Equitable Treatment in the Rehabilitation Process: Implications for Future Investigations Related to Ethnicity.

Section 21 of the 1992 Rehabilitation Act Amendments summarized much of the research related to diversity issues and state vocational rehabilitation agencies. It stated:

   Patterns of inequitable treatment of minorities have been documented in all
   major junctures of the vocational rehabilitation process. As compared to
   white Americans, a larger percentage of African-American applicants to the
   vocational rehabilitation system is denied acceptance. Of applicants
   accepted for service, a larger percentage of African American cases is
   closed without being rehabilitated. Minorities are provided less training
   than their white counterparts. Consistently, less money is spent on
   minorities than their white counterparts. Section 21 (a)(3)

The body of literature contributing to and resulting from Section 21 is extensive (e.g., Atkins & Wright, 1980 Alston & Mngadi, 1992; Crystal & Alston, 1991; Daneck & Lawrence, 1982; Dziekan & Okacha, 1993; Feist-Price, 1995; Galea'i, 1994; Griffin, 1994; Herbert & Martinez, 1992; James, DeVivo, & Richards, 1993; Leal, Leung, Martin & Harrison, 1988; Leung, 1993a, b; McConnell, 1993; National Council on Disability, 1993; Riggar, Eckert, & Crimando, 1993; Royall & Corthell, 1981; Watson, 1988; Wheaton, 1995; Wheaton, Finch, Wilson, & Granello, 1997; Wheaton, Wilson, & Brown, 1996; Wright, 1988).

Of the empirical studies that have been conducted, the seminal study (Atkins & Wright, 1980) included the 10 Rehabilitation Services Administration Regions. However, subsequent investigations have focused on the state level. For example, state agency investigations have included a northeastern state (Herbert & Martinez, 1992), a southeastern state (Feist-Price, 1995), a midwestern state (Dziekan & Okocha, 1993), and a large, industrial midwestern state (Wheaton, 1995; Wheaton et al., 1996; Wheaton et al., 1997).

Similarly, the interventions that have been recommended to ensure equitable treatment and a diverse workforce have been relatively broad-based. In addition to management strategies (Riggar, et al., 1993), role specific behaviors have been recommended for (a) rehabilitation administrators (Griffin, 1994), (b) rehabilitation counselors (Rubin, Pusch, Fogarty, & McGinn, 1995), and (c) pre-service education (Alston, 1996; Leal-Idrogo, 1997).

From an intervention viewpoint, it is helpful to know whether the patterns of difference exist throughout a state or only in selected areas. Moreover, despite the extensive body of literature related to ethnicity and rehabilitation service delivery, there is a paucity of information concerning within-state differences and actions that have been taken by states to address identified inequities. Therefore, the purpose of the present study was to extend the investigation to within-state differences related to rehabilitation rates and expenditures for African Americans in a large southeastern state vocational rehabilitation agency.

Method

Data Collection

This study, which used an ex post facto design, was based on RSA 911 closure data for the 14,182 individuals whose cases were closed in FY 1996 (October 1996 - September 1997) in a southeastern state. Because the focus of the investigation was on European Americans and African Americans, individuals who were Asian (n = 76, 5%) or Native American (n = 76, 5%) were not included in the data analyses. Therefore, of the 14,030 cases that were analyzed, 3102 (22%) were African American individuals and 10,928 (78%) were European American individuals. Based on 1990 census data, the percentage of African Americans was greater than that which actually existed in the state (i.e., 14%). The increased percentage of African Americans included in the data set may reflect the increased levels of disability among individuals from minority groups. For example, the rate of blindness among African Americans is higher than that of European individuals (Prevent Blindness America, 1994). Also, the percentages of men (53% European American and 52% African American) and women (47% European American and 48% African American) were similar for both races.

