evidence assessment library
Job Training Programs & Job Placement Supports

Job Training Programs & Job Placement Supports

There is sufficient evidence that job training programs and job placement supports are associated with improved social outcomes.

This assessment was made possible through support from Elevance Health. HealthBegins retains full editorial independence, and the content herein reflects its sole views and conclusions.

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Study Characteristics and Contextual Tags

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Impact Assessment

The findings below synthesize the results of the studies on job training programs and job placement supports across three domains of measurement:

  • Healthcare Cost, Utilization & Value: More evidence is needed on the impact of job training programs and job placement supports on outcomes pertaining to healthcare costs, utilization, and value. None of the identified studies assessed this outcome.
  • Health: More evidence is needed on the impact of job training programs and job placement supports on health outcomes. None of the identified studies assessed this outcome.
  • Social: There is sufficient evidence across systematic reviews, randomized controlled trials, and observational studies that job training programs and job placement supports can improve social outcomes, particularly employment rates and earnings among adults with low-incomes. However, effects are generally modest and may attenuate over time. Medicaid-specific voluntary employment programs show promising but more limited results, with low uptake and engagement representing key implementation challenges.
Background of the Need / Need Impact on Health

Employment is a foundational social driver of health, providing not only income but also facilitating access to healthcare coverage in many cases. In 2019, 71% of civilian workers had access to employer-sponsored health insurance[1]. Without employment, individuals are more likely to delay or forgo care. People without employment experience about 2.5 times as many preventable emergency care visits as those who are employed[2]. This translates directly into avoidable healthcare utilization costs.

Sudden job loss and sustained unemployment are associated with a wide range of poor health outcomes, notably mental health conditions such as depression, risk of suicidality, psychological distress, anxiety, and substance misuse[3],[4], as well as physical conditions, such as cardiovascular illnesses and the overall risk of dying[5].

Supporting employment through job training programs and job placement supports has the potential to address a root cause of both coverage instability and preventable healthcare utilization.

Background on the Intervention

Job training programs and job placement supports may take a wide range of approaches, including job interview training, resume development, networking skills, mentorship and coaching, supported employment, and structured employer engagement[6],[7]. They may be delivered across a wide range of institutions such as community colleges, prisons, secondary and postsecondary institutions, and community-based organizations. They may also incorporate both online and virtual platforms[8],[9].

Traditional Medicaid does not directly reimburse for general job training programs and job placement supports as a standalone benefit. However, Medicaid-funded care coordination and case management may include supports with a connection to employment. In addition, states may cover non-traditional services, such as employment supports, through managed care flexibilities and waivers[10]. Medicaid agencies are also working to connect Medicaid enrollees with other state programs that support connection to employment. The One Big Beautiful Bill Act requires that no later than 2027, most non-disabled adults (aged 19-64) without dependent children (commonly referred to as the expansion population) must complete 80 hours per month of qualifying community engagement (work, community service, work program, or educational program) to maintain Medicaid eligibility[11]. This requirement may increase some Medicaid agencies’ interest in supporting connectivity to employment supports and services. 

Individuals with disabilities may receive employment support from Medicaid programs through a number of avenues including the Medicaid rehabilitation option, home- and community-based services authorities, Section 1115 demonstration waivers, and in-lieu-of services (ILOS)[6]. For individuals with serious mental illnesses, supported employment models such as Individual Placement and Support (IPS) offer a more established reimbursement pathway. IPS is supported by over two dozen randomized controlled trials, and its return on investment is more than three times higher than traditional vocational services[12]. Secondary benefits of supported employment include reduced psychiatric hospitalizations, fewer months of homelessness or incarceration, and improved quality of life[6]. 

As health plans face growing accountability for social needs screening and referral, job training programs and job placement supports could be a meaningful opportunity to address a foundational driver of economic instability and its downstream effects on healthcare utilization, health, and overall wellbeing.

Additional Research and Tools
Evidence Review
Note: The vocabulary used in the table is the same terminology used in the study in order to preserve the integrity of the summary. 
Study
Population
Intervention Summary
Type of Study Design
Outcomes

Temporary Assistance for Needy Families (TANF) recipients in Los Angeles County. Adults with low incomes subject to welfare-to-work requirements.

Transitional subsidized employment program comparing two models: (1) Paid Work Experience (PWE) in public/nonprofit sector placements; (2) On-the-Job Training (OJT) in private for-profit sector placements; (3) Control group receiving standard welfare-to-work services. Time-limited subsidized placements designed to increase employment stability, earnings, and job quality.

Randomized Controlled Trial (RCT). N=2,622 participants randomly assigned to PWE, OJT, or control.

