Determinants of employment outcomes of transition-age youth with depressive disorders

1.1 Employment barriers faced by persons with depressive disorders

Barriers to successful employment may stem from myriad issues for TAY with depressive disorders. The behavioral, and cognitive symptoms associated with depressive disorders—such as irritability, difficulty concentrating, memory loss—can interfere with one’s employment (Lerner et al., 2004). Employees with depressive disorders experience high absenteeism, diminished productivity and tend to earn lower in income than their peers without depressive disorders (Beck et al., 2014; Kessler et al., 2006; Lerner & Henke, 2008). Aside from symptoms, limited work experience, low educational attainment, and lack of support may constitute significant challenges for TAY during job search (Davis et al., 2013; Marrone & Taylor 2013; Stone et al., 2015). Societal barriers such as stigma, negative workplace climate, inadequate workplace support and accommodation may impede their ability to be successful when they secure employment (Krupa, 2011; Lloyd & Waghorn, 2010). The scale of these challenges is yet to be met with critical insights about improving the employment-related problems among persons with depressive disorders. Research remains meagre in this area, but some researchers have advocated for the development of more employment-based interventions for this population (Peer & Tenhula, 2011).

Thousands of youth with depressive disorders have sought support to address these challenges by enrolling in the U.S state-federal vocational rehabilitation (VR) program. The state-federal VR program provides a wide range of pre- and post-employment support services, such as job search assistance, job placement services, career assessments, vocational training, counseling, job coaching, and transportation services. These services serve to mitigate the barriers that individuals with disabilities encounter in their quest to secure and maintain employment. Current estimates suggest the state-federal VR program serves approximately one million clients annually (Chan et al., 2014). Youth with disabilities represent one-third of VR program enrollees (Honeycutt et al., 2015); while those with mental health conditions such depressive disorders, schizophrenia, anxiety and personality disorders constitute the second largest group of youth enrolled in the program (Marrone, & Taylor, 2013).

The Workforce Innovation and Opportunity Act (WIOA), which passed in 2014, expanded state-federal VR programming for TAY. The WIOA requires VR agencies to allocate at least 15%of their annual budget to provide more comprehensive career and educational development services for youth with disabilities (Hoff, 2014). This growing attention to career development needs of TAY with disabilities has led researchers to identify several determinants of employment outcomes. Strong predictors of competitive employment include interagency collaboration, (Fabian et al., 2016), early VR services initiation (Honeycutt, 2017), prior employment experience, parental involvement, and participation in vocational instruction (Dong et al., 2016; Park & Bouck, 2018; Wehman et al., 2015). While these prior studies have advanced the current knowledge base, further inquiry is required to explore rehabilitation experiences, services and factors influencing employment outcomes of specific clients including TAY with depressive disorders.

1.2 Extant research involving rehabilitation services administration (RSA-911) data

Research indicates that the state-federal VR program can contribute to better employment outcomes for individuals with disabilities. The annual successful employment rate ranges from 45%to 57%(Office of Special Education and Rehabilitation Services [OSERS], 2020). However, recent evidence shows low employment rates among TAY with mental health conditions, including those with depressive disorders (Honeycutt, 2017), a population that were less likely to receive VR services (Honeycutt, 2017). Existing Rehabilitation Services Administration (RSA-911) dataset studies involving individuals with depressive disorders suggest that employment outcomes of VR program participants can vary based on client’s demographic characteristics and services received. For instance, in examining 2004 RSA-911 dataset, Schaller and Yang (2007) reported employment outcomes for clients with disabilities varied by race/ethnicity and gender. Using the RSA-911 2013 dataset, Kaya and Chan (2017) reported that individuals with depressive disorders who received VR counseling, on-the-job support, job placement, on-the-job training, vocational training, job search, and technical assistance services were more likely to secure competitive employment than those who did not receive these services. Sanchez (2018) revealed similar findings when examining employment outcomes for individuals with depressive disorders within the 2011 RSA-911 data. In similar vein, individual-level characteristics and VR services have been found to influence VR clients’ earnings. Factors such as significant disability, gender, race/ethnicity, and the receipt of college services, job readiness training and on-the-job has been identified as key predictors of clients’ earnings (Kang et al., 2019; Migliore et al., 2012).

