The COVID-19 pandemic’s influence on employment outcomes of veterans enrolled in VA healthcare vocational rehabilitation

Abstract

BACKGROUND:

Employment has been shown to be the fourth most commonly reported need for veterans and their families, and unemployment rates have ranged from 1–69% dependent on the mental health diagnosis. Complications from the COVID-19 pandemic have had a significant impact on psychological functioning, and social isolation has led to increased psychiatric symptoms. Vocational rehabilitation is an intervention provided to Veterans in an attempt to remove barriers to employment while also increasing involvement in gainful work activity.

OBJECTIVE:

The purpose of the current study was to examine the impact that COVID-19 has had on employment rates at discharge for veterans with mental health disorders participating in a VHA vocational rehabilitation program.

METHODS:

An outcome-based, summative program evaluation design was used to assess the quality of Veterans served (2016-2021) at a vocational rehabilitation program served at a medical center located in VISN 12 of the U.S. Department of Veteran Affairs.

RESULTS:

Findings showed that veterans with Bipolar and Psychosis were less likely to discharge with employment (not considering COVID-19).

CONCLUSION:

No significant meaningful differences existed in employment rates when comparing pre/post March 2020 (official start of COVID-19 pandemic) for veterans with psychiatric diagnoses.

Keywords

Vocational rehabilitation veterans employment veteran affairs compensated work therapy

1 Introduction

Employment has been shown to be the fourth most reported need for Veterans and their families (Van Slyke & Armstrong, 2020). Identified employment barriers include limited interviewing skills, and difficulty in managing the impact of stigma, transition of military skills to civilian jobs, and locating services within the Veteran Health Administration (VHA) such as rehabilitation and training (Humensky et al., 2013; Keeling et al., 2018; Perkins et al., 2019; Schulker, 2017). Significant employment barriers for Veterans with mental health issues exist, such as legal issues, co-occurring substance/alcohol use disorders, finding a career path, dealing with sustained injuries and disabilities, housing/homelessness, and social interaction and connection (Finlay et al., 2014). Not only having these issues existed historically, the COVID-19 pandemic has led to an increase in mental health symptomology (Tran et al., 2022).

Other issues stemming from the COVID-19 pandemic include concern that isolation due to lack of employment would increase harm in psychological health and well-being (Adams et al., 2021; Bishop & Rumrill, 2021; Rumrill et al., 2021; Umucu, 2021). Within the VHA, the use of telemedicine (i.e., VA Video Connect [VVC]) showed some effectiveness in the delivery of medical and mental health services (Rosen et al., 2020). However, interventions that improve employment outcomes (e.g., vocational rehabilitation) have not been assessed for disruption to service-delivery. VHA vocational rehabilitation is a mental health service-delivery model/treatment designed to help veterans obtain and maintain competitive employment (Stevenson et al., 2022; U.S. Department of Veteran Affairs, 2019).

VHA vocational rehabilitation is a program offered by all medical centers within the VHA health care system (Wyse et al., 2018). As aforementioned, the program is an evidence-based service-delivery model designed to help veterans obtain and maintain employment compatible with their knowledge, skills, abilities, interests, and functional abilities while also reducing barriers that prevent achievement of their employment goals. Recent literature has focused on the challenges that the COVID-19 pandemic has created for VR service-delivery such as longer waitlists, dissatisfaction with overall services and communication issues between the assigned VR counselor, lack of specific training (Levine et al., 2022) and concern that isolation due to lack of employment will increase harm in psychological health and well-being (Adams et al., 2021; Bishop & Rumrill, 2021; Rumrill et al., 2021; Umucu, 2021). However, research is limited which examines the impact that psychiatric disorders and COVID-19 has had on employment at discharge for veterans with psychiatric disorders.

Earlier research showed unemployment rates differing across mental health diagnoses (Wenzlow et al., 2011), including anxiety (5%), bipolar (2%), depression (12%), post-traumatic stress disorder (9%), schizophrenia (1%), and substance use disorder (4%). Recent research has shown unemployment rates as high as 69% for Veterans with schizophrenia (Lin et al., 2022), 29.2% for those diagnosed with SUDs (Bond et al., 2022), 18% for PTSD (Lin et al., 2022; Richman, 2022). In comparison, the unemployment rate for all veterans ranged between 4.4–6.5 percent (2020-2021) and 5.3 percent for non-veterans in 2021 (U.S. Bureau of Labor Statistics, 2021). The purpose of the current study was to examine the impact that COVID-19 has had on employment rates at discharge for veterans with mental health disorders participating in a VHA vocational rehabilitation program. The following research questions guided the current study:

To what extent has COVID-19 impacted employment rates at discharge for Veterans with psychiatric disorders and enrolled in VHA VR?

