16 March 2022
In this blog, ADR UK Research Fellow Dr Hannah Dickson explains how her research will support more effective interventions to prevent prolific offending by identifying the early drivers of this behaviour.
Generally, criminal offending follows distinct pathways or trajectories. Some individuals begin offending early in childhood and continue into adulthood, known as ‘prolific’ or persistent offending. Others offend for only short periods of time, such as during adolescence. A 2019 Ministry of Justice (MoJ) report indicated that approximately 42% of the prison population on 31 March 2019 were prolific offenders, suggesting that a large proportion of criminal offences are committed by these individuals. An MoJ report in 2018 based on a cohort of offenders in 2016 who continued to offend over a 12-month period estimated the total costs of reoffending at £18.1 billion.
Research that follows groups of people over long periods of time has identified some important drivers of different offending patterns. These include poor academic attainment, school exclusion, and disadvantaged social environments. However, this research is limited because:
- sample sizes for disadvantaged groups are too small
- research participants don’t represent the full population
- data is not collected regularly.
If we can better understand the early drivers of prolific offending, then maybe we can intervene early – before involvement with the criminal justice system begins. This could potentially reduce the economic and social costs of crime for both victims and offenders.
How can administrative data research help?
Recently, the Department for Education (DfE) and MoJ created a large dataset linking together de-identified administrative data on education, social care and crime. The dataset contains lots of important information on every child in mainstream education. It is also cost effective because the data has already been collected.
The recent funding of ADR UK by the Economic and Social Research Council, part of UK Research and Innovation means that it is now possible for researchers like me to use this data. I hope that this will showcase new ways to tackle public health problems and improve public services.
In my 12-month project, I will use the de-identified dataset to identify different patterns of offending behaviours following a first recorded conviction or caution. Then I will build statistical models to see if I can identify the key factors related to education and social care that drive the different offending patterns.
The project has the potential to identify previously unknown offending patterns based on ‘real world’ data from the UK population. It may also identify unknown drivers or even preventative factors for offending. Overall, the results of this project will highlight whether administrative data can be used to inform UK offending reduction strategies in a highly efficient and cost-effective way.
However, using de-identified administrative data for research purposes like this can raise some important ethical and legal questions. That is why I plan to consult with the people affected by this research – such as ex-offenders and young people – during the project. Giving those involved a voice in the research I am undertaking will help shape the project and provide ideas on how to use its results in future.
Dr Hannah Dickson is an ADR UK-funded Research Fellow using linked MoJ-DfE data made available through Data First.