Oke, Nicholas John (2010)
Clin.Psy.D. thesis, University of Birmingham.
LITERATURE REVIEW What do we know about working through foster carers? A review of psychologically based consultancy and training approaches in the UK.
RESEARCH PAPER ‘Against the Odds’ : Foster carers’ perceptions of family, commitment and belonging in successful placements. The thesis comprises three sections. The first is a Literature Review covering UK published studies over the past twenty years on psychologically based interventions for foster carers. With increased recognition of the crucial role that foster carers play in promoting the psychological well-being and mental health of children in care, there has been a corresponding proliferation of consultation and training programmes aimed at assisting carers with this task. The Review examines the effectiveness of these, with pointers for further research in this area. The second section describes a qualitative study related to unexpected positive outcome in foster care. The specific aim is the exploration of perceptions of ‘family’, ‘commitment’ and ‘belonging’ in foster carers who are providing a placement for a young person who has succeeded with them ‘against the odds’. The study employs Interpretative Phenomenological Analysis to identify common themes in the carers’ accounts and the findings are presented in the Results section of the paper, followed by discussion and personal reflection on the enquiry process. The implications of what these ‘successful’ carers reveal are considered with a view to the training and support of foster carers generally. References for each of the first and second papers are included after each respectively. The third section consists of Appendices, including a Public Domain briefing paper, quality estimations of the research studies reviewed and tabulated summaries of each article. The participant information and consent relating to the Empirical paper are also included in the third Section, as well as the Interview schedule and examples of two stages in data analysis.
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