Abstract
BACKGROUND:
The State-Federal Vocational Rehabilitation (VR) Program provides rehabilitation services to people with disabilities with the intention of assisting them in securing competitive employment. The VR services offer substantial resources to help individuals who are hard-of-hearing to enhance their quality of life and employment opportunities.
OBJECTIVE:
The current study investigated the impact of demographic variables and the use of VR services on employment outcomes among hard-of-hearing consumers. Specific VR services that lead to successful employment among hard-of-hearing consumers were thoroughly examined.
METHODS:
Binary logistic regression, Chi-square, and Chi-square Automatic Interaction Detector analyses were used to analyze the data extracted from the 2014 fiscal year US. Department of Education Rehabilitation Service Administration Case Service Report (RSA-911).
RESULTS:
Logistic regression reveals that VR services such as diagnosis and treatment of impairments (p-value 0.000), counseling, and guidance (p-value 0.000), and rehabilitation technology (p-value 0.000) were influential factors in determining the successful employment outcome among the consumers. The relative importance of the factors based on the mean decrease in accuracy in CHAID identifies rehabilitation technology (0.264), diagnosis and treatment of impairments (0.090), job placement assistance (0.016), transportation (0.016), and secondary disability (0.010) to be among the most contributing factors.
CONCLUSION:
Overall, rehabilitation technology services were especially beneficial, particularly for minority consumers, in achieving a successful employment outcome.
Introduction
Recent data from the National Center for Health Statistics (2015) indicates approximately 37.2 million Americans live with hearing loss or a reduced ability to hear sounds. According to the Committee on Accessible and Affordable Hearing Health Care for Adults (2016), hearing loss may develop at any point during the life course, with variable onset due to numerous causes (e.g., trauma, infection, genetic syndromes, aging, or excessive noise exposure), thus no general or overall profile of the typical person with hearing loss exists, but all causes and circumstances of onset potentially result in significant adaptive concerns. For example, occupational stressors, poorer self-rated health, long-term illness, and symptoms of long-lasting stress are significantly associated with hearing problems and communication difficulties (Hasson et al., 2011; Stika & Trybus, 2002).
Much of the literature concerning people with hearing loss focus on severely to profoundly deaf individuals and members of the Deaf 1 community (Bat-Chava et al., 2002), who hear little to no environmental sounds, use manual languages such as American Sign Language and have become relevant as a distinct linguistic minority group (Nakaji, 2014). Many Deaf individuals receive counseling and employment support services through the State-Federal VR Program under the Department of Education Rehabilitation Services Administration (Dowden et al., 2016; Patterson et al., 2005).
Although it would seem intuitively true that individuals with severe to profound deafness have the most difficulty with employment, research suggests that in some instances, people who have less severe hearing loss and are hard-of-hearing face more significant employment restrictions and more limited employment opportunities (Bowe et al., 2005; Luft et al., 2009; Punch, 2016). As a result, unemployment and underemployment for people who are hard-of-hearing have seemed difficult to overcome (Danermark, 2005; Punch, 2016; Punch et al., 2004). Despite these long-standing trends, some research has demonstrated that individuals who are hard-of-hearing can benefit from the State-Federal VR Program to enhance their quality of life and increase their employment opportunities (Huang et al., 2016).
Employment issues for individuals who are hard-of-hearing
Housed within the Department of Education, the Rehabilitation Services Administration (RSA) is the primary agency for implementing VR services, employment opportunities, and maintains the case service report dataset (RSA-911), which includes information regarding demographic characteristics, type of disability, services provided, and case outcomes (Dowden et al., 2016). Through the State-Federal VR Program, individuals who are hard-of-hearing may develop self-advocacy, obtain information and referral services to community resources, and receive much other employment and independent living services.
VR service categories are broad, and few services are unique to individuals who are hard-of-hearing, though the specific way in which they are provided, or the specific devices provided may differ. For example, job placement services may be provided to consumers with many different disabilities, but for those with hearing loss, placement may focus on work with limited public interaction. Similarly, a consumer with a learning disability may obtain a screen reader as rehabilitation technology, while a consumer who is hard-of-hearing may be provided hearing aids instead. Nonetheless, previous studies have found that individuals with hearing loss are less likely to recognize the need for assistance from VR professionals than members of other diagnostic groups (Bradley et al., 2013; Glass & Elliott, 1993; Jennings & Shaw, 2008; Hayward & Schmidt-Davis, 2003).
In addition, there exist complicating factors among individuals who are hard-of-hearing related to the intersection of gender, race and ethnicity, age, level of education, and those with a secondary disability. The intersectionality of these factors, along with a more general ableist frame of reference (Bitman & John, 2019; Ruiz-Williams et al., 2015), may create interdependent and recursive systems of disadvantage for hard-of-hearing individuals.
