for those with over four years of services only 80.7% were employed at closure (compared to 99.0% for study group/node 94). Group 62: This group represents 56 customers who closed with an education level of post-secondary education, no degree (Figure 5.1). While only 40.1% of customers at this level of education were employed at closure nearly everyone this subgroup closed employed (n=54). The entire group achieved closure within one years of application. Just over half (5 1 .8%) received more than $10,000 up to $20,000 in goods and purchased services, with an additional 46.4% receiving more than $20,000 up to $50,000 in goods and purchased services and just 1.8% received $50,000 or more in goods and purchased services. The group was predominately male (71.4%). White or Asian customers represented (75.0%) of the group followed by African American or Blacks (19.6%), All Other Races (3.6%) and Hispanics (1.8%).The majority of customers (37.5%) earned between $8.50 and $11.49 an hour, an additional 25.0% eamed between $11.50 and $17.49 an hour and 17.9% earned over $17.50 an hour. For this group, the index score was 191.33% (046/024). This index score indicates that the proportion of customers who achieved employment at closure 91.3% better than the employment rate for the overall sample. While these 56 customers represent less than 1% of the study population; 96.4% of this group achieved employment at closure. This group’s counterparts (groups/nodes 61 & 62; illustrated in Figure 5.1) who received lower levels of funding had a lower percentage of customers employed at 155 closure; for those receiving over $1,000 and up to $10,000, 76.7% were employed at closure and 51.9% of customers receiving more than $ 10,000 in goods and services were employed at closure as well (compared to 96.4% for study group/node 60). Group 46: This group represents 234 customers who closed with an education level of special education certificate of completion (n=3) or high school graduate equivalency (n=231) (Figure 4.1). While only 42.1% of customers at this level of education were employed at closure 92.3% of this subgroup closed employed (n=216). The entire group achieved closure within one year of application. Over half (54.7%) received more than $5,000 and up to $10,000 in goods and purchased services, an additional 29.5% received more than $10,000 and up to $20,000 in goods and purchased services with an additional 15.0% receiving more than $20,000 up to $50,000 in goods and purchased services and less than 1.0% received $50,000 or more in goods and purchased services. The group was predominately male (80.8%). White and Asian customers represented (77.4%) of the group followed by African American or Blacks (15.4%), All Other Races (2.1%) and Hispanics (5.1%).The majority of customers (34.6%) earned between $8.50 and $11.49 an hour. An additional 17.9% earned between $6.50 and $8.49 an hour followed by 15.8% who earned between $11.50 and $17.49 an hour and 12.0% earned over $17.50 an hour. For this group, the index score was 183.15% (185/1.01). This index score indicates that the proportion of customers who achieved employment at closure was 83.2% better than the employment rate for the overall sample. While these 234 customers represent approximately 1% of the study population; 92.3% of this group achieved 156 employment at closure. This group’s counterparts (groups/nodes 44 & 45; illustrated in Figure 4.1) who received lower levels of finding had a lower percentage of customers employed at closure; 49.2% of those who received no funding up to $1,000 were employed at closure and 74.7% of those who received over $1,000 and up to $5,000 were employed at closure as well (compared to 92.3% for study group/node 46). Group 47: This group represents 722 customers who closed with a Special Education Certificate of Completion or High School Graduate Equivalency (Figure 4.2). Afier level of education the next most important predictor for this group was the number of days from application to closure with this group achieving closure afier one year but less than two years of services. The cost of purchased services for this group was the next important predictor. This group received less than $1000.00 in goods and service and only 31.7% were employed at closure (n =229). Of this group 64.7% were male. White and Asian customers represented (69.4%) of the group followed by African American or Blacks (21.5%), All Other Races (2.4%) and Hispanics (6.5%). Of those employed (n =229) the majority of customers (55.0%) earned less than $8.50 an hour. An additional 25.0% earned between $8.50 and $11.49 an hour followed by 12.5% who earned between $11.50 and $17.49 an hour. A final 7.5% earned over $17.50 an hour. An analysis of age at application revealed that just over 15.4% of this group were 21 years of age or younger, 13.7% were between 22 and 29 years old, 23.7% were between 30 and 39 years old, an additional 31.2% were between 40 and 49 years of age and just over 16.1% over 50 years of age. For this group, the index score was 62.93% (196/3.12). This index score indicates that the proportion of customers who achieved employment in this group is 6.3% of the 157 competitive employment rate. While these 722 customers represent 3.1% of the study population; only 31.7% of this group achieved employment at closure. This group’s counterparts (groups/nodes 48, 49 & 50; illustrated in Figure 4.2) who received higher levels of funding had a higher percentage of customers employed at closure; for those receiving over $1,000 and up to $5,000 53.9% were employed at closure, 70.6 percent of customers receiving over $5,000 but less than $20,000 were employed at closure and 87.2% of customers receiving more than $20,000 in goods and services were employed at closure as well (compared to 31.7% for study group/node 47). Group 71: This group represents 1,501 customers who closed with a Post- Secondary Education, no degree (Figure 5.4). After level of education the next most important predictor for this subset was years of service with this group achieving closure after four or more years of services; only 28.4% achieved employment at closure. The receipt of job placement services was the next important predictor. Of this subgroup (group 71) no customers received job placement services and only 24.3% of this subgroup closed employed (n=365). Of this group 65.8% were male. White and Asian customers represented (73.5%) of the group followed by African American or Blacks (15.3%), All Other Races (3.1%) and Hispanics (8.2%). Of those employed (n =107) the majority of customers (58.8%) earned less than $8.50 an hour. An additional 22.4% earned between $8.50 and $11.49 an hour followed by 15 .0% who earned between $11.50 and $17.49 an hour. Fewer than four percent (3.7%) earned over $17.50 an hour. An analysis of age at application