Data Analysis

The independent variable (i.e., racial-ethnic status) was categorized into two groups: African Americans and European Americans. The dependent variables were closure status, expenses, similar benefits, district, and county. Descriptive statistics (e.g., mean, range, standard deviations), Analyses of Variance (ANOVA), and Analysis of Covariance (ANCOVA) were used to analyze the data. Because of the large size of the data set (n = 14,030), a significance level of .01 was used.

Results

Statewide Analyses

One-way ANOVAs were used to investigate expenditures (vocational rehabilitation agency case service dollars that are spent in the rehabilitation process), closure status (closed rehabilitated vs. not rehabilitated), and similar benefits (non-vocational rehabilitation agency monies that are used to provide rehabilitation services) by racial-ethnic status. The difference in expenditures for European Americans and African Americans was significant, F(1, 14028) = 69.42, p [is less than] .01. The mean for African American expenditures was $2095.51 (sd = 2121.74, range 09992), whereas the mean for expenditures for European American individuals was $2478.60 (sd = 2297.89, range 0-9974). Although the mean dollar amount for similar benefits was greater for European Americans ($1999.48) than African Americans ($1717.77), this difference was not statistically significant, F(1, 14028) = 3.34, p [is greater than] .01.

The difference in closure status of European Americans and African Americans was also significant, F(1, 14026) = 31.02, p [is less than] .01. The rehabilitation rate (i.e., number of individuals closed as successfully rehabilitated divided by the total number of case closures) for European Americans individuals was 60.3%, compared with 54.7% for African Americans.

Analyses of Covariance (ANCOVAs) were used to investigate expenditures and closure status by race, severity of disability, and district with educational level as a covariate. In relationship to expenses, significant interactions were noted between: (a) closure status and severity of disability; (b) closure status and district; and (c) severity of disability and district. In relationship to closure status, significant interactions were noted between: (a) race and district, and (b) severity of disability and district. (See Tables 1 and 2).

Table 1 Expenses by Race, District, Severity of Disability, and Closure Status with Education as a Covariant 

                          Sum of
Source of Variation       Squares      DF

Covariates                   874567       1
  ED_LEVEL                   874567       1

Main Effects             1484879254      10
  RACE                     37796333       1
  REHAB                  1025659815       1
  SEVERE                   99221617       1
  DISTRICT                414941356       7

2-Way Interactions        348078413      24
  RACE       REHAB          2423758       1
  RACE       SEVERE        11186379       1
  RACE       DISTRICT      67513549       7

  REHAB      SEVERE        31764483       1
  REHAB      DISTRICT     123827130       7
  SEVERE     DISTRICT     117835417       7

Explained                5398466614      35
Residual                58885162087   12776
Total                   64283628701   12811

Covariate Raw Regression
Coefficient ED_LEVEL

                             Mean                  Sig
Source of Variation         Square          F      of F

Covariates                  874566.982      .190   .663
  ED_LEVEL                  874566.982      .190   .663

Main Effects             148487925.380    32.217   .000
  RACE                    37796332.888     8.200   .004
  REHAB                 1025659815.16    222.532   .000
  SEVERE                  99221616.803    21.528   .000
  DISTRICT                59277336.513    12.861   .000

2-Way Interactions        14503267.193     3.147   .000
  RACE       REHAB         2423758.292      .526   .468
  RACE       SEVERE       11186379.383     2.427   .119
  RACE       DISTRICT      9644792.730     2.093   .041

  REHAB      SEVERE       31764482.588     6.892   .009
  REHAB      DISTRICT     17689590.061     3.838   .000
  SEVERE     DISTRICT     16833630.943     3.652   .001

Explained                154241903.260    33.465   .000
Residual                   4609045.248
Total                      5017846.281

Covariate Raw Regression
Coefficient ED_LEVEL             3.542

14030 cases were processed. 1218 cases (8.7 pct) were missing.