Primarily, racial and ethnic differences among White, Black or African American, and Hispanic and Latino populations who are hard-of-hearing are common and long-standing (Wilson, 1999; Wilson & Senices, 2005; Wilson et al., 1999, 2001). Another study by Moore (2001) found that Hispanic and Latino consumers who are hard-of-hearing experienced a lower rate of success in closures in VR service programs than non-Latinos with similar hearing loss. More recently, Smith and Samar (2016) investigated “hearing earnings gaps”, defined as wage and overall earning differences between workers with and without hearing loss, and found that hard-of-hearing individuals from racial and ethnic minority groups earn significantly less than their White counterparts. Additional intersectional factors, including age, level of education, gender, and secondary diagnoses also affect hard-of-hearing individuals’ employment and service outcomes.
Some early studies found that younger people who are hard-of-hearing had less chance of successful employment than older individuals who are hard-of-hearing (Lafitte, 1978; Parving & Christensen, 1993), while more recent research has found that an early onset of hearing loss is related to employment difficulties later (Perkins-Dock et al., 2015). Hogan and colleagues (2009) also found that being hard-of-hearing may reduce workforce participation for middle and older age groups, suggesting that access to VR services among the different age groups of individuals who are hard-of-hearing plays a role in employment outcomes.
As an employment-related factor, age tends to relate to educational status, in that younger individuals may simply not have acquired as much education earlier in life. Regarding the level of education, hard-of-hearing individuals tend to have attained lower levels of education than their hearing counterparts (Hogan et al., 2009; Woodcock & Pole, 2008). Boutin (2010) further indicated most consumers who are hard-of-hearing with higher levels of education were nonetheless underemployed, suggesting that employee training and preparedness alone do not fully capture the barriers to employment faced by people who are hard-of-hearing.
Regarding gender, previous studies demonstrate slightly more women with hearing loss received services, despite the fact that men are more likely to be hard-of-hearing (Boutin & Wilson, 2009; Cruickshanks et al., 2015; Nakaji, 2014). More recently, Smith and Samar (2016) found that women with hearing loss earn significantly less than their hearing counterparts, and also significantly less than both hearing and hard-of-hearing men, although these researchers note that gender-based factors regarding self-selection into the labor market may exist.
The existence of a secondary disability also plays a role in VR outcomes for people who are hard-of-hearing, though few studies have investigated the experiences of hard-of-hearing individuals only (Dammeyer & Chapman, 2017; Nakaji, 2014). Nonetheless, one previous study by Hogan et al. (2009) found when the primary condition was a hearing loss, 66.2%of these individuals were employed full-time, but when the prime condition was not a hearing loss, only 46.4%were employed full-time. Further research suggests that individuals who are hard-of-hearing are diagnosed with more physical and mental disorders than the general population, and that these secondary diagnoses may further impede employment and VR outcomes (Fordyce & Riddell, 2015; Moore et al., 2002).
While some research exists about the various factors that affect VR services and outcomes for people who are hard-of-hearing, the intersectionality of these factors merits additional investigation. The purpose of the present study was to analyze the RSA-911 data to explore relationships between demographic variables (gender, race and ethnicity, age, level of education, and secondary disability), VR services, and employment outcome variables among individuals who are hard-of-hearing. This study also explored which VR services most significantly contributed to employment outcomes for individuals who are hard-of-hearing.
Materials and methods
To investigate further, the following research questions were developed:
What is the relationship between demographic variables, VR services, and employment outcome variables among individuals who are hard-of-hearing when demographic variables include gender, race and ethnicity, age, level of education, and secondary disability? What VR services contribute to employment outcomes for individuals who are hard-of-hearing?
Predictor variables and participants
Using data from the RSA-911 FY 2014 service report, this study included 24,983 consumers who were hard-of-hearing, including individuals with both successful and unsuccessful employment outcomes. Predictor variables of this study were demographic factors: gender, race and ethnicity, level of education, age, secondary disability, and various VR services received by the consumers. Appendix A presents a detailed description of all vocational rehabilitation services considered in this study. The study population consisted of 50.2%females, with 76.7 %Non-Hispanic White. Most consumers, 45.1%, were ages 25–54, and 47.8%had no formal schooling or had a high school diploma/GED. Over seventy percent (72.9%), did not have a secondary disability. Table 1 presents the details of the demographic information and the subcategories into which each predictor variable was grouped.
Summary of the Study Population
Summary of the Study Population
The response variable for this study was VR employment outcome —successful or unsuccessful. According to the RSA-911 Reporting Manual (Rehabilitation Services Administration, 2013), a “successful rehabilitation” outcome occurs after VR consumers have been accepted for services, developed and signed a written Individualized Plan for Employment, and obtained and maintained employment for a minimum of 90 days, and an “unsuccessful rehabilitation” outcome occurs after a consumer has been accepted for and provided with VR services, but did not obtain or maintaining employment for at least 90 days.