revealed that just over 21.5% of this group were 21 years of age or younger, 19.0% were between 22 and 29 years old, 27.1% were between 158 30 and 39 years old, an additional 24.7% were between 40 and 49 years of age and just over 7.0% over 50 years of age. For this group, the index score was 48.25% (313/6.49). This index score indicates that the proportion of customers who achieved employment in this group is 4.8% of the competitive employment rate. While these 1501 customers represent 6.5% of the study population; only 24.3% of this group achieved employment at closure. This group’s counterpart (group/node 71) who did receive job placement services (illustrated in Figure 5.4) had a higher percentage of customers employed at closure (46.0% compared to 24.3%). Research Question Three (Part Two) Analysis of Five Year Patterns of Change in Significant Predictor Variables This final section examines any recognizable patterns in the service provisions most often associated with positive or negative employment outcomes for customers with SCI. The exhaustive CHAID analysis, of the 30 predictor variables, selected six variables as the most significant predictors of employment outcome. These include level of education attained at closure, cost of services categories, categories for number of days from application to closure, rehabilitation technology services received, job placement assistance services received and number of supports at closure. This section will examine the five year patterns associated with these variables. These factors were fully explored as a part of research question and are summarized for convenience. Level of Education at Closure 159 Table 14 illuminated five years patterns in education. The percentage of customers with high school graduate equivalency at the time of case closure decreased from 32.9% in 2004 to 29.4% in 2008. The percentage of customers with bachelor's degrees increased from 12.6 % in 2004 to 15.2 % in 2008 and the percentage of customers with master's degree or higher increased from 4.0% in 2004 to 6.1% in 2008. Cost of Goods and Purchased Services by Year As reflected in Table 13 there was an increase in the funding and allocation of services provided to customers during this five year period. There was a consistent decrease in the number of customers receiving funding in all dollar amount categories that were $10,000 or below and an increase in all funding categories above $10,000. Days from Application to Closure As illustrated in Table 16 several changes occurred. The percentage of customers closing within one year of application increased by 5.7% from 13.4% in 2004 to 19.1% in 2008. The percentage of customers closing between two to three years from application to closure decreased by 6.6% from 19.7% in 2004 to 13.1% in 2008. The number of customers closing within three to four years from application to closure also decreased by over 6% from 15.4% in 2004 to 9.1% in 2008. Finally the percentage of customers closing four or more years from application to closure increased by 4.2% from 30.8% in 2004 to 35.0% in 2008. Number and Percent of Customers Receiving Services, by Year The number of those who received rehabilitation technology services increased by almost 10% from 20.1% in 2004 to 29.8% in 2008 and the number of job placement 160 assistance recipients grew with 3.5% from 22.8% in 2004 to 26.3% in 2008. Refer to Table 14 for more details. Number of Supports at Closure Table 16 fiirther illustrates changes in the Number of Supports at Closure. The percentage of customers who received zero supports decreased by over 5% from 49.3% in 2004 to 44.2% in 2008. In contrast, the number of customers who received one support increased slightly from 43.3% in 2004 to 48.0% in 2008. 161 CHAPTER 5 Discussion The purpose of this study was to examine employment outcomes for individuals with spinal cord injury served by the state vocational rehabilitation services program between 2004 and 2008. Research questions that guided the study were: 1. What are the characteristics of customers with SCI served by the VR system? a. Have the characteristics of customers with SCI served by the VR system changed over the five (5) year span? 2. Are there differences in outcomes (type of closure) based on characteristics for this population and have they changed over the five (5) year span? 3. What are the factors (characteristics and/or services?) associated with positive outcomes for customers with SCI? a. Is there a recognizable pattern displaying an increase in the service provisions most often associated with positive outcomes for customers with SC 1? Characteristics of customers with SCI served by the VR system and the significant changes in customer profiles between 2004 and 2008 This first section provides an overview of the aggregate population of customers with a status 26 or 28 closure served between 2004 and 2008 and statistically significant changes that occurred during this time. The first observation for discussion is the drop in participation of customers with SCI. There was a consistent decline each year for 162 customers served with SCI totaling over 33.0% for the five years studied; participation numbers dropped from 5,916 in 2004 to 3,803 in 2008 in contrast to an 8.3% reduction for the aggregate group; from 379,158 in 2004 to 350,071 in 2008. A comparison of the percentage of SCl customers in comparison with the aggregate population reflects a consistent decrease from 0.016% to 0.011% (Table 33). Because spinal cord injury is a severe disability, order of selection should not have limited the acceptance rate of this group. While estimates suggest that each year 12,000 individuals sustain an SCI, no overall incidence studies have been recently conducted to determine annual injury rates (N SCISC, 2009). Such a significant drop should be addressed nationally and through VR. Table 33 SCI Customer Characteristics by Year 2004 2005 2006 2007 2008 n n n n n % % % % % VR Customers 379,158 351,292 347,711 340,454 350,071 (No SCI) VR Customers 5,915 4,937 4,427 4,053 3,803 (SCI Only) % of VR Customers 0.016 0.014 0.013 0.012 0.011 The majority of customers served were male (65.0%). While on the surface this appears as an over representation of males the opposite is true as males represent over 80.0% of the population of individuals with SCI (N SCISC, 2009) but only 65 .0% of those who achieved a status 26 or 28 employment outcome. This distribution was consistent between years 2004 through 2007, with a spike of just over 2.0% in males in year 2008. While the majority of customers were White or Asian (70.6%) these numbers are within one percentage point of the aggregate population estimates for 2008 (US. Census Bureau, 2010). As illustrated in Table 34, African American or Black customers 163 are overrepresented by 4.2% and Hispanic customers