Rehabilitation and Employment Outcomes for Adults Who Are Blind or Visually Impaired: An Updated Report
By Edward C. Bell, Ph.D., and Arielle M. Silverman, Ph.D.
Edward C. Bell, Ph.D., is the director of the Professional Development and Research Institute on Blindness at Louisiana Tech University.
Arielle Michal Silverman, Ph.D., is the founder and principal consultant of Disability Wisdom Consulting in Silver Spring, Maryland.
Abstract
The Adult Rehabilitation and Employment Survey originally conducted in 2011 by Bell and Mino (2013) demonstrated an employment rate of 37% for blind and visually impaired (VI) adults residing in the United States. Five years later, the second survey of adults on rehabilitation and employment factors showed similar findings, with only 32% of blind/VI adults holding full-time employment. The findings from the 2016 Adult Rehabilitation and Employment Survey affirmed the earlier study, supporting the notion that people with a higher level of education, who reported reading braille frequently, and who were members of a blindness consumer organization, particularly the National Federation of the Blind, were most likely to be working either in a traditional full-time job or in self-employment. These individuals were also least likely to be receiving Social Security disability benefits. Individuals who become blind later in life may especially benefit from supports to help them develop blindness skills (such as braille) and to acquire blind mentors and role models.
Keywords
Blind, visually impaired, rehabilitation outcomes, employment, factors associated with employment, braille, education
Introduction
This study was conducted as a replication and extension of the original Adult Rehabilitation and Employment Survey (ARES) (Bell & Mino, 2013). As in the original ARES, we sought to describe the demographic, educational, and financial status of individuals who are blind and visually impaired (VI) in the US. In addition, the updated ARES explored factors that are correlated with employment and financial self-sufficiency for this section of the population. In order to do so, a summary of the most current federal employment data is included, followed by an updated review of recent literature that report on factors correlated with employment for blind and VI individuals in the United States.
Employment Status of Blind and VI Individuals: Federal Reports
As of April 2017, the Bureau of Labor Statistics reported that approximately 2 million individuals ages 16 to 64 were identified as having vision loss according to the Current Population Survey. Of them, 61% were not in the civilian labor force (i.e., those who were identified as not actively looking for work during the reported month and thus not included in the unemployment rate, even though they were not employed as well). By comparison, only 27% of working age adults without vision loss in the United States were out of the labor force. Also as of April 2017, of the 39% of working age Americans with vision loss who were in the labor force, 10% were unemployed, compared with only 4% of working age Americans without vision loss who were in the labor force. Furthermore, the employment to population ratio showed that of the 2 million working age adults with vision loss, only 35% were employed, half of the 70% employment-population ratio for the general population (American Foundation for the Blind, 2017). These data have not changed substantially in the last decade; Bell (2010) reported that by 2007, only 37% of adults who were legally blind exiting the vocational rehabilitation (VR) system were achieving competitive employment.
The present study analyzed how the above reports are reflected in the current employment situation of blind and VI individuals. And, more importantly, whether specific rehabilitation, education, and/or civic factors could be identified that might be indicative of increased employment.
Disability, Employment, and the Vocational Rehabilitation System
In the pursuit of employment, each person, especially those with significant disabilities, has to navigate a whole host of social services, institutions, and processes that are aimed at assisting them in achieving their vocational goals. These include the state-federal VR process (Groomes, Shoemaker, Vandergoot, & Collins, 2015; Schroeder, 2000); public financial support, such as Social Security Disability Insurance (SSDI) and Supplemental Security Income (SSI) (Vaughn & Omvig, 2005); and the interplay of VR services with a multitude of education and employment preparation institutions (Fabian, Simonsen, Deschamps, Shengli, & Luecking, 2016; Song, Osmanir, Kortering, & Dalun, 2015; Taylor, Morgan, & Callow-Heusser, 2016). For those who have successfully achieved employment, these social systems worked, in some form or fashion, to facilitate success. While for many others, these same systems have served as a minefield, with continual roadblocks, delays, and dead ends.
Predictive factors of employment according to Lukyanova, Suarez-Balcazar, Balcazar, and Oberoi (2015) include previous work experience, family support, clear VR goals, and involved VR counselors. Factors that impeded employment included poor health, poor work history or work performance, lack of transportation, unstable home life, and receipt of SSI (p. 37).
Much has been reported recently on the ineffectiveness of the VR system in securing competitive employment for individuals with disabilities. Ipsen and Goe (2016) investigated consumer engagement in general VR services in hopes of reducing premature exits. They calculated that $365 million is spent each year on individuals who do not complete the VR process. In studying responses from consumers at various stages of the VR process, 50% of the respondents at every stage said the VR process was too slow. Consumers did not experience the level of commitment they expected from their VR Counselor, did not receive timely training services, and were not placed in jobs soon enough to support themselves or their families. By this study, 71% of premature and thus unsuccessful closures were due to this slow pace. Furthermore, consumers who had higher levels of goal setting and problem-solving skills had more successful experiences with VR programs.
In addition to unemployment, underemployment is also problematic. While advocating for the success of transition programs, Hemmeter, Donovan, Cobb, and Asbury (2015) still reported that the average salary at age 30 of successful student placements was $15,000; according to the United States Department of Health and Human Services (2015), the poverty line for a household of two in 2015 was $15,939. The study by Lukyanova et al. (2015) pointed out that many individuals with higher level skills or professional certifications were often placed in employment positions lower than their skill level (p. 37). Bates-Harris (2012) noted that it is common for individuals with disabilities to be paid subminimum wage in non-competitive employment (e.g. sheltered workshops). Instead of a competitive wage, individuals are paid a commensurate wage based on productivity as compared to a non-disabled worker. By Bates-Harris’s analysis, this practice reinforces a life of poverty for those with disabilities.