Statistical methods
A Chi-square Automatic Interaction Detection (CHAID; Kass, 1980) analysis was used to find the most influential demographic variables and the VR services contributing to a successful employment outcome among the consumers who are hard-of-hearing. CHAID is a decision tree that identifies relationships between a set of predictor variables and the response variable, so it is particularly useful in studies that seek to explore intersectional relationships. It gradually builds a predictive decision tree model using a chi-square test to illustrate the relationship between the response and the predictor variables. The process repeats to find the predictor variable on each leaf by significance, branch by branch, until no further factors are found to have a statistically significant effect on the response (Milanović & Stamenković, 2016). It calculates all possible cross-tabulations for each categorical predictor up until the best outcome is achieved, and no further splitting that can be performed. Each pair of predictor categories are evaluated to establish what is least significantly different with respect to the response variable. A Bonferroni adjusted p-value is calculated for the merged cross-tabulation due to applying these steps of merging (Statistics Solutions, 2019).
Next, a binary logistic regression model was developed to quantify the effect and to identify the impact of each factor towards the successful employment outcome along with their corresponding odds ratios by controlling for other factors. The odds ratio determines the likelihood of a successful employment outcome for individuals with specific consumer characteristics and vocational rehabilitation services compared to those who did not exhibit those consumer characteristics. A stepwise model selection method was followed based on the Akaike information criterion (Akaike, 1973), in developing the binary logistic regression model.
Results
Univariate and CHAID analyses
Univariate analysis with Chi-square tests revealed that there exist significant associations between the response and all predictor variables except the gender (p-value 0.084). The first split of the final CHAID model, hence the most significant predictor variable, was the utilization of vocational rehabilitation services. In fact, VR services such as diagnosis and treatment of impairments, counseling, and guidance, and rehabilitation technology (Chi-square test p-value was 0.000) were among the most influential factors in determining the successful employment outcome for the study population. In Table 2, among demographic variables, level of education attained at closure, age at application, and secondary disability were the most significant variables in predicting a successful employment outcome. The most significant intersections found through the final CHAID model are summarized in Table 2.
CHAID Interactions
CHAID Interactions
Note: The code significance for each variable were: gender: male = male and female = female, race and ethnicity: Non-Hispanic White = 1, Non-Hispanic Black = 2, Hispanic = 3, and Other = 4, age at application: 14–24 = 1, 25–54 = 2, 55+ = 3, level of education attained at closure: no formal schooling or had a high school diploma/GED = 1, vocational/technical certificate or license = 2, post-secondary education to occupational credential beyond undergraduate degree work = 3, and master’s degree to occupational credential beyond graduate degree work = 4, secondary disability: mental = 1, physical = 2, other = 3, and none = 4, VR services: not received = 0, received = 1, and missing = 2, and employment outcome: not successful = 0, successful = 1, and missing = 2.
Additionally, we scored the relative importance of the explanatory variable in the CHAID based on the mean decrease inaccuracy. The variables were ranked as follows: (a.) rehabilitation technology (0.264), (b.) diagnosis and treatment of impairments (0.090), (c.) job placement assistance (0.016), (d.) transportation (0.016), (e.) secondary disability (0.010), (f.) age at application (0.010), (g.) maintenance (0.006), (h.) other services (0.005), (i.) job search assistance (0.003), (j.) race and ethnicity (0.001), (k.) vocational rehabilitation counseling and guidance (0.001), (l.) level of education attained at closure (0.001), (m.) interpreter services (<0.001), and (n.) information and referral services (<0.001). The CHAID model was also used to make a prediction for a new testing dataset. It resulted in an 81%accuracy, 57%sensitivity, and 92%specificity. This means that out of consumers who are hard-of-hearing, 81%who had a successful employment outcome were correctly identified by the CHAID model. Moreover, out of hard-of-hearing consumers who had a successful employment outcome, 57%of them were correctly identified by the CHAID model, and out of these consumers who did not have a successful employment outcome, 92%of them were correctly identified by the CHAID model.
The effect from each individual explanatory variable was first identified and removed from the model before including any interaction effects. Several variables (apprenticeship training, basic academic remedial or literacy training, disability-related skills training, on-the-job supports-short term) showed high standard errors, and this was a clear indication of the multicollinearity effect. As progression was made by removing non-significant variables in each step, that issue was resolved, so the final model does not demonstrate multicollinearity. Several goodness of fit tests were used, including the Omnibus and the likelihood ratio tests for model validation. The final model had a Cox & Snell R2 (31%) and Nagelkerke R2 (43%), which demonstrates adequate predictive power. The final logistic regression model resulted in an accuracy of 82%, a sensitivity of 88%, and a specificity of 67%. The area under the ROC curve was 0.85, which is another indication of good discriminatory power.