Social: PWE participants experienced higher employment rates and earnings during the first year post-random assignment compared to control. Some impacts persisted through 30 months, particularly for work intensity (hours worked). Evidence showed improved job quality at 30 months for PWE participants, including higher likelihood of full-time work and employer-sponsored health insurance. OJT effects were smaller and less consistent. Impacts attenuated over time but demonstrate short-term gains from subsidized employment.

Medicaid expansion enrollees ages 19–49 in Arkansas subject to voluntary employment referral under the Arkansas Works (ARWorks) Section 1115 demonstration waiver.

Passive voluntary referral program in which all ARWorks Medicaid enrollees received written notification directing them to utilize employment and training services offered by the Arkansas Division of Workforce Services (DWS). No active outreach, case management, or job training was provided by the Medicaid program directly. Participants could access DWS services including job search assistance, skills training, and resume support voluntarily.

Descriptive study (state administrative data). Program-wide administrative tracking of DWS service utilization among all referred ARWorks enrollees from January–October 2017. N not reported; however, the sample reflects all ARWorks beneficiaries referred during the period. In nearby timepoints, the ARWorks population was approximately 170,000 individuals, suggesting a large program-wide sample.

Social: From January to October 2017, only 4.7% of ARWorks beneficiaries acted upon the referral and utilized DWS services. Of those who engaged, 23% subsequently obtained employment. The state attributed low uptake in part to insufficient outreach and education infrastructure. The evaluation design noted that income is likely under-reported and that beneficiaries needed more active assistance navigating available services.

Medicaid enrollees in Ohio, Indiana and Georgia.

CareSource JobConnect provides employment assistance to non-elderly adults enrolled in Medicaid, helping them to prepare for a job search, obtain employment and succeed in the workplace.

Return on investment (ROI) analysis.

Social: Ohio reported the highest number of participants and employed workers, with a 13:1 ROI. Indiana showed a 12:1 ROI. Georgia's results were positive (5:1 ROI) but showed opportunities for improvement in employment success and economic return.

Montana Medicaid expansion enrollees.

HELP-Link is a voluntary workforce training program designed to improve the employment and wage outcomes of individuals enrolled in certain types of Montana Medicaid, with the goal of reducing clients’ reliance on Medicaid for health insurance and improving Montana’s workforce. The program was created in the 2015 Legislative Session through the Montana Health and Economic Partnership Act, more commonly known as the HELP-Act (Senate Bill 405).

Pre-post analysis. N=2,968 specifically served with HELP-Link funds.

Social: Among the 81 HELP-Link clients who completed training programs by the end of 2016, 81% were employed after completion. Among those employed, 71% experienced wage increases, with the median increase equal to $8,712.

Men aged between 26 and 58 who were incarcerated in one of two prisons (minimum and medium security) and were returning to society. Participants were required to be within three months of their earliest possible release date, have a high school diploma or equivalency, or  be at moderate-to-high risk for reoffending violent crimes - assessed by the Michigan Department of Corrections (MDOC) via the Correctional Offender Management Profiling for Alternative Sanctions.

Exclusion criteria included the presence of an uncorrected hearing or visual problem that interfered with using Virtual Reality Job Interview Training (VR-JIT), and a medical illness that compromised cognition (e.g., moderate-to-severe traumatic brain injury).

VR-JIT added to service-as-usual (SAU) within prison-based vocational services.

Randomized controlled trial. N=44. N=28 were in SAU+VR-JIT and N=16 in SAU only.

Social: SAU+VR-JIT showed significant improvements (large effect sizes [ES]) in interview skills, interview training motivation, and interview anxiety (all p<0.05; ηp²>0.15) compared to SAU. Greater employment was noted by the six-month follow-up (Odds Ratio [OR]=7.4, p=0.045). VR-JIT was rated as highly acceptable and usable by participants.

People in Minnesota who were unemployed and seeking jobs. 

50.7% were women and 87.0% were White. Respondents were 46.92 years old on average (Standard Deviation [SD]=11.20) and had 22.76 years of full-time work experience (SD=10.90). 

A majority of the sample (60.5% of respondents) had personal annual incomes of $60,000 or more before becoming unemployed. Approximately 25% of the sample reported that their last job had been in a professional specialty occupation; 22% reported executive, administrative, or managerial fields; 14% reported working in sales; and 39% worked in technical, related, administrative support, or other fields. On average, participants had been unemployed for 49.34 days upon enrollment (SD = 28.25).

Building Relationships and Improving Opportunities (BRIO), a publicly available online networking intervention built on networking literature and social cognitive theory, designed to increase networking intensity, networking self-efficacy, and proximal networking benefits.

Randomized controlled trial. N=491.