Prior investigations involving RSA-911 data have helped advance the field’s understanding of individuals with disabilities who access VR services. But they also exposed blind spots in the literature. For example, to our knowledge, little information exists on employment outcomes of TAY with depressive disorders from the state-federal VR program. Effectively serving this population in state-federal VR program requires a robust understanding of the determinants of important outcomes from the program. Furthermore, little is known about whether demographic variables such as race/ethnicity and severity of disability interact with VR services to impact employment outcomes for TAY with depressive disorders. Understanding the moderating role of such demographic variables could offer critical insights into why and how this important subgroup of clients in the state-federal VR program experience improved outcomes. Moreover, few studies, if any, have attempted to unpack employment outcomes by examining specific indicators of successful employment such as job earnings among clients with depressive disorders. Using the 2015 RSA-911 dataset, the current study seeks to address these gaps in the literature by investigating whether and to what extent demographic characteristics and VR services received correlate with successful employment and earnings of TAY with depressive disorders who participated in the state-federal VR program. The following research questions were explored:

Do demographic characteristics (i.e., age, gender, race/ethnicity, severity of disability, social security recipient status and education level) predict successful employment outcome of TAY with depressive disorders?

2.1 Data source and sample selection

The data for the current study was extracted from the RSA-911 dataset for the 2015 federal fiscal year (FY). The RSA-911 dataset is a national administrative data that contains information about state-federal VR program clients for each FY. Such information includes clients’ demographic information, disability type, disability benefits received, employment services received, providers, cost of services provided, education, and employment outcome achieved (RSA, 2013). It is important to note that the RSA made major changes to its data collection and reporting paradigm following the authorization of WIOA and subsequent changes in the VR program. Those changes introduced new services and performance measures. The process of incorporating these changes into RSA-911 dataset began in 2014 FY (Center for Large Data Research and Data Sharing in Rehabilitation, 2016). It was for this reason that the 2015 FY (October 1, 2014, through September 30, 2015) was selected for current study because it was the most comprehensive data file available at the time of this study. Our final analytic sample of 4,772 TAY were selected based on the following criteria: (a) clients between age 16 and 24 who were classified as having depressive/mood disorders at the time of application for VR program; (b) received VR services; (c) had their case file closed with an employment status (either employed or unemployed); (d) reported no co-occurring condition or secondary disabilities, and (e) were not employed at the time of application for VR services. Data for Asian, Native American or Alaskan Native, and Native Hawaiian or other Pacific Islander clients were excluded from our analysis because there were few individuals in these racial/ethnic categories. Our sample of 4,772 White, Black/African American and Hispanic/Latino TAY represented approximately 6%of the 80,091 clients with depressive disorders in the 2015 RSA-911 dataset.

2.2 Variables

All data analyses were conducted with the Statistical Package for Social Sciences (SPSS, version 25). Descriptive analyses including mean, percentages, and frequencies were computed to summarize participants characteristics. For the first and second research questions, logistic regression analysis was used to determine the relationships between demographic characteristics, VR services and successful employment outcome. Three models were fitted for these research questions. The first model examined the relationship between demographic characteristics (i.e., age, gender, race, level of education, receipt of social security benefits, severity of disability) and successful employment. The second model tested the relationship between the 13 VR service variables and successful employment while controlling for the effects of demographic characteristics. A third interaction model was added to explore whether and to what extent race/ethnicity and severity of disability moderated the relationship between VR services and successful employment. Multilinear regression analysis was computed for the third research question to examine the effects of demographic and VR service variables on weekly earnings. The analysis included two models. Demographic characteristics were entered as independent variables in the first model, while the second model consisted of 13 VR service predictors, while controlling for the effects of the demographic characteristics. Alpha was set to 0.05 for all three research questions.

