Predictors of employment for youths with visual impairments: findings from the second national longitudinal transition study.
Visually disabled persons
Visually disabled persons (Employment)
Visually disabled persons (Research)
|Author:||McDonnall, Michele Capella|
|Publication:||Name: Journal of Visual Impairment & Blindness Publisher: American Foundation for the Blind Audience: Academic Format: Magazine/Journal Subject: Health Copyright: COPYRIGHT 2011 American Foundation for the Blind ISSN: 0145-482X|
|Issue:||Date: August, 2011 Source Volume: 105 Source Issue: 8|
|Topic:||Event Code: 530 Labor force information; 310 Science & research|
|Geographic:||Geographic Scope: United States Geographic Code: 1USA United States|
Abstract: The study reported here identified factors that predict
employment for transition-age youths with visual impairments. Logistic
regression was used to predict employment at two levels. Significant
variables were early and recent work experiences, completion of a
postsecondary program, difficulty with transportation, independent
travel skills, and social skills.
Levels of employment among youths with visual impairments (that is, those who are blind or have low vision) who are making the transition to adulthood (aged 16-24) have long been a concern of professionals who work with this population. In 2009, data became available to document the severity of the problem among these youths. The results from the Current Population Survey indicate that 19.8% of youths with visual impairments aged 16-19 are working (the employment-population ratio), compared to 29.2% of the youths in the general population, and 39.5% of youths with visual impairments aged 20-24 are working, compared to 63.8% of those in the general population (Bureau of Labor Statistics, 2009).
Despite the difficulty with employment that youths with visual impairments face, there has been only limited research in this area. Most federal-state vocational rehabilitation programs provide special programs to help youths who are visually impaired prepare to make the transition to work, yet the contents of these programs are generally not based on empirical evidence. The purpose of the study presented here was to identify factors that are related to future employment for youths with visual impairments to assist professionals in the field to work with this population and to provide an empirical foundation for the development of transition programs.
A substantial amount of research has been conducted on factors that affect successful transition outcomes for youths with disabilities, with employment being one of the key outcomes. Several variables have consistently been found to be important to helping youths with disabilities obtain employment, including early work experiences, self-determination, and academic competence (Benz, Lindstrom, & Yovanoff, 2000; Bremer, Kachgal, & Schoeller, 2003; Stodden, Dowrick, Gilmore, & Galloway, 2001). Other research has documented an association between employment and level of education, health, and the receipt of Supplemental Security Income (SSI) for transition-age youths with disabilities (Berry, 2000). A much more limited amount of research has been conducted on factors that influence employment outcomes for youths who are visually impaired. Studies involving this population have supported the importance of self-determination, early work experiences (including the number of experiences), academic competence, level of education, parental support
and expectations, health, level of functional vision, and use of assistive technology (McDonnall, 2010; McDonnall & Crudden, 2009; Shaw, Gold, & Wolffe, 2007).
Research has identified variables that are associated with the employment of adults with visual impairments. Several studies have specifically focused on barriers to employment for this population. Some of the most commonly identified barriers are employers' negative attitudes, transportation problems, receipt of social security benefits and associated medical benefits, access to assistive technology, and the lack of or limited work experience (Crudden & McBroom, 1999; Crudden, Sansing, & Butler, 2005; Kirchner, Johnson, & Harkins, 1997; O'Day, 1999). Other studies have focused on factors that are associated with successful employment. Some key factors that were identified were good social skills, the ability to travel independently (that is, good orientation and mobility skills) and to work independently, communication skills, basic academic skills, the receipt of an educational certificate or degree, and having worked since one became visually impaired (Capella-McDonnall, 2005; DeMario, 1992; Golub, 2003).
The goal of the study presented here was to expand the field's understanding of the factors that affect employment for youths who are visually impaired by using data from the most comprehensive study available for this population: the second National Longitudinal Transition Study (NLTS2). The NLTS2 includes variables to measure many of the factors found to be important to employment for persons with visual impairments. The following research question was addressed: What factors are the most important predictors of employment for youths who are visually impaired?