To what extent do employment rates differ between pre COVID and during COVID by type of psychological disorder?

2 Methods

2.1 Data source and procedures

The current study involved analyzing pre-existing quality assurance data from a VHA vocational rehabilitation program located in a medical center in the VA Great Lakes Health Care System. Specifically, the U.S. is geographically divided into 18 Veterans Integrated Service Networks (VISN), which are also known as regional systems of care (U.S. Department of Veteran Affairs, 2021). Since the current study was retrospective in nature, the U.S. Department of Veteran Affairs’ Institutional Review board (IRB) provided a recommendation that the study receive exempt status. The co-author’s institution was used for additional IRB endorsement (approval #13460) to verify that institutional support was provided for the current study. The dataset analyzed in the current study includes information from all veterans served between 2016 and 2021 in the VHA vocational rehabilitation program within a VA Medical Center in VISN 12. As a referral for VHA vocational rehabilitation services is made, all data (e.g., gender, date of birth, race/ethnicity) were collected by the assigned vocational rehabilitation counselor and entered into a Microsoft Access database (only accessible by the vocational rehabilitation program staff). Information is collected in the form of a consult reply, intake interview, and by examining the Computerized Patient Record System (CPRS) and Joint Legacy Viewer (JLV), which includes medical records and data (e.g., medical, and mental health diagnoses) at the local VA medical center and all other VA medical centers where care was provided.

Intake information collected included variables contained within several primary categories, including basic demographic information, treatment team members, educational and employment history, core vocational objectives, family/culture/community background, military service, legal issues, medical and mental health diagnoses and treatment, and employment goals (long-term/short-term). Once the dataset was obtained, the primary author verified the information gathered for accuracy by reviewing medical progress notes and charts (via CPRS and JLV). The data was coded and split into pre-COVID / COVID by reviewing referral dates (when examining the program enrollment outcome variable) and discharge dates (when examining employment at discharge outcome variable) for veterans served prior to and after the date of March 11, 2020. This was the date that the World Health Organization characterized COVID-19 as a pandemic (Yale Medicine, 2020). Veterans that started in the program prior to the pandemic and were still being served during the pandemic were not included in the analysis. Descriptive data for study participants is provided in Table 1. Most of the veterans reported being of the male gender (87.3%, n = 1313), were white non-Hispanic (40.4%, n = 655) or black non-Hispanic (44.6%, n = 724), and held a high school diploma or GED (96%, n = 1348). All data from the intake interview are recorded in a Microsoft Access Spreadsheet, and this was converted to an excel file.