Another argument is that companies are not as willing to hire individuals with disabilities as they are to hire those without. Harris, Owen, Jones, and Caldwell (2013) suggested that the financial incentive to employers to provide accommodations is not well known, and employers who are already uneasy about the ability of disabled persons to perform the job are further discouraged. This is particularly true for individuals who are blind or VI, as participants of the study reported having faced job discrimination when seeking accommodations during the hiring process. O'Neill, Kaczetow, Pfaller, and Verkuilen (2017) also reflect that VR consumers who are blind or VI experience the lowest rates of competitive employment. The next section summarizes findings on predictors of employment specifically for the blind and VI population.
Blindness, Employment, and the Vocational Rehabilitation System
According to the literature, there are several factors that predict employment for the blind and VI. Among them, educational level, age, previous employment, training in blindness skills, not receiving SSDI benefits, and visual status remain consistent across the research studies.
Bell (2010) offered a comprehensive analysis on the competitive employment rates for VR consumers who were legally blind. Results from fiscal year 1997 to 2007 (obtained by using the RSA-911 data system) showed an average employment rate of 31.79%. In fact, the Competitive Consumer Rates showed a steady climb from 27% in 1997 up to a high of 37% in 2007. In addition, earnings of consumers also increased. Some of the factors that seemed to correlate with employment outcomes were gender, race, education, and veteran status. Results demonstrated that men earned $0.63 more an hour than women in 1997, and this increased by 2007 to a $0.86 difference on average. In addition, while the average spread between earnings was about $6.00 in 1997, the variability in earnings had increased to nearly $12 for men but only $8 for women. On the other hand, Native Americans had less employment in 1997 than the other racial groups, and this group remained substantially behind by 2007. Asian/Pacific Islanders earned the highest average wages and Black/African Americans earned the lowest average hourly rates. Those with a master’s degree or higher had almost a 40% greater chance of being employed and had $4.00 an hour more in earnings than did individuals with less than a high school degree. In addition, American veterans were underrepresented in the RSA-911 data system, and where they were identified the rates of employment were 19%.
A study by Giesen and Cavenaugh (2012) supported the factors of gender, race, education, disability, severity of visual impairment, receipt of SSI, and earnings at time of application to VR (which presumes previous work experiences) as predictive of employment. One of the most telling negative service factors for transition-age youth acquiring competitive employment was remedial instruction and assistance, suggesting that individuals with multiple disabilities in addition to blindness are the most disadvantaged. An additional study by Giesen and Cavenaugh (2013) found that higher education and previous work experience were the most telling predictors of future employment. Connors, Curtis, Emerson, and Dormitorio (2014) agreed. In their research, they found that individuals with visual impairments who had paid work experience during high school were 3.6 times more likely to obtain competitive employment than those who did not, and those who completed high school were 3.3 times more likely to be employed than those who did not. McDonnall and O’Mally (2012), however, noted that not all work experiences are the same. Specifically, they found previous paid work experiences led to a 3.3 times greater chance for future employment. The length, duration, and having found employment on one’s own were also deemed relevant factors. The same study found that school sponsored programs are not linked to future employment. It was also noted that individuals receiving SSI benefits have lower odds of employment. By contrast, Miller (2014) opted to consider that it is not the physical disability of blindness that is the hindrance but the lack of employability skills and proposed that school sponsored programs are beneficial in developing employability skills, an idea also supported by Daviso, Baer, Flexer, and Meindl (2016).
Darensbourg (2013) concluded that, on demographics alone, an individual who was 36 or younger, male, self-referred to VR, with less severe vision loss, not receiving Medicaid, had a higher level of education, and had previous work experience prior to vision loss would be the most probable successful VR closure. This study recognized, however, that by focusing solely on demographics, it did not capture the impact of societal attitudes toward the blind nor competency in alternative techniques, two factors confirmed by other research (Bell & Mino, 2013; Lynch, 2013; McDonnall, 2016). Advanced skills in orientation and mobility (O&M) (Cmar, 2015), computer competency (Zhou, Smith, Parker, & Griffin-Shirley, 2013), braille, and career mentoring (Blackshear, 2014; Kane & Kent, 2013; O'Mally & Antonelli, 2016) are associated with higher self-efficacy rates and more successful employment outcomes (Duquette, 2013).
Education and Rehabilitation Factors
In the previous ARES, Bell and Mino (2013) showed that the employment rate (as defined as having a full-time job) for individuals who are legally blind/visually impaired was 37% and identified specific factors linked with employment. Employment rates did not vary by age, gender, race/ethnicity, or self-reported visual status. However, education was positively correlated with employment. In addition, individuals who completed training at a Structured Discovery type of training center, continued to read braille on a daily or weekly basis, used a white cane for mobility, and affiliated with the National Federation of the Blind (NFB) were employed at a rate of 75%, earning an annualized salary of $53,600. Conversely, those individuals who received training at a conventional program or had no formal training, who affiliated with the American Council of the Blind (ACB) or no consumer organization, and who did not use a white cane or braille were employed at a rate of 44%, earning $36,000 annually. Furthermore, independent of training or consumer organization membership, individuals who read braille at least once a week earned an average annualized salary about $11,000 higher than those individuals who read braille less than once a week or who did not use braille.
The observed link between Structured Discovery Cane Travel (SDCT), braille usage, and consumer organization involvement with employment is consistent with other research. Regarding SDCT, the study by Cmar (2015) recognized that more advanced mobility skills such as traveling in unfamiliar areas was associated with the ability to acquire employment. Malik (2015) analyzed the effect of O&M skills on social adjustment and found a direct correlation between independent movement and a positive self-concept, which is an important factor in achieving and maintaining employment (Shaw & Gold, 2011).