Table 2 Closure Status by Race, District, and Severity of Disability with Education as a Covariant

                           Sum of             Mean
Source of Variation        Squares      DF   Square

Covariates                  13.134       1   13.134
  ED_LEVEL                  13.134       1   13.134

Main Effects                53.628       9    5.959
  RACE                       2.204       1    2.204
  SEVERE                    21.642       1   21.642
  DISTRICT                  12.202       7    1.743

2-Way Interactions          12.293      15     .820
  RACE SEVERE                 .412       1     .412
  RACE DISTRICT              5.244       7     .749
  SEVERE DISTRICT            6.574       7     .939

Explained                  110.415      25    4.417
Residual                  2985.191   12786     .233
Total                     3095.606   12811     .242
Covariate Raw Regression                      -.014
  Coefficient ED_LEVEL

                                    Sig
Source of Variation          F      of F

Covariates                 56.255   .000
  ED_LEVEL                 56.255   .000

Main Effects               25.522   .000
  RACE                      9.439   .002
  SEVERE                   92.694   .000
  DISTRICT                  7.466   .000

2-Way Interactions          3.510   .000
  RACE SEVERE               1.765   .184
  RACE DISTRICT             3.209   .002
  SEVERE DISTRICT           4.023   .000

Explained                  18.917   .000
Residual
Total
Covariate Raw Regression
  Coefficient ED_LEVEL

14030 cases were processed. 1218 cases (8.7 pct) were missing.

District Comparisons

One-way ANOVAs were used to investigate expenditures, closure status, similar benefits, and total cost (expenditures plus similar benefits) by racial-ethnic status in each of the eight DVR districts. Significant differences in expenditures were found between European Americans and African Americans whose cases were closed in District 1: F (1, 1580) = 34.3942, p [is less than] .01; District 3: F (1, 2039) = 9.5998, p [is less than] .01; and District 8: F (1, 2442) = 19.6134, p [is less than] .01, with more money expended on European Americans. When similar benefits were added to expenditures (total cost), the differences in these districts were no longer significant; however, the differences in another district (District 5) were significant, F(1, 2034) = 7.7787, p [is less than] .01.

Significant differences in closure status were found between European Americans and African Americans in District 7: F (1, 933) = 7.1636, p [is less than] .01 and District 8: F (1, 2442) = 39.2751, p [is less than] .01 with significantly more European American cases closed as rehabilitated.

County Comparisons

One-way ANOVAs were used to investigate expenses and closure status by race in the eleven counties (16%) that closed 50 or more African American cases. Because statistical analyses were not appropriate in those counties that closed fewer than 50 African-American cases, most counties (n = 56 - 84%) were eliminated from these analyses. Significant differences in expenditures between European Americans and African Americans were found in three (27%) of the eleven counties that were analyzed, with more money spent on European Americans: District 1, County A: F (1,888) = 10.2143, p [is less than] .01; District 3, County B: F (1, 776) = 7.3005, p [is less than] .01; and District 8, County C: F (1, 2296) =18.6597, p [is less than] .01. A significant difference in the closure status of European Americans and African Americans occurred in one (1) of the eleven counties: District 8, County C: F(1, 2296) = 35.0018, p [is less than] .01, with more European Americans than African Americans closed as rehabilitated.

Because (a) a majority of the counties were eliminated in the statistical analyses and (b) the closure rates do not take into consideration the demographic characteristics of each of the counties, 1990 census data was used to provide another comparison between European American and African American closures. For example, if 30% of the closures were African American in a county with a racial composition of 50% European Americans individuals and 50% African American individuals, the 30% closure would appear to be lower than anticipated. In contrast, in a county that had 30% African Americans and 70% European Americans individuals, the 30% closure statistic would be consistent with that of county demographics. A ten percent (10%) difference between the percentage of African American individuals reflected in the census data and the closure data was arbitrarily selected as a difference that would warrant additional investigation.

