UNASSIGNED: We will analyse linked administrative data for England using the Education and Child Health Insights from Linked Data (ECHILD) database. A target trial emulation approach will be used to specify data extraction from ECHILD, comparisons of interest and our analysis plan. Our target population is all children enrolled in year one of state-funded primary school in England who were born in an NHS hospital in England between 2003 and 2008, grouped by gestational age at birth (extremely preterm (24-<28 weeks), very preterm (28-<32 weeks), moderately preterm (32-<34 weeks), late preterm (34-<37 weeks) and full term (37-<42 weeks). The intervention of interest will comprise categories of SEN provision (including none) during year one (age five/six). The outcomes of interest are rates of unplanned hospital utilisation, educational attainment, and absences by the end of primary school education (year six, age 11). We will triangulate results from complementary estimation methods including the naïve estimator, multivariable regression, g-formula, inverse probability weighting, inverse probability weighting with regression adjustment and instrumental variables, along with a variety for a variety of causal contrasts (average treatment effect, overall, and on the treated/not treated).
UNASSIGNED: 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).
One third of all children need extra help with learning in school, such as support from a teaching assistant. Children born preterm are more likely to need extra help compared to those born at term. In England, this help is called special educational needs (SEN) provision. The aim of this study is to find out whether special educational need provision affects education and health outcomes. We will use information collected by hospitals and schools for all children who were born in England between 2003 and 2008. We will compare those with who received and did not receive extra help in school who have a similar gestational age at birth.
■我们将使用链接数据中的教育和儿童健康见解(ECHILD)数据库分析英格兰的链接行政数据。目标试验仿真方法将用于指定从ECHILD中提取数据,比较兴趣和我们的分析计划。我们的目标人群是在2003年至2008年期间在英格兰NHS医院出生的所有在英格兰国家资助的小学一年级入学的儿童,按出生时的胎龄分组(极度早产(24-<28周),非常早产(28-<32周),中度早产(32-<34周),晚期早产(34-<37周)和足月(37-<42周)。感兴趣的干预将包括第一年(五岁/六岁)期间的SEN条款类别(包括无)。利息的结果是计划外的医院利用率,教育程度,小学教育结束时缺勤(六年级,年龄11岁)。我们将对互补估计方法的结果进行三角测量,包括幼稚估计器,多元回归,g-公式,逆概率加权,具有回归调整和工具变量的逆概率加权,以及各种因果对比(平均治疗效果,总的来说,和处理/未处理)。
■对于本方案中描述的ECHILD数据库的分析,我们已有研究伦理批准。我们将向不同的受众传播我们的发现(学者,政府有关部门,服务用户和提供商)通过研讨会,同行评审的出版物,非学者的简短简报报告和信息图表(发表在研究网站上)。
三分之一的孩子在学校学习方面需要额外的帮助,比如助教的支持。与足月出生的孩子相比,早产的孩子更可能需要额外的帮助。在英国,这种帮助被称为特殊教育需求(SEN)规定。这项研究的目的是找出特殊教育需求的提供是否会影响教育和健康结果。我们将使用医院和学校收集的信息,用于2003年至2008年间在英格兰出生的所有儿童。我们将比较那些在学校接受和没有接受额外帮助的人,他们出生时胎龄相似。