Regarding braille, one of the most cited studies in the field conducted by Ryles (1996) revealed that reading braille was one main skill that predicted, for congenitally legally blind adults, higher employment rates and higher education levels than reading print as their original medium. The main results showed that those individuals that utilized braille as their primary reading medium had a significantly lower unemployment rate (44%) than those who utilize print as their primary reading medium. The author affirmed that even though reading braille as a primary medium did not increase an individual’s opportunities for employment, those who learned braille when they were children and used braille extensively as their primary reading medium were employed at a higher rate. However, those who learned braille after using print did not have a higher employment rate than those who never read braille. According to Golub (2006), employers believed that possessing updated braille skills represented an important factor that contributed to successful work experiences for their employees.
Finally, regarding consumer involvement, anecdotal and research evidence points to the positive role of mentoring in employment success (Beck-Winchatz & Riccobono, 2008; Omvig, 2005; Phelps, 2005). However, the stories of many individuals who are blind tell of families who were overprotective (Omvig, 2002), of communities that put up restrictions (Ferguson, 2001), and of support groups that promoted unemployment and dependence (Vaughn & Omvig, 2005). What research needs to accomplish is to tease out how these factors serve as facilitators rather than deterrents so that training and education can impact greater growth and evolution. O’Mally and Antonelli (2016) measured the effect of blind mentors on employment outcomes for blind college graduates. Although the data showed the mentoring relationship did not have a significant effect on employment outcomes, it did suggest a positive impact on employment skills such as assertiveness and job seeking skills. Role models appeared to be a relevant variable in maintaining motivation. They serve as examples to others and provide helpful insight on how to address some of the employment barriers. The authors stated that establishing blind mentors for blind college students could ultimately facilitate “self-efficacy and career adaptability” (p. 304). Similarly, Silverman (2015) found that effective sensitivity training requires mastery of blindness skills and a direct mentoring connection with a blind individual. Even though there is a lack of empirical studies about the impact of a consumer affiliation on employment outcomes, there are sufficient testimonies of blind individuals who express the opinion that their involvement in a consumer organization changed their lives completely. Omvig (2002) stated the NFB has been a key in his life and the lives of many blind individuals. He emphasizes the importance that competent and successful blind people who are part of this organization have as positive role models. These role models are the living proof that with proper training and opportunity, blind people can live normal, successful, and meaningful lives (Omvig, 2002).
The Present Study
We conducted the 2016 Adult Rehabilitation and Employment Survey (ARES 2016) to test whether the findings of Bell and Mino (2013) would be replicated in a new sample of legally blind adults. We also included some additional variables, such as the age of onset of blindness (early in life vs. later in life) and whether or not the participant had additional disabilities besides blindness, to evaluate whether these additional factors were correlated with employment. In addition to measuring employment rates, we also measured the percentage of participants who were beneficiaries of earnings-tested Social Security disability programs (SSI and SSDI) in various employment categories (unemployed, employed part-time, self-employed, and employed full-time), as well as the factors that correlated with being on the SSDI rolls.
Research Questions
The following research questions guided this study:
Q1: What is the employment rate for adults who are blind/VI in a US national sample, and what is the breakdown between full-time, part-time, and self-employment?
Q2: What demographic or disability factors are linked with higher employment rates?
Q3: What education or rehabilitation factors are linked with higher employment rates?
Q4: What is the prevalence of receiving Social Security disability benefits among those who are employed and unemployed?
Method
Participants
All participants were adults living in the United States who self-identified as blind or visually impaired. We used similar recruitment procedures as those described in Bell and Mino (2013), except that we included both working age adults (ages 18-70) and older adults (ages 71 and older). Participants were recruited through all available listservs of the NFB and the ACB and their monthly publications. We also distributed study announcements through state libraries, agencies, and training centers for the blind, and on social media. Participants were entered into a raffle prize drawing in appreciation of their time.
The final sample contained complete data from 1,153 participants with an average age of 46.06 years (SD = 15.22; Range = 18-89 years). The sample included 665 females (57.63%), 460 males (39.86%), and 29 participants (2.51%) who did not specify their gender. Most participants (73.22%) were white or Caucasian.
Materials
Participants completed the ARES 2016, an updated version of the instrument administered in Bell and Mino (2013). The ARES 2016 assesses: (1) disability variables, including degree of blindness, age of blindness onset, and the presence or absence of other disabilities; (2) variables related to living situation, including marital and parenting status; (3) variables related to involvement with VR, blindness training received, and current use of braille and mobility aids; (4) affiliation with blindness groups and involvement in local non-blindness community activities; (5) educational attainment and past and current employment status; and (6) financial variables, including income, receipt of Social Security disability benefits, and health insurance status. Participants were also asked if they would be willing to participate in follow-up studies.
Procedures
Participants completed ARES 2016 either electronically or over the phone with research staff. Before beginning ARES 2016, they read (or had read to them) an informed consent form describing the study and explaining that their participation was voluntary. The survey took approximately 15 minutes to complete. All procedures were approved by the institutional review board at the host university.
Results
Participant Demographics and Disability Variables
The sample included participants from all US states except Wyoming, with the largest group being from California (n = 78). Tables 1(a) through 1(e) summarize participant demographics, including gender, race/ethnicity, and disability variables. Most participants (75.02%) self-identified as blind, while the remaining participants self-identified as visually impaired. When asked when they first became blind or visually impaired, more than half (58.54%) indicated a congenital onset (at birth or before age 2). Most participants (61.32%) reported that they have little or no functional vision (hand motion or less). About one-third of participants reported having at least one additional disability or health condition besides blindness.