are underrepresented by 6.6%. There was only a 0.1% difference between the US. census estimates and study participants for All Other Races. Examining outcomes by race the majority of White and Asian (52.8%) and Hispanic (51.5) customers were employed at closure. Fewer than 50.0% of All Other Races (44.8%) and Afiican American or Black (40.9%) customers were employed at closure. Table 34 S CI Customer Population compared to National Averages White African Hispanic All or American Other Asian or Black Races % % % % Percentage of US. Population by 70.1 12.8 15.4 2.9 Race* Percentage of VR Customers with SCI by Race 71.1 17.0 8.8 3.0 *2008 Population Estimates total 101.2% due to customers reporting more than one race A majority of customers (53.9%) were between 30 and 49 years of age at application (Table 2). The majority of the study population reported at least a high school graduate equivalency (40.0%), with an additional 40% reporting at least a post secondary education at the time of application for VR services. During the five years of study there was an approximate 6.0% improvement in customers with an associate degree or higher level. At time of application about 8.5 % were students and 17.5% were working. Wages for those working improved over the study period (customer’s earning above $17.50 an hour increased by almost 10%). Of the 23,091 customers who received support, over 40.0% used public assistance with an additional 34.2% reporting assistance from family and friends; there was close to 164 a 3.0% decrease in those seeking support from family and fi'iends and just over a 2.0% increase in the use of public support between 2004 and 2008. A further analysis indicated an increase in the use of SSDI and SSI and a decrease in the use of other public supports. Medicaid, Medicare and other public sources of medical insurance increased during the study period as well. Fewer than 10% of customers with SCI received two or more supports at application. On average over 50.0% of customers received eligibility within 30 days; a slight improvement was observed over time. There was an increase in the amount of funding for goods and purchased services between 2004 and 2008. An analysis of the aggregate group of customers with SCI revealed 32.2% received between $1,001 and $5,000 in funding while slightly less than 30.0% received less than $1,000 in funding. However, during the study period, funding in these categories decreased with an increase in all funding categories above $10,000. The services most frequently provided included assessment and vocational rehabilitation and guidance. Just over 35.0% received transportation services and just under a quarter received services associated with rehabilitation technology. Services that increased during the study period include information and referral, job placement assistance and rehabilitation technology, transportation and other (non-specified) services. There were several improvements noted for customers with SCI at closure. The aggregate of customers reporting a post secondary education and above grew by over 17%, from 40% to 57.4%; with an overall pattern of growth evidenced by year as well. Midrange earnings (between $8.50 and $ 17.49) improved on average by over 20.0% from application to closure. An improvement in proportion of customers earning wages above $11.50 an hour was reported between 2004 and 2008. A review of employment outcomes 165 over the study’s five year period revealed a non-linear progression. The number of customers employed at closure grew from 47.8% in 2004 to 52.0% in 2007 but settled at 50.2% in 2008. A review of the overall use of customer supports at closure was mixed. A review of customer supports at closure on average reflected a 4.3% increase in SSDI recipients. A 5.0% increase in Medicare was revealed as well. A review of years 2004 through 2008 reflected linear growth of SSDl, suggesting a pattern of increasing utilization of this support; there was a less linear pattern but overall grth in the utilization of Medicare. A 2.1% increase in SSI and a 3.5% increase in Medicaid was detected during this five year period as well. In line with previous findings, a review of five year patterns revealed a linear increase in the number of supports used by customers at closure (5.0% over five years). While these increases were reported, customers’ use of other types of support including Worker’s compensation, TANF and general assistance decreased. The time from application to closure had mixed findings as well. There was linear improvement of 6.0% for customers closing in less than one year and a 4.2% increase in customers closing within four or more years. There was a reciprocal decline in customers closing in more than one but less than three years. Differences in Outcomes (Type of Closure) Based On Characteristics for This Population Including Changes in Customer Employment Outcomes over a Five Year Span This next section reports on factors associated with research question two of which examined differences in outcomes (type of closure) based on characteristics for this population, including changes in customer employment outcomes over a five year span. Women had a slightly better employment outcome on average, with 51.8% of 166 women employed at closure as compared to 49.8% of their male counterparts. There were no five year patterns observed for either group. The majority of White, Asian and Hispanics were employed at closure. While White or Asian customers make up 71.1% of customers served, 74.5% achieved a positive employment outcome. Hispanics achieved a slightly higher than average outcome, representing 8.8% of customers served and 9.0% of customers with a positive employment outcome. The reverse is true for African American or Black and All Other Race customers. African American or Black customers comprised 17% of customers and only 13.8% of those employed at closure and finally All Other Races represented 3% of customers and 2.7% of those employed. There were no observable linear patterns of change in employment outcomes by race during the five years of study. A review of customer’s age at application revealed a linear relationship between age and employment with older customers achieving better outcomes. Over 60.0% of those over 64 years of age and 55.5% of those 60 to 64 were employed at closure. The majority of customers aged 30 to 59 years of age were employed at closure as well. Conversely approximately 49.0% of those 29 years of age and younger were employed at closure. The only five year pattern observed for age at application was a steady increase in the number of customers aged 40-49 employed at closure; from 46.7% in 2004 to 52.2% in 2008. There was a positive linear relationship between level of education at application and employment outcome as well. The majority of customers with