Causal Impact Analysis

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Displaying 81 - 90 of 1084

Medicaid work requirements in Arkansas: Two-year impacts on coverage, employment, and affordability of care (Sommers, 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study's objective was to examine the impact of work requirements for Medicaid recipients on public benefits receipt, employer benefits receipt, and employment. The study used a difference-in…
Efficacy of the ‘Stand and Move at Work’ multicomponent workplace intervention to reduce sedentary time and improve cardiometabolic risk: A group randomized clinical trial (Periera et al., 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study's objective was to examine the impact of the Stand and Move at Work intervention on health outcomes. This study was a randomized controlled trial. Using data collected via…
Feasibility and preliminary outcomes of a Brief Mindfulness-Based Intervention (BMBI) to decrease stress and improve well-being in secondary school teachers (Roberts, 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Moderate Causal Evidence
The study's objective was to examine the impact of a brief mindfulness-based intervention on the health and wellness outcomes. This study was a randomized controlled trial assessing the…
Bridging the school-to-work divide: Interim implementation and impact findings from New York City's P-TECH 9-14 schools (Rosen et al., 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study's objective was to examine the impact of the P-TECH 9-14 model on credit accumulation. The study was a randomized controlled trial in New York City schools. Using NYC Department of…
Using technology to redesign college advising and student support: Findings and lessons from three colleges' efforts to build on the iPASS initiative [UNCC] (Miller et al., 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study's objective was to examine the impact of the enhanced Integrated Planning and Advising for Student Success (iPASS) on education outcomes. This profile focuses on the University of North…
Using technology to redesign college advising and student support: Findings and lessons from three colleges' efforts to build on the iPASS initiative [MCCC] (Miller et al., 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study's objective was to examine the impact of the enhanced Integrated Planning and Advising for Student Success (iPASS) on education outcomes. This profile focuses on the Montgomery County…
Using technology to redesign college advising and student support: Findings and lessons from three colleges' efforts to build on the iPASS initiative [Fresno State] (Miller et al., 2020)
Study Type: Causal Impact Analysis
Causal Evidence Rating: High Causal Evidence
The study's objective was to examine the impact of the enhanced Integrated Planning and Advising for Student Success (iPASS) program on education outcomes. This profile focuses on the California…
Net impact and benefit-cost estimates of the workforce development system in Washington state. (Upjohn Institute Technical Report No. 13-029). (Hollenbeck & Huang 2014)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of participating in apprenticeship programs registered with the state of Washington on employment rates, earnings, and benefit receipt. The authors…
Net impact and benefit-cost estimates of the workforce development system in Washington State. Upjohn Institute technical report no. TR06-020. [Dept. of Services for the Blind] (Hollenbeck & Huang 2006)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of the Department of Services for the Blind (DSB) program on the employment rate and earnings of low-income adults who are blind. The authors used a…
Net impact and benefit-cost estimates of the workforce development system in Washington State. (Upjohn Institute Technical Report No. 13-029). [VOC] (Hollenbeck & Huang 2014)
Study Type: Causal Impact Analysis
Causal Evidence Rating: Low Causal Evidence
The study’s objective was to examine the impact of Vocational Rehabilitation (VOC) programs on the employment rate, earnings, and benefit receipt of adults with disabilities in Washington State. The…

CLEAR Icon Key

Below is a key for icons used to indicate important details about a study, such as its type, evidence rating, and outcome findings.

High Causal Evidence

Strong evidence the effects are caused by the examined intervention.
Moderate Causal Evidence

Evidence that the effects are caused to some degree by the examined intervention.
Low Causal Evidence

Little evidence that the effects are caused by the examined intervention.
Causal Impact Analysis

Uses quantitative methods to assess the effectiveness of a program, policy, or intervention.
Descriptive Analysis

Describes a program, policy, or intervention using qualitative or quantitative methods.
Implementation Analysis

Examines the implementation of a program, policy, or intervention.
Favorable

The study found at least one favorable impact in the outcome domain, and no unfavorable impacts.
Mixed

The study found some favorable and some unfavorable impacts in the outcome domain.
None

The study found no statistically significant impacts in the outcome domain.
Unfavorable

The study found at least one unfavorable impact in the outcome domain, and no favorable impacts.
Not applicable

Not applicable because no outcomes were examined in the outcome domain.
Favorable - low evidence

The study found at least one favorable impact in the outcome domain, and no unfavorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Mixed - low evidence

The study found some favorable and some unfavorable impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
None - low evidence

The study found no statistically significant impacts in the outcome domain. The study received a low causal evidence ratings so these findings should be interpreted with caution.
Unfavorable - low evidence

The study found at least one unfavorable impact in the outcome domain, and no favorable impacts. The study received a low causal evidence ratings so these findings should be interpreted with caution.