SOURCE OF DATA
The NLTS2 consisted of a nationally representative sample of students receiving special education services who were aged 13 to 16 in December 2000. The sample was stratified on the basis of several factors, including disability, resulting in a nationally representative sample of youths with visual impairments who received special education services while in high school. The data were collected via interviews with the youths and their parents, interviews with school personnel, and direct assessments of the youths. At the time of the analyses reported here, data were available from the first four waves--Wave 1: 2001-02, Wave 2: 2003-04, Wave 3: 2005, and Wave 4: 2007--and data for all four waves were used in the analyses. The data cover multiple topics, including the characteristics of the youths, the characteristics of the households, the youths' access to and use of services, the involvement of the youths' families, the youths' academic and functional skills, the youths' postsecondary education, and the youths' employment. Because this is a restricted-use dataset, unweighted sample sizes can only be provided to the nearest 10. Therefore, sample sizes reported in this study are approximates, not exact numbers. Additional information about the NLTS2 is available at http://www.nlts2. org/studymeth/index.html.
The sample was restricted to youths whose visual impairments were identified as the primary disability under which they were eligible for special education services. It was further limited to youths who (1) had employment data available at Wave 4, (2) had completed or were no longer attending high school, and (3) were not currently attending postsecondary school, resulting in a maximum available sample of 250. The sample size for each analysis varied because of missing data on the independent variables. The sample size available for the multivariate analyses ranged from 140 to 200. Demographic information on the sample that was available for the majority of the multivariate analyses (N = 180) is presented in Table 1.
The dependent variable was employment, measured at two levels: working 20 or more hours per week and working 35 or more hours per week (full time). Both levels of the variable were dichotomous and were coded 0 if the individual did not work at all or worked less than the specified number of hours per week or if the individual worked the specified number of hours (or more) per week. The levels of this variable were created from two items in NLTS2: a dichotomous variable indicating whether the youth was currently employed and a variable indicating the total number of hours the youth worked per week (based on all jobs held).
Independent variables were selected for the study on the basis of prior empirical research that supported their importance to the employment outcomes of youths with visual impairments or other disabilities or for adults with visual impairments. All independent variables were based on a single item in the NLTS2 database, although the item was taken from more than one wave of data in three cases. Several categorical items were changed to dichotomous variables (to increase the numbers in each category and to preserve power for the multivariate analyses). The following coding system was used to identify the origin of each variable that was included in the analyses: created (created from more than one wave of data or other change), SRI (original item in the NLTS2), dichotomized (made into a dichotomous variable from a categorical NLTS2 variable). Because missing data on key variables reduced the available sample size for the multivariate analyses, univariate analyses of each variable were conducted to identify those that were significantly related to employment for this sample. Only those variables that were significantly related to employment in the univariate analyses were considered for inclusion in the logistic regression models, as recommended by Hosmer and Lemeshow (2000). The numbers and percentages reported in the following descriptions of the independent variables are based on the data available for the univariate analyses.
Work experience. Two variables were used to measure early and recent work experience. High school employment (created) was a dichotomous variable that indicated paid work experience anytime between one year prior to Wave 1 to the Wave 3 interview if the individual was in high school during that time. Just over 42% (100 out of 240) of the youths were employed at some point during high school. Number of recent jobs (created) represented the number of jobs the youth had held in the two years before the Wave 4 interview (original SRI variable), excluding the job currently held if the person was employed. The mean number of jobs held was 0.75 (1.37), with a range of 0 to 11.
Receipt of SSI benefits (SRI). This dichotomous variable was based on an item that asked the youths to report whether they had received SSI benefits in the two years prior to the Wave 4 interview. Almost 63% (120 out of 190) of the youths had received SSI benefits during that period. Academic competence (SRI). Academic competence in reading and mathematics was measured with standard scores on four subtests of the Woodcock-Johnson III Tests of Achievement (WJ-III ACH): Passage comprehension and synonyms-antonyms (reading) and applied problems and calculation (mathematics). Standard scores are normed to a mean of 100, with a standard deviation of 15 at each grade, and can be used for across-grade analyses. The WJ-III ACH was administered to the participants as part of the direct assessments during Wave 1 or Wave 2, when the youths were at least 16 years old. The WJ-III ACH is a well-developed and psychometrically sound instrument; it is considered the best available instrument to measure achievement (Cizek, 2003). Passage comprehension involves reading a short passage and identifying a missing word (M = 82.45, SD = 26.71). Synonyms-antonyms requires reading a word and supplying either a synonym or antonym for that word (M = 92.03, SD = 21.01). Applied problems involves analyzing and solving mathematics problems, including deciding the appropriate mathematical operations to use and which data to include (M = 83.99, SD = 22.18). Calculation requires performing mathematical calculations ranging from simple addition to calculus (M = 88.83, SD = 25.40).
