HighStudy design
Design:
Study group formation:
Time period of study:
Primary outcome domains examined:
Increase short-term earnings, Increase long-term earnings, Increase short-term employment, Increase long-term employmentOther outcome domains examined:
NoneStudy funded by:
Results
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| Outcome domain | Measure | Timing | Study quality by finding | Comparison group mean | Program group mean | Impact | Units | Findings | Sample size |
|---|---|---|---|---|---|---|---|---|---|
| Increase short-term earnings | Annual earnings | Year 1 |
High
|
15,018.00 | 15,335.00 | 317.00 | 2005 dollars |
|
697 |
| Increase short-term earnings | Weekly earnings | Year 1 |
High
|
273.00 | 259.00 | -14.00 | 2005 dollars |
|
485 |
| Increase long-term earnings | Annual earnings | Year 3 |
High
|
14,146.00 | 13,777.00 | -369.00 | 2007 dollars |
|
697 |
| Increase short-term employment | Currently employed | 12 months |
High
|
77.60 | 71.70 | -5.90 | percentage points |
|
485 |
| Increase short-term employment | Employed for four consecutive quarters | Year 1 |
High
|
71.60 | 78.40 | 6.80 | percentage points |
|
697 |
| Increase short-term employment | Ever employed, annual | Year 1 |
High
|
97.40 | 98.80 | 1.40 | percentage points |
|
697 |
| Increase long-term employment | Employed for four consecutive quarters | Year 3 |
High
|
63.10 | 65.80 | 2.70 | percentage points |
|
697 |
| Increase long-term employment | Ever employed, annual | Year 3 |
High
|
86.30 | 86.20 | -0.10 | percentage points |
|
697 |
Short-term outcomes are those measured 18 months or fewer after participants are first offered services. Long-term outcomes are those measured between 18 months and 5 years after participants are first offered services. Very long-term outcomes are those measured 5 years or more after participants are first offered services.
Means are not displayed when not reported or not aligned with the impact estimates. For example, if the impact estimate is regression-adjusted but only unadjusted means are reported in the study, the unadjusted means are not displayed as they are not aligned with the adjusted impact estimate.
Impact estimates are not shown when the estimate units cannot be converted to natural units.
High
Moderate
The findings quality describe our confidence that a given study’s finding is because of the program. We do not display findings that rate low.
A moderate-to-large favorable finding that is unlikely to be due to chance
A moderate-to-large favorable finding that might to be due to chance
A small favorable finding that is unlikely to be due to chance
A small favorable finding that might be due to chance
A favorable finding that is unlikely to be due to chance, but we cannot determine the standardized effect size
A favorable finding that might be due to chance, but we cannot determine the standardized effect size
A moderate-to-large unfavorable finding that is unlikely to be due to chance
A moderate-to-large unfavorable finding that might to be due to chance
A small unfavorable finding that is unlikely to be due to chance
A small unfavorable finding that might be due to chance
An unfavorable finding that is unlikely to be due to chance, but we cannot determine the standardized effect size
An unfavorable finding that might be due to chance, but we cannot determine the standardized effect size
A finding that is unlikely to be due to chance, but we cannot determine the standardized effect size or direction
A finding of no effect that might be due to chance
Sample characteristics
Employers and firms were small to medium-sized (40 percent had 150 to 200 employees). Most employers and firms had a high turnover rate and offered an Employee Assistance Program; about a quarter of the employers were unionized. Most employees (82 percent) were female; about 56 percent were Black and non-Hispanic; about 73 percent had a high school diploma, GED, or higher; and the average wage was less than $9 per hour.
Age
| Mean age | 33 years |
| Young adults (age 16-24) | 35% |
| Adults (age 25+) | 66% |
Sex
| Female | 82% |
| Male | 18% |
Race and ethnicity
| Black or African American |
56%
|
| White, not Hispanic |
34%
|
| Hispanic or Latino of any race |
6%
|
| Unknown, not reported, or other |
3%
|
The race and ethnicity categories may sum to more than 100 percent if the authors reported race and ethnicity separately; in these cases, we report the category White, rather than White, not Hispanic.
Family status
| Married | 22% |
| Parents | 60% |
Employment and public benefit status
| Were employed | 100% |
Education
| Had a high school diploma or GED | 74% |
| Did not have a high school diploma or GED | 26% |
Program implementation
Implementing organization:
Program history:
Program services:
Mandatory services:
Comparison services:
Service receipt duration:
Program funding:
Study publications
Hendra, Richard, Keri-Nicole Dillman, Gayle Hamilton, Erika Lundquist, Karin Martinson, Melissa Wavelet, Aaron Hill, and Sonya Williams (2010). The Employment Retention and Advancement project: How effective are different approaches aiming to increase employment retention and advancement? Final impacts for twelve models, Washington, DC: Office of Planning, Research, and Evaluation, Administration for Children and Families, U.S. Department of Health and Human Services. Available at https://www.acf.hhs.gov/opre/resource/the-employment-retention-and-advancement-project-how-effective-are.
Miller, Cynthia, Vanessa Martin, Gayle Hamilton, Lauren Cates, and Victoria Deitch (2008). The Employment Retention and Advancement project: Findings for the Cleveland Achieve model: Implementation and early impacts of an employer-based approach to encourage employment retention among low-wage workers, New York: MDRC. Available at https://www.mdrc.org/sites/default/files/cleveland%20Achieve%20Model%20Full%20Report.pdf.
View the glossary for more information about these and other terms used on this page.
Pathways to Work refers to programs by the names used in study reports or manuscripts. Some program names may use language that is not consistent with our style guide, preferences, or the terminology we use to describe populations.
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