Table 1(a). Age
| N | Mean |
SD |
Range |
|---|---|---|---|
1153 |
46.06 |
15.22 |
18-89 |
Table 1(b). Gender
| Gender | Frequency |
Percent |
|---|---|---|
Female |
665 |
57.68% |
Male |
459 |
39.81% |
Other/prefer not to answer |
29 |
2.52% |
Table 1(c). Race/Ethnicity
Race/Ethnicity |
Frequency |
Percent |
|---|---|---|
White/Caucasian |
845 |
73.29% |
Black/African American |
98 |
8.50% |
Hispanic/Latino |
63 |
5.46% |
Asian |
41 |
3.56% |
Native American/Alaska Native |
13 |
1.13% |
Native Hawaiian/Pacific Islander |
4 |
0.35% |
Other |
36 |
3.12% |
Prefer not to answer |
53 |
4.60% |
Table 1(d). Blindness Variables
| Blindness Variables* | Frequency |
Percent |
|---|---|---|
Identification: blind |
865 |
75.02% |
Identification: visually impaired |
287 |
24.98% |
Congenitally blind |
675 |
58.54% |
Noncongenitally blind |
478 |
41.46% |
Has usable vision |
425 |
36.86% |
No usable vision |
707 |
61.32% |
*Numbers may not add to total due to missing data.
Table 1(e). Additional Disabilities
Additional Disabilities* |
Frequency |
Percent |
|---|---|---|
No additional disabilities |
783 |
67.91% |
Deaf/hearing impaired |
132 |
11.45% |
Orthopedic/mobility impaired |
90 |
7.81% |
Other physical impairment |
49 |
4.25% |
Learning disability |
40 |
3.47% |
ASD/autism |
16 |
1.39% |
Cognitive/intellectual |
11 |
0.95% |
Mental health condition |
80 |
6.94% |
Speech or communication |
69 |
5.98% |
Other disability or health condition |
138 |
11.97% |
* Participants could check more than one disability.
Tables 2(a) through 2(e) summarize living and family variables for the sample. The largest segment of participants (47.70%) reported owning their own home. About 40% of participants were married, while another third were single (never married). Slightly more than half of participants (54.64%) reported having never raised any children. Among those participants who had raised children, the most common number of children was two (34% of parents). Most of the participants (81.70%) had no children currently living in their home. About half of participants reported living in cities, with another 22% living in large towns and the remaining participants living in smaller communities.
Table 2(a). Living Situation
Living Situation |
Frequency |
Percent |
|---|---|---|
Own a home |
550 |
47.70% |
Live in rental unit |
438 |
37.99% |
Live with parent/guardian |
122 |
10.58% |
Live in dorm or training setting |
25 |
2.17% |
Live in other's home as a guest |
18 |
1.56% |
Table 2(b). Marital Status
Marital Status |
Frequency |
Percent |
|---|---|---|
Married |
469 |
40.68% |
Single, never married |
383 |
33.22% |
Divorced |
128 |
11.10% |
In a committed relationship |
124 |
10.75% |
Widow/widower |
32 |
2.78% |
Separated |
17 |
1.47% |
Table 2(c). Children Raised
Children Raised |
Frequency |
Percent |
|---|---|---|
None |
630 |
54.64% |
1 |
147 |
12.75% |
2 |
175 |
15.18% |
3 |
97 |
8.41% |
4 |
47 |
4.08% |
5 or more |
57 |
4.94% |
Table 2(d). Children Living at Home
Children living at home now |
Frequency |
Percent |
|---|---|---|
none |
942 |
81.70% |
1 |
111 |
9.63% |
2 |
71 |
6.16% |
3 or more |
29 |
2.52% |
Table 2(e). Community Population Size
Community Population Size |
Frequency |
Percent |
|---|---|---|
Rural area |
48 |
4.16% |
Small town (<5000) |
53 |
4.60% |
Midsize town (5001-20000) |
180 |
15.61% |
Large town (20001-100000) |
249 |
21.60% |
City (100001-500000) |
319 |
27.67% |
Large city (>500000) |
256 |
22.20% |
Unsure/don't know |
48 |
4.16% |
Vocational Rehabilitation, Training, and Blindness Skill Usage
Participants were asked whether or not they had received VR services, and if they currently had an open VR case. Most participants (95.14%) reported having had a VR case before; of these, 34.73% reported that their case was still open, while the remaining 65.27% reported that their case had been closed.
Table 3 shows participants’ responses to the question, “What has been your primary source of adjustment-to-blindness training?” Most participants reported having had some training; the most common sources were an adult residential training program, or school or home-based training during childhood.
Table 3. Primary Training Sources
Primary Training Source |
Frequency |
Percent |
|---|---|---|
Attended a residential training center |
274 |
23.76% |
Learned as a child at school or home |
267 |
23.16% |
Someone came to my home to provide training |
86 |
7.46% |
Attended a day training program |
60 |
5.20% |
Attended more than one center |
52 |
4.51% |
Dog guide school |
18 |
1.56% |
Currently at a residential center |
18 |
1.56% |
Someone currently comes to my home |
14 |
1.21% |
Currently at a day program |
8 |
0.69% |
Training from lots of different sources |
188 |
16.31% |
No formal training/self-taught |
111 |
9.63% |
We also asked participants about their current mobility aid and braille usage. Most participants said that they use a cane as their main mobility aid (n = 794, 68.86%), while another 149 (12.92%) reported using a guide dog, 79 (6.85%) reported using both a dog and cane, and 90 (7.81%) said they do not use any mobility aids. The remaining 41 participants reported using other mobility techniques such as human guide or a wheelchair or walker to address orthopedic disabilities.
About three-fourths of participants (n = 862, 74.76%) reported knowing braille. Of these, 162 (19.37%) reported using it daily, 428 (49.62%) reported using it once a week to daily, and 241 (27.96%) reported using braille less than once a week. Twenty-six participants (3.02%) said they are currently learning braille.
Table 4 shows the level of education that participants reported having when they first opened a case with VR, compared with their current level of education. Generally, participants tended to enroll in VR while in high school or between high school and college. After receiving VR services, many participants increased their education, with more than half attaining a bachelor’s degree or higher.