Social: The intervention increased networking intensity (B=0.28, p<0.05; d=0.32), networking self-efficacy (B=0.37, p<0.01; d=0.49), and proximal networking benefits (B=0.33, p<0.01; d=0.40). The intervention generated higher quality reemployment through its positive effects on networking self-efficacy (job improvement: B=0.08, p<0.05; income: B=0.25, p<0.05; indirect effects: 0.03 and 0.09, respectively). Individuals who completed the intervention and were lower in extraversion showed the most positive improvements in networking self-efficacy and reemployment quality (interaction B=−0.11, p<0.05; low extraversion: B=0.31 vs. high extraversion: B=0.13).

Systematic Reviews
Note: The vocabulary used in the table is the same terminology used in the study in order to preserve the integrity of the summary. 
Study
Population
Intervention Summary
Type of Study Design
Outcomes
Pathways to Work Evidence Clearinghouse (2024)

Individuals with low incomes, including public benefits recipients, parents, single parents, people with disabilities, people with prior justice system involvement, and people with substance use disorders.

Case management interventions providing direct, personalized one-on-one support to assess needs related to employment, education, housing, health, or public benefit receipt and to provide or refer clients to services to address identified needs. Services often include needs assessment, career counseling, job search assistance, and education or training.

Evidence snapshot. 27 studies of 21 interventions.

Social: On average across 18 case management interventions, short-term annual earnings increased by $410 and long-term annual earnings increased by $490, compared to a control group. Long-term employment increased by 1 percentage point on average and annual public benefit receipt decreased by $167 in the short term and $120 in the long term. 

The Pathways Clearinghouse classifies a large effect as exceeding 0.25 standard deviations, equivalent to approximately $5,229 in 2018 earnings, suggesting these average gains fall below that threshold.

Overall effects were modest: only one intervention, Integrated Case Management (ICM), showed favorable effects across three domains (earnings, employment, and public benefit receipt). A study of ICM found that the program led to a long-term annual earnings increase of $1,987, a long-term employment gain of 2.5 percentage points and a long-term reduction in annual public benefit receipt of $545. 

Nine of the 21 interventions had at least one moderate- or high-quality study showing statistically significant favorable findings in at least one outcome domain, but none had two or more such studies across any domain.

Streke & Rotz (2022)

Adults with low incomes participating in employment and training programs across the United States, including TANF, SNAP, workforce development, and related public benefit populations. Evidence base includes 191 impact studies covering 144 interventions.

Employment and training interventions designed to increase employment and earnings. Intervention categories included education and occupational skills training, sectoral training, work-based learning, transitional jobs, subsidized employment, career pathways, and soft-skills/job-readiness programs. Programs varied in intensity, duration, provider type (public, nonprofit, private), and whether participation was voluntary or mandatory.

Systematic review and meta-analysis of 191 rigorous impact studies (primarily randomized controlled trials and strong quasi-experimental designs). Statistical aggregation of standardized employment and earnings effect sizes across studies.

Social: There were modest but meaningful improvements overall (average ES=0.047, p<0.05). Across studies, employment increased by about 2 percentage points on average, and participants earned roughly $1,000 more per year than those not in the programs. The strongest results tended to come from education and training (ES=0.068, approximately $1,400/year), occupational and sectoral training models (ES=0.039, p<0.01, approximately $821/year), work-based learning (ES=0.061, approximately $1,300/year), transitional jobs (ES=0.060, p<0.01, approximately $1,250/year), and soft-skills programs. Programs that were voluntary (ES=0.062) generally performed better than mandatory ones (ES=0.037, difference=-0.025, p=0.014), and those run by private providers (ES=0.064) generally performed better than those delivered solely through public systems (ES=0.039). While the effects were not large, falling below the typical 0.25 standard deviation threshold typically, they were consistent across a wide range of studies.