Table 1
Descriptive data for study participants

Total reported Percent Mean Std. Dev

Employment at discharge 1622 43.7

CWT status coded 1622

Discharge date was Post COVID (3/11/20) 1008 7.6

CWT Program code 1608

Community-based employment 296 18.4

Supported employment 165 10.3

Transitional work 1120 69.7

VocA 9 0.6

TBI 14 0.9

Sup Ed 4 0.2

Age 1600 55.40 13.069

Homeless Status Code 1579 2.5

Race/Ethnicity Code 1622

White 655 40.4

Black – non-Hispanic 724 44.6

Hispanic – White 122 7.5

Asian 16 1.0

Nat. Haw – Pac Isl 5 0.3

AIAN – 1^st Nat 6 0.4

Other 29 1.8

Not reported 65 4.0

Gender - Male 1313 87.3

Years of education (up to 20) 1575 13.95 2.022

HS Diploma / GED 1348 96.0

Felony – reported 1583 19.1

Psychiatric disorders

Depression diagnosis 1622 41.4

Anxiety diagnosis 1622 16.0

Adjustment disorder diagnosis 1622 9.7

PTSD diagnosis 1622 30.6

Bipolar diagnosis 1622 8.2

Schizophrenia diagnosis 1622 1.1

Schizoaffective 1622 1.5

Psychosis 1622 1.3

Psychiatric Disability Indicated – at least 1 1622 73.2

	Total reported	Percent	Mean	Std. Dev
Employment at discharge	1622	43.7
CWT status coded	1622
Discharge date was Post COVID (3/11/20)	1008	7.6
CWT Program code	1608
Community-based employment	296	18.4
Supported employment	165	10.3
Transitional work	1120	69.7
VocA	9	0.6
TBI	14	0.9
Sup Ed	4	0.2
Age	1600		55.40	13.069
Homeless Status Code	1579	2.5
Race/Ethnicity Code	1622
White	655	40.4
Black – non-Hispanic	724	44.6
Hispanic – White	122	7.5
Asian	16	1.0
Nat. Haw – Pac Isl	5	0.3
AIAN – 1^st Nat	6	0.4
Other	29	1.8
Not reported	65	4.0
Gender - Male	1313	87.3
Years of education (up to 20)	1575		13.95	2.022
HS Diploma / GED	1348	96.0
Felony – reported	1583	19.1
Psychiatric disorders
Depression diagnosis	1622	41.4
Anxiety diagnosis	1622	16.0
Adjustment disorder diagnosis	1622	9.7
PTSD diagnosis	1622	30.6
Bipolar diagnosis	1622	8.2
Schizophrenia diagnosis	1622	1.1
Schizoaffective	1622	1.5
Psychosis	1622	1.3
Psychiatric Disability Indicated – at least 1	1622	73.2

2.2 VHA vocational rehabilitation structure and service-delivery

The VHA vocational rehabilitation program, also known as compensated work therapy (CWT), is required at every medical center across the country (U.S. Department of Veteran Affairs, 2019). As stated in VA Policy Directive 1163.02, all programs are mandated to provide two specific programs, including transitional work (TW) and supported employment (SE). TW is marketed as a time-limited (6-month lifetime), noncompetitive employment through worksite placement within the medical center. Before assigning a veteran to a work site, the vocational rehabilitation counselor conducts a thorough assessment of the veteran’s employment barriers, vocational interests, skills, and functional abilities. Once this assessment is completed, the vocational rehabilitation counselor assesses their mental health diagnoses (if one exists) and determines if they have had active psychosis in the past 12-months. If the veteran has an active psychosis diagnosis, they are only eligible for services provided from the SE program. If the veteran has a serious mental health disorder (e.g., Bipolar I) but no active psychosis in the past 12 months, they are assessed for whether TW or SE is more clinically appropriate.

The SE program uses the Individual Placement and Support (IPS) model to assist veterans with serious mental health disorders in obtaining competitive employment prior to training (place then train), versus traditional supported employment models emphasizing train than place into employment. The intensive individualized supports offered within the SE program include (U.S. Department of Veteran Affairs, 2019a; IPS Employment Center, 2022):

Zero Exclusion: One cannot and will not be excluded from employment services due to job readiness, employment history, level of disability, employment goal, legal history, or vocational goal.

Preferences: The services provided to the individual are established through their individualized interests, strengths, and skills.

Competitive Employment: Individuals are expected to apply to jobs where pay is at least minimum wage within the local community.

Systematic Job Development: Vocational Counselors assist with making relationships with employers within the community that correlate with the persons experience and/or interest, which often leads to possession of the job.

Rapid Job Search: Within 30 days of entering the program the individual is expected to search for employment options and contact employers.

Integrated Services: The individuals clinical treatment team will be included in the process to ensure the proper supports are given to help the person reach their goals.

Benefits Counseling: Vocational Counselors are expected to help link the individual with the necessary resources for benefits counseling to ensure an informed choice can be made in relation to their employment goal.

Time Unlimited Supports: Vocational Counselors will continue to provide follow along employment supports for however long the person wants and or needs supports.

The program analyzed has a 6-month lifetime eligibility requirement for the TW program. Specifically, veterans that have not yet been enrolled in TW (at the specific VHA Medical Center or at another VA Medical Center) and do not have active psychosis (or other serious mental health disorder that would result in SE being more clinically appropriate) are eligible for TW. However, if a veteran is deemed inappropriate for SE, and has already receive TW services in the past, they may be eligible for the community-based employment services (CBES) program. Under VA policy directive 1163.02, this is an optional program that is strongly encouraged to be offered at all VHA vocational rehabilitation programs (U.S. Department of Veteran Affairs, 2019). CBES is specifically designed for veterans with sporadic employment, trouble maintaining employment, or have barriers associated with the veteran’s ability to conduct job searches. While CBES is also based on principles of the Individualized Placement and Support model, it utilizes a flexible approach in services. The key differential when deciding eligibility of programs between SE and CBES is if the Veteran has a diagnosis relating to psychosis, serious mental illness, and or a physical disability who need intense support relating to employment.

