Data Insight: Childhood educational predictors of re-offending trajectories

This Data Insight examines the feasibility of using childhood educational information to develop predictive models of re-offending trajectories. A re-offending trajectory is the pattern by which a person commits crimes throughout their lifetime. Read more about what this means. This research aimed to explore whether we could use de-identified administrative educational and social care data to potentially identify the characteristics of individuals who may go on to become persistent offenders.

The research used the Ministry of Justice and Department for Education linked dataset – England. This included de-identified data from the Police National Computer (PNC) and National Pupil Database (NPD).

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Background

Criminal behaviour is a global public health problem, associated with a wide range of poor health and social outcomes for both victims and perpetrators. Such behaviour typically follows distinct pathways or trajectories, with some individuals behaving antisocially throughout their life, and others for only short periods of time such during adolescence. This is known as the taxonomy of antisocial behaviour – taxonomy is the practice of categorisation. In the first part of Dr Hannah Dickson's ADR UK Research Fellowship, she found five different re-offending trajectories:

1. Non-violent adolescent-limited prolific (AdolLim-prolific): this group committed a higher than average number of non-violent offences during adolescence only.
2. Non-violent adolescent-limited low density (AdolLim-Low): this group committed a low number of non-violent offences in adolescence only.
3. Mixed offence type life course prolific (LCP): this group committed different offence types at a higher-than-average rate throughout their lives.
4. Mixed offence type ‘later’ onset with escalating offence history (Adol-Late Onset): this group committed different offence types, with the number of offences rising more steeply in adulthood than in adolescence.
5. Non-violent adult-limited low density (Adult-low): this group committed a low number of non-violent offences in adulthood only.

Administrative education and social care data in England represents a rich but under-utilised longitudinal source of de-identified information on every child in state education. This includes demographic, education and socioeconomic information. The aim of the second part of this ADR UK-funded fellowship was to examine whether it was possible to use administrative education and social care data to identify the characteristics of children and adolescents that indicate they are more likely to become persistent and prolific offenders, before involvement with the criminal justice system begins. This insight could support better targeting of possible therapeutic interventions.

What we found

The findings are based on 694,192 individuals born between 1 September 1990 and 31 August 1999, who offended between January 2000 and December 2017 and had information on month and year of birth in the NPD. Figure 1 shows how some of the model educational variables differed according to the different re-offending trajectories. From Figure 1, we can see that that there were larger proportions of individuals who:

• were male
• were eligible for free school meals
• performed below KS1 attainment thresholds
• were receiving special educational needs support in the LCP compared to other re-offending trajectories.

The research also found higher proportions of individuals from Black ethnic backgrounds in the LCP and Adol-Late Onset trajectories. There were proportionally more females in the AdolLim-Low trajectory compared to the others. Approximately one-third of all individuals in this analysis had been excluded from school prior to their first involvement with the criminal justice system. However, for individuals in the AdolLim-Low trajectory, this was only around 25%. 

Figure 1. Breakdown of educational variables according to re-offending trajectories