Kate Lewis, Vincent Nguyen, Ania Zylbersztejn, Ruth Gilbert, Bianca De Stavola, Lorraine Dearden
{"title":"地方当局在主要先天性畸形儿童中提供小学记录的特殊教育需求方面的差异:一项研究方案","authors":"Kate Lewis, Vincent Nguyen, Ania Zylbersztejn, Ruth Gilbert, Bianca De Stavola, Lorraine Dearden","doi":"10.3310/nihropenres.13466.1","DOIUrl":null,"url":null,"abstract":"<ns3:p><ns3:bold>Introduction: </ns3:bold>Special educational needs (SEN) provision has been called a 'postcode lottery’ in England, but the extent to which this represents underlying inequities has not been sufficiently investigated. This study will focus on children with similar underlying health characteristics to explore sources of systematic variation in SEN provision by local authority (LA) in England.</ns3:p><ns3:p> <ns3:bold>Methods and analysis: </ns3:bold>We will use linked individual-level state-funded hospital and school records from the Education and Health Insights from Linked Data (ECHILD) database, alongside open-source school-level data. Our cohort will be defined as singleton children with major congenital anomalies born in England between 1 September 2003 and 31 August 2012. We will identify major congenital anomalies from diagnoses in hospital records in the first year of life using European Surveillance of Congenital Anomalies (EUROCAT) guidelines. LA (152 in total) will be defined by child’s residential address reported in education records at entry into year one of school (aged five years old). SEN provision will be defined by a recording of an educational health and care plan or SEN support in any census in Reception, year one or two of primary school (ages four/five to six/seven). To quantify variation in SEN provision we will fit multilevel logistic regression models to the individual records, with a-priori selected individual-, school- and LA-level characteristics. We will report the estimated intraclass correlation coefficient at each stage of the model, signifying the percentage of remaining variation in the odds of recorded SEN provision that is due to differences between LAs.</ns3:p><ns3:p> <ns3:bold>Ethics and dissemination</ns3:bold>: We have existing research ethics approval for analyses of the ECHILD database described in this protocol. We will disseminate our findings to diverse audiences (academics, relevant government departments, service users and providers) through seminars, peer-reviewed publications, short briefing reports and infographics for non-academics (published on the study website).</ns3:p>","PeriodicalId":74312,"journal":{"name":"NIHR open research","volume":"75 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Local authority variation in primary school-recorded special educational needs provision among children with major congenital anomalies: A research protocol\",\"authors\":\"Kate Lewis, Vincent Nguyen, Ania Zylbersztejn, Ruth Gilbert, Bianca De Stavola, Lorraine Dearden\",\"doi\":\"10.3310/nihropenres.13466.1\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<ns3:p><ns3:bold>Introduction: </ns3:bold>Special educational needs (SEN) provision has been called a 'postcode lottery’ in England, but the extent to which this represents underlying inequities has not been sufficiently investigated. This study will focus on children with similar underlying health characteristics to explore sources of systematic variation in SEN provision by local authority (LA) in England.</ns3:p><ns3:p> <ns3:bold>Methods and analysis: </ns3:bold>We will use linked individual-level state-funded hospital and school records from the Education and Health Insights from Linked Data (ECHILD) database, alongside open-source school-level data. Our cohort will be defined as singleton children with major congenital anomalies born in England between 1 September 2003 and 31 August 2012. We will identify major congenital anomalies from diagnoses in hospital records in the first year of life using European Surveillance of Congenital Anomalies (EUROCAT) guidelines. LA (152 in total) will be defined by child’s residential address reported in education records at entry into year one of school (aged five years old). SEN provision will be defined by a recording of an educational health and care plan or SEN support in any census in Reception, year one or two of primary school (ages four/five to six/seven). To quantify variation in SEN provision we will fit multilevel logistic regression models to the individual records, with a-priori selected individual-, school- and LA-level characteristics. We will report the estimated intraclass correlation coefficient at each stage of the model, signifying the percentage of remaining variation in the odds of recorded SEN provision that is due to differences between LAs.</ns3:p><ns3:p> <ns3:bold>Ethics and dissemination</ns3:bold>: We have existing research ethics approval for analyses of the ECHILD database described in this protocol. 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Local authority variation in primary school-recorded special educational needs provision among children with major congenital anomalies: A research protocol
Introduction: Special educational needs (SEN) provision has been called a 'postcode lottery’ in England, but the extent to which this represents underlying inequities has not been sufficiently investigated. This study will focus on children with similar underlying health characteristics to explore sources of systematic variation in SEN provision by local authority (LA) in England.Methods and analysis: We will use linked individual-level state-funded hospital and school records from the Education and Health Insights from Linked Data (ECHILD) database, alongside open-source school-level data. Our cohort will be defined as singleton children with major congenital anomalies born in England between 1 September 2003 and 31 August 2012. We will identify major congenital anomalies from diagnoses in hospital records in the first year of life using European Surveillance of Congenital Anomalies (EUROCAT) guidelines. LA (152 in total) will be defined by child’s residential address reported in education records at entry into year one of school (aged five years old). SEN provision will be defined by a recording of an educational health and care plan or SEN support in any census in Reception, year one or two of primary school (ages four/five to six/seven). To quantify variation in SEN provision we will fit multilevel logistic regression models to the individual records, with a-priori selected individual-, school- and LA-level characteristics. We will report the estimated intraclass correlation coefficient at each stage of the model, signifying the percentage of remaining variation in the odds of recorded SEN provision that is due to differences between LAs.Ethics and dissemination: We have existing research ethics approval for analyses of the ECHILD database described in this protocol. We will disseminate our findings to diverse audiences (academics, relevant government departments, service users and providers) through seminars, peer-reviewed publications, short briefing reports and infographics for non-academics (published on the study website).