an associate’s degree or higher achieved a positive employment outcome. More than three quarters (77.5%) of customers with a master’s degree and two thirds (68.3%) of customers with a bachelor's degree were employed at closure. As reported in Chapter 167 Four the further analysis by employment outcome and year resulted in small populations within each category so no further analysis was completed. Employment status at application impacted employment outcomes at closure. The majority of customers unemployed at application (N = 7,426) were also unemployed at closure; only 43.6% achieved employment. The majority of customers employed at application in an integrated setting without supports were still employed at closure (78.3%) as were customers employed in an integrated setting with supports (84.4%) and those who were self-employed (81.7%). An examination of demographic factors associated with customers employed at application and closure revealed a number of items for discussion. First race and gender differences were not statistically significant however a higher percentage of Whites and Asians as well as males exited employed. The majority of customers with fewer than three supports at application were also employed at closure. The types of services received by customers employed at application were also examined. The largest proportion of customers utilized assessment services (n = 2634), diagnostic and treatment services (n = 1,736), rehabilitation technology services (n = 1,504), transportation services (n = 703), vocational rehabilitation counseling and guidance services (n = 2,010). Only 561 customers received college or university training services; 64.2% were employed at closure. In a review of five year patterns, a positive linear relationship was found in the percentage of Other Unemployed customers employed at closure, with a progressive increase between 2004 (41 .3%) and 2008 (57.4%). As with prior findings, there was a statistically significant and positive linear relationship between hourly wage at 168 application and employment closure with higher salary ranges at application correlating with a higher percentage of employment at closure: Close to 90.0% of those earning over $17.50 an hour were employed. Customers reporting hours worked at application were more likely to be employed at closure as well. There were no observable five year patterns for either of these employment related variables. As was reported in previous research (Marini, 2007; Rosenthal, 2008) public support can be a disincentive and result in decreased employment. Similar findings were found in this present study: Only 42.2% of customers who received any type of public support at application were employed at closure. Customers utilizing SSI, TANF and general assistance had particularly low rates of employment, as did customers utilizing Medicaid. In addition to the type of supports, the number of supports also impacted employment outcome: The majority of customers with one or more supports at application were unemployed at closure. Finally the majority of customers who achieved eligibility within thirty days were employed at closure. Cost of goods and purchased services appears to be highly correlated with employment status at closure. Less than 35% of customers who received $1,000.00 or less in goods and purchased services achieved employment at closure as opposed to almost 70% of those receiving over $20,000.00. Services that appear most linked to employment at closure include on-the-job training, rehabilitation technology, job placement assistance, on-the-job-support and technical assistance. Job search assistance, maintenance, other services, information and referral, job readiness training and vocational rehabilitation and guidance appeared impactful as well. No patterns of change 169 were observed in either the cost of goods and purchased services or the distribution of services. This next section examines factors associated variables associated with closure. As earlier indicated, there appears to be a correlation between level of education and employment outcome. Nearly 80% of customers with a master’s degree or higher, 72.7% of customers with a bachelor’s degree and 61.7% of those with an Associate degree or vocational technology certification were employed at closure. The majority of customers with a post secondary education with no degree or below were unemployed at closure. Similar to reports for customers at application, the majority of customers utilizing public support at closure were unemployed. Approximately two thirds of customers utilizing SS1, TANF, worker’s compensation and other public support were unemployed at closure as were 39.5% of customers utilizing Medicaid. In line with these findings the majority of customers who reported using even one type of support at closure were unemployed. Findings related to length of service supports earlier research (Marini, 2008). Over 70.0% of customers who closed within one year of application were employed at closure. The majority of customers receiving services from the VR for more than two years were more likely to close without employment. There were no patterns observed that would indicate an increase in earlier closures. An Analysis of the Allocation and Patterns of Change of Predictor Variables This next section examines the final analysis of the study. Variables found to be statistically significant and as such impactful on customers employment outcomes were selected as predictor variables for further analysis using data mining techniques. Through the use of a systematic algorithm the strongest relationships between predictors and the 170 outcome variable (status 26 or 28 employment outcome) were identified and organized into a hierarchical framework similar to a tree with branches. A top-down, step-wise approach was utilized; as the predictor variable with the strongest relationship to the outcome variable was presented first, followed by splits or branches that identify the next set of variables with the strongest relation to the outcome variable (nodes). The analysis resulted in a total of three branches with 97 nodes (65 end nodes). Of the 30 predictor variables included in the analysis the six variables selected as the most significant predictors of employment outcome include level of education attained at closure, cost of services categories, categories for number of days from application to closure, rehabilitation technology services received, job placement assistance services received and number of supports at closure. The most significant predictor of employment outcomes was level of education attained at closure. While level of education attained at closure was the most significant predictor of employment, interactions with other service factors must be considered. Of the 191 customers with a master’s