Authors (I did not succeed in adding the second and third author in the format). - Konijn, Carolien (Spirit Youth Care, c.konijn@spirit.nl, corresponding author) - Stams, Geert-Jan (Professor of Forensic Child and Youth Care... [ view full abstract ]
Authors (I did not succeed in adding the second and third author in the format).
- Konijn, Carolien (Spirit Youth Care, c.konijn@spirit.nl, corresponding author)
- Stams, Geert-Jan (Professor of Forensic Child and Youth Care Sciences at the University of Amsterdam, g.j.j.m.stams@uva.nl)
- Lindauer, Ramon (Child and adolescent psychiatrist, head of the department child and adolescent psychiatry at the Academic Medical Centre of Amsterdam, Associate professor at the University of Amsterdam, r.lindauer@debascule.com)
Objective.
Foster care has proven preferable compared to institutional care for the well-being of children who are not able to grow up in their own homes (Roy, Rutter, & Pickles, 2000). However, disruptions of foster care placements often occur. Between 20% and 50% of children in long term foster care experience a premature ending of their stay (Minty, 1999). In 2006 Oosterman and colleagues have published a meta-analysis of 26 studies examining risk and protective factors for placement breakdown in foster care. The present meta-analysis is a replication and extension of the study of Oosterman et al., examining risk and protective factors for disruptions in foster care over the past 25 years using new meta-analytic techniques. The association with disruptions will be examined for factors in the background of the foster child such as the age, reasons for out of home placement, characteristics of the biological parents and family, placement history and behavior problems. Also factors related to the placement will be studied such as kinship care, foster parent’s biological children, characteristics of the foster parents (age, competences, motivation and attitude) and the role of the biological parents during placement.
Method.
A three-level approach to meta-analysis is used in which effect sizes extracted from the same study (i.e., dependent effect sizes) can be modeled. In this way, all available effect sizes can be used, so that all information can be preserved, and maximum statistical power can be achieved.
Results and conclusions.
At the moment of submitting this abstract the analyses are still in progress. On the EUSARF conference in September the results will be available.
