Stop and search and young Black people’s mental health: How a new data tool can facilitate research
Article by Dr Jolyon Miles-Wilson
Quantitative Research Fellow
2nd February 2023
Rates of mental illness in England vary by ethnic group[1]. Social determinants of health (e.g., education, employment, discrimination) are likely to play an important role in these disparities. For people racialized as ‘Black’[2], structural and institutional racism across domains contribute to ill health[3]. One such domain is policing. Stop and search – the power by which police officers can detain and search who they suspect have been, are currently, or are about to be, involved in crime – is disproportionately targeted at Black people, especially boys and young men[4].
From December 2021 to November 2022, in England and Wales Black people were 6.5 times more likely to be stopped and searched than White people[5]. Being over-policed in this way likely has negative consequences on mental health. Indeed, our colleagues’ research at King’s College London suggests that young people who were stopped and searched were 2-3 times more likely to report high levels of mental distress compared to young people who were not stopped[6]. These findings highlight the need for closer scrutiny of stop and search practice.
Scrutiny relies on accessible, comprehensive, and up-to-date data. However, there are often limitations to accessing and using stop and search data that create obstacles for researchers and others. For example, the Home Office’s Police Powers and Procedures[7] statistical release combines stops made under the Police and Criminal Evidence Act 1984 with other legislation, such as the Misuse of Drugs Act 1971. However, users may be interested in distinguishing between these legislations, especially since the majority of all stops (62%) between 2017-2021 were made under the Misuse of Drugs Act [8], (see Table 1).
As part of the Wellcome Trust’s Mental Health Data Prize[1], we aimed to address these limitations and facilitate research on stop and search. We did so by creating an R[2] package, called extractss[3], that makes it easier to acquire comprehensive stop and search data. extractss contains algorithms that extract stop and search data via the Police’s API[4] and organises them into a format ready for use in research. This saves researchers considerable time and effort; extractss can acquire all stop records in England and Wales for the past 36 months (approximately 1.5 million stops) using a single command. The data acquired via extractss relate to stops that are more recent and made under a broader range of legislation compared to other sources and include a comprehensive set of variables that can speak to a range of research questions, including disproportionality over time (Figure 1), reasons and outcomes of stops, and times and locations.
Researchers could also combine these data with other datasets, as we have done. To investigate the relationship between the use of stop and search and young Black people’s mental health, we combined stop and search data with data from Understanding Society, a longitudinal household panel study. The results of our analyses are not yet ready for sharing, but an example code of how we combined the two datasets can be found here and illustrates how researchers could combine data from extractss with other datasets to investigate its impact on individuals.
extractss makes it possible to derive more temporally and geographically relevant insights on stop and search that have the potential to empower communities and drive change. Our hope is that this will serve as a useful tool in the pursuit of knowledge that will promote fair and just policing and mitigate the potential negative mental health consequences associated with being stopped and searched.
FOOTNOTES
[1] ‘Mental Health and Wellbeing in England: Adult Psychiatric Morbidity Survey 2014’ (Leeds, UK: NHS Digital, 2016), https://digital.nhs.uk/data-and-information/publications/statistical/adult-psychiatric-morbidity-survey/adult-psychiatric-morbidity-survey-survey-of-mental-health-and-wellbeing-england-2014
[2] We refer to race categories with quotes to highlight the fact that race is a social construct. Broad race categories homogenise diverse populations, and are not real beyond the social context that defines them.
[3] ‘“The Violence of the System”: Race, Mental Health, State Violence’, Institute of Race Relations, accessed 2 February 2023, https://irr.org.uk/article/race-mental-health-state-violence/
[4] Simon Flacks, ‘The Stop and Search of Minors: A “Vital Police Tool”?’, Criminology & Criminal Justice 18, no. 3 (1 July 2018): 364–84, https://doi.org/10.1177/1748895817720485; Juan José Medina Ariza, ‘Police-Initiated Contacts: Young People, Ethnicity, and the “Usual Suspects”’, Policing and Society 24, no. 2 (15 March 2014): 208–23, https://doi.org/10.1080/10439463.2013.784301; Michael Shiner et al., ‘The Colour of Injustice: “Race”, Drugs and Law Enforcement in England and Wales’, 2018, 86.
[5] ‘BlackThrive/Feb23_ss_blog_, accessed 2 February 2023, https://github.com/BlackThrive/feb23_ss_blog_analysis.
[6] Samantha Davis et al., ‘Police Contact, Stop and Search, and Mental Distress among Young People in Inner-City London: Findings from the Resilience, Ethnicity and AdolesCent Mental Health (REACH) Cohort Study’, in prep.
[7] Home Office, ‘Police Powers and Procedures England and Wales Statistics’ (London: Home Office, 2022), https://www.gov.uk/government/collections/police-powers-and-procedures-england-and-wales
[8] ‘BlackThrive/Feb23_ss_blog_analysis’.
[9] ‘Wellcome Mental Health Data Prize’, Wellcome, accessed 26 January 2023, https://wellcome.org/grant-funding/schemes/wellcome-mental-health-data-prize
[10] R is a programming language used by many researchers for data management and statistical analysis
[11] Details on extractss and its use can be found here: https://github.com/BlackThrive/extractss
[12] ‘Data.Police.Uk’, accessed 26 January 2023, https://data.police.uk/.
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