degree who received over $10,000 in goods and purchased services and closed within a year of application, 99.0% achieved employment. For similar customers with a master’s degree who received over $10,000 in goods and purchased services who closed after four years, the success rates drops to 80.7%. Decreases in the cost of goods and purchased services and increases in the time from application to closure and number of supports dropped customer success rate to as low as 34.0%. To better understand the predictor variables and their influence, a gains chart was developed to examine the “homogeneous end groups” (Marini et. al., 2008, p.11). Factors found to influence success for customers varied and were dependent on the interacting 171 variables. These findings suggest that customers needs vary and a successful outcome cannot be hierarchically prescribed. While level of education is clearly an important predictor of success it is not the only factor. Findings illustrate that customers with a lower level of education can be successful with the right combination of factors. This is an important for consideration as not all customers will chose to or be provided further levels of education. For these clients job placement assistance and rehabilitation technology may be of greater service. One final analysis looked at the pattern in allocation of the services associated with a positive employment. Most directly was there a pattern of change in services or customer variables associated with success at closure from 2004 and 2008? Findings from the analysis are encouraging. There was an increase in the number of customers who closed with a bachelor or master’s degree. The amount of goods and purchased services customers received improved as well. The number of customers who closed within a year of application increased. Those closing within four or more years also increased but this may be attributed to an increase in education levels. Rehabilitation technology services and job placement assistance increased as well. One final factor for review is the customer supports at closure. There was an increase in the number of customers using supports at closure. Comparison of Stuoy Findings with Previous Research As addressed earlier, this study is an extension of a prior study by Irmo Marini, Gloria K. Lee, F ong Chan, Martha H. Chapin and Maria G. Romero who examined employment outcomes for individuals with spinal cord injury served by the state vocational rehabilitation services program between 2001. Similar to this current study, 172 Marini and colleagues examined the effect of demographic characteristics, disincentives and service variables on the employment outcomes of customers with SCI served by the state VR. Table 34 provides a comparison of customer characteristics between the current study and 2008 study by Marini and colleagues. There were demographic differences noted between the two studies however, comparisons on one year of data may not be indicative of patterns or trends. In addition, employment outcomes for the 2001 customer population were higher; 54.0% in 2001 compared to an average of 50.4% between years 2004 and 2008. The first difference of note is a 2.0% variation in the employment outcome of males from the 2001 to the current study however similar variances also occurred between years 2006, 2007 and 2008 in the current study. The employment outcomes for all races appear to decrease between study periods; most notably for African American or Blacks and Hispanic or Latino customers as did the outcome for all levels of education. As reported in 2001 findings work disincentives still appear to impact the employment outcome of customers and have increased. by an average of 3.0% during 2004 and 2008. 173 Table 34 Comparison of Employment Rates of VR Clients in 2001 and 2004 through 2008 Study (Author, Year) Marini, et a1. Current Study Marini, et al. Current Study 2008 2008 Employed Employed Not Employed Not Employed 2001 2004-2008 2001 2004-2008 Gender Male 52.6% 49.6% 47.4% 50.4% Female 55.2% 51.8% 44.8% 48.2% Race White 54.7% 52.8% 45.3% 47.2% and Asian' 55.9% 44.1% African American or 48.8% 40.9% 51.2% 59.1% Black Hispanic or Latino 53.3% 51.5% 46.7% 48.5% Education Less than High 45.6% 41.0% 54.4% 59.0% School High School Graduate 53.0% 47.3% 47.0% 52.7% As least some college 60.1% 58.0% 39.9% 42.0% Work Disincentive2 Yes 43.1% 40.9% 56.9% 59.1% No 56.6% 61.2% 43.4% 38.8% 1. White and Asian customers combined in current study 2. Work disincentives in Marini, et a1. (2008) study used SSI, SSDI numbers; current study used number of supports at closure This next comparison examines the findings of the CHAID analysis conducted on data from Marini et al.’s (2008) study of VR customers with SCI served in 20013nd the current study’s analysis of VR customers with SCI served between 2004 and 2008. Findings from the Marini et a1. (2008) study suggest job placement services to be the most important predictor of employment, followed by case expenditures (cost of goods and purchased services) and work disincentives. In addition, physical and/or mental restoration, substantial counseling, and assistive technology were found to be important predictors of employment for the Marini study (2008). A primary difference between the 174 studies is the importance of level of education as the most significant predictor of employment in the current study with customers served between 2004 and 2008. The next most significant predictor for this group was dependent on level of education and included an additional variable not included in the 2001 study, the number of days from application to closure, along with cost of goods and purchased services, number of supports at closure variables. The final predictor variables for the 2004 through 2008 customers were job placement assistance and rehabilitation technology services. Cost of purchased services, work disincentives (e.g., number of supports at closure), job placement assistance service and rehabilitation technology were found to be strong predictors of employment outcomes in both studies. Assumptions and Limitations of the Study Several limitations in this study should be addressed. First, this study used Rehabilitation Services Administration RSA 911 data and as result there are several limitations that are resultant of using an archival dataset. First there are limitations in the characteristics of the customers, their geographic location and resulting socioeconomic conditions as well as the perceived or actual quality of any received services. In addition, the use of archival data restricts the ability of the researcher to control for human error that may have occurred during the coding of customer records. Also because this study’s timeframe is limited to a five year period there aren’t enough cycles (n <10) for an actual trend