Table 4. Educational Attainment Before and After VR Enrollment
Education Before VR |
Frequency |
Percent |
Education After VR |
Frequency |
Percent |
|---|---|---|---|---|---|
Less than high school |
296 |
25.67% |
Less than high school |
6 |
0.52% |
High school diploma or GED |
366 |
31.74% |
High school diploma or GED |
80 |
6.94% |
Some college, but no degree |
154 |
13.36% |
Some college, but no degree |
192 |
16.65% |
Vocational or trade school |
20 |
1.73% |
Vocational or trade school |
53 |
4.60% |
Associate's degree |
49 |
4.25% |
Associate's degree |
73 |
6.33% |
Bachelor's degree |
161 |
13.96% |
Bachelor's degree |
335 |
29.05% |
Master's/graduate degree |
88 |
7.63% |
Master's/graduate degree |
327 |
28.36% |
Law degree |
9 |
0.78% |
Law degree |
32 |
2.78% |
Doctorate |
10 |
0.87% |
Doctorate |
55 |
4.77% |
Organizational and Community Involvement
When asked about their membership in blindness consumer organizations, 159 participants (13.79%) were members of the ACB, 507 (43.97%) were members of the NFB, 61 (5.2%) were members of both ACB and NFB, 51 (4.42%) were members of another consumer organization, and 375 (32.52%) were not members of any blindness consumer organization. In addition to blindness groups, most participants (68.86%) reported being involved in at least one other local community activity. The most common activity was participation in a local place of worship (n = 541, 46.92%) with 211 of those participants holding leadership or teaching positions at their place of worship. Others reported participating in music or theater groups (n = 186, 16.13%), political committees (n = 183, 15.87%), sports teams (n = 118, 10.23%), and business groups such as Kiwanis (n = 80, 6.94%). In addition, 307 participants (26.63%) named other community activities.
Employment and Financial Variables
For the employment analyses, we excluded 31 participants who were over the age of 70, to limit analyses to participants of working age (Bell & Mino, 2013). Table 5 lists employment statistics for the working age sample as a whole, as well as for the 691 individuals who reported having completed VR services. Among those individuals, 64% were working either full-time, part-time, or as self-employed workers; 18% were unemployed or working only as volunteers; 11% were retired; and the remaining 7% reported other statuses, such as being a student or a stay-at-home parent.
Table 5. Employment Status for Whole Sample and for Those Completing VR
Employment (Whole Sample) |
Frequency |
Percent |
Employment (Completed VR) |
Frequency |
Percent |
|---|---|---|---|---|---|
Unemployed not looking for work |
75 |
6.69% |
Unemployed not looking for work |
47 |
6.80% |
Unemployed looking for work |
188 |
16.77% |
Unemployed looking for work |
55 |
7.96% |
Volunteer only |
36 |
3.21% |
Volunteer only |
21 |
3.04% |
Employed part-time |
111 |
9.90% |
Employed part-time |
52 |
7.53% |
Self-employed |
114 |
10.17% |
Self-employed |
85 |
12.30% |
Employed full-time |
367 |
32.74% |
Employed full-time |
307 |
44.43% |
Stay-at-home parent |
18 |
1.61% |
Stay-at-home parent |
12 |
1.74% |
Full-time student |
69 |
6.16% |
Full-time student |
8 |
1.16% |
Retired |
100 |
8.92% |
Retired |
81 |
11.72% |
Other/Multiple |
43 |
3.84% |
Other |
22 |
3.18% |
We also asked the participants to report their monthly income, health insurance status, and whether or not they were receiving government cash benefits such as SSI or SSDI. Among the whole sample, the average monthly income reported was $4,125.14 (SD = $2,682.03, Mdn = $3,500, Range = $190-$18,000). Slightly more than half of the participants (n = 641, 57.89%) reported receiving some form of government cash benefits. The most common benefit was SSDI (n = 446, 38.73% of the full sample); 223 participants (19.41%) reported receiving SSI; and 130 participants (11.27%) reported receiving other benefits, such as state disability, veterans’, or retirement benefits. Nearly all participants (98.49%) reported having health insurance; 541 of them (48.13%) reported having only public insurance such as Medicare or Medicaid, while 407 participants (36.21%) reported having only private coverage (from an individual or employer-sponsored health plan) and 158 participants (14.15%) reported a combination of public and private health coverage.
Correlates of Employment
In the next set of analyses, we looked at factors that were associated with higher employment rates. Because a number of individuals still had an open VR case or did not know the status of their VR case, the remainder of this analysis is confined to those 691 individuals who have had their VR case closed and are of working age. Among the 691 working age participants who had completed VR, employment was defined as currently having either a full-time job or being self-employed; 397 individuals (55%) were employed by this criterion. Of these individuals, 357 reported an average monthly income of $4,429.83, (SD = 2,605.51, Mdn = 3,979, Range $190.00-$12,500.00). For the individuals working part-time, 39 individuals reported an average monthly income of only $2,714.33 (SD = 2,093.96, Mdn = $2,100, Range = $700-$9,000).
When we examined demographic factors, we found that the employed participants were younger (Mdn = 46.78 years, SD = 12.43) than the unemployed participants (Mdn = 51.57, SD = 13.34, t (689) = -4.86, p < .001, d = .37). Participants with at least one additional disability had a lower employment rate (45%) than those with no additional disabilities (62%, χ2 = 14.51, p = .001, OR = .52). Participants who were congenitally blind (from birth or infancy) had a higher employment rate (61%) than those participants who became blind at age 2 or later (53%, χ2 = 4.82, p = .03, OR = 1.41). Employment rates did not differ by gender, ethnic minority status, or presence of usable vision.
Next, we examined rehabilitation factors including educational attainment, use of braille and mobility aids, and membership in a blindness consumer organization. Consistent with expectations, higher educational attainment was associated with a higher employment rate (with education treated as a continuous variable: χ2 = 37.72, p < .001). Participants with an associate’s degree or less had an employment rate of 37%, compared with those having a bachelor’s degree (62%), those with a master’s degree (67%), and those with a doctorate or law degree (76%).