2.3 VHA vocational rehabilitation program inclusion/exclusion

There are some reasons why a Veteran may be denied program enrollment into the VHA VR program (e.g., unable to contact after the consult is placed –three attempts made, obtained a job prior to program entry, pursuing supplemental security income or social security disability insurance [SSI/SSDI], future medical procedures preventing a delay in ability for service or unable to obtain medical clearance from the medical/psychiatric provider, or not interested in obtaining competitive employment). If a Veteran consistently misses meetings (AWOL status –three missed meetings with no contact –a letter is also sent to the Veteran indicating they have 10 business days to contact their VR case manager), shows misconduct (e.g., sexual harassment, physical altercations/violence), obtains employment, transfers to another VA medical center, or experiences other medical/psychological issues resulting in not obtaining medical clearance, they will be discharged.

2.4 Data analysis –predictor and outcome variables

For the study, a between-group design (Gravezetter & Forzano, 2009) was used to compare employment outcomes (i.e., discharged with employment, discharged without employment) from their VR program while examining the impact of the COVID-19 cut-off date. As aforementioned, the date of March 11, 2020, is the date when WHO declared the pandemic. Each mental health disorder was dichotomized (i.e., yes/no), and the outcome variables were either enrolled for services (i.e., yes/no) or employment at discharge (i.e., yes/no). For obvious reasons, we were not able to randomly sort the two groups into control and experimental groups, so this analysis is a non-experimental design. Through regression analysis, an attempt was made to control for the effect of a number of variables which were likely to impact participant employment outcomes, in addition to participation in the VR program. Since the employment outcome variable was binomial (employed or not), binary logistic regression was used to analyze the data. The regression analysis was followed with a comparative descriptive analysis. Since date variable and outcome dependent variable were both nominal, a chi-square was employed to analyze the differences between the group outcomes. To answer the second research question, multiple chi-squares analyses using layering with each of the psychological conditions of interest was used. A layering technique allows for analyses per subgroup (layering technique is noted in results section for analysis involving this technique).

3 Results

The binary logistic regression model was statistically significant, though the model only accounts for about 12.1% of the change in the dependent variable outcome (Nagelkerke R2 = .121, p < .001) (see Table 2). Since active psychosis (i.e., yes, no) is a determinant of the SE program, we analyzed this predictor variable and found that veterans with active psychosis were less likely to discharge with employment. Similarly, we found veterans diagnosed with bipolar disorder were less likely to discharge with employment. According to the results of regression, COVID status is significantly associated with job placement [B = –1.310, Exp(B) = 0.270, p < 0.01]. The relationship is negative meaning that the likelihood of employment at the end of the program was significantly lower between pre-COVID to post-COVID. This represents the difference between participating in the VHA vocational rehabilitation programs pre-COVID (level 0, the reference category), and participating post-COVID (level 1). That is, holding all other variables in the equation constant, when shifting from “pre-COVID” to “post-COVID”, the odds of being employed at program completion decrease by 1.310. Of the psychological disorders, only the adjustment disorder diagnosis yielded statistically significant differences pre COVID and during COVID, but the clinical significance is limited (note: only 5 Veterans were enrolled during COVID). Table 3 provides the employment outcome comparisons for the pre-COVID and post-COVID participants.

Table 2
Bivariate regression results for VA program clients at the sites with covariates and program employment at discharge outcomes

Job placement (n = 1612)

B SE Exp(B)

Pre/Post COVID –1.310 0.423 0.270

CWT program - CBES (ref. category)

Supported employment –0.225 0.287 0.799

Transitional work 0.344 0.187 1.410

Vocational assistance 0.708 1.459 2.030

Supported employment - TBI –20.525 22345 0.000

Supported education –19.079 40193. 0.000

Age –0.003 0.006 0.997

Homeless status – no/yes 0.247 0.407 1.280

White (reference category)

