The First Four Months in a New Foster Placement: Psychosocial Adjustment, Parental Contact and Placement Disruption

Article excerpt

Intake and four-month follow-up measures were obtained for 235 children referred into a new foster care placement over a 12-month period in the Australian State of South Australia. Twenty-five percent of the sample returned home within 4-months, and for those who remained in care throughout, there had been modest gains in behavior, psychological adjustment and adjustment at school. On the other hand, there were considerable levels of placement disruption, a high degree of non-compliance with parental visiting plans, and a high proportion of children fell outside ninety-five percent confidence intervals for the general adolescent population on most well-being measures, particularly conduct disorder.


Despite the fact that child welfare legislation everywhere advances child well-being as one of its most fundamental objectives, efforts to measure the well-being of children in state care have been surprisingly rare and unsustained. Altshuler and Gleeson (1999), for example, recently noted that measures of success in foster care are dominated by indicators of permanency and safety, while child well-being is rarely incorporated into administrative databases or built into the evaluation of system performance. No doubt one of the reasons for this omission is that whereas permanency and safety can be readily inferred from administrative data such as re-abuse and re-referral rates, the measurement of child well-being is a more subjective and potentially labour-intensive task.

In a recent paper on the measurement of child well-being, Barber and Delfabbro (2000) argued that for well-being assessments to become routine, there is a need for briefer, more useable measures than are currently available; measures that can be incorporated into the day-to-day casework of child welfare professionals. Many of the more commonly advocated measures of child well-being such as the Child Well-Being Scales (Magura & Moses, 1986) and the Child Behavior Checklist (Achenbach, 1981) are much too laborious to pass this test. Another problem with the available research into foster child well-being is that most studies have been cross-sectional (see Altshuler & Gleeson, 1999 for a review). In the most common research design, the functioning of children in foster care is compared with that of children in the general population or from comparable groups in the child welfare population at a single point in time (cf. Kinard, 1994). Such designs provide no adequate baseline against which to compare change in foster care outcomes. What longitudinal studies have been conducted are mainly retrospective. Large archival data-sets, such as those routinely maintained by agencies, have been used to examine the long-term outcomes of care (e.g., Courtney, 1994, 1995; Courtney & Wong, 1996; Fernandez, 1998; Goerge, 1990). These studies have proved highly effective in predicting changes in case-status over time, but have been limited by the range of variables included, the sophistication of the measures available, and by the absence of follow-up measures more proximal to the outcomes predicted. For example, it is questionable whether particular outcomes can be clearly associated with factors such as abuse which may have occurred 5-10 years earlier.

Accordingly, prospective longitudinal studies are increasingly advocated in the child welfare field (Courtney et al., 1998; Fanshel, 1975a; Wulczyn, 1997). In addition to being able to compare subsequent results with a consistent baseline, prospective studies are in a position to collect a greater volume of information, and to choose what information should be collected. Archival or case-file information can be combined with child self-reports and reports from others who have regular face-to-face contact with the child. Furthermore, although concerns can be raised about potential biases resulting from the selective loss of subjects over time, a prospective study often has the capacity to identify, and maybe control for, any systematic differences between the retained sample and those who drop out. …


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