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Effects of Psychological Distress on Employment among Mothers in Low-Income Families Leigh Ann White June 7, 2004 AcademyHealth Annual Meetings San Diego,

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Presentation on theme: "Effects of Psychological Distress on Employment among Mothers in Low-Income Families Leigh Ann White June 7, 2004 AcademyHealth Annual Meetings San Diego,"— Presentation transcript:

1 Effects of Psychological Distress on Employment among Mothers in Low-Income Families Leigh Ann White June 7, 2004 AcademyHealth Annual Meetings San Diego, CA

2 Support for this research National Institute for Mental Health Johns Hopkins Bloomberg School of Public Health, Department of Health Policy & Management University of Michigan, National Center on Poverty I would like to acknowledge Eric Slade, Dan Ford, Darrell Gaskin, Nan Astone, Harold Pollack, and others for their input on my dissertation and working papers. Thanks also go to Andy Cherlin, Robert Moffitt, Paula Fomby, and Jen Roff for their work on the survey component of the Welfare, Children, and Families Three-City Study.

3 Objective How does mental health of low-income women affect their ability to find and retain work? Main outcome: Labor force attachment –proportion of time, in fractions of months, that a woman spent in employment during a specified period

4 Rationale Previous evidence –documented relationship between mental illness and labor market outcomes Policy concern: Welfare Reform –Those left on the rolls experience more obstacles to employment. Magnitude of problem –relatively high prevalence of mental illness among low-income women

5 Data WCF Three-City Study –Longitudinal; 2 interview waves (1999 and 2000-01) –Post-1996 Welfare Reform, pre-recession experiences of 2,400 child/caregiver dyads in Boston, Chicago, and San Antonio Study sample –Female caregivers of sampled focal children, interviewed in both waves, with complete data on key variables –In households <200% of FPL –N=1,656 female caregivers aged 18-64

6 Mental Health Status@T1 Personal and Family Characteristics Human Capital (education, job tenure, employment history) Welfare Experience Nonlabor Income Social and Behavioral Stressors Survey-related variables Employment Status and Work Experience @T1 Labor Force Attachment T1 - T2 (Two-limit Tobit) Conceptual Framework

7 Measure of mental health status Brief Symptom Inventory (BSI-18) –sensitive screening instrument (Derogatis) –self-reported of level of distress, 0-4; 18 items Scoring –Global Severity Index (GSI) –Three subscores (DEP, ANX, SOM) Case criteria –Standardized GSI or any of three subscores met recommended clinical cutoff –19% in this sample met case criteria

8 Labor Force Attachment: Descriptive Statistics SampleMean (95% C.I.) Total sample (N=1,656) Held a job between interviews Proportion of time in employment, Wave 1-2 Conditional proportion of time employed (N=1,138).69.50 (.48,.52).73 (.71,.74) Limited to those with work experience (N=1,255) Held a job between interviews Proportion of time in employment, Wave 1-2 Conditional proportion of time employed (N=1,121).91.65 (.63,.67).73 (.71,.75)

9 Results: Model Coefficients CovariateOLS (N=1,656) Tobit (N=1,656) Tobit (N=1,255) Met BSI-18 case criteria-.071-.129-.086 Age-.004-.009NS Non-Hispanic Black.072.109.053 Married-.088-.152NS Pregnant-.179-.290-.202 Log of nonlabor income-.037-.055-.024 Other receiving SSDI-.116-.231-.009 Months on welfare since 1/96-.004-.006-.001 Dealt or used drugs in past year-.097-.162-.151

10 Results: Model Coefficients (con’d) CovariateOLS (N=1,656) Tobit (N=1,656) Tobit (N=1,255) Log of job tenure--.047 Education (HS omitted) <HS >HS -.140.044 -.216.068 -.116 NS Sample city (Chicago omitted) Boston San Antonio -.049 -.056 -.087 -.078 NS Adjusted or Pseudo R-squared N left-censored N uncensored N right-censored.1975.1178 518 1,017 121.1195 134 1,002 119

11 Model Predictions from Two-Limit Tobit Did not meet BSI- 18 Case Criteria Met BSI-18 Case Criteria Total sample (N=1,656) Prob [Employed] E [Prop time employed] N=1,347.57.49 (.002) N=309.51.43 (.004) Limited sample (N=1,255) Prob [Employed] E [Prop time employed] N=1,047.71.57 (.002) N=208.75.51 (.005)

12 Implications Some evidence of a relationship between mental health and job retention –“job churning” a possibility –Interventions improving mental health status are likely to have a positive impact on productivity. Importance of addressing stressors –Why does there exist a relationship between mental health and employment? –How do proximate and distal stressors induce symptoms and affect employment?

13 Welfare, Children and Families Three- City Study: Principle Investigators Ronald J. Angel, University of Texas at Austin Linda M. Burton, Pennsylvania State University P. Lindsay Chase-Lansdale, Northwestern University Andrew J. Cherlin, Johns Hopkins University Robert A. Moffitt, Johns Hopkins University William Julius Wilson, Harvard University Website: http://www.jhu.edu/~welfare/http://www.jhu.edu/~welfare/

14 Welfare, Children and Families Study: Federal Funding Agencies National Institute of Child Health and Human Development U.S. Department of Health and Human Services: Office of Disability, Aging, and Long-Term Care Policy, Office of the Assistant Secretary for Planning and Evaluation Administration on Developmental Disabilities Administration for Children and Families Office of Research, Evaluation, and Statistics, Office of Policy, Social Security Administration National Institute of Mental Health

15 Welfare, Children, and Families Study: Foundation Support The Boston Foundation The Annie E. Casey Foundation The Edna McConnell Clark Foundation The Lloyd A. Fry Foundation Hogg Foundation for Mental Health The Robert Wood Johnson Foundation The Joyce Foundation W.K. Kellogg Foundation Kronkosky Charitable Foundation The John D. and Catherine T. MacArthur Foundation Charles Stewart Mott Foundation Woods Fund of Chicago


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