Black non-Hispanic –0.312 0.161 0.732

Hispanic - White –0.198 0.299 0.821

Asian 1.094 0.720 2.985

Nat. Haw. – Pacific Islander 0.745 1.256 2.107

AIAN/1^st Nations 20.987 23128 1301492356

“Other” –0.047 0.485 0.954

Race/Ethnicity not reported –0.879 0.594 0.415

Years of education (up to 20) 0.109 0.039 1.115

HS diploma/GED - no/yes 0.304 0.425 1.355

Felony status - no/yes –0.487 0.195 0.615**

Military discharge conditions – not/met –0.423 0.551 0.655

Depression diagnosis - no/yes 0.041 0.156 1.041

Anxiety diagnosis - no/yes –0.404 0.234 0.668

Adjustment disorder diagnosis – no/yes 0.300 0.248 1.350

PTSD diagnosis - no/yes 0.099 0.167 1.104

Bipolar diagnosis - no/yes –0.808 0.321 0.446*

Schizophrenia diagnosis - no/yes –1.325 1.114 0.266

Schizoaffective - no/yes 0.119 0.947 1.127

Psychosis - no/yes –1.621 0.807 0.198*

Constant –1.377 0.869 0.252

Nagelkerke R2 (change) 0.121***

	Job placement (n = 1612)
Pre/Post COVID	–1.310	0.423	0.270**
CWT program - CBES (ref. category)
Supported employment	–0.225	0.287	0.799
Transitional work	0.344	0.187	1.410
Vocational assistance	0.708	1.459	2.030
Supported employment - TBI	–20.525	22345	0.000
Supported education	–19.079	40193.	0.000
Age	–0.003	0.006	0.997
Homeless status – no/yes	0.247	0.407	1.280
White (reference category)
Black non-Hispanic	–0.312	0.161	0.732
Hispanic - White	–0.198	0.299	0.821
Asian	1.094	0.720	2.985
Nat. Haw. – Pacific Islander	0.745	1.256	2.107
AIAN/1^st Nations	20.987	23128	1301492356
“Other”	–0.047	0.485	0.954
Race/Ethnicity not reported	–0.879	0.594	0.415
Years of education (up to 20)	0.109	0.039	1.115**
HS diploma/GED - no/yes	0.304	0.425	1.355
Felony status - no/yes	–0.487	0.195	0.615**
Military discharge conditions – not/met	–0.423	0.551	0.655
Depression diagnosis - no/yes	0.041	0.156	1.041
Anxiety diagnosis - no/yes	–0.404	0.234	0.668
Adjustment disorder diagnosis – no/yes	0.300	0.248	1.350
PTSD diagnosis - no/yes	0.099	0.167	1.104
Bipolar diagnosis - no/yes	–0.808	0.321	0.446*
Schizophrenia diagnosis - no/yes	–1.325	1.114	0.266
Schizoaffective - no/yes	0.119	0.947	1.127
Psychosis - no/yes	–1.621	0.807	0.198*
Constant	–1.377	0.869	0.252
Nagelkerke R2 (change)	0.121***

Note: *p≤0.05; **p≤0.01; ***p≤0.001; CBES = Community-Based Employment Services.

Table 3

Chi-square Comparisons: Pre-COVID vs COVID for participants at the sites

	Employment at discharge	Cramer’s V
All Participants
Pre-COVID	404/931
COVID	20/77	0.094**
(Total)	424/1008
Depression diagnosis
Pre-COVID	165/375
COVID	10/33	0.075
Anxiety diagnosis
Pre-COVID	44/116
COVID	4/13	0.045
Adjustment disorder diagnosis
Pre-COVID	50/98
COVID	0/5	0.219*
PTSD diagnosis
Pre-COVID	106/251
COVID	9/32	0.091
Bipolar diagnosis
Pre-COVID	20/65
COVID	1/10	0.157
Schizophrenia diagnosis
Pre-COVID	1/7
COVID	0/2	0.189
Schizoaffective
Pre-COVID	3/8
COVID	0/3	0.375
Psychosis
Pre-COVID	2/12
COVID	0/2	0.167
Combined - At least one disorder diagnosis
Pre-COVID	284/653
COVID	15/64	0.116**

Note: *p≤0.05; **p≤0.01; ***p≤0.001 indicates statistically significant differences.