Transportation difficulties (dichotomized). Difficulty with transportation was measured with an item from Wave 4 that asked the participants to report how difficult it is for them to get where they need to go. A dichotomous variable was created to indicate whether the youth experienced difficulty with transportation; it was coded 1 if the participant reported that transportation was "very difficult" or "somewhat difficult" and 0 if he or she reported that transportation was "somewhat easy" or "very easy." Almost 44% of the youths (90 of 210) reported difficulty with transportation. Self-determination (SRI). This variable was measured with items from the Arc's Self-Determination Scale (Wehmeyer, 2000). Items with the highest factor loadings and face validity were selected from the original instrument by SRI to measure four domains of self-determination: personal autonomy, career planning autonomy, self-realization, and psychological empowerment (Facts from OSEP's, 2005). This scale was administered to the youths during Wave 1 or 2, when they were at least 16 years old.
Health (dichotomized). Health was measured with one item from the Wave 4 youth or parent interview that asked the respondent to describe the youth's general health. Response options were used to create a dichotomous variable, with excellent, very good, or good given a value of 1, and fair or poor given a value of 0. A large majority of the youths were in good or better health (200 out of 230, or 88%).
Completion of a postsecondary program (SRI). This dichotomous variable was based on responses to three questions regarding whether the youth had received a diploma, certificate, or license from a two-year or community college; a four-year college or university; or a vocational, business, or technical school. Less than 18% of the youths (40 out of 250) had completed any type of postsecondary program at Wave 4.
Parental expectations (created). The parents were asked about their expectations regarding the youth's ability to support himself or herself financially in the future. They provided their opinion on the likelihood that the youth would earn enough without financial help from his or her family or a government benefit program. The dichotomous variable used for this study was created from these responses, with negative parental responses (probably won't or definitely won't) given a score of 1 and positive parental responses (definitely will or probably will) given a score of 0. Data on this variable were available from Waves 1 to 3; the most recent data available for the youth were used. The majority of parents had positive expectations about the youth's ability to support himself or herself financially (64%, or 140 out of 220). Level of vision loss (SRI). This variable was based on the parents' report of the youth's disability. The parents were asked in Wave 1 whether the youth had a disability (from a list of disabilities), including blindness. Youths whose parents identified them as being blind in Wave 1 received a score of 1; youths who were not identified as being blind received a score of 0. Thirty-seven percent of the youths (90 out of 240) were classified as blind.
Social skills (SRI). Several variables were available to measure social skills. One was a social skills scale, created by SRI on the basis of the parents' responses in Wave 1 to questions about the youths' involvement in social activities, ability to cope with frustration and deal with conflict, and ability to cooperate. Scores could range from 0 to 22; the mean for the youths in this study was 14.70 (3.67). Two other items were also used as proxy measures of social skills: whether the youth was invited to social activities in the past 12 months (yes or no; the most recent wave of data available was used) and the number of days per week that the youth got together with friends during the 12 months prior to the Wave 4 interview (on a scale of 0 to 5, with 0 being never and 5 being six or seven days per week). A large majority of the youths (77%, 190 out of 240) were invited to social activities, and the average score on getting together with friends was 2.23 (1.62), which corresponds to approximately one day per week.
Independent travel skills (dichotomized). In Wave 1, the parents were asked how well the youth was able to get to places outside the home on his or her own without help. Examples of places were school, a nearby store or park, or a neighbor's house. This item was used to create a dichotomous variable that measured independent travel skills; the parents' responses "not at all well" or "not very well" received a score of 0, and those of "pretty well" or "very well" received a score of 1. A majority of the youths (62%, or 140 out of 230) exhibited good travel skills as rated by their parents.
Use of assistive technology (created). The youth and his or her parents were asked whether the youth used assistive technology for the computer. This dichotomous item was asked during the Wave 1 through Wave 3 interviews, and the most recent data available were used. A majority of the youths (58%, or 140 out of 240) used assistive technology.