Participants who used braille at least once a week had a higher employment rate (65%) than those who used braille less than once a week or not at all (χ2 = 17.06, p < .001, OR = 1.24). The participants who used braille less than once a week had an employment rate which did not differ significantly from those who never used braille (53% vs. 45%, χ2 = 2.04, p = .15). The type of mobility aid used (cane, guide dog, both, or neither) had no relationship with employment rates.
Finally, participants who were not members of any blindness organization reported an employment rate of 50%. This was significantly lower than the 60% employment rate reported by participants who were members of at least one blindness organization (χ2 = 5.93, p = .014, or = 1.50). This effect was driven by a higher employment rate among members of the NFB (67%), whereas ACB members reported an employment rate that did not differ from that of unaffiliated participants (50%).
Predictors of Disability Cash Benefit Receipt
We explored the prevalence and predictors of Social Security disability beneficiary status among the participants who were of working age (18-70 years) and who had completed their VR cases. We defined a beneficiary as an individual who reported receiving cash payments from SSI, SSDI, or both at the time of the survey. Beneficiary status data was available from 654 participants who were working age and had completed VR. A total of 303 participants (46%) reported being beneficiaries. Not surprisingly, most of the participants who lacked paid employment of any kind (82%) were beneficiaries. In addition, 73% of the individuals who were working part-time, 62% of the self-employed individuals, and 10% of those who were working full-time were beneficiaries. This suggests that the part-time and self-employment in which some participants engaged was insufficient to allow the participant to exit the Social Security disability rolls.
Predictors of beneficiary status were similar to predictors of employment status. Beneficiary status did not vary by gender, race/ethnicity, or blindness factors. Beneficiaries were marginally older (Mdn = 49.48, SD = 12.86) than non-beneficiaries (Mdn = 47.67, SD = 13.08, t (652) = 1.78, p = .08). Sixty-one percent of participants with additional disabilities were beneficiaries, compared with only 39% of those without additional disabilities (χ2 = 20.04, p < .001, OR = 2.22). More educated participants were less likely to be beneficiaries (χ2 = 30.68, p < .001). Participants who reported reading braille less than once a week were more likely to be beneficiaries (61%) than those who read braille at least once a week (44%, χ2 = 17.36, p < .01, OR = 1.94). Among the participants who were not members of any blindness organization, 52% were beneficiaries, compared with 44% of those who were members of any blindness organization (χ2 = 4.34, p = .037, OR = 1.42). Again, this was mainly driven by the lower rate of beneficiary status among NFB members; only 38% of NFB members were beneficiaries, significantly less than the 52% of individuals who were not members of any organization (χ2 = 9.42, p = .0021, OR = .57). The rate of beneficiary status among ACB members was not significantly lower (47%) than that of individuals who were not members of any blindness organization.
Discussion
The aim of this study was to replicate and extend research by Bell and Mino (2013) on employment outcomes for legally blind adults in the United States. Our findings were broadly consistent with those of Bell and Mino (2013). When looking specifically at full-time employment, the rate in our entire working age sample was 32.74%, a bit lower than the 37.22% reported by Bell and Mino (χ2 = 4.80, p = .029). However, among those participants in our sample who had completed a case with VR, the rate of full-time employment rose to 44%. In this study, we also found that 10.17% of the working age participants were self-employed, an employment status that was not explored in the prior survey. Some of these individuals may have been counted as employed full-time or employed part-time in the prior survey. Self-employment may be a promising alternative to traditional work for blind adults, bypassing barriers related to transportation or discriminatory hiring practices. Indeed, a recent study found that blind individuals were more likely to close their VR cases due to self-employment than those with other disabilities (Ipsen & Swicegood, 2017). While self-employment may hold promise, a majority of self-employed participants in this study were still receiving Social Security disability benefits, indicating that their income may be below the level of substantial gainful activity. Future research on the jobs and earnings of blind adults who are self-employed, as well as those who hold part-time jobs, could be useful.
When we looked at correlates of employment, our findings were similar to those of Bell and Mino (2013). People with a higher level of education, who reported reading braille frequently, and who were members of a blindness consumer organization, particularly the National Federation of the Blind, were most likely to be working either in a traditional full-time job or in self-employment. These individuals were also least likely to be receiving Social Security disability benefits. Because this was a cross-sectional study, we cannot draw firm conclusions about causation. For example, it is possible that individuals who are proficient in braille experience a competitive advantage in the workplace, leading to higher employment rates. However, it is also possible that individuals who are employed have more motivation to use braille regularly. In the future, it will be useful to follow participants over time after they receive blindness skill training to identify the causal impacts of training on employment.
In this study, we also found that about one third of participants have at least one disability in addition to blindness. These individuals reported a much lower employment rate than those who did not have additional disabilities (45% vs. 62%) and were much more likely to be Social Security disability beneficiaries (59% vs. 39%). This suggests that traditional rehabilitation programs for the blind may not adequately meet the complex needs of blind individuals with hearing, physical, and other disabilities. As the number of blind persons with multiple disabilities continues to grow, it will be important to identify facilitators and barriers to employment for this unique subgroup.
We also evaluated the possible correlation of blindness factors with employment; specifically, whether the person has been blind since birth or became blind later in life, and whether or not the person had usable residual vision. Consistent with the prior survey, we found no relationship between amount of usable vision and employment. However, congenitally blind participants reported a higher employment rate than those who became blind later in life. One might expect that congenitally blind individuals, who have had more time to develop blindness skills and networks, would be more frequent users of braille and be more involved in blindness organizations, factors associated with higher employment rates. Indeed, the congenitally blind participants in the current sample were much more likely to use braille at least once a week (65%) than the adventitiously blind participants (40%), and they also had a somewhat higher rate of consumer organization membership (69% vs. 59%). Individuals who become blind later in life may especially benefit from supports to help them develop blindness skills (such as braille) and to acquire blind mentors and role models.