3.1 Characteristics of study participants

Table 2 displays details such as participant characteristics and the VR services they received. The mean age of our sample was 19 years and 6 months (SD = 2 years, 6 months). Majority of the participants were male (51.1%), White (63.8%), and held high school diploma (60%). Approximately 8.5%held a special education certificate. The majority (36%) of participants in our analytic sample were referred to the VR program from an educational institution (i.e., high school or college), whereas approximately 26%established contact with the VR program on their own. Of the 4,772 participants who received VR services, 49.9%achieved a successful employment outcome. Of those successfully employed, 50.6%were males. Procurement of successful employment by race/ethnicity was as follows: 63.8%for White participants, 21.4%for Black/African Americans, and 14.8%for Hispanic/Latino. The average weekly earnings were $318.51 (SD = $192.5). On average, male participants earned more money per week (M = $325.68, SD = $193.7). White participants had the highest weekly earnings (M = $322.02, SD = $196.7), followed by Hispanic/Latino participants (M = $316.66, SD = $204.1), and Black/African Americans (M = $291.78, SD = $157.2). On average, participants received four different types of VR services (SD = 2). Guidance and counseling, job search assistance (32%), and job placement (31%) were the three most frequently used services.

For the analysis for research questions 1 and 2, the results of Hosmer and Lemeshow, χ2 showed that the model was a good fit of the data. The Omnibus test of model coefficients χ2 [24, (N = 4772) = 807.229, p < 0.001] suggest that one or more demographic variables and VR services had significant relationship with employment outcomes. The models correctly classified 67.4%of the overall sample; the Nagelkerke R² coefficients (0.43, p < 0.05) was also statistically significant, which suggests that 43%of the variance in successful employment was explained by demographic characteristics and VR services. For the multilinear regression analysis for question 3, linear regression assumption violations were checked through visual inspection of P-P plots and scatterplots of the residuals, histogram, kurtosis and skewness of the outcome variable (i.e., weekly earnings). We also checked for multicollinearity with Variance Inflation Factor (VIF) and Tolerance statistics. Visual inspection and results (Skewness of weekly earnings = 2.26, Kurtosis of weekly earnings = 7.92; VIF < 10, tolerances > 0.2) showed no regression and multicollinearity assumptions violation (Field, 2009). The overall model suggests that, when combined, demographic variables and the receipt of certain VR services explained approximately 23%of the variance in participants’ weekly earnings. Result of the regression analysis showed a moderate correlation between demographic characteristics and weekly earning (r = 0.443) with the adjusted R² (0.197), suggesting that approximately 20%of the variability in weekly earnings was accounted for by demographic characteristics (p < 0.001). The correlation between VR services and weekly earnings was also moderate (r = 0.482), with 3%of the variability in weekly earnings was explained by VR services (p < 0.05).

4.1 Demographic factors associated with successful employment and weekly earnings

To address the first and third research questions, we examined the influence of demographic characteristics such as age, gender, race/ethnicity, significant disability, receiving social security benefits and level of education on whether or not participants achieved successful employment and higher weekly earnings. While significant associations between age, gender and successful employment did not surface, we did observe several significant relationships with other demographic variables and successful employment. For instance, post-secondary education attainment was a strong positive predictor of successful employment and higher earnings. Our results revealed that TAY who attained associate, bachelor’s or graduate degrees were more likely (56%to 85%higher odds) to achieve successful employment outcome than clients with a high school diploma. Although this was an anticipated finding, it further underscored the need to make postsecondary educational support more accessible to youth with mental health conditions, who tend to experience a high rate of school dropout, poor academic achievement, and low postsecondary degree attainment (Newman et al., 2009; Newman et al., 2011). This subgroup of youth is also less likely to receive postsecondary education support in the state-federal VR program (Honeycutt, 2017). Only 15%of the TAY in this study, for example, received some form of post-secondary education support. Yet, the demand for postsecondary education in the current labor market remains high (Carnevale & Rose, 2015). Whether acquired through two-year college, four-year college, or technical training school, postsecondary education attainment ensures the development of critical employability skills that are necessary for sustained success in the job market. VR practitioners should therefore seriously consider expanding postsecondary participation support for youth with mental health conditions who enroll in their programs.