Assessment Synthesis Criteria
Strong Evidence
There is strong evidence that the intervention will produce the intended outcomes.
  • At least one well-conducted systematic review or meta-analysis (including two or more large, randomized trials) showing a significant and clinically meaningful health effect; and  
  • Consistent findings of health effects from other studies (cohort, case-control, and other designs).
Sufficient Evidence
There is sufficient evidence that the intervention will produce the intended outcomes.
  • At least one well-conducted systematic review or meta-analysis (including two or more large, randomized trials) showing a significant and clinically meaningful health effect, but inconsistent findings in other studies; or
  • Consistent findings from at least three non-randomized control trial studies (cohorts, practical trials, analysis of secondary data); or
  • A single, sufficiently large well-conducted randomized controlled trial demonstrating clinically meaningful health effect and consistent evidence from other studies; or 
  • Multiple expert opinions/government agencies supporting the intervention.
More Evidence Needed or Mixed Evidence
There is insufficient evidence that the intervention will produce the intended outcomes, however the results may indicate potential impact.
  • Lack of demonstration of improved health outcomes based on any of the following: (a) a systematic review or meta-analysis; (b) a large randomized controlled trial; (c) consistent positive results from multiple studies in high-quality journals; or (d) multiple expert opinions or government agencies supporting the intervention. 
  • An insufficient evidence rating does not mean there is no evidence, or that the intervention is unsafe or ineffective. 
  • In many cases, there is a need for more research or longer-term follow-up.
There is strong evidence that the intervention will produce the intended outcomes.
There is sufficient evidence that the intervention will produce the intended outcomes.
There is insufficient evidence that the intervention will produce the intended outcomes, however the results may indicate potential impact.
  • At least one well-conducted systematic review or meta-analysis (including two or more large, randomized trials) showing a significant and clinically meaningful health effect; and  
  • Consistent findings of health effects from other studies (cohort, case-control, and other designs).
  • At least one well-conducted systematic review or meta-analysis (including two or more large, randomized trials) showing a significant and clinically meaningful health effect, but inconsistent findings in other studies; or
  • Consistent findings from at least three non-randomized control trial studies (cohorts, practical trials, analysis of secondary data); or
  • A single, sufficiently large well-conducted randomized controlled trial demonstrating clinically meaningful health effect and consistent evidence from other studies; or 
  • Multiple expert opinions/government agencies supporting the intervention.
  • Lack of demonstration of improved health outcomes based on any of the following: (a) a systematic review or meta-analysis; (b) a large randomized controlled trial; (c) consistent positive results from multiple studies in high-quality journals; or (d) multiple expert opinions or government agencies supporting the intervention. 
  • An insufficient evidence rating does not mean there is no evidence, or that the intervention is unsafe or ineffective. 
  • In many cases, there is a need for more research or longer-term follow-up.
Sources

[1] Office of Disease Prevention and Health Promotion. Employment: literature summary. Healthy People 2030, U.S. Department of Health and Human Services. https://odphp.health.gov/healthypeople/priority-areas/social-determinants-health/literature-summaries/employment

[2] Udalova, V., Powers, D., Robinson, S., Notter, I. (2022, January). Who makes more preventable visits to the ER? U.S. Census Bureau. https://www.census.gov/library/stories/2022/01/who-makes-more-preventable-visits-to-emergency-rooms.html

[3] Cantor, J., Van Horn, C., Mouzon, D. M., Walkup, J. (2023, October). Unemployment and mental health: an important opportunity for cross-sector action. Milbank Memorial Fund blog. https://www.milbank.org/2023/10/unemployment-and-mental-health-an-important-opportunity-for-cross-sector-action/

[4] Franke, A. G., Schmidt, P., Neumann, S. (2024). Association Between Unemployment and Mental Disorders: A Narrative Update of the Literature. Int J Environ Res Public Health,21(12):1698. https://doi.org/10.3390/ijerph21121698

[5] Meneton, P., Kesse-Guyot, E., Méjean, C., et al. (2015). Unemployment Is Associated with High Cardiovascular Event Rate and Increased All-Cause Mortality in Middle-Aged Socially Privileged Individuals. Int Arch Occup Environ Health, 88(6):707-716. doi:10.1007/s00420-014-0997-7

[6] Center for Health Care Strategies. (2025, August). Connecting Medicaid Members to Work: Expanding Access to Evidence-Based Employment Models.https://www.chcs.org/resource/connecting-medicaid-members-to-work-expanding-access-to-evidence-based-employment-models/

[7] Wheeler, L., Garlick, R., Johnson, E., Shaw, P., Gargano, M. (2022). LinkedIn(to) Job Opportunities: Experimental Evidence from Job Readiness Training. Am Econ J Appl Econ., 14(2):101-125. DOI: 10.1257/app.20200025

[8] Urban Institute. (2022). Career Readiness Training. Local Workforce System Guide. https://workforce.urban.org/node/36.html

[9] New Avenues for Youth. Job readiness training. https://newavenues.org/job-readiness-training/

[10] Medicaid. In Lieu of Services and Settings. Medicaid.gov. https://www.medicaid.gov/medicaid/managed-care/guidance/lieu-of-services-and-settings

[11] Congress.gov. Health Coverage Provisions in One Big Beautiful Bill Act (H.R.1), https://www.congress.gov/crs-product/R48569

[12] Colorado Behavioral Health Administration. (2025, December). Individual Placement and Support. Colorado Behavioral Health Administration. https://bha.colorado.gov/behavioral-health/ips

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