Dr. Janet Box-Steffensmeier, Department of Political Science
Rank at time of award: Professor
Ideally, children placed in state custody would either be returned to their parents or placed for adoption in a relatively short period of time. Those in state custody would experience stable placements with foster parents or in community-based institutional settings (such as group homes). However, two decades of research indicates that actual practice departs substantially from this ideal. Children and adolescents can remain in state custody for long periods of time, shuttling between placements. We use the term, "episodes," to refer to time spent in out-of-home care. We use the term, "spells," to refer to time spent in a specific placement, such as a group home. Both are important and distinct dimensions of the dynamics of out-of-home care, with spells nested within episodes.
A central and recurrent theme in research on child welfare involves the deleterious effects of this instability. The negative effects may occur for many reasons, such as a weakened attachment to the child's primary care giver (Wulczyn 2002). Not surprisingly, these effects have been linked to a variety of negative outcomes, including problem behaviors (Cook 1991; Zimmerman 1982). Heightening concern about this issue is the fear that this instability gains momentum over time. Children affected by frequent changes may become more likely to experience future instability. This form of event dependence would occur if, for example, instability fosters behavioral problems that make it difficult for child welfare agencies to maintain the children in subsequent placements or for children to remain with their parents once returned to their homes (Fahlberg 1985; Fanshel1990; Goldstein 1973; Leiberman 1987; VanderKolk 1987).
Placement stability or "permanency," is a focus of ongoing efforts to improve the child welfare system. Class-action lawsuits involving children in Foster Care filed by their advocates often focus on time spent in Foster Care or on placement instability. Settlements involving the state and plaintiffs often promise to cut the time children spend in Foster Care or reduce placement turnover. In Tennessee, for example, the settlement agreement for Brian A. et al vs. Sundquist and Hattaway specifies a series of performance measures that will be used to gauge improvements in the state's system. These measures include length of time in care as well as the number of placements.
The importance of the dynamics of out-of-home care also can be seen in legislation to improve and reform the child welfare system, such as the landmark Adoption and Safe Families Act of 1997. Several features of the law could affect the dynamics of out-of-home care. The law, for example, accelerated the timeline with which states must hold permanency hearings for children in out-of-home care from 18 to 12 months. Such hearings involve the determination of whether and when a child will be returned home; have the rights of his or her parents terminated; be placed for adoption; be referred for legal guardianship or be placed in another permanent living arrangement (such as living with a relative). In addition, the law requires states in most cases to file a petition to terminate parental rights and concurrently identify, recruit, process and approve a qualified adoptive family on behalf of any child, regardless of age, that has been in foster care for 15 out of the most recent 22 months. (This requirement can be set aside in several circumstances, such as when termination is not in the best interest of the child.) There are several other relevant aspects of ASFA, including adoption incentives provided to states.
Our proposal has an associated methodological component that sees a modeling solution that is to a large degree independent of the unknown features of the data generating process, i.e., that performs well whether event dependence and/or heterogeneity are features of the processes of interest. None of the currently available modeling options are consistent with a process characterized by both unobserved heterogeneity and event dependence. This means that our confidence in health and policy proscriptions is low. We cannot reliably estimate the effects of treatments or programs such as the Adoption and Safe Families Act of 1997 Act, for example, if unobserved or unmeasured characteristics of children or their circumstances affect the risk for multiple placements and if disruptions in placement themselves increase the risk of future placement change. Our preliminary work suggests that a conditional frailty model presents a solution. The proposed research will demonstrate the promise of this model, extend it to the multi-level case, as well as multiple outcomes (re: competing risks setups).
Publications resulting from this seed grant
Box-Steffensmeier, Janet M., and Suzanna De Boef. 2006. Repeated Events Survival Models: The Conditional Frailty Model. Statistics in Medicine. 25(20, October): 3518-3533. PMID: 16345026
Box-Steffensmeier, Janet M., and Lyndsey Young. 2007. The Cox Proportional Hazards Model, Diagnostics, and Extensions. In the Handbook of Longitudinal Research: Design, Measurement, and Analysis, ed. Scott Menard.Elsevier.
Box-Steffensmeier, Janet M., Suzanna De Boef, and Kyle Joyce. 2007. Event Dependence and Heterogeneity in Duration Models: The Conditional Frailty Model. Political Analysis. 15(3): 237-56.
Box-Steffensmeier, Janet M., and Lyndsey Sandfill Young. 2008. Event History Analysis, Entry in the International Encyclopedia of Political Science, George T. Kurian, ed., American Political Science Association and CQ Press.
Box-Steffensmeier, Janet M. (Lead Editor), Henry Brady, and David Collier. 2008. Oxford Handbook of Political Methodology, Oxford University Press.
Box-Steffensmeier, Janet M., Henry Brady, David Collier. 2008. Introduction to the Oxford Handbook of Political Methodology. Box-Steffensmeier, Brady, and Collier, eds. Oxford Handbook of Political Methodology, Oxford University Press
Brady, Henry, David Collier, and Janet M. Box-Steffensmeier. 2009. Political Methodology: Post Behavioral Movements and Trends. Robert Goodin, ed. Oxford Handbook of Political Science. Oxford University Press.
Box-Steffensmeier, Janet M., and Anand E. Sokhey. 2009. Event History Methods and Politics. Kevin T. Leicht and J. Craig Jenkins, eds. Handbook of Politics: State and Civil Society in Global Perspective.
Box-Steffensmeier, Janet M., and Byungwon Woo. 2010. Event History Analysis. In International Encyclopedia of Political Science, Bertrand Badie, Dirk Berg-Schlosser, and Leonardo Morlino, eds., Thousand Oacks, CA: Sage Publications.
Blake, Daniel J., Janet M. Box-Steffensmeier, and Byungwon Woo. 2010. Structural Interdependence and Unobserved Heterogeneity in Event History Analysis. In Longitudinal Research with Latent Variables, Kees van Montfort, Johan Oud, and Albert Satorra, eds., Berlin, Germany: Springer.
Box-Steffensmeier, Janet M., John Freeman, Matthew Hitt and Jon Pevehouse. 2014. Time Series for Social Scientists. Cambridge: Cambridge University Press.