The differences in percentages ranged from -24 to +31, with negative differences indicating the percentage that was lower than the census data. Conversely, a positive difference indicates that more African Americans were represented in the closure data than in the county census data. In Districts 4, 6, and 8, none of the percentages was larger than - 10% (The percentages ranged from + 10 to -1 in District 4, +8 to +14 in District 6, and +19 to -3 in District 8). Those counties with percentage differences greater than -10% were as follows: (a) District 1: County A (-19%), County B (-18%), and County C (-11%); (b) District 2: County D (-14.5%), County E (-19%), and County F (-24%); (c) District 3: County G (-15%); (d) District 5: County H (-11%); and (e) District 7: County I (-14%), County J (-19%)

Discussion

Although significant differences between European Americans and African Americans in terms of expenditures and cases closed as rehabilitated were found on a state-wide basis, statistically significant differences did not exist in all districts. This appears to be an important finding in terms of broadening the types of short-term and long-range interventions that are initiated to counter the identified inequities. For example, in addition to on-going state-wide initiatives, three steps were taken after the data was analyzed. First an individual district analysis was distributed to each district administrator. This was followed by a meeting with the district administrators to discuss the data and answer questions related to the analyses. Lastly, each district was required to develop an "Action Plan" to correct disparities where they existed.

Such an approach compliments existing state-wide initiatives and also allows states to address rural and urban differences. For example, addressing inequities in a county with a population of 2,808,094 would be different than addressing inequities in a county with a total population of 7591. Although it is too early to evaluate the results of the action plans, the plans include a number of elements such as (a) identifying an African American liaison :in outlying counties, (b) increasing the networking with African American churches and other referral sources in outlying counties, (c) adding a rehabilitation technician as a support position to provide additional outreach, (d) providing district-level inservice training on diversity, (e) tracking staffing and hiring patterns within districts and units within the districts, and (f) in very limited circumstances, transferring caseloads among counselors.

Providing the information based on district and county statistics also allowed (a) district directors to examine unit-specific spending patterns to further identify disparate patterns and (b) unit supervisors to hold individual meetings with counselors and help them develop their own action plans, where it appeared that financial or access inequities were due to individual counselors. In another instance, one counselor asked to review her data, because she suspected some errors in coding the data. Additional statewide initiatives have also been planned as a result of this investigation. For example, an increased focus on diversity and indicators of equal access to service has been added to the agency's New Counselor Orientation Program.

A number of limitations related to this investigation need to be acknowledged. For example, the 1990 census data is nearly 10 years old and the use of a 10% difference between census and closure percentages was selected arbitrarily. Moreover, the difference between census and closure percentages does not address the issue of higher disability rates among minorities. Another limitation relates to the manner in which the data was coded. For example, the coding system was based on RSA's system, which includes individuals who are European American, African American, Asian, and Native American, but does not include Hispanic American individuals. Given the racial composition in one of the largest districts, it was evident that the differences found in this district were more likely differences between the large Hispanic American population and African Americans. Additional investigations within this district are already in progress. Another limitation is that this investigation focused on expenditures (both costs and similar benefits), but did not focus on number and types of services. Future research should be able to address many of these limitations, since new census data will soon be available and RSA will be coding Hispanic American individuals.

This investigation highlights the need for additional research into within-state differences as well as research into the results of intervention strategies that are being utilized in various state vocational rehabilitation agencies. Another area that warrants additional investigation is combining similar benefits and expenditures, since it significantly changed the data in some districts. Because inequitable treatment within the state vocational rehabilitation agencies is contrary to the philosophical foundations of rehabilitation, there is no doubt that the empirical research related to diversity will exponentially increase as agencies strive for a diverse workforce, which provides equitable treatment to all individuals with disabilities.

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Jeanne Boland Patterson University of North Florida

Tamara Bibb Allen Linda Parnell Robert Crawford Roxana Lizzraga Beardall Florida Division of Vocational Rehabilitation

Jeanne Boland Paterson, Ed.D., CRC, University of North Florida, 4567 St. John's Bluff Road. S., Jacksonville, FL 32224-2645. Email: [e-mail].