Another important finding in this study pertained to the severity of disability. The study found that participants with a significant disability showed lower chances of success in employment and in obtaining a higher income compared to their peers with a non-significant disability. In a similar vein, individuals with severe depressive symptoms showed a greater susceptibility to work-related challenges such as absenteeism, low productivity, and functional impairment (Beck et al., 2014; Lerner et al., 2004). It therefore should come as no surprise that TAY who had a significant disability experience reduced odd of successful employment. Research suggests that interventions focused on depressive disorders’ symptoms management can lead to improved work functioning and better employment outcomes (Beck et al., 2014; Wang et al., 2007). A rehabilitation model that incorporates high quality mental health care and employment support services may prove effective for youth with depressive disorders and youth with other mental health conditions in the VR program.

We also found that participants who received social security benefits (i.e., SSI and SSDI) were less likely to achieve a successful employment outcome or higher income compared to those that did not receive such benefits. This finding corresponds with prior existing research (Kang et al., 2019; Kaya et al., 2016; Sanchez, 2018). The debate on whether social security benefits motivate or impede employment participation has been a longstanding one in the vocational rehabilitation community. Some have argued that social security benefits disincentivize employment, while others have attributed the consistent low employment participation among social security benefit recipients to issues ranging from fear of losing benefits to not understanding of how employment might negatively affect their eligibility for much-needed benefits (Bond et al., 2007; Kang et al., 2019). Participation in benefits counseling has shown promise in addressing some of these concerns while promoting employment engagement among TAY who receive social security benefits. Schlegelmilch et al. (2019), for example, reported high employment rate and income for SSI recipient TAY who received work incentive benefit counseling. The Social Security Administration (SSA) provides various work incentive programs to support recipients’ return to work while temporarily retaining their benefits but navigating the Social Security Administration (SSA) rules governing eligibility for the program can prove complicated for clients. TAY can secure crucial support through work incentive benefit counseling as they navigate SSA programs and gain insight into how stable employment and/or increased income might affect their benefits (Schlegelmilch et al., 2019). Rehabilitation practitioners working with TAY should consider embracing the practice of encouraging their clients to participate in work incentive benefit counseling.

Race/ethnicity was also a significant predictor of employment outcomes. African American and Hispanic/Latino participants were found to experience significantly lower odds of securing employment compared to their White peers. Specifically, Hispanic/Latino participants were 56 times on average less likely to make more earnings compared to White participants. Similar results were found for African American participants. Collectively, these findings reflect data reported by the Bureau of Labor Statistics, which consistently highlights lower employment rates and earnings for Hispanic/Latino and African Americans than White youth (BLS, 2010- 2020). These findings resonate with extant research in VR literature about youth with other types of disabilities (Glynn & Schaller, 2017; Ji et al., 2015).

A constellation of factors, including disparities in educational achievement, social economic gap, racial discrimination across social institutions, and the lack culturally appropriate employment support, are implicated as contributors to poor employment outcomes experienced by Black and Hispanic VR clients (Alston et al., 2007; Lukyanova et al., 2014; Olney & Kennedy, 2002). Disparities in educational attainment likely accounted for this aspect of our findings. In our study, White participants were more likely to hold postsecondary degrees than Blacks/African Americans. Additionally, we found a disparity in access to services. White participants showed more likelihood than their peers to use services that correlate with successful employment. For example, our analyses revealed that White participants were more likely than African American and Hispanic/Latino participants to receive job search services, which are strong positive predictors of a successful employment outcome. These variables likely combined to produce the racial disparity we observed in our study. The consistency of this finding with past research indicates the need for more equitable services provision for these underserved populations in the VR program, while also accounting more carefully for how race impacts access to existing services. It would be important to understand, for example, why Black/African American and Hispanic/Latino clients experience poor outcomes in the VR program. Future studies on this subgroup of VR program clients are necessary to understand their experiences with the VR program along with the facilitators to securing and maintaining employment.