In the final model, significant main effects were identified based on the likelihood ratio test. These include level of education attained at closure (p-value 0.0000), secondary disability (p-value 0.0000), assessment (p-value 2.2e-16), diagnosis and treatment of impairments (p-value 0.0000), vocational rehabilitation counseling and guidance (p-value 0.0000), information and referral services (p-value 0.0005), junior or community college training (p-value 0.0793), job readiness training (p-value 0.0010), job search assistance (p-value 0.0000), job placement assistance (p-value 0.0000), transportation (p-value 3.293e-07), maintenance (p-value 1.393e-05), rehabilitation technology (p-value 0.0000), other services (p-value 2.898e-07), miscellaneous training (p-value 0.003468), on-the-job supports-supported employment (p-value 2.2e-16), benefits counseling (p-value 0.0298), interpreter services (p-value 0.0166), race and ethnicity (p-value 0.0000), and age at application (p-value 0.0000).
Based on the likelihood ratio test (LRT), several interactions were found significant. The interaction of the level of education attained at closure and rehabilitation technology stood out as one of the most meaningful interactions. Results were: secondary disability and diagnosis and treatment of impairments (p-value 4.68e-7), secondary disability and job placement assistance (p-value 0.0006), secondary disability and age at application (p-value 1.366e-05), level of education attained at closure and vocational rehabilitation counseling and guidance (p-value 4.438e-06), level of education attained at closure and rehabilitation technology (p-value 0.0006), level of education attained at closure and age at application (p-value 2.2e-16), diagnosis and treatment of impairments and age at application (p-value 0.0294), job search assistance and age at application (p-value 6.03e-12), job placement assistance and age at application (p-value 0.0004), rehabilitation technology and age at application (p-value 1.357e-07), and rehabilitation technology and race and ethnicity (p-value 0.0018).
An odds ratio, or exp β, was calculated for each of the predictor variables in the model, with more significant numbers (positive or negative) indicating a higher likelihood of a particular outcome (successful or unsuccessful employment outcome) when specific services were present (Pallant, 2010). Thus, an odds ratio greater than one indicates a higher likelihood of successful employment outcome, while an odds ratio less than one indicates a decreased likelihood of attaining successful employment, while an odds ratio equal to one would indicate that individuals are equally likely to be in one of the two groups (i.e., employed or not employed). The Estimated Odds Ratio and 95%Confidence Intervals with lower and upper limits are shown by the service variable in Table 3.
Estimated Odds Ratio and 95%Confidence Intervals
Estimated Odds Ratio and 95%Confidence Intervals
Note: The reference (base) levels for each explanatory variable were: gender = “male”, race and ethnicity = “Non-Hispanic White”, age at application=“14–24”, level of education attained at closure = “no formal schooling or had a high school diploma/GED”, secondary disability = “none”, and all VR services = “did not receive VR service”.
A variety of intersectional factors exist that may result in relative advantages and disadvantages in the experience and outcomes of hard-of-hearing consumers who are seeking employment-related VR services. In this study, 69.7%of hard-of-hearing consumers reached a successful employment outcome. The demographic variables most significantly related to a successful employment outcome were race and ethnicity, age, secondary disability, and level of education. Gender was found not to be statistically significant. The VR services that contributed most significantly to successful employment outcomes included assessment, diagnosis, and treatment of impairments, rehabilitation technology, vocational rehabilitation counseling and guidance, information and referral services, job placement assistance, job search assistance, transportation, maintenance, and other services. These results are generally consistent with prior research (Albertini et al., 2011; Atkins & Wright, 1980; Boutin, 2009, 2010; Boutin & Wilson, 2009; Bradley et al., 2013; Capella, 2003; Cruickshanks et al. 2015; Dalton, 2007; Hyde et al. 2016; Millner & Kim, 2017; Moore, 2001; Punch, 2016; Sevak et al. 2015; Walter & Dirmeyer, 2013; Wilson et al. 1999).
Interactions of demographic and VR service variables
In this study, gender, race and ethnicity, age, secondary disability, and level of education were found to result in interdependent patterns of service utilization among the hard-of-hearing individuals in the dataset. For clarity, these interactions are described here in the context of the most significant demographic variables. Some meaningful interactions, more specifically related to the type of service provided than to demographics, also follow.
Race and ethnicity-related interactions
Non-Hispanic Whites (76.7%) comprised the largest group of hard-of-hearing consumers served, followed by Non-Hispanic Black consumers who are hard-of-hearing (10.4%), Hispanic consumers who are hard-of-hearing (9.5%), and American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, or Multiracial individuals made up the least amount of consumers (3.5%). These results are validated earlier research (i.e. Boutin, 2010; Bradley et al., 2013; Choi et al., 2018; Cruickshanks et al., 2015) indicating that Non-Hispanic hard-of-hearing Whites are the most served group in the VR program, despite overall national demographic trends.
For technology-related VR services, Non-Hispanic White consumers received rehabilitation technology at a higher rate (57.0%) than all other groups. This finding was somewhat expected, given that recent research indicated this group uses hearing aids and hearing-related assistive technologies at a higher rate than any other group (Bainbridge & Ramachandran, 2014). However, Hispanic consumers’ results for the provision of rehabilitation technology (55.9%) were closer to the majority group than expected, somewhat contradicting previous studies specifying consumers from this group were less likely to receive assistive technology (Huang et al., 2016).