Logistic regression was the statistical technique that was used for this study, and SAS version 9.2 was the statistical software that was used. Power for the multivariate analyses was limited because of the small sample, which was due, in part, to the large amount of missing data on the independent variables. Therefore, the method recommended by Hosmer and Lemeshow (2000) was used to select variables for and build the logistic regression models. The first step in this process, univariate analyses of all the independent variables of interest, involved chi-square tests for the categorical variables and t-tests for the continuous variables. All variables that exhibited a significant relationship with employment in the univariate analyses were then considered for inclusion in the logistic regression models. Some of these variables were eliminated because of patterns of missing data that resulted in too few observations available for the logistic regression models. All the remaining significant variables were included in the two models (one for each level of employment--working 20 hours or more per week and working 35 hours or more per week; N = 140). Variables that were not found to be significant in the logistic regression model were removed from the model, one at a time, and a new model was evaluated. Generally, variables were removed on the basis of their p-values; an exception was that the first variable removed was SSI benefits, since it had the smallest available sample size. The sample size was reestablished with SSI benefits removed (N = 180), and thereafter that sample was used to test each new model that was fit, as one variable was removed at a time. When the final models were established, SSI benefits was reintroduced to the models because of its presumed importance, but was not found to be significant. The final models for each dependent variable were then fit with the full sample available for them (N = 200 and N = 190). An alpha level of. 10 was used because of the relatively low power for the models.
Univariate analyses of 22 potential predictor variables for the logistic regression models were conducted. Thirteen of these variables significantly predicted employment at p < .05, and two predicted employment at p < .10 (see Table 2). Because all variables had been identified in previous research as factors that are associated with employment, it is not surprising that most of them were also significant predictors in the NLTS2 data. Perhaps what is more interesting to note are the variables that were not found to be significant predictors even in the univariate analyses: health, some measures of self-determination (the self-advocacy, empowerment, and self-realization scores), a global measure of social skills (rated by the parents), the use of assistive technology, and reading achievement (one measure significant at p <. 10 for working 20 hours or more per week only).
LOGISTIC REGRESSION MODELS
Only the variables that were statistically significant in the univariate analyses were considered for the logistic regression models. Variables with the largest effect sizes were considered first; however, some of these variables had a large amount of missing data, which would result in a substantial decrease in the sample size for the multivariate analyses. Because of missing data, mathematics achievement, personal autonomy, and one of the social skills measures could not be included in the models. The remaining social skills measure (invited to social activities by peers) was a significant predictor only of working 20 hours or more per week and therefore was entered only into that model.
Each model was fit with the remaining variables (9 for the 20-hour work model and 8 for the 35-hour work model). Model fitting proceeded as described in the Method section, with variables removed in the following order:
1. 20-hour work model: receipt of SSI, level of vision loss, parental prediction, independent travel skills
2. 35-hour work model: receipt of SSI, level of vision loss, parental prediction
After the last nonsignificant variable was removed and the models were refit with the largest sample available, the final models were established. The results for these models are presented in Table 3. Four variables were significant in both final models: early work experiences, number of recent work experiences, difficulty with transportation, and completion of a postsecondary program. One additional significant variable was present in each model: Peer social skills predicted employment at 20 hours or more per week, and independent travel skills predicted employment at 35 hours or more per week. The relative importance of the predictor variables differed in the two models, with early and recent work experiences being the best predictor of employment at 20 hours or more, whereas these experiences were the weakest predictors of employment at 35 hours or more. With both employment variables in the full-time work model, neither one reached significance at p < .05; if only one was retained in the model, it was significant at p < .05 (because of the low power available for the analyses). Despite these differences, the estimated effect sizes (odds ratios) for the variables were similar in the models.
As was found in other recent studies, early work experiences and the number of work experiences were important predictors of employment for youths with visual impairments. These other studies used different data and therefore represented different populations of youths with visual impairments (youths who received vocational rehabilitation services; see McDonnall & Crudden, 2009) and youths from the general population who self-reported difficulty with vision (McDonnall, 2010). These three studies provide compelling evidence of the importance of not just obtaining work experience while in high school, but of obtaining multiple work experiences. In this study, the size of that effect was substantial: Youths who had just two jobs in the past two years had odds 1.6 to 2.1 times higher of being employed at Wave 4 than did youths who held no jobs in the past two years.
