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Related Studies

Displaying 141 - 150 of 157
464

Ampaw, F., & Jaeger, A. (2011). Understanding the factors affecting degree completion of doctoral women in the science and engineering fields. New Directions for Institutional Research, 152, 59-73.

  • Topic Area: Women in Science, Technology, Engineering, & Math (STEM)

Study Type: Descriptive Analysis

Outcome Effectiveness:

Youth programs Science, Technology, Engineering, and Math (STEM) programs Preventing discrimination

432

Carrington, W.J., McCue, K., & Pierce, B. (2000). Using establishment size to measure the impact of Title VII and affirmative action. Journal of Human Resources, 35(3): 503-523.

  • Topic Area: Employer Compliance

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Affirmative action Civil Rights Act of 1964 Executive Order 11246 (E.O. 11246)

2071
Varona, D. A. (2019). Using mindfulness to reduce occupational stress and burnout in music teachers: A randomized controlled trial. (Ph.D., University of Maryland, College Park). ProQuest Dissertations and Theses. (2305850906)

Study Type: Causal Impact Analysis

Causal Evidence Rating: Low Causal Evidence

Outcome Effectiveness:

Other Behavioral Interventions Behavioral interventions

2307
Samek, A., Kapteyn, A., & Gray, A. (2022). Using vignettes to improve understanding of Social Security and annuities. Journal of Pension Economics & Finance, 21(3), 326-343. https://doi.org/10.1017/S1474747221000111
  • Topic Area: Behavioral Finance: Retirement

  • Topic Area: Financial Literacy

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

Other Financial Literacy Retirement planning

2214
Lusardi, A., Samek, A., Kapteyn, A., Glinert, L., Hung, A., & Heinberg, A. (2017). Visual tools and narratives: New ways to improve financial literacy. Journal of Pension Economics & Finance, 16(3), 297-323. https://doi.org/10.1017/S1474747215000323 [Informational brochure]
  • Topic Area: Financial Literacy

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

Other Financial Literacy General

2213
Lusardi, A., Samek, A., Kapteyn, A., Glinert, L., Hung, A., & Heinberg, A. (2017). Visual tools and narratives: New ways to improve financial literacy. Journal of Pension Economics & Finance, 16(3), 297-323. https://doi.org/10.1017/S1474747215000323 [Written narrative]
  • Topic Area: Financial Literacy

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

Other Financial Literacy General

2212
Lusardi, A., Samek, A., Kapteyn, A., Glinert, L., Hung, A., & Heinberg, A. (2017). Visual tools and narratives: New ways to improve financial literacy. Journal of Pension Economics & Finance, 16(3), 297-323. https://doi.org/10.1017/S1474747215000323 [Video narrative]
  • Topic Area: Financial Literacy

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

Other Financial Literacy General

2171
Lusardi, A., Samek, A., Kapteyn, A., Glinert, L., Hung, A., & Heinberg, A. (2017). Visual tools and narratives: New ways to improve financial literacy. Journal of Pension Economics & Finance, 16(3), 297-323. https://doi.org/10.1017/S1474747215000323 [Interactive visual tool]
  • Topic Area: Financial Literacy

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

Other Financial Literacy General

1801
Jones, D., Molitor, D., & Reif, J. (2019). What do workplace wellness programs do? Evidence from the Illinois workplace wellness study. The Quarterly Journal of Economics, 134(4), 1747–1791.
  • Topic Area: Behavioral Insights

Study Type: Causal Impact Analysis

Causal Evidence Rating: High Causal Evidence

Outcome Effectiveness:

Other health and safety Other wages and benefits Paid leave Behavioral Interventions

576

Riegle-Crumb, C., Moore, C., & Ramos-Wada, A. (2011). Who wants to have a career in science or math? Exploring adolescents’ future aspirations by gender and race/ethnicity. Science Education, 95(3), 458-476.

  • Topic Area: Women in Science, Technology, Engineering, & Math (STEM)

Study Type: Descriptive Analysis

Outcome Effectiveness:

Youth programs Science, Technology, Engineering, and Math (STEM) programs Other disparities or discrimination in employment and earnings