The current survey is the first of a series of surveys assessing participants’ rehabilitation and employment experiences. Therefore, in the current survey, we did not ask detailed questions about the type of rehabilitation training that participants received, or about the type of cane they use for mobility. We are conducting a more in-depth follow-up survey with ARES respondents to learn more about their training history and perceptions of their training. We intend to analyze these data in order to gain a finer-grained understanding of the training components that are most predictive of employment success. In a second follow-up survey, we are gathering more details about the types of jobs that employed ARES respondents have, how they obtained those jobs, and what barriers they have encountered when seeking employment. These data may help rehabilitation professionals, researchers, and policymakers to identify the most important contributors to unemployment for blind Americans.
Implications
- Employment rates have not improved appreciably for blind Americans in the last five years.
- Like Bell and Mino (2013), we found three factors associated with higher employment rates: educational attainment, use of braille, and consumer organization membership. Rehabilitation professionals may want to focus their attention on helping clients obtain education, become proficient in braille, and connect with consumer organizations.
- A significant number of blind Americans are under-employed, particularly those in part-time jobs or self-employment, who are still receiving Social Security disability benefits. These individuals may benefit from ongoing rehabilitation supports to help them find higher-paying jobs.
- Individuals with other disabilities in addition to blindness face a higher risk for unemployment or under-employment. These individuals may require different rehabilitation supports than those who are blind without additional disabilities, and may face unique barriers to education and employment.
- People who became blind later in childhood or as adults have lower employment rates than people who became blind early in life. These individuals may benefit from more intensive support to master blindness skills, such as braille, and to become involved with blindness organizations.
- More research is needed to understand the biggest barriers to employment and the reasons why so many blind Americans drop out of the labor force.
References
American Foundation for the Blind. (2017). Putting data to work - Reinforcing labor force statistics. Research Navigator. Retrieved from http://www.afb.org/info/programs-and-services/public-policy-center/research-navigator-a-quarterly-series-on-research-in-blindness-and-visual-impairment/putting-data-to-work-reinforcing-labor-force-statistics/1235
Bates-Harris, C. (2012). Segregated and exploited: The failure of the disability service system to provide quality work. Journal of Vocational Rehabilitation, 36(1), 39-64. doi: 10.3233/JVR-2012-0581
Beck-Winchatz, B., & Riccobono, M. A. (2008). Advancing participation of blind students in science, technology, engineering, and math. Advances in Space Research, 42(11), 1855-1858. doi: 10.1016/j.asr.2007.05.080
Bell, E. C. (2010). Competitive employment for consumers who are legally blind: A 10-year retrospective study. Journal of Rehabilitation Research & Development, 47(2), 109-116. doi: 10.1682/JRRD.2009.08.0120
Bell, E. C., & Mino, N. M. (2013). Blind and visually impaired adult rehabilitation and employment survey: Final results. Journal of Blindness Innovation and Research, 3(1). Retrieved from https://nfb.org/images/nfb/publications/jbir/jbir13/jbir030101abs.html. doi: http://dx.doi.org/10.5241/2F1-35
Blackshear, J. (2014). The guys group: Navigating the terrain of adult life using aspects of the expanded core curriculum. Journal of Visual Impairment & Blindness, 108(6), 491-495.
Cmar, J. L. (2015). Orientation and mobility skills and outcome expectations as predictors of employment for young adults with visual impairments. Journal of Visual Impairment & Blindness, 109(2), 95-106.
Connors, E., Curtis, A., Wall Emerson, R., & Dormitorio, B. (2014). Longitudinal analysis of factors associated with successful outcomes for transition-age youths with visual impairments. Journal of Visual Impairment & Blindness, 108(2), 95-106.
Darensbourg, B. L. (2013). Predictors of competitive employment of VR consumers with blindness or visual impairments. Journal of Vocational Rehabilitation, 38(1), 29-34. doi: 10.3233/JVR-120618
Daviso, A. W., Baer, R. M., Flexer, R. W., & Meindl, R. (2016). Career and technical education, work study, & school supervised work: How do they impact employment for students with disabilities? Journal of Applied Rehabilitation Counseling, 47(2), 10-19. Retrieved from https://www.questia.com/library/journal/1P3-4111336841/career-and-technical-education-work-study-school
Duquette, J. (2013). Factors influencing work participation for people with a visual impairment: Information monitoring summary. Longueuil: INLB. Retrieved from http://www.inlb.qc.ca/recherche-publ/factors-influencing-work-participation-for-people-with-a-visual-impairment/
Fabian, E., Simonsen, M., Deschamps, A., Shengli, D., & Luecking, D. M. (2016). Service system collaboration in transition: An empirical exploration of its effects on rehabilitation outcomes for students with disabilities. Journal of Rehabilitation, 82(3), 3-10. Retrieved from https://www.questia.com/library/journal/1G1-466783058/service-system-collaboration-in-transition-an-empirical
Ferguson, R. (2001). We know who we are: A history of the blind in challenging educational and socially constructed policies: A study in policy archeology. San Francisco, California: Caddo Gap.
Giesen, J. M., & Cavenaugh, B. S. (2012). Transition-age youths with visual impairments in vocational rehabilitation: A new look at competitive outcomes and services. Journal of Visual Impairment & Blindness, 106(8), 475-487.
Giesen, J. M., & Cavenaugh, B. S. (2013). Disability insurance beneficiaries with visual impairments in vocational rehabilitation: Socio-demographic influences on employment. Journal of Visual Impairment & Blindness, 107(6), 453-467.
Golub, D. B. (2006). A model of successful work experience for employees who are visually impaired: The results of a study. Journal of Visual Impairment & Blindness, 100(12), 715-725.