It is relevant to consider Why having multiple work experiences is so valuable to future employment. One hypothesis is that multiple work experiences result in a stronger network of people who can assist the youth in finding a job. Using personal contacts (a network) in a job search is commonly considered the best way to obtain employment. Furthermore, research has shown that most jobs are found through acquaintances, rather than close friends and family members, and that the more diverse and expansive a person's network is, the more likely that this network will result in a successful job lead (Luecking, Fabian, & Tilson, 2004). Having a large network may be a problem for many youths with visual impairments: research has documented that youths who are visually impaired have smaller social networks than do sighted youths (Kef, 1997; Sacks, Wolffe, & Tierney, 1998). It is possible that the connections made through multiple work experiences while younger result in a greater network of contacts to call on when one searches for a job later.
Another variable that was identified as a significant predictor of employment at both levels was transportation difficulties. Transportation difficulties have long been considered a major barrier to employment for persons with visual impairments, but little empirical evidence to support this variable has been available. Youths in this study who reported that transportation was easy or somewhat easy had odds 2.4 times greater of being employed than did those who reported difficulties with transportation. The fact that transportation problems were important even when other variables were taken into account is relevant. For example, if youths experienced difficulty with transportation, despite having a positive work history, their odds of being employed were lower.
The fourth variable that significantly predicted employment in both models was having completed a postsecondary program resulting in a diploma, certificate, or license. Previous research documented the importance of completing a postsecondary educational program, but not of only participating in such a program (Capella-McDonnall, 2005). This was the strongest predictor of working full time for youths with visual impairments, since those who had completed a postsecondary program had odds three times greater of being employed at 35 hours per week or more. It is particularly relevant to note that for the sample in this study, completing a postsecondary educational program was a more important predictor of full-time employment than was previous work experience. It may be that the diploma, certificate, or license actually helps the person obtain a job, but it is also possible that the personal characteristics of the person that enabled him or her to complete a postsecondary program despite a significant visual impairment contribute to the influence of this variable.
Another variable in the full-time employment model with an effect similar to completion of a postsecondary educational program was independent travel skills. These skills were rated by the youths' parents at Wave 1, approximately six years before the employment outcome. Youths whose parents indicated that they could get to places outside the home on their own pretty well or very well were almost three times as likely to be employed full time at Wave 4. It is interesting that this variable did not significantly predict fewer hours of employment (the 20-hour work model). It is possible that this variable represents more than simply travel skills, such as a sense of independence in general, which is important to the capacity to work independently.
The final significant predictor in the 20-hour employment model was peer social skills. The estimated effect for peer social skills was large: Those who were invited by friends to social activities had 3.5 times greater odds of being employed than did those who were not. The importance of social skills to employment is obvious for everyone, visually impaired or not. Social skills are a particular concern for youths who are visually impaired, however, since it is considered challenging for persons with visual impairments to learn social skills because the acquisition of these skills generally occurs through observation in an incidental way (Skellenger, Hill, & Hill, 1992).
The nonsignificance of one variable in particular deserves attention. The recent receipt of SSI benefits, although a significant predictor when considered alone, was clearly not important when considered in combination with other variables. This finding indicates that the other variables in the model were more important predictors of employment than was the receipt of SSI. This is an important finding because the receipt of benefits from the Social Security Administration is often considered a major barrier to employment for persons with visual impairments. Perhaps these financial and medical benefits are not as great a deterrent for transition-age youths as they are for older persons who are visually impaired. It is important to study the effect of the receipt of SSI while young on obtaining early work experiences. If the receipt of SSI deters youths from attempting to work when young, the lack of work experience may have a negative impact on future employment, resulting in an indirect effect of the receipt of SSI on future employment.
The major limitation of the study was its small sample, which was due, in part, to a large amount of missing data on some independent variables. Some variables that were strongly associated with future employment in the univariate analyses (such as personal autonomy and mathematics achievement) could not be included in the logistic regression models because of the small samples, but may have been important predictors in the multivariate models. With a larger sample, the variables that were found to be the most important predictors of employment could have been different.
Implications for professionals
There are important implications for professionals with regard to each of the six factors that were found to predict employment for youths with visual impairments. First, the value of obtaining employment experiences, including working during high school, must be emphasized to these youths. A focus on educational studies often prevents youths from working (O'Day, 1999), but youths should be encouraged to find time to devote to obtaining work experience. Parents may also need encouragement and education in this area, since they may not realize the importance of early work experiences to their children's ability to obtain employment in the future.
