文章基本信息

标题：Permanently Progressing? Building Secure Futures for Children in Scotland: Pathways and outcomes for looked after children
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作者：Linda Cusworth ; Jade Hooper ; Nina Biehal 等
期刊名称：International Journal of Population Data Science
电子版ISSN：2399-4908
出版年度：2018
卷号：3
期号：2
页码：1-1
DOI：10.23889/ijpds.v3i2.500
出版社：Swansea University
摘要：BackgroundEach year many children in Scotland who cannot be cared for by their birth parents become looked after by Local Authorities. Where reunification is not an option, children need to be settled as soon as possible in safe and secure alternative homes. However, more research evidence is needed to guide the placement decisions that are so crucial to children’s wellbeing. ObjectivesThe Permanently Progressing? study aims to help identify factors that are associated with children achieving a permanent home. The study hopes to inform policy, planning and practice in relation to young children who cannot live with abirth parent. MethodsUsing the Children Looked After Statistics that are collected by the Scottish Government from all 32 Local Authorities, the study followed a group of children who became ‘looked after and accommodated’ at age five or under (n=1355) in 2012-13. Children’s pathways through the system over a four-year period were investigated and compared to another group of children aged five or under who became ‘looked after’ in the same year but remained with their birth parent(s) at this time(n=481). FindingsThe paper discusses children’s pathways through the looked after system, together with factors which may influence these pathways, such as age when becoming looked after, number and type of placements, and types of permanence achieved3-4 years after becoming looked after. ConclusionsThis longitudinal analysis of administrative data offers unique insights into factors that may influence child welfare system responses to vulnerable children, which will be discussed, along with issues surrounding the difficulties associated with the definition and measurement of outcomes using these data.