4.2 VR services associated with successful employment and weekly earnings

To address the second research question and further unpack the third, we explored the effects of VR services on successful employment and weekly earnings. Our findings suggest that occupational/vocational training constitutes a major predictor of both successful employment and higher wages. Specifically, individuals who received occupational training services had 28%higher odds of obtaining successful employment and 36 times more likely to make more money than those who did not access this specific service. The reported association between occupational training and higher earnings mirrors findings of existing research involving TAY with mental health conditions (Honeycutt, 2017) and other RSA-911 data studies involving youth with varying disabilities, including ADHD, autism, and intellectual disabilities (Glynn & Schaller, 2017; Kaya, 2018; Miglore et al., 2012). Additionally, similar to the findings of Sanchez (2018) and Kaya and Chan (2017), participants in the current study who received job search and job placement services showed a higher likelihood of successful employment. Job searches can be daunting endeavors for most clients. But such endeavors pose an even more significant challenges for individuals with depressive disorders. Weak job-search skills and limited access to labor market information also constitutes major barriers for TAY with disabilities who seek employment. Access to job search services such as job application support, job analysis, contacting employers, interview preparation might have helped mitigate these challenges and increased the opportunity for positive outcomes among TAY in the current study. In light of existing research (e.g., Kaya & Chan, 2017), our findings further underline the importance of job search and placement services for people with disabilities.

We found surprising, however, that while job search and placement services appeared to help participants secure employment, such services were negatively correlated with higher weekly earnings. That is, participants who received these services and job readiness training were, on average, less likely to make higher earnings compared those who did not access these services. Our findings overlap with those from previous studies that suggest that the average earnings of clients who received job readiness training (Migliore et al., 2012) and job placement service (Schonbrun et al., 2007) were significantly lower than those who received other services. Since prior work experience is a strong predictor of higher earnings, it is plausible that the TAY who received job search and placement services possessed little to no prior work experience. Consequently, a lack of prior experience likely reduced their chance of securing high-paying jobs. Also, certain pre-employment services, such as job readiness training, are helpful to secure employment. However, this basic training does not typically cover more competitive skills that tend to be rewarded with higher wages. Given the correlative nature of this study, it cannot be definitely determined that the use of job search or placement services caused lower wages. Therefore, experimental research is needed to provide a more robust picture of how certain VR services impact the quality of employment and level of income.

Post-placement services such as on-the-job support, supported employment, on-the-job training and transportation can also play an important role in helping people with depressive disorders retain employment. As previously reported (Kaya & Chan, 2017; Sanchez, 2018) participants who received on-the-job training, on-the-job-supports and supported employment had significant higher odds of achieving successful employment. Functional impairments from depressive disorders can contribute to poor work performance, absenteeism, and low productivity (Adler et al., 2006; Lerner & Henke, 2008). It is therefore plausible that on-the job employment support services helped the participants in this study function better at work, thereby increasing the likelihood of their maintaining employment. In addition, receiving one-on-one assistance from a supported employment specialist or a job coach might have helped participants manage work-induced stress and deal with issues that potentially impacted their productivity.