That the number of recent work experiences is significantly related to employment suggests the importance of youths building a network of contacts that may help them find employment in the future. Research has documented that unemployed college graduates who are visually impaired have less extensive social and supportive networks and use them in more limited ways than do employed college graduates who are visually impaired (Roy, Dimigen, & Taylor, 1998). One way to build a network is through work experiences, but there are several other avenues to increase network contacts (including extracurricular school activities, volunteer work, and membership in religious or other formal organizations). Youths need first to become aware of the importance of building a network and then strive to increase their number of personal contacts. Increasing a youth's knowledge of how to find a job, including how to build and use a network to do it, is an important lesson that could be included in transition programs.
Completion of a postsecondary educational program was associated with fulltime employment. To complete a postsecondary program, youths with visual impairments may need some support. In postsecondary school, youths who are visually impaired have the responsibility to request their accommodations and locate the support they need to succeed, a situation that is in stark contrast to that of secondary school. Transition programs can help prepare youths for the different atmosphere and requirements of postsecondary school, which may help increase their ability to succeed and complete a postsecondary program. Vocational rehabilitation counselors can also provide support and assistance, as needed, to ensure the success of their consumers who are attending postsecondary school.
Teachers of students with visual impairments and other professionals in the field are well aware of the importance of social skills and independent travel skills to the success of their students, as evidenced by the inclusion of these topics in the expanded core curriculum (Hatlen, 1996). The findings of this study provide additional support for the importance of these variables as they relate to future employment, which is a central measure of successful transition for young adults with visual impairments. It is imperative that the Individual Education Programs for youths with visual impairments include goals in these areas. Teachers of students with visual impairments and parents should ensure that youths are trained in both areas as part of their school curricula. Transition programs could also include components that focus on social skills, such as providing feedback on poor social skills in everyday interactions and in formal interactions like job interviews. Helping youths learn to solve transportation problems is another area that teachers of students with visual impairments, rehabilitation counselors, and transition programs could address as part of their education or rehabilitation programs.
Youths and their parents want the youths to obtain employment following their education, yet they will likely not be aware of important factors that may contribute to their ability to do so. Professionals are in a position both to assist youths in these areas and to educate them and their parents. Transition programs that are designed to assist these youths as they move from secondary school to postsecondary school or work must incorporate the factors that have been found by empirical research to predict employment. Professionals who are working in these programs should evaluate the programs' contents to ensure that they are relevant to their consumers.
Benz, M. R., Lindstrom, L., & Yovanoff, P. (2000). Improving graduation and employment outcomes of students with disabilities: Predictive factors and student perspectives. Exceptional Children, 66, 509-529.
Berry, H. G. (2000). The Supplemental Security Income Program and employment for young adults with disabilities: An analysis of the National Health Interview Survey on Disability. Focus on Autism and Other Developmental Disabilities, 15, 176-181.
Bremer, C. D., Kachgal, M., & Schoeller, K. (2003). Self-determination: Supporting successful transition. In Research to Practice Brief, 2(1). Minneapolis: National Center on Secondary Education and Transition. Retrieved from http://www.ncset. org/publications/viewdesc.asp?id=962
Bureau of Labor Statistics. (2009). [Unpublished data tables of specific disability questions in the Current Population Survey]. Washington, DC: Author.
Capella-McDonnall, M. E. (2005). Predictors of competitive employment for blind and visually impaired consumers of vocational rehabilitation services. Journal of Visual Impairment & Blindness, 99, 303-315.
Cizek, G. J. (2003). Review of Woodcock-Johnson III. In B. S. Plake, J. C. Impara, & R. A. Spies (Eds.), The fifteenth mental measurements yearbook (pp. 1019-1024). Lincoln, NE: Buros Institute of Mental Measurements.
Crudden, A., & McBroom, L. W. (1999). Barriers to employment: A survey of employed persons who are visually impaired. Journal of Visual Impairment & Blindness, 93, 341-350.
Crudden, A., Sansing, W., & Butler, S. (2005). Overcoming barriers to employment: Strategies of rehabilitation providers. Journal of Visual Impairment & Blindness, 99, 325-335.
