The longitudinal association between school performance trajectories and offending behaviour

了解犯罪和再犯罪的风险和保护因素是司法部的一个重点研究领域。彻底了解导致犯罪行为的环境对于制定减少犯罪活动的公共政策至关重要，这反过来又会带来社会和经济效益。作为对这一优先领域的回应，该研究项目将使用相关的国家学生数据库（NPD）和警察国家计算机（PNC）数据来调查学校表现，作为犯罪行为的关键预测因素。受教育程度低被认为与犯罪行为的风险增加有关。但我们对整个童年和青春期的学校表现变化知之甚少，也不知道在校期间持续的低表现或下降的表现轨迹是否会增加犯罪和再犯罪的风险。在学校期间持续的高表现或提高表现是否会降低已知弱势群体的犯罪风险，比如那些来自贫困背景的人，照顾孩子的人，有特殊教育需要的学生，这也是未知的。在拟议的研究项目中，我的目标是确定遵循不同学校表现轨迹的学生亚组，并调查他们与不同类型的犯罪和再犯罪行为（如暴力，性犯罪，盗窃和抢劫）的关系。我还旨在调查高水平或不断提高的学校表现轨迹是否会降低弱势群体和边缘群体的犯罪行为风险，以及这些关系是否存在地区差异。我将使用1990年至1997年间出生的学生纵向队列，并使用我之前在NPD数据中开发的统计建模技术来实现这一目标。了解这一点可以为表现出遵循某些学校表现轨迹的早期迹象的儿童提供早期识别和预防策略，并证明让弱势群体参与教育的重要性。该项目还将探索相关的NPD-PNC数据资源，并向数据的未来用户提出建议。特别是，以前的数据联系表明，社会人口统计信息在行政数据集之间的记录并不总是一致的。因此，在这个项目的过程中，将检查NPD和PNC在性别和种族记录上的差异，并提出建议以协调发现的任何差异。此外，研究人员还将探讨利用该数据资源进行准实验性试验的可能性，例如调查提供特殊教育需要是否会减轻犯罪风险。这可能为后续的高级团契工作奠定基础。合作和产出的设计是为了使这个项目的影响最大化。我将在项目设计和分析的各个方面咨询专业利益相关者、数据至上用户代表小组和一个由当地年轻人组成的咨询小组。我还将主持一个利益相关者参与活动，以建立跨部门合作，帮助解释调查结果，并为政策影响提供信息。在资助期内，我将专注于生产用户友好的输出和分享我开发的任何代码。在整个资助期间，我还将参与网络、知识交流以及相关的领导和参与培训机会。我将嵌入一个团队，成功地将NHS心理健康记录与NPD联系起来，目前正在将NHS心理健康记录与PNC联系起来。因此，我将能够利用各种数据联系进行有影响力的研究，并且从长远来看，可以扩大ADR英国数据优先的职权范围，包括心理健康、教育和刑事司法记录之间的三方数据联系。

Understanding risk and protective factors for offending and re-offending is a key research priority area for the Ministry of Justice. A thorough understanding of the circumstances driving offending behaviour is imperative for shaping public policy to reduce criminal activity, which will in turn have societal and economic benefits. Developed in response to this priority area, this research project will use linked National Pupil Database (NPD) and Police National Computer (PNC) data to investigate school performance as a key predictor of offending behaviour. Low educational attainment is thought to be associated with increased risk of criminal behaviour. But little is known about changes in school performance throughout childhood and adolescence and whether consistently low or declining performance trajectories through school increase offending and re-offending risk. It is also unknown whether consistently high or improving performance through school might mitigate risk for offending among known vulnerable groups, such as those from deprived backgrounds, looked after children, and pupils with special educational needs. In the proposed research project, I aim to identify subgroups of pupils who follow different school performance trajectories, and investigate their association with different types of offending and re-offending behaviours (such as violence, sexual offences, theft and robbery). I also aim to investigate whether high or increasing school performance trajectories mitigate risk for offending behaviour in vulnerable and marginalised groups, and whether there are regional differences in these relationships. I will achieve this using a longitudinal cohort of pupils born between 1990 and 1997, and using statistical modelling techniques that I have previously developed in NPD data.Understanding this could inform early identification and prevention strategies for children showing early signs of following certain school performance trajectories, and demonstrate the importance of engaging vulnerable groups in education.This project will also explore the linked NPD-PNC data resource and make recommendations to future users of the data. In particular, previous data linkages have shown that socio-demographic information is not always consistently recorded between administrative datasets. Therefore, in the course of this project, the NPD and PNC will be checked for discrepancies in gender and ethnicity recordings, and recommendations will be made for reconciling any discrepancies identified. The potential for the data resource to be used to conduct quasi-experimental trials, for example investigating whether special educational needs provision mitigates offending risk, will also be explored. This may lay the groundwork for subsequent advanced fellowship work.Collaborations and outputs have been designed to maximise the impact of this project. I will consult with professional stakeholders, the Data First User Representation Panel and a local advisory group of young people at various points of project design and analysis. I will also host a stakeholder engagement event to build cross-sector collaborations, help interpret findings, and inform policy implications. Within the funding period, I will focus on producing user-friendly outputs and sharing any code I develop. I will also engage in networking, knowledge exchange, and relevant leadership and engagement training opportunities throughout the funding period. I will be embedded in a team which has successfully linked NHS mental health records to the NPD, and is currently linking NHS mental health records to the PNC. I will therefore be positioned to use various data linkages for impactful research and, long-term, can extend the ADR UK Data First remit to include three-way data linkages between mental health, education and criminal justice records.