Groomes, D. G., Shoemaker, M., Vandergoot, D., & Collins, S. W. (2015). Excellence is within your reach: The importance of planning for performance in the state-federal vocational rehabilitation program. Journal of Rehabilitation, 81(2), 39-46. Retrieved from https://www.questia.com/library/journal/1G1-421907257/excellence-is-within-your-reach-the-importance-of
Harris, S. P., Owen, R., Jones, R., & Caldwell, K. (2013). Does workfare policy in the United States promote the rights of people with disabilities? Journal of Vocational Rehabilitation, 39(1), 61-73. doi: 10.3233/JVR-130642
Hemmeter, J., Donovan, M., Cobb, J., & Asbury, T. (2015). Long term earnings and disability program participation outcomes of the Bridges transition program. Journal of Vocational Rehabilitation, 42(1), 1-15. doi: 10.3233/JVR-140719
Ipsen, C., & Goe, R. (2016). Factors associated with consumer engagement and satisfaction with the Vocational Rehabilitation program. Journal of Vocational Rehabilitation, 44(1), 85-96. doi: 10.3233/JVR-150782
Ipsen, C., & Swicegood, G. (2017). Rural and urban vocational rehabilitation self-employment outcomes. Journal of Vocational Rehabilitation, 46(1), 97-105. doi: 10.3233/JVR-160846
Kaine, N., & Kent, R. (2013). Activities to encourage employability skills in middle childhood. Journal of Visual Impairment & Blindness, 107(6), 524-528.
Lukyanova, V., Suarez-Balcazar, Y., Balcazar, F., & Oberoi, A. (2015). A case file review of employment outcomes from community rehabilitation providers. Journal of Vocational Rehabilitation, 43(1), 33-40. doi: 10.3233/JVR-150752
Lynch, K. A. (2013). Survey reveals myths and misconceptions abundant among hiring managers about the capabilities of people who are visually impaired. Journal of Visual Impairment & Blindness, 107(6), 408-410.
Malik, S. (2015). Orientation and mobility training in special education curriculum on the social adjustment problems of visually impaired children in family. Proceedings of The Multidisciplinary Academic Conference, 439-456.
McDonnall, M. C. (2016). The relationship between vocational rehabilitation professional’s interactions with businesses and employment outcomes for consumers who are blind or visually impaired. Rehabilitation Counseling Bulletin, 59(4), 203-212. doi: 10.1177/0034355215586389
McDonnall, M. C., & O'Mally, J. (2012). Characteristics of early work experiences and their association with future employment. Journal of Visual Impairment & Blindness, 106(3), 133-144.
Miller, J. (2014). Meeting the expectations of the workplace in the schoolplace. Journal of Visual Impairment & Blindness, 108(6), 495-499.
O'Mally, J., & Antonelli, K. (2016). The effect of career mentoring on employment outcomes for college students who are legally blind. Journal of Visual Impairment & Blindness, 110(5), 295-307.
Omvig, J. (2002). Freedom for the blind: The secret is empowerment. Hot Springs, Arkansas: Region VI Rehabilitation Continuing Education Program, University of Arkansas Press.
Omvig, J. (2005). The characteristics of an NFB orientation center. Braille Monitor, 48(4). Retrieved from http://www.nfb.org/Images/nfb/Publications/bm/bm05/bm0504/bm050403.htm
O'Neill, J., Kaczetow, W., Pfaller, J., & Verkuilen, J. (2017). Impairment, demographics and competitive employment in vocational rehabilitation. Journal of Vocational Rehabilitation, 46(2), 149-158. doi: 10.3233/JVR-160851
Phelps, A. (2005). NFB launches National Center for Mentoring Excellence. Journal of Visual Impairment & Blindness, 99(4), 247-248.
Ryles, R. (1996). The impact of braille reading skills on employment, income, education, and reading habits. Journal of Visual Impairment & Blindness, 90(3), 219-226.
Schroeder, F. (2000). Changing patterns in the rehabilitation system: Meeting the needs of the blind and otherwise disabled. Braille Monitor, 43(8). Retrieved from http://www.nfb.org/images/nfb/publications/bm/bm00/bm0008/bm000805.htm
Shaw, A., & Gold, D. (2011). Development of a tool for the assessment of employment preparedness specifically for persons who are blind or partially sighted. Work, 39(1), 49-62. doi: 10.3233/WOR-2011-1150
Silverman, A. M. (2015). The perils of playing blind: problems with blindness simulation and a better way to teach about blindness. Journal of Blindness Innovation and Research, 5(2), Doi: http://dx.doi.org/10.5241/5-81
Song, J., Osmanir, K., Kortering, L., & Dalun, Z. (2015). Vocational rehabilitation transition outcomes: A look at one state's evidence. Journal of Rehabilitation, 81(2), 47-53. Retrieved from https://www.questia.com/library/journal/1G1-421907258/vocational-rehabilitation-transition-outcomes-a-look
Taylor, D. L., Morgan, R. L., & Callow-Heusser, C. A. (2016). A survey of vocational rehabilitation counselors and special education teachers on collaboration in transition planning. Journal of Vocational Rehabilitation, 44(2), 163-173. doi: 10.3233/JVR-150788
U.S. Department of Health and Human Services, Office of the Assistant Secretary for Planning and Evaluation. (2015). Poverty Guidelines. Retrieved from https://aspe.hhs.gov/2015-poverty-guidelines
Vaughan, E., & Omvig, J. (2005). Education and rehabilitation for empowerment. Greenwich, Connecticut: Information Age.
Zhou, L., Smith, D. W., Parker, A. T., & Griffin-Shirley, N. (2013). The relationship between perceived computer competence and the employment outcomes of transition-aged youths with visual impairments. Journal of Visual Impairment & Blindness, 107(1), 43-53.
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