Predicting Behavioral Health Outcomes Among Low-Income Families: Testing a Socioecological Model of Family Resilience Determinants
Over the past decade, the concept of family resilience among impoverished families has increased as a main focus area for family scholars. Similarly, individual, family, and community-level factors that promote family resilience and their impact on behavioral health outcomes have particularly received increased amounts of attention. To date, however, few empirical studies have simultaneously validated the socioecological determinants of family resilience within multi-dimensional conceptual frameworks. In the current study, we test such a model using a cross-sectional design among 380 women and men with an average age of 35 experiencing poverty as a chronic stressor, the majority of whom are ethnic minorities. Individual, family and community determinants of family resilience are examined for their differential effect on outcomes of physical and mental health, as well as risks for substance abuse. Results from structural equation modeling provide support for the model. Findings suggest that community-level determinants impact health through indirect pathways. In this case, community factors predict family and individual-level determinants, and individual factors then directly predict health. Similarly, the relationship between family-level determinants and health was indirect through individual-level factors. Although, a strong positive relationship was found between individual-level determinants and health, the relationship between individual-level factors and substance abuse was also found to be indirect through health. Methodological limitations and implications for family life education, clinical interventions, policy, and future research that are socioecologically-informed are discussed.
KeywordsLow-income families Mental health Resiliency Structural equation modeling Substance abuse
- Bentler, P. (2006). EQS structural equations program manual. Encino, CA: Multivariate Software.Google Scholar
- Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge: Harvard University Press.Google Scholar
- Danziger, S. K., Corcoran, M., Danziger, S. H., Helflin, C., Kalil, A., Levine, J., et al. (1999). Barriers to the employment of welfare recipients. Ann Arbor, MI: University of Michigan.Google Scholar
- Derogatis, L. R. (1993). Brief Symptom Inventory (BSI) administration, scoring, and procedures manual (4th ed.). Minneapolis, MN: National Computer Systems.Google Scholar
- HUD. (2011). Financial Literacy Resources Retrieved August 9, 2011, from http://www.hud.gov/offices/hsg/mfh/nnw/consortia/consortiafinancialliteracy.cfm.
- Hungelmann, J., Kenkel-Rossi, E., Klassen, L., & Stottenwerk, R. (1989). JAREL spiritual well-being scale. Milaukee, WI: Marquette University College of Nursing.Google Scholar
- Joshi, P., Hardy, E., & Hawkins, S. (2009). The role of religiosity in the lives of the low-income population: A comprehensive review of the evidence. Washington, D.C.: U.S. Department of Health and Human Services.Google Scholar
- Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). New York, NY: Guilford press.Google Scholar
- McCubbin, H. I., Thompson, A. I., & McCubbin, M. A. (1996). Family assessment: Resiliency, coping, and adaptation. Inventories for research and practice (3rd ed.). Madison, WI: University of Wisconsin Publishers.Google Scholar
- National Housing Law Project. (2002). False hope: A critical assessment of the HOPE VI public housing redevelopment program. San Francisco: National Housing Law Project.Google Scholar
- Rosenberg, M. (1979). Conceiving the self. New York: Basic Books.Google Scholar
- Tabachnick, B. G., & Fidell, L. S. (2007). Using multivariate statistics (5th ed.). Boston: Allyn and Bacon.Google Scholar