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Start for Life: tackling inequalities in child development at age 2
Children living in poverty can be less ready to start primary school than children from families with higher incomes, with particular gaps in speech and language. This can be a direct result of low income (e.g: having access to fewer books, educational toys and activities, suitable housing for play, sufficient good quality food) or because other challenges that lead to parenting stress (e.g. mental health problems and domestic abuse) are more frequently experienced by low income households. Children who are already behind when they start school aged 4 years old struggle to catch up, tending to do less well than their peers throughout their school career. This can affect a child’s opportunities and wellbeing into their adolescence and then adulthood. However, the picture is mixed. When we look at the whole country, there are areas where children are doing better than we might expect given the high levels of poverty. Furthermore, we do not currently know why some children in some deprived areas seem to be doing better in terms of child development than in other equally deprived areas. If we can understand why some parts of the country do better than others given similar rates of poverty, we can draw out learning about what might work to support better child development for preschool children across all deprived areas. Our study will help local leaders who are required to revise and publish their ‘Start for Life’ offer of services for children and their families in the first 1000 days of life (conception to age 2). This is a mixed methods study using national data routinely collected from services (quantitative) with interviews and analysis of documents from local areas (qualitative). We will describe the relationship between family adversity and need from before conception to birth and child development at age 2 at an area level, including how this relationship varies across local authorities providing different levels of services. We will use a mixture of individual level data and area level indicators of family deprivation and adversity. We will use Ages and Stage Questionnaire (ASQ-3 TM) at an area level as our measure of child development. Using machine learning techniques, we will select a model that best predicts child development outcomes across all areas of England in order to identify `outperforming’ local authorities (with area level child development outcomes higher than expected). We will carry out a qualitative study of three local ‘outperforming’ areas in England and Wales using a case study approach. In each area we will interview professionals and families to build a detailed picture of why these area appear to be ‘outperforming’ others. This will involve further teasing out the ways in which child and family characteristics and local services drive child development before age 2. We will then draw out any general principles that could be shared with other areas. This study is part of the work of the NIHR Children and Families Policy Research Unit More information on the study is available here https://www.ucl.ac.uk/children-policy-research/projects/start-life-tackling-inequalities-child-development-age-2
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