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Expansion of quality preschool in Philadelphia: Leveraging an evidence-based, integrated data system to provide actionable intelligence for policy and program planning
Children and Youth Services Review ( IF 2.4 ) Pub Date : 2021-06-02 , DOI: 10.1016/j.childyouth.2021.106093
John Fantuzzo , Katherine Barghaus , Kristen Coe , Whitney LeBoeuf , Cassandra Henderson , Caroline C. DeWitt

To address the national priority for school readiness, there is a growing body of research investigating early care and education (ECE) deserts. This research identifies geographies within jurisdictions where there are high demands for and low supplies of ECE programs. The current study used a new approach to investigate preschool deserts in Philadelphia that addressed shortcomings in existing research. This approach used evidence-based measures of supply and demand across neighborhoods to identify and respond to preschool deserts in real time. A population-based data model of early childhood risks derived from a disciplined, local Integrated Data System (IDS) was used to calculate demand and triage it by multiple evidence-based early risk experiences. Actual counts of the number of slots in preschool centers with an evidence-based high-quality rating were used to calculate supply. High-quality, preschool deserts were defined as the neighborhoods with the greatest number of children with multiple evidence-based early risks and the lowest number of high-quality preschool slots relative to the city average. Results showed that about 3 out of 10 preschool children in Philadelphia live in a high-quality preschool desert. A report on how policymakers used the findings to increase high-quality preschool capacity was provided. Findings demonstrate how this evidence-based approach to the investigation of preschool deserts can increase the possibility of providing relevant, actionable intelligence to local policymakers and public service providers.



中文翻译:

在费城扩大优质学前班:利用基于证据的综合数据系统为政策和项目规划提供可操作的情报

为了解决入学准备的国家优先事项,越来越多的研究调查早期护理和教育 (ECE) 沙漠。这项研究确定了对 ECE 计划有高需求和低供应的司法管辖区内的地理区域。当前的研究使用了一种新方法来调查费城的学龄前沙漠,以解决现有研究中的不足。这种方法使用基于证据的社区供需测量来实时识别和应对学龄前沙漠。一个基于人群的早期儿童风险数据模型来自于规范的本地综合数据系统 (IDS),用于计算需求并通过多种基于证据的早期风险经验对其进行分类。使用具有循证高质量评级的学前中心的实际数量来计算供应量。高质量的学前沙漠被定义为与城市平均水平相比,具有多重循证早期风险的儿童数量最多且高质量学前班数量最少的社区。结果显示,费城每 10 个学龄前儿童中约有 3 个生活在高质量的学前沙漠中。提供了一份关于政策制定者如何利用调查结果来提高高质量学前班能力的报告。调查结果表明,这种以证据为基础的学前沙漠调查方法如何能够增加向当地政策制定者和公共服务提供者提供相关的、可操作的情报的可能性。学前沙漠被定义为与城市平均水平相比,具有多重循证早期风险的儿童数量最多且高质量学前班数量最少的社区。结果显示,费城每 10 个学龄前儿童中约有 3 个生活在高质量的学前沙漠中。提供了一份关于政策制定者如何利用调查结果来提高高质量学前班能力的报告。调查结果表明,这种以证据为基础的学前沙漠调查方法如何能够增加向当地政策制定者和公共服务提供者提供相关的、可操作的情报的可能性。学前沙漠被定义为与城市平均水平相比,具有多重循证早期风险的儿童数量最多且高质量学前班数量最少的社区。结果显示,费城每 10 个学龄前儿童中约有 3 个生活在高质量的学前沙漠中。提供了一份关于政策制定者如何利用调查结果来提高高质量学前班能力的报告。调查结果表明,这种以证据为基础的学前沙漠调查方法如何能够增加向当地政策制定者和公共服务提供者提供相关的、可操作的情报的可能性。

更新日期:2021-06-17
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