Facts from OSEP's National Longitudinal Studies: The self-determination of youth with disabilities. (2005, June). Menlo Park, CA: SRI International. Retrieved from www.nlts2.org/fact_sheets/nlts2_fact_sheet_ 2005_06-2.pdf
DeMario, N. (1992). Skills needed for successful employment: A review of the literature. RE:view, 24, 115-125.
Golub, D. B. (2003). Exploration of factors that contribute to a successful work experience for adults who are visually impaired. Journal of Visual Impairment & Blindness, 97, 774-778.
Hatlen, P. (1996). The core curriculum for blind and visually impaired students, including those with additional disabilities. RE:view, 28(1), 25-32.
Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression. New York: John Wiley & Sons.
Kef, S. (1997). The personal networks and social supports of blind and visually impaired adolescents. Journal of Visual Impairment & Blindness, 91, 236-245.
Kirchner, C., Johnson, G., & Harkins, D. (1997). Research to improve vocational rehabilitation employment barriers and strategies for clients who are blind or visually impaired. Journal of Visual Impairment & Blindness, 91, 377-392.
Luecking, R. G., Fabian, E. S., & Tilson, G. P. (2004). Working relationships: Creating career opportunities for job seekers with disabilities through employer partnerships. Baltimore, MD: Paul H. Brookes.
McDonnall, M. C. (2010). Factors predicting post-high school employment for young adults with visual impairments. Rehabilitation Counseling Bulletin, 54(10), 36-45.
McDonnall, M. C., & Crudden, A. (2009). Factors impacting employment success for transition-age youths with visual impairments, Journal of Visual Impairment & Blindness, 103, 329-341.
O'Day, B. (1999). Employment barriers for people with visual impairments. Journal of Visual Impairment & Blindness, 93, 627-642.
Roy, A. W. N., Dimigen, G., & Taylor, M. (1998). The relationship between social networks and the employment of visually impaired college graduates. Journal of Visual Impairment & Blindness, 92, 423-432.
Sacks, S. Z., Wolffe, K. E., & Tierney, D. (1998). Lifestyles of students with visual impairments: Preliminary studies of Social Networks. Exceptional Children, 64, 463-478.
Shaw, A., Gold, D., & Wolffe, K. (2007). Employment-related experiences of youths who are visually impaired: How are these youths faring? Journal of Visual Impairment & Blindness, 101, 7-21.
Skellenger, A. C., Hill, M., & Hill, E. (1992). The social functioning of children with visual impairments. In S. Odom, S. R. McConnell, & M. A. McEvoy (Eds.), Social competence of young children with disabilities (pp. 165-188). Baltimore, MD: Paul H. Brookes.
Stodden, R. A., Dowrick, P., Gilmore, S., & Galloway, L. M. (2001). A review of secondary school factors influencing postschool outcomes for youths with disabilities: Report from the National Center for the Study of Postsecondary Educational Supports [online]. Retrieved from http:// www.rrtc.hawaii.edu/documents/products/ phase1/043-H01.pdf
Wehmeyer, M. L. (2000). The Arc's Self-Determination Scale: Procedural guidelines (Revised). Silver Spring, MD: The Arc of the United States.
Michele Capella McDonnall, Ph.D., CRC, research professor and interim director, Research and Training Center on Blindness and Low Vision, Mississippi State University, P.O. Box 6189, Mississippi State, MS 39762;
The contents of this article were developed with support from Grant H133A070001 from the Department of Education, National Institute on Disability and Rehabilitation Research. However, the contents do not necessarily represent the policy of the Department of Education, and readers should not assume endorsement by the federal government.