Interestingly, our results revealed that the receipt of on-the-job and supported employment supports were negatively related to higher earnings. On average, TAY who received these services earned significantly lower wages. Factors such as severity of participants’ disability, prior work experience, skill level, and job type might have influenced this result. For example, individuals with more severe depressive symptoms might experience more work absenteeism. Consequently, these factors likely impact their earnings. Also, services such as on-the job support and supported employment are typically provided to people with severe disabilities that rely on additional support to perform their job responsibilities (Wehman et al., 2014). The provision of some these services at work likely impacted productivity, thus, leading to reduced earnings. Since ongoing job support services are important to individuals with disabilities, additional research is needed to shed light onto how such services impact key aspects of employment (e.g., productivity, earnings, employee relations) and how they can be improved to yield better economic outcomes.

Finally, our study found the use of diagnosis and treatment services were positively associated with both successful employment and higher earnings. Receiving diagnosis and treatment services appeared to increase the odds of achieving successful employment and higher earnings by 14 and 21 times, respectively. The effects of psychotherapy treatment on work functioning of employees with depressive disorders has not been extensively researched, but symptoms reduction from pharmacological treatment have been linked to improved work productivity and less work absenteeism (Beck et al., 2014; Rost et al., 2004). While we agree that depressive symptoms management can have a positive impact on work productivity, our findings should be interpreted with caution because information on the exact types of treatment services received are not captured in the 2015 RSA-911 dataset. Nonetheless, integrating mental health and vocational services is an effective rehabilitation strategy for people with depressive disorders (Lerner et al., 2011). Thus, we encourage VR practitioners to take mental health care into consideration when serving youth with depressive disorders, particularly because they are known to struggle with accessing and using mental health treatment services on their own.

4.3 Implications for research and practice

Findings from this study have implications for future research despite the limited research available on this topic. First, continued analysis of the RSA-911 dataset is needed to provide deeper insights into the utility of the state-federal VR program for youth with depressive disorders. Second, excluded from this study are several factors that influence employment outcomes of TAY with depressive disorders. Depressive symptoms, length of depressive episode, socioeconomic status, social and family support, side effects of medication, job accommodation and work environment are potential factors that influence work performance, work productivity and employment maintenance. In-depth exploration of these factors could yield crucial insights into how they shape employment experience and outcomes. Information gleaned from such research could reveal additional strategies for effectively serving clients with depressive disorders in the VR program.

The implications of this extends to service delivery and VR practice. We have illustrated the promise of job search, job placement, treatment, on-the job training, occupational training, and supported employment services for TAY with depressive disorders. Although we did not investigate the causal relation between these services and successful employment/higher earnings, our findings do suggest these services are correlated with improved employment outcomes for these youth. The usefulness of these services for TAY with depressive disorders could be further improved upon and evaluated in future interventions. We found, as have previous studies (Honeycutt, 2017), low rate of postsecondary degree attainment and postsecondary education services usage. There are potential benefits in VR programs that prioritize postsecondary education support for enrolled young people. The significant disparities in employment outcomes based on race and severity of disability underscores the need for VR practitioners to pay closer and a critical attention to the hidden challenges faced by clients of color as well as those with severe disabilities in their efforts at securing and retaining of employment. The VR program could expand effective strategies for practitioners who work with this subgroup of VR clients. Expanding cultural competency training for practitioners, using bilingual practitioners, advocating for family involvement, and adopting community-based rehabilitation model for those with significant disabilities are helpful strategies for equitably improving employment outcomes.

4.4 Limitations

This study has limitations that should be considered when interpreting its findings. The first lies in the self-report nature of clients’ information in the RSA-911 dataset. The dependent variables in this study were recorded in the RSA database based on information provided by clients to VR counselors. Second, the definition of some VR services provided in the RSA manual are often broad, making it difficult to determine, in some cases, the exact type of services that TAY received from the program. Third, our definition of successful employment was limited to securing and maintaining employment for at least 90 days. This scope allowed us to reduce the data analyzed to a manageable size. Future studies should explore the long-term benefits of the VR services on the sustainability of employment for TAY with depressive disorders beyond the three-month time period. Finally, we analyzed only individual level variables considered relevant to the targeted outcome. Other variables that contributed to the variability in employment outcomes may have been missed.