In other areas of service provision, the results related to race and ethnicity were somewhat surprising, particularly in relation to previous research. Hispanic consumers in this study received assessment (76%), diagnosis and treatment of impairments (63.5%), VR counseling and guidance (62.6%), and information and referral services (29.4%) at higher rates than all other groups. Conversely, consumers categorized as hard-of-hearing and American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, or Multiracial utilized assessment (56.2%), diagnosis and treatment of impairments (38.2%), and rehabilitation technology (42.5%) at slightly lower rates than all other groups. These findings further validate previous research that indicated patterns of under service to these groups (Choi et al. 2018; Gellert et al., 2017).
Age-related interactions
Most consumers in this study were from the typical working-age group, 25–54, (45.1%) followed by older consumers 55 years old or older (42.5%), with 14 to 24-year-old age (transition) consumers comprising the smallest group at 12.4%. This breakdown was similar to prior research results, such as Dalton (2007), who found 42%consumers who were Deaf or hard-of-hearing between ages 35–54 were the most served VR consumer group, followed by 33%of consumers between ages 16-34 and 16%and 9%of consumers between ages 55–64 and 65 years or older, respectively. Across all age groups, the most utilized VR services were assessment, diagnosis and treatment of impairments, vocational rehabilitation counseling and guidance, rehabilitation technology, and information and referral services; however, the effect of these services on employment outcomes was not uniform.
Nevertheless, regardless of age group, if a consumer received either short-term on-the-job supports, such as job coaching, on the job training, or on the job support through supported employment, the odds of achieving a successful employment outcome were 5.58 and 6.39 times greater, respectively, when compared to consumers who did not receive those particular VR services. This effect is likely due to the nature of this particular set VR services, which may be provided for as long as 18 months, and are specifically provided to stabilize the employment placement and enhance job retention consistent with the employment goal on the individualized plan for employment.
Assessment, diagnostic, and treatment services were the most frequently utilized VR services for the age group 25–54 and 55 + . Sixty-one percent of consumers between the ages of 25–54 and 57.9 %of consumers 55 years old and older received an assessment, 61.9%, and 57.9%, respectively, and diagnosis and treatment of impairments, 54.2%, and 52.8%, respectively. However, one of the remarkable interactions observed was that regardless of age or education at closure, consumers who only received diagnosis and treatment as a VR service still achieved a successful employment outcome. Regarding consumers in the transition age group (between ages 14–24), who are hard-of-hearing were provided diagnosis and treatment of impairments, then this predicted they would become successfully employed. Similarly, if these individuals received rehabilitation technology, it was anticipated they would achieve a successful employment outcome as well.
Consumers of any race and ethnicity who were between ages 25–54 or 55 + who received a combination of diagnosis and treatment of impairments, vocational rehabilitation counseling and guidance, and rehabilitation technology as VR services were also successfully employed, suggesting that increasing the number of services provided has an additive effect. However, for consumers ages 25–54 or 55+, no additional differences were found related to race and ethnicity when the only VR services received were diagnosis and treatment of impairments, vocational rehabilitation counseling and guidance, information and referral services, and rehabilitation technology.
Finally, there were significant differences among transition-age consumers, ages 14–24, as these consumers utilized VR services at lower rates than consumers from older age groups. For example, only 30.4%of consumers who are hard-of-hearing between the ages of 14–24 received rehabilitation technology, suggesting that in this critical area, younger consumers are underserved. That poses concern since prior research indicates that earlier onset of hearing loss is related to employment difficulties later in life (Hogan et al., 2009; Kent & Smith, 2006). Further, potential issues with the hearing aid and assistive technology use among younger consumers could be addressed through counseling and guidance, but that particular VR service was utilized less by this age group (49.8%) than any other group.
Secondary disability interactions
Nearly three-quarters of the consumers in this study (72.9%) were not categorized in the RSA dataset as having a secondary disability. However, among those who were identified with a secondary disability, physical disabilities were most common (13.6%), followed by secondary mental diagnoses (9.6%) and other sensory/communicative diagnoses (3.9%). This is particularly noteworthy as prior research suggested that hard-of-hearing individuals are typically diagnosed more frequently with mental disorders than the general population (Dammeyer & Chapman, 2017). It is possible that due to underreporting, more consumers in this study actually had a secondary disability than was reflected in the data since VR counselors tend to place a priority on deafness rather than a secondary disability (Nakaji, 2014).
Despite their lower numbers, some noteworthy patterns among consumers with secondary disabilities and certain services merit mention. Specifically, consumers with secondary sensory/communicative impairments received the highest rates of assessment and vocational rehabilitation counseling and guidance, significantly higher rates than consumers without secondary disabilities (72.7%and 60.4%). Diagnosis and treatment of impairments (57.8%) and information and referral services (22.8%) were also provided at higher rates when compared to consumers with mental or physical secondary disabilities and those without a secondary disability. Further, consumers with any secondary disability who also received rehabilitation technology achieved a successful employment outcome.