Since the data were nominal, a chi-square was employed for the analysis. To answer the second research question, the chi-square analysis was layered by psychological disorder as well. Differences were significant overall and for adjustment disorder. Given the small number of post-COVID participants, there was concern that statistical differences would be muted, so a measure combining all of the disorders was used. As anticipated, this proved significant as well. All three differences showed higher rates of employment at program completion pre-COVID compared to post-COVID. A Cramer’s V was utilized to illustrate strength of association. None indicated more than a small relationship, though that is not surprising given the comparatively small number of post-COVID participants.

4 Discussion

The purpose of the current study was to evaluate the impact that COVID-19 has had on employment rates at discharge for veterans with mental health disorders participating in a VHA vocational rehabilitation program. Not surprisingly, Veterans served and discharged during COVID-19 experienced lower job placements/employment at discharge compared to Veterans served pre-COVID. A multitude of factors could explain the differences, including (1) transportation-related barriers –bus schedules, ride sharing, and other means of transportation may have been significantly reduced during COVID, (2) limited employment options –places of employment may have reduced their workforce or lowered hours of operation, (3) utilization of alcohol or other substances to cope with self-isolation, increase of psychological symptoms, or mental health treatment access issues. When examining the impact of mental health diagnoses on employment at discharge for only Veterans served during COVID-19, adjustment disorders were the only psychiatric diagnosis that resulted in lower employment rates at discharge compared to Veterans without these diagnoses.

Evidence has shown that Veterans with PTSD try to resolve their problems by themselves without following-up with mental health care (Graziano & Elbogen, 2017) and Veterans tend to not engage in treatment across several mental health disorders (Kline et al., 2022). Perhaps Veterans with psychological issues were discharging from services prior to successfully obtaining competitive employment, as they tried to resolve their issues without further mental health treatment. Another factor that was not the consideration of the current study was the immediacy of program engagement. Research has shown that earlier engagement in mental health treatment has better outcomes of Veterans following-up for future appointments/care (Knight et al., 2022). Although engagement immediacy and meeting frequency could explain disparities in Veterans with mental health disorders discharging without employment and should be considered as a covariate, the authors of the current study will pursue additional research on the impact of this variable.

Richman (2022) found 18% employment rates for Veterans diagnosed with PTSD, yet the current study findings did not match prior research. It was somewhat surprising that employment rates at discharge did not differ for Veterans with and without each psychiatric disability type (with the exception of adjustment disorder). These findings conflict with prior unemployment rates as high as 18% for Veterans diagnosed with PTSD, and 69% for Veterans diagnosed with Schizophrenia. However, prior research showed longer waitlists, dissatisfaction with overall services and communication issues between the assigned VR counselor in other studies (Levine et al., 2022). Given the concern that isolation due to lack of employment will increase harm in psychological health and well-being (Adams et al., 2021; Bishop & Rumrill, 2021; Rumrill et al., 2021; Umucu, 2021), research should continue to investigate factors that influence program acceptance/enrollment rates and develop interventions to decrease the number of Veterans that do not engage in services. These inconsistent findings could be attributed to the low frequency of Veterans evaluated post March 2020, and future research should focus on two factors related to this concept: (1) duration/days between consult and program entry and the impact of COVID-19, and (2) is length of treatment longer post-March 2020 than pre-COVID.

5 Conclusions

The U.S. Department of Veteran Affairs has focused much attention on improving access and service-delivery for Veterans receiving healthcare within the VHA. Prior studies have shown disparities in program enrollment rates for Veterans based on several factors (Sprong et al., 2022a; 2022b; 2023), and the current study showed lower employment rates for Veterans with Bipolar or Active Psychosis (no differences existed within these psychiatric diagnoses when compared pre COVID and during COVID). Evidence based interventions such as supported employment has been used to serve Veterans with severe mental illness (e.g., Bipolar, Active Psychosis, Schizoaffective Disorder). However, disparities in employment rates at discharge still existed for Veterans with this population, regardless of pre COVID or during COVID.

National studies will assist in determining if these disparities exist on a larger scale, and thus would indicate if additional interventions are needed to improve employment rates at discharge. The supported employment (SE) model currently mandates the use and implementation of the Individual Placement and Support Model (U.S. Department of Veteran Affairs, 2019). One component of SE is that Veterans can stay enrolled in the program (follow-along supports) even after obtaining employment. If a Veteran loses employment while enrolled in the program, they may choose to be discharged, resulting in a negative outcome. Future research should also consider examining if concurrent mental health and/or substance use disorder treatment impacts program enrollment rates and employment rates at discharge, while also examining the frequency/intensity of VR meetings while enrolled in the VHA VR program.

