Fred Wulczyn

Placement Stability and Movement Trajectories

We discuss placement stability and movement patterns among children placed in family and group foster care. Although placement stability has been a focus of child welfare policy and practice, little research explores the actual patterns of movement while a child is in out‐of‐home care. We apply event count and movement trajectory models to unravel these patterns. The models were tested with a group of children placed out of home in New York City. We provide the results of these analyses, with a description of the latent movement trajectories that characterize the movement histories of the children in the study.

Foster Care in New York and Illinois: The Challenge of Rapid Change

Foster care caseloads around the country grew rapidly during the late 1980s. A lack of national data has made it difficult to identify the sources of this growth. In this study, we use administrative data from New York State and Illinois to demonstrate how the growth of the foster care population is related to an increase in admissions, especially among children under the age of 10. Special attention is paid to the rate of placement among infants. We also describe a dramatic increase in the number of children placed in relative foster care. The tendency of children to remain with relatives for longer periods of time contributed significantly to a drop in the number of children discharged.

Caseload Dynamics and Foster Care Reentry

In recent years, foster care caseloads have been on the rise. This article examines foster care reentry in New York State to determine what role, if any, foster care reentry plays in caseload dynamics. In addition, the placement histories of individual foster children are studied in an effort to uncover the characteristics of children that are associated with reentry. Last, the analysis examines the relationship between brief placements and cohort size as one indicator of a possible interaction between the supply of foster care beds and the placement experience of children.

A Statistical and Methodological Framework for Analyzing the Foster Care Experiences of Children

The attention now being paid to child welfare outcomes raises a number of important questions for researchers and practitioners. Among the most important questions are those that pertain to the issue of change and the statistical and methodological models used to understand how the delivery of services influences the path of change. In this article, I recommend that the study of change be divided into studies of individual-level and aggregate-level dynamics. I present a statistical framework for both types of analysis. I also stress the need to emphasize longitudinal research based on cohorts of children. In particular, I demonstrate how cross-sectional samples distort our impressions of both individual- and aggregate-level dynamics. A failure to recognize the bias in cross-sectional samples will hinder the study of outcomes in general.

A computational future for preventing HIV in minority communities: how advanced technology can improve implementation of effective programs.

Abstract:African Americans and Hispanics in the United States have much higher rates of HIV than non-minorities. There is now strong evidence that a range of behavioral interventions are efficacious in reducing sexual risk behavior in these populations. Although a handful of these programs are just beginning to be disseminated widely, we still have not implemented effective programs to a level that would reduce the population incidence of HIV for minorities. We proposed that innovative approaches involving computational technologies be explored for their use in both developing new interventions and in supporting wide-scale implementation of effective behavioral interventions. Mobile technologies have a place in both of these activities. First, mobile technologies can be used in sensing contexts and interacting to the unique preferences and needs of individuals at times where intervention to reduce risk would be most impactful. Second, mobile technologies can be used to improve the delivery of interventions by facilitators and their agencies. Systems science methods including social network analysis, agent-based models, computational linguistics, intelligent data analysis, and systems and software engineering all have strategic roles that can bring about advances in HIV prevention in minority communities. Using an existing mobile technology for depression and 3 effective HIV prevention programs, we illustrated how 8 areas in the intervention/implementation process can use innovative computational approaches to advance intervention adoption, fidelity, and sustainability.

Child Well-Being: The Intersection of Schools and Child Welfare

this chapter, we argue for closer collaboration between public schools and the public child welfare system, on behalf of children placed at risk, with respect to whether they will do as well in school as their abilities suggest they might, all else being equal. The need for closer collaboration is tied to two developments affecting schools and the child welfare system. First, both systems, as the result of relatively recent federal, state, and local initiatives, are focused on accountability as never before. For schools, accountability fostered by the No Child Left Behind act means that educators have to pay closer attention to children placed at risk who may fall behind in school if their educational needs are not addressed. In this context, the overall well-being of children involved in the child welfare system poses particular challenges because the incidence of cognitive, social, and behavioral impairment is substantially higher than the rates found in the general population. From the perspective of the child welfare system, public agencies are starting to look at school success as a measure of child well-being and as an indicator of their own service quality, an expanded view of responsibility that was introduced in the wake of the Adoption and Safe Families Act passed in 1997. As a consequence, advocates are pushing child welfare agencies to consider placing foster children within their own home school districts in an effort to preserve educational continuity and minimize disruption in the childrens lives. In turn, the new wave of accountability has focused attention on the shear magnitude of the dually involved population. According to the most recent national data, of the more than 3 million reports of child maltreatment received annually, about 610,000 school-age children (4to 17-year-olds) are involved in a substantiated allegation of maltreatment each year, a figure that represents about 70% of all official maltreatment

Adoption Dynamics and the Adoption and Safe Families Act

This article evaluates the effects of the federal Adoption and Safe Families Act of 1997 (ASFA) on the adoption process. Using a cohort sequential design, the article studies 13 successive entry cohorts of children admitted to foster care in six states from 1990 to 2002. The results of discrete‐time hazard models indicate that a significant increase in the probability of adoption occurs after the passage of ASFA. However, the analyses find no firm evidence of a slowdown in the average time required to complete adoptions in the mid‐1990s, although that act was originally designed to address an alleged slowdown in adoption. This article also examines the state‐specific patterns of change in the adoption process, both before and after the act’s passage.

The Effect of Population Dynamics on Performance Measurement

The methodological issues involved in measuring the outcomes of programs are not straightforward. For example, in the case of foster care, overlapping stays in care for various entry cohorts influence how outcomes are perceived. In this article we combine the results from a simulation model with empirical research to explore the way basic population dynamics and sampling strategy jointly affect understanding of one outcome, placement duration. The results suggest that exit cohort data are a poor substitute for longitudinal data and that the federal reporting system should shift as soon as practical to a longitudinal perspective based on entry cohorts.

Implementation and evaluation of linked parenting models in a large urban child welfare system

During the past decade, there have been increased efforts to implement evidence-based practices into child welfare systems to improve outcomes for children in foster care and their families. In this paper, the implementation and evaluation of a policy-driven large system-initiated reform is described. Over 250 caseworkers and supervisors were trained and supported to implement two evidence-based parent focused interventions in five private agencies serving over 2,000 children and families. At the request of child welfare system leaders, a third intervention was developed and implemented to train the social work workforce to use evidence-based principles in everyday interactions with caregivers (including foster, relative, adoptive, and biological parents). In this paper, we describe the policy context and the targeted outcomes of the reform. We discuss the theory of the interventions and the logistics of how they were linked to create consistency and synergy. Training and ongoing consultation strategies used are described as are some of the barriers and opportunities that arose during the implementation. The strategy for creating a path to sustainability is also discussed. The reform effort was evaluated using both qualitative and quantitative methods; the evaluation design, research questions and preliminary results are provided.

Evaluating Child Welfare Policies with Decision-Analytic Simulation Models

The objective was to demonstrate decision-analytic modeling in support of Child Welfare policymakers considering implementing evidence-based interventions. Outcomes included permanency (e.g., adoptions) and stability (e.g., foster placement changes). Analyses of a randomized trial of KEEP—a foster parenting intervention—and NSCAW-1 estimated placement change rates and KEEP’s effects. A microsimulation model generalized these findings to other Child Welfare systems. The model projected that KEEP could increase permanency and stability, identifying strategies targeting higher-risk children and geographical regions that achieve benefits efficiently. Decision-analytic models enable planners to gauge the value of potential implementations.