Level of education interactions
In this study, 47.8%of consumers had completed a high school degree or equivalency certificate (GED) or less, while 42.2%had some post-secondary education to a bachelor’s degree or an occupational credential beyond undergraduate degree work. Only 6.2%of consumers in this study had a master’s degree or higher, and only 3.9%had a vocational/technical certificate or license. The number of hard-of-hearing consumers with some college education or a college degree seemed consistent with findings from previous research that suggests these individuals seek educational pathways and careers that more readily accommodate hearing loss (Boutin, 2009; Schroedel & Geyer, 2000).
The outlook for successful closure for consumers with master’s degrees or higher at closure was especially positive; their estimated odds of achieving a successful employment outcome was 11.71 (95%) times higher than the estimated odds consumers with high school degrees, a GED, or less after controlling for other factors in the model. Another interesting outcome relates to the level of education and consumers with a vocational/technical certificate or license and the use of VR services. Consumers who had a vocational/technical certificate or license received assessment (70.1%), diagnosis and treatment and impairments (59.3%), vocational rehabilitation counseling and guidance (61.1%), rehabilitation technology (60.4%), and information and referral services (24.7%) at higher rates than consumers in the other educational brackets. Consumers may or may not have received vocational training from the VR program, but these consumers were nonetheless utilizing VR services to their benefit.
Gender-related interactions
The successful closure difference between males (49.8%) and females (50.2%) in this study was not statistically significant. Further, the study found that females used VR services at close to the same rate as men, and there were no significant gender differences found regarding the types of services consumers received other than a slight difference in educational attainment—4.0%of females received four-year college or university training compared to just 2.8%of males. This result suggests that any differences are more likely due to broader societal trends regarding higher education-related gender differences than gender-related rehabilitation service provision preferences (Goldin, Katz, & Kuziemko, 2006; Reijnders, 2018).
Implications
The primary implications of the study involve the intersectionality of several different demographic variables, the effects of those variables on services, and the ways in which counselors should consider the intersecting variables when providing services, particularly in relation to race and ethnicity and rehabilitation technologies.
Implications for rehabilitation education and training
First, and perhaps most importantly, the results of this study indicated that White consumers were served at a higher rate and received more services more frequently than any other racial or ethnic group. While this outcome was not surprising in the context of prior research (Choi et al. 2018; Gellert et al., 2017), the significant patterns of under-serviced across all minority groups is nonetheless concerning. Several studies have considered the effects of both explicit biases, which involve deliberate discriminatory actions, and implicit biases, which are unconscious, on attitudes toward and service provision to minority individuals with hearing loss (Bodner-Johnson & Benedict, 2012; Clarq & Walter, 2019; Dallman et al., 2016; Whyte et al., 2013). These studies suggest some tendency toward the internalized normalization of the able-bodied white experience, and the subsequent marginalization (however unintentional it may be) of minorities with hearing disabilities, even among service providers who consider themselves allies of these individuals.
Dallman et al. (2016) have noted that most service providers are members of the majority culture, hearing, and non-disabled; thus, they are working across areas different. When these differences are left unexamined and unconsidered, even for VR counselors and other helping professions who consider themselves culturally competent, implicit biases may thwart their otherwise good intentions. To counteract such effects, Chan et al. (2018) have called for educational service provision structures and strategies that are inclusive of diverse groups to help lessen the effects of both implicit and explicit bias.
Similarly, Clarke and McCall (2013) have stressed the need for increased collaborative efforts across disciplines, including social work and rehabilitation services, to create a mutually meaningful framework for address intersectional issues. In practical terms, this means a need exists for improved advocacy and implicit bias pre-service education and continuing education training for rehabilitation professionals along with interprofessional education and training in partnership with fields such as social work that already promote a social justice framework (Chapple, 2019; Dallman et al., 2016; Wheeler & Tharpe, 2020).
In addition to the implications related to race and ethnicity, the study results in the areas of age and secondary disability also have noteworthy implications for VR counselor preparation and training. For example, working-age consumers across all racial and ethnic groups were more heavily represented in the dataset than other age groups, a finding that supports previous research indicating that the disability-related employment gap seems to be the largest during middle age (Sevak et al., 2015). These consumers may already be aware of their hearing limitations and the impact this may cause in the workplace, so they more readily see the benefits of VR utilization.
Nonetheless, it is important for VR counselors to continue to evaluate their perceptions of working with older individuals and the health care, employment, and emerging age-related disability issues these consumers may face to reduce job-related barriers (Cichy et al., 2017). Further, since early hearing loss is related to employment barriers at older ages, VR counselors and younger consumers may mutually benefit from additional attention to hard-of-hearing in the transition age group, who in the current study were notably underserved. This result suggests a need for VR counselors to more effectively identify school-age consumers who are hard-of-hearing.
Implications for specific service provision
Of the contributing service factors, the provision of rehabilitation technology services was especially beneficial, especially for minority consumers. For instance, receiving rehabilitation technology service was found to result in successful employment outcomes for Non-Hispanic Black, Hispanic, or American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, or Multiracial consumers in the working-age and 55 years and older groups. It is surmised that for individuals in these groups, VR technology services may have offered their first or only access to assistive hearing devices, making that service especially impactful.