analysis. Finally, because this study population was composed of VR customers findings may be less applicable to populations being served by other employer networks; especially those incurred as a result of an accident who receive services, including VR, from a private vendor such as workers compensation or other insurers including auto. 175 Limitations more directly related to this study include the multi-collinarity of predictor variables with the dependent variable. Several variables included in the initial chi-square analysis were removed from the decision tree analysis as they were closely related to employment outcome (e. g., hourly wages at closure). A future study could include these variables to better understand their relationship with input, service and outcome variables. While level of education has a less direct relationship to employment there is a positive linear relation with employment outcome. This variable was not excluded as it allowed for a more in-depth exploration of employment success at different levels of education and provided firrther insight of the interrelation with other variables included in this study. Conclusions Findings from this study indicate that the factors associated with employment outcomes for consumers with SCI is complex. Through the use of chi-square and decision tree analysis several factors surfaced as key indicators of employment but findings from the analysis suggest that these factors do not operate in isolation and as a result aren’t the sole driving forces associated with outcome success. This is important for several reasons; first it provides a hierarchical representation of variables based on their relationship with the dependent variable, and other predictor variables, second it suggests that employment is possible even for particularly challenging customers (e.g., customers with lower levels of education), third it suggests that even with the prescribed supports and services other factors may impact customer success (funding for goods and services) and fourth it suggests that customers needs are varied and a single solution or set of solutions may not work for customers seeking services. 176 While several analytic methods are available to examine predictors of employment outcomes, classification methods such as decision tree analysis offered several benefits to this study. First it allowed for a graphical display of findings which allowed for easier interpretation and dissemination of information, second it provided a method for “detecting, explicating and interpreting interactions in categorical data” and third the hierarchical nature of the tree provided a schema of the interaction and interrelationship of variables and their impact on the dependent variable (Kosciulek, 2004,p.142) Implications for future research This study while extensive only scratched the surface of the inter-relation of customer characteristics, service provisions and outcome factors. A more thorough examination of the population of customers within each end-node from the CHAID analysis is needed to further identify factors that are particularly important for sub groups of customers. The exhaustive CHAID analysis also determined that a combination of factors may be supportive or prohibitive of employment at closure. As suggested and illustrated in Figure 5.3 the percentage of those at closure fluctuated from 51.9% to 96.4% depending on the number of year from application to closure and the cost of goods and purchased services in addition to other factors. As provided for the five end nodes examined further exploration of the other factors associated with these groups or clusters of customers needs to be explored. Pattern or trend analysis may be an important tool for firrther studies of VR customers. This five year analysis provided insight into the changes occurring within the 177 population which may warrant further investigation. These include a statistically significant reduction of customers with SCI in comparison with the aggregate group of customers, a reduction of younger customers which may be an indication of changes within the SCI population or a result of a shift in VR recruiting methods, and evidence that services suggested as effective in improving employment outcomes show a pattern of increased allocation. An important finding for customers employed at application should also be noted for further examination. Study findings suggest that the proportion of customers employed at application may be accessing VR for specific services including assessment services, diagnostic and treatment services, rehabilitation technology services, transportation services and vocational rehabilitation counseling and guidance services. Implication for Rehabilitation Counselors and Policy Directors Findings suggest that level of education at closure; funding and services allocation, days from application to closure and the use of public supports at closure are important predictors of employment outcome. However careful analysis of these findings are recommended as there may be a number of critical factors or unknown variables coming into play during the time a customers is receiving services. For example the number of days from application to closure may be more indicative of a customer’s health as opposed to the diligence of either the customer or the counselor. Because the time spent from application to closure appeared to be highly impactful on outcomes counselors may benefit from understanding customers delays and methods for mitigating roadblocks as well as facilitating service provision when applicable to allow for earlier closures. While a higher level of education is associated with higher levels of income, 178 cost of goods and purchased services was impactful as well. Customers who received over $5,000 in services did markedly better than customers with less funding. While these findings suggest providing funding to clients appears impactful an understanding of the actual services provided to customer may help illuminate service benefits. Finally because findings suggest the number of public supports at closure impact employability counselors may want to better understand these customers and how they may be best transition from public support to employment. Again, caution is stressed in that customer’s needs are unique and using research findings without the consideration of the human element could result in boilerplate service provisions that inadequately serve all customers equally. 