Another important consideration for future research is examining the impact of COVID-19 on program acceptance/enrollment for Veterans with psychiatric disorders. We intended to include this analysis within the current study, yet the frequencies of mental health diagnoses post March 11, 2020, data was too small to perform any meaningful analyses. It was expected that there would be some impact, as prior research has shown disparities when analyzing the impact of COVID-19 for other populations (Wong et al., 2021; Frank, 2020; Ching et al., 2022; Strauser et al., 2021; Tichy et al., 2022). Furthermore, prior research has shown that COVID-19 has resulted in longer waitlists, dissatisfaction with services and communication issues between assigned vocational rehabilitation counselor, and a variety of other concerns (Levine et al., 2022) that negatively impacts psychological health and well-being (Umucu, 2021; Rumrill et al., 2021; Adams et al., 2021; Bishop & Rumrill, 2021).

5.1 Limitations

There were limitations that existed within the current study. The data analyzed in the current study was at one VA medical center, thus limiting the external validity associated with the study findings. Although VA policy directive 1163.02 mandates the program structure for SE, TW, CBES, research has not yet analyzed policy adherence and implementation differences among VHA vocational rehabilitation programs across the U.S. Thus, it would be difficult to randomly select vocational rehabilitation programs and have conclusive evidence due to significant variability in how services are provided (and several covariates/confounding variables). We believe however, that the findings of this study may be useful for suggesting additional research at other locations. Second, the relatively low number of individuals in the study means that the analysis is less likely to indicate statistically significant differences. This is less of an issue for the regression analyses using the entire group but was a potential hindrance for the chi-square analysis of the smaller subsets by condition. Last, we had hoped to analyze the impact of COVID-19 on program acceptance/enrollment using this dataset. However, we could not, due to low frequency of Veterans with psychological diagnoses post-March 2020. We hope to revisit this if we are able to obtain more longitudinal data from the site.

Footnotes

Acknowledgments

None to report.

Conflicts of interest

The authors report that there are no conflicts of interest.

Ethics statement

This research was classified as exempt from ethical approval by the Department of Veteran Affairs’ Institutional Review Board (IRB) since the data was collected as a part of quality improvement/assurance. Participants were not recruited for the current study.

Funding

There was no funding associated with this study.

Informed consent

Informed consent was not necessary from individual Veteran patients given that this study involved analyzing pre-existing data.

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	Job placement (n = 1612)
	B	SE	Exp(B)
Pre/Post COVID	–1.310	0.423	0.270**
CWT program - CBES (ref. category)
Supported employment	–0.225	0.287	0.799
Transitional work	0.344	0.187	1.410
Vocational assistance	0.708	1.459	2.030
Supported employment - TBI	–20.525	22345	0.000
Supported education	–19.079	40193.	0.000
Age	–0.003	0.006	0.997
Homeless status – no/yes	0.247	0.407	1.280
White (reference category)
Black non-Hispanic	–0.312	0.161	0.732
Hispanic - White	–0.198	0.299	0.821
Asian	1.094	0.720	2.985
Nat. Haw. – Pacific Islander	0.745	1.256	2.107
AIAN/1^st Nations	20.987	23128	1301492356
“Other”	–0.047	0.485	0.954
Race/Ethnicity not reported	–0.879	0.594	0.415
Years of education (up to 20)	0.109	0.039	1.115**
HS diploma/GED - no/yes	0.304	0.425	1.355
Felony status - no/yes	–0.487	0.195	0.615**
Military discharge conditions – not/met	–0.423	0.551	0.655
Depression diagnosis - no/yes	0.041	0.156	1.041
Anxiety diagnosis - no/yes	–0.404	0.234	0.668
Adjustment disorder diagnosis – no/yes	0.300	0.248	1.350
PTSD diagnosis - no/yes	0.099	0.167	1.104
Bipolar diagnosis - no/yes	–0.808	0.321	0.446*
Schizophrenia diagnosis - no/yes	–1.325	1.114	0.266
Schizoaffective - no/yes	0.119	0.947	1.127
Psychosis - no/yes	–1.621	0.807	0.198*
Constant	–1.377	0.869	0.252
Nagelkerke R2 (change)	0.121***