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Table 1 Demographic characteristics of the sample. Variable Percentage Age 19 5 20 24 21 22 22 29 23 20 Gender Female 44 Male 56 Race or ethnicity White 61 African American 25 Hispanic 13 Asian American or Pacific Islander 2 When youth left high school Within the past 2 years 48 More than 2 years ago 52 Table 2 Univariate analyses predicting employment for youths with visual impairments. Variable N Working 20+ hours Dichotomous [chi [rho] [phi] variables square] Paid work while in 240 11.04 <.001 .22 high school Parent expectations: Able 220 11.60 <.001 -.23 to support self (yes or no) Blind (parents' 240 3.89 .049 -.13 report, completely blind) Receipt of SSI 190 6.77 .01 -.19 benefits (past 2 years) Has difficulty with 210 5.31 .02 -.16 transportation (yes or no) Independent travel 230 10.98 <.001 .22 skills Completion of 250 8.37 .00 .18 postsecondary program Good health 230 0.41 .52 .04 Social skills: Invited to social 240 5.14 .02 .15 activities by peers (yes or no) Use of assistive 240 0.80 .37 -.06 technology Continuous t-test p d variables Number of jobs held 230 -4.62 <.001 .70 in past 2 years Math achievement: 130 -2.30 .02 .43 Applied problems score Math achievement: 160 -1.67 .10 .29 Calculation score Reading achievement: 160 -1.74 .08 .30 Passage comprehension score Reading 160 -1.16 .25 .20 achievement: Synonyms-antonyms Self-determination: 160 -2.31 .02 .40 Career autonomy scale Self-determination: 140 -3.19 .002 .58 Personal autonomy scale Self-determination: 160 0.75 .45 .13 Empowerment scale Self-determination: 160 -0.26 .80 .04 Self-realization scale Social skills: How often youths go 190 -3.03 .003 .50 together with friends Social skills scale 230 -1.09 .27 .16 Variable N Working 35+ hours Dichotomous [chi [rho] [phi] variables square] Paid work while in 240 9.21 .00 .20 high school Parent expectations: Able 220 10.50 .00 -.22 to support self (yes or no) Blind (parents' 240 4.69 .03 -.14 report, completely blind) Receipt of SSI 190 4.50 .03 -.15 benefits (past 2 years) Has difficulty with 210 5.34 .02 -.16 transportation (yes or no) Independent travel 230 10.96 <.001 .22 skills Completion of 250 10.45 .00 .21 postsecondary program Good health 230 .23 .63 .03 Social skills: Invited to social 240 1.97 .16 .09 activities by peers (yes or no) Use of assistive 240 .21 .64 -.03 technology Continuous t-test p d variables Number of jobs held 230 -3.97 <.001 .69 in past 2 years Math achievement: 130 -2.61 .01 .54 Applied problems score Math achievement: 160 -1.76 .08 .33 Calculation score Reading achievement: 160 -.98 .33 .18 Passage comprehension score Reading 160 -1.20 .23 .22 achievement: Synonyms-antonyms Self-determination: 160 -1.08 .28 .20 Career autonomy scale Self-determination: 140 -3.45 <.001 .68 Personal autonomy scale Self-determination: 160 1.22 .23 .22 Empowerment scale Self-determination: 160 .35 .73 .06 Self-realization scale Social skills: How often youths go 190 -2.79 .01 .53 together with friends Social skills scale 230 -.69 .49 .11 Table 3 Logistic regression models predicting employment for youths with visual impairments. Working 20 or more hours/week (a) Wald [chi Odds ratio Variable [beta] SE square] p [95% CI] High school work 0.44 0.18 6.40 .01 2.42 [1.22, 4.81] Number of recent 0.36 0.12 8.95 .003 1.44 (1.13,1.82] jobs Transportation -0.44 0.19 5.54 .02 0.42 [0.20, 0.86] difficulty Postsecondary 0.41 0.21 3.72 .05 2.25 [0.99, 5.12] completion Peer social skills 0.63 0.28 4.95 .03 3.51 [1.16, 10.64] Independent travel -- -- -- -- -- Working 35 or more hours/week (b) Wald [chi Odds ratio Variable [beta] SE square] p [95% CI] High school work 0.37 0.21 3.25 .07 2.10 [0.94, 4.7] Number of recent 0.24 0.13 3.72 .05 1.28 [1.00, 1.63] jobs Transportation -0.44 0.22 4.04 .04 0.41 [0.17, 0.98] difficulty Postsecondary 0.55 0.23 5.86 .02 3.03 [1.23, 7.42] completion Peer social skills -- -- -- -- -- Independent travel 0.54 0.25 4.60 .03 2.96 [1.10, 7.97] (a) Model [chi square] (5, N = 200) = 37.78, p <.0001; Nagelkerke [R.sup.2] = .25. (b) Model [chi square] (5, N = 190) = 29.65, p <.0001; Nagelkerke [R.sup.2] = .23.
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