Pairing rehabilitation technology and other services also produced successful outcomes across multiple demographics. As previously noted, when consumers received rehabilitation technology services and diagnosis and treatment services, the estimated odds of achieving successful employment outcomes were far higher than for consumers who did not receive those VR services. Drilling down further, for consumers who received rehabilitation technology and maintenance service, rehabilitation technology and diagnosis and treatment, rehabilitation technology and interpreter services, rehabilitation technology and job placement assistance, or rehabilitation technology and job search assistance, successful employment outcomes occurred. These results demonstrate the critical role effectively addressing consumers’ assistive technology needs plays in the success of many other services.
Yet, the rehabilitation technology provided to hard-of-hearing consumers still primarily consists of hearing aids. Further, the teletypewriter (TTY), the telecommunication device for the Deaf (TDD), and other text transcription services that were once considered state-of-the-art technologies have become markedly less popular over the last decade (Okuyama & Iwai, 2011). In a study by Maiorana-Basas and Pagliaro (2014), results indicated that consumers with hearing loss prefer the internet, mobile, and app-based technologies instead of TTY, TDD, and similar services, but the availability of these services to people with hearing loss may not be keeping pace. As a result, rehabilitation professionals must be well-versed in up-to-date assistive technologies, but also up understand the related accessibility issues associated with common and popular devices.
Limitations
Several limitations exist in this study. First, only consumers who are hard-of-hearing were taken into consideration, so individuals who are classified as Deaf were not analyzed, which due to differences in self and counselor definitions and identification of hearing loss, may have resulted in over or under-representation of the target population. Second, only archival data from the FY 2014 RSA-911 dataset was explored, so causality cannot be inferred, and previous or future year cohorts may differ from the cohort analyzed, affecting generalizability. Also, due to low population numbers for American Indian or Alaska Native, Asian, Native Hawaiian or Other Pacific Islander, or Multiracial groups, these consumers were generalized rather than analyzed individually. Further, while CHAID is a well-recognized and rigorous analytic technique, the resultant variable is essentially qualitative, and distinctions between them are subject to some researcher interpretation (Díaz-Pérez & Bethencourt-Cejas, 2016).
Conclusion
The State-Federal Vocational Rehabilitation (VR) Program represents a substantial public investment in employment and independent living outcomes for people with disabilities and plays a vital role in serving the employment-related rehabilitation needs of consumers who are hard-of-hearing. However, prior research indicates that not all individuals are able to access or benefit from those services equitably. This study examined the interactions between select demographic variables, state-federal VR service provision, and successful employment outcomes. Results indicate that assessment, diagnosis and treatment of impairments, rehabilitation technology, counseling and guidance, and maintenance, transportation, and the category of “other” services most consistently contributed to successful employment outcomes across all demographic groups. Future research more closely investigating the nuances of this population’s hearing disabilities, which are very heterogeneous, and how those differences affect service utilization would be useful.
Stated concisely, consumers may or may not have received vocational training from the VR program, but these consumers nonetheless utilized many different VR services to their benefit. Factors such as negative explicit and implicit attitudes, access to rehabilitation technology, and other educational and workplace limitations have made it difficult for many hard-of-hearing consumers to realize their career goals and to achieve self-sufficiency, but additional research and improved training for service providers are important steps toward addressing the intersectionality of demographic and service provision variables that affect rehabilitation outcomes.
Conflict of interest
The authors declare that they have no competing interests.