179 APPENDICES The Reporting Manual for the Case Service Report [PD-06-01] provides detailed edit and relational edit specifications for reporting RSA-911 data. Specific categories of variables include demographic, public support and VR services. While the majority of variables were in a format that allowed for a comparative analysis (e. g. nominal or ordinal) some variables were continuous and were recoded into categories. The following provides a definition of all variables included in this study including any recoding. Demographic Variables Demographic variables included in this study include gender (male or female), race/ethnicity categories used in the rehabilitation literature (African American, Native American, Asian American, European American, Hispanic American), age at application (16-24, 25-34, 35-54, and 55-64), level of education at intake and closure (no formal schooling; elementary education grades 1-8; secondary education; no high school diploma grades 9-12; special education certificate of completion/diploma or in attendance; high school graduate or equivalency certificate; post-secondary education, no degree; associate degree or vocational/technical certificate; Bachelor's degree; Master's degree or higher), IEP (had an IEP or did not have an IEP), and previous closure (previous closure within past 36 months or no previous closure within past 36 months). Employment status at intake included seven categories: employment without supports in an integrated setting, extended employment, self-employment, state agency-managed Business Enterprise Program (BEP), homemaker, unpaid family worker, and employment with supports in an integrated setting. These categories are described below: 180 Employment without supports in an integrated setting covered individuals who worked for wages, salary, commissions, tips, or piece-rates, below, at, or above the minimum wage. This category did not include self-employed individuals. Extended employment covered those who worked for wages or salary in a non-integrated setting for a public or nonprofit organization. The organization provided any needed support services that enabled the individual to train or prepare for competitive employment. This category applied only to individuals who received services and were placed in extended employment. This category was not considered an employment outcome. Self-employment (except BEP) applied to those who worked for profit or fees including those operating their own business, farm, shop or office. Sharecroppers were included in this category, but wage earners on farms were not. State Agency-managed Business Enterprise Program (BEP) referred to Randolph-Sheppard vending facilities and other small businesses operated by individuals with significant disabilities under the management and supervision of a State VR agency. This category included home industry where the work was done under the management and supervision of a State VR agency in the individual's own home or residence for wages, salary, or a piece-rate. Individuals capable of activity outside the home, as well as homebound individuals, engaged in this type of employment. Homemaker referred to men and women whose activity was keeping house for persons in their households, or for themselves if they lived alone. 181 o Unpaid family worker referred to persons who worked without pay on a family farm or in a family business. 0 Employment with supports in integrated setting covered full-time or part-time employment in an integrated setting with ongoing support services for individuals with significant disabilities. Additional demographic variables included type of closure (employed or not); hourly wage at intake and hourly wage at closure (recoded from a continuous variable into five categories: less than or equal to $6.49, $6.40 to $8.49, $8.50 to $11.49, $11.50 to $17.49, and $ 17.50 or more); and hours worked per week at intake and hours worked per week at closure (recoded from a continuous variable into six categories: 0 hours, 1 to 10 hours, 11 to 20 hours, 21 to 30 hours, 31 to 35 hours, 36 to 40 hours, and 41 hours or more). Public Support Variables Seven variables addressed the type of public support received at intake and seven variables addressed the type of public support at closure. Types of public support included Supplemental Security Income (SSI), Social Security Disability Insurance (SSDI), Temporary Assistance for Needy Families (TANF), general assistance, veterans' disability benefits, workers' compensation, and other. Each of these variables had two possible values: yes (service received) or no (service not received). Five variables represented the type of medical insurance coverage at intake and five variables represented the type of medical insurance coverage at closure. Types of medical insurance coverage included Medicaid, Medicare, public insurance from other source, private insurance through own employment, and private insurance through other 182 means. Each of these variables had two possible values: yes (service received) or no (service not received). In addition to the 24 support variables discussed above, eight additional support- related variables were considered. Two variables, primary source of support at intake and primary source of support at closure, had four response options: personal income (earnings, interest, dividends, rent); family and friends; public support (for example, SS1, SSDI, TANF); and all other sources (for example, private disability insurance and private charities). Two variables, number of supports at application and number of supports at closure, had values ranging from 0 to 5, representing up to five sources of support. Number of days from application to eligibility for services was recoded from a continuous variable into five categories (0 to 30 days, 31 to 60 days, 61 to 90 days, 91 or more days, and not eligible for services). Number of years from application to closure was recoded from a continuous variable into five categories (less than one year, one to less than two years, two to less than three years, three to less than four years, and four or more years). Cost of goods and purchased services was recoded from a continuous variable into five categories (up to $539; $540 to $2,131; $2,132 to $5,109; $5,110 to $12,841; and $12,842 or more). VR Service Variables VR services variables included Assessment, Diagnosis and Treatment of Impairments, Vocational Rehabilitation Counseling and Guidance, College or University Training, OccupationaWocational Training, On-the-Job Training, Basic Academic Remedial or Literacy Training, Job-Readiness Training, Disability-Related Augmentative Skills Training, Miscellaneous Training, Job Search Assistance, Job Placement 183 Assistance, On-the—Job Supports, Transportation Services, Maintenance Services, Rehabilitation Technology, Reader Services, Interpreter Services, Personal Attendant Services, Technical Assistance Services, Information and Referral Services, Other Services. A description of these services follows: 0 Assessment: Services provided and activities performed to determine an individual's eligibility for VR services, to assign an individual to a priority category of a state VR agency that operates under an order of selection, and/or to determine the nature and scope of VR services to be included in the Individual Plan for Employment (IPE); included in this category are trial work experiences and extended evaluation. 