Footnotes
Appendix A
Vocational Rehabilitation Services
| Types of VR Services | Description of VR Services |
| Assessment | Assessment includes 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 vocational rehabilitation agency, which operates under an order of selection, and/or to determine the nature and scope of VR services to be included in the individualized plan for employment. Trial work experiences and extended evaluation are included in this category. |
| Diagnosis and treatment of impairments | Diagnosis and treatment of impairments includes corrective surgery, dentistry, nursing services, drugs and supplies, prosthetics and orthotics, physical therapy, occupational therapy, speech therapy, mental health services, and other medically related rehabilitation services. |
| Vocational rehabilitation counseling and guidance | Vocational rehabilitation counseling and guidance is defined as information and support services to assist an individual exercise informed choice; this service is distinct from the case management relationship between the counselor and the individual during the vocational rehabilitation process. |
| Graduate college or university training | This full-time or part-time academic training may lead to a degree recognized as being beyond a baccalaureate degree, such as a Master of Science, Arts (M.S. or M.A.) or Doctor of Philosophy (Ph.D.) or Doctor of Jurisprudence (J.D.); such training can be provided by a college or university. |
| Four-year college or university training | This training involves full-time or part-time academic training leading to a baccalaureate degree, a certificate, or other recognized educational credential; such training can be provided by a four-year college or university or technical college. |
| Junior or community college training | This training involves full-time or part-time academic training above the high school level leading to an associate degree, a certificate, or other recognized educational credential; such training would be provided by a community college, junior college, or technical college. |
| Occupational or vocational training | This training involves occupational, vocational, or job skill training provided by a community college and/or business, vocational/trade or technical school to prepare students for gainful employment in a recognized occupation. |
| On-the-job training | This training involves training in specific job skills by a prospective employer; generally, the paid trainee may remain in the same or a similar job once successful completion is achieved. |
| Apprenticeship training | This training is a work-based employment and training program which combines hands-on, on-the-job work experience in a skilled occupation with related classroom instruction. It includes supervision and structured mentoring, provides for wage increases as an apprentice’s skills increase, is based on an employer-employee relationship, and provides an industry recognized certificate of completion of the program. |
| Basic academic remedial or literacy training | This literacy training or training is provided to remediate basic academic skills needed to function on the job in the competitive labor market. |
| Job Readiness training | This training prepares an individual for the world of work (e.g., appropriate work behaviors, getting to work on time, appropriate dress and grooming, increasing productivity). |
| Disability-related skills training | This training 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 | This training involves any training not recorded in one of the other categories listed, including GED or high school training leading to a diploma. |
| Job search assistance | Job search assistance involves activities which support and assist an individual in searching for an appropriate job; this service may include help with resume preparation, identifying appropriate job opportunities, developing interview skills, and can include making contacts with companies on behalf of the consumer. |
| Job placement assistance | Job placement assistance involves a referral to a specific job resulting in an interview, whether or not the individual attained the job. |
| On-the-job supports-short term | On-the-job supports-short term services are provided to an individual who has been placed in employment in order to stabilize the placement and enhance job retention; services include short-term job coaching for persons who do not have a supported employment goal consistent with the employment goal on the individualized plan for employment. |
| On-the-job supports-supported employment | On-the-job supports-supported employment services are on-going and help to support and maintain an individual with a most significant disability in supported employment for a period of time generally not to exceed 18 months; services included job coaching for individuals who have supported employment and long-term supports identified on the individualized plan for employment. |
| Transportation | Transportation includes travel and related expenses necessary to enable an applicant or eligible individual to participate in a vocational rehabilitation service; this service also includes adequate training in the use of public transportation vehicles and systems. |
| Maintenance | Maintenance means monetary support 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 while receiving services under an individualized plan for employment. |
| Rehabilitation technology | Rehabilitation technology means the systematic application of technologies, engineering methodologies, or scientific principles that meet the needs of, and address the barriers confronted by, individuals with disabilities in areas that include education, rehabilitation, employment, transportation, independent living, other assistive devices including, but not limited to, hearing aids, low vision aids and wheelchairs. Rehabilitation technology includes rehabilitation engineering, assistive technology devices, and assistive technology services. |
| Reader services | Reader services include, in addition to reading aloud, transcribed printed information into Braille or sound recordings. These services are generally for individuals who are blind or deaf-blind but may also include individuals unable to read due to serious neurological disorders, specific learning disabilities, or other physical or mental impairments. |
| Interpreter services | Interpreter services include sign language or oral interpretation services for individuals who are deaf or hard-of-hearing. These services also include tactile interpretation services for individuals who are deaf-blind. |
| Personal attendant services | Personal attendant services are personal services performed by an attendant for an individual with a disability including, but not limited to, bathing, feeding, dressing, providing mobility and transportation, in multiple settings such as the home, work, and training facilities/school. |
| Technical assistance services | Technical assistance services include conducting market analyses, developing business plans, and providing resources to individuals in the pursuit of self-employment, telecommuting and small business operation outcomes. |
| Information and referral services | Information and referral services are provided to individuals who may need services from other agencies not available through the vocational rehabilitation program. |
| Benefits counseling | Benefits counseling is provided to a person who is interested in employment but is uncertain of the impact work income may have on any disability benefits and entitlements being received, and/or is not aware of benefits, such as access to healthcare available to support any work attempt. This service involves an analysis of an individual’s financial situation, current benefits, such as SSDI and SSI, and the effect different income levels from employment may have on the individual’s future financial situation. |
| Customized employment services | Customized employment services include strategies resulting in the provision of individually negotiated and designed services, supports, and job opportunities for an individual leading to an employment outcome of customized employment, including self-employment. These services include customizing a job description based on current unidentified and unmet needs of the employer and the needs of the employee, developing a set of job duties or tasks, developing a work schedule (including determining hours worked), determining a job location, developing a job arrangement (such as job carving, job sharing, or a split schedule), or determining specifics of supervision. |
| Other services | Other services include all other vocational rehabilitation services which cannot be recorded elsewhere. These services include occupational licenses, tools and equipment, and initial stocks and supplies. |
The terms hearing loss and hard of hearing are used interchangeably to refer to a reduced ability to hear sound, while the term d/Deaf refers to a severe to profound loss of hearing with significant difficulty to inability to understanding speech.