0 Diagnosis and Treatment of Impairments: Surgery, prosthetics and orthotics, nursing services, dentistry, podiatry, occupational therapy, physical therapy, speech or hearing therapy, and drugs and supplies; this category includes diagnosis and treatment of mental and emotional disorders as well treatment of special medical services. 0 Vocational Rehabilitation Counseling and Guidance: Discrete therapeutic counseling and guidance services necessary for an individual to achieve an employment outcome, including personal adjustment counseling; counseling that addresses medical, family, or social issues; vocational counseling; and any other form of counseling and guidance necessary for an individual with a disability to achieve an employment outcome; this service is distinct from the general 184 counseling and guidance relationship that exists between the counselor and the individual during the entire rehabilitation process. Training College or University Training. F ull-time or part-time academic training above the high school level that leads to a degree (associate, baccalaureate, graduate, or professional), a certificate, or other recognized educational credential; such training may be provided by a four-year college or university, community college, junior college, or technical college. OccupationaWocational Training: Occupational, vocational, or job skill training provided by a community college and/or a business, vocational/trade, or technical school to prepare students for gainful employment in a recognized occupation not leading to an academic degree or certification. On-the-Job Training: Training in specific job skills by a prospective employer; generally the individual is paid during this training and will remain in the same or a similar job upon successful completion; this category also includes apprenticeship training programs conducted or sponsored by an employer, a group of employers, or a joint apprenticeship committee representing both employers and a union. Basic Academic Remedial or Literacy Training: Literacy training or training provided to remediate basic academic skills needed to function on the job in the competitive labor market. 185 1 ob Readiness Training: Training to prepare an individual for the world of work (e.g., appropriate work behaviors, methods for getting to work on time, appropriate dress and grooming, methods for increasing productivity). Disability-Related, Augmentative Skills Training: Service includes, but is not limited to, orientation and mobility, rehabilitation teaching, training in the use of low vision aids, Braille, speech reading, sign language, and cognitive training/retraining. Miscellaneous Training: Any training not recorded in one of the other categories listed, including GED or high school training leading to a diploma. Job-Related Services Job Search Assistance: Assistance includes activities that support and assist a consumer in searching for an appropriate job. These may include help in preparing resumes, identifying appropriate job opportunities, and developing interview skills, and may include making contacts with companies on behalf of the consumer. Job Placement Assistance: A referral to a specific job resulting in an interview, whether or not the individual obtained the job. On-the—Job Supports: Support services provided to an individual who has been placed in employment in order to stabilize the placement and enhance job retention; such services include job coaching, follow-up and follow-along, and job retention services. 186 Transportation Services: Travel and related expenses necessary to enable an applicant or eligible individual to participate in a VR service; includes adequate training in the use of public transportation vehicles and systems. Maintenance Services: Monetary support provided for expenses such as food, shelter, and clothing that are in excess of the normal expenses of the individual and that are necessitated by the individual's participation in an assessment for determining eligibility and vocational rehabilitation needs or that are incurred while an individual receives services under an Individualized Plan for Employment (IPE). Rehabilitation Technology: The systematic application of technologies, engineering methodologies, or scientific principles to meet the needs of, and address the barriers confronted by, individuals with disabilities in areas that include education, rehabilitation, employment, transportation, independent living, and recreation; includes rehabilitation engineering services, assistive technology devices, and assistive technology services. Personal Assistance Services Reader Services: Services for individuals who cannot read print because of blindness or other disability. Reader services include, in addition to reading aloud, transcription of printed information into Braille or sound recordings if the individual requests such transcription. Reader services are generally for individuals who are blind or deaf-blind, but may also include individuals unable to read because of serious neurological disorders, specific learning disabilities, or other physical or mental impairments. 187 Interpreter Services: Sign language or oral interpretation services for individuals who are deaf or hard of hearing and tactile interpretation services for individuals who are deaf—blind. Specially trained individuals perform sign language or oral interpretation. Also include here real-time captioning services for persons who are deaf or hard of hearing. Do not include language interpretation in this category, but in "other services". Personal Attendant Services: Includes services that an attendant performs for an individual with a disability such as bathing, feeding, dressing, providing mobility and transportation, etc. Technical Assistance Services: Includes technical assistance and other consultation services provided to conduct market analyses, to develop business plans, and to provide resources to individuals in the pursuit of self-employment, telecommuting and small business operation outcomes. Information and Referral Services: Services provided to individuals who need assistance from other agencies (through cooperative agreements) not available through the VR program. Other Services: All other VR services that cannot be recorded elsewhere; included here are occupational licenses, tools and equipment, initial stocks and supplies, and medical care for acute conditions arising during rehabilitation and constituting a barrier to the achievement of an employment outcome. 188 REFERENCES Aday, L. (1993). 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