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The effect of digital technology on prisoner behavior and reoffending: a natural stepped-wedge design

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Abstract

Objectives

Although prisons aspire to rehabilitate offenders, they fail to prepare prisoners for release into our modern digitally sophisticated society. The objectives of the current study were to assess the impact of digital technology on the culture of prisons, and on prisoners’ ability to self-manage their behavior and reoffending.

Method

Using a natural stepped-wedge design, 13 prisons in the UK were examined that had installed self-service technology over a period of 7 years. A longitudinal multi-level model was used to analyze frequencies of disciplinary proceedings within and between the prisons before and after installation. Reoffending was examined in comparison with a control sample. Quantitative results were supported by a prisoner survey and usage data.

Results

Prison disciplinary offenses were significantly reduced over a two-year period, and reoffending in the first year after release was reduced by 5.36% compared to a 0.78% reduction in comparison prisons. The prisoner survey and usage data suggested that prisoners felt much more in control of their lives in prison and much more confident in coping with technology in the outside world.

Conclusions

The changes created by the introduction of digital technology offer the opportunity to make prisons more efficient for staff, and places of improved learning and rehabilitation for prisoners, contributing to a safer society. This study offers an important contribution to the field of corrections, providing the first quantitative assessment of the effect of prisoner self-service technology on prisoner behavior and reoffending.

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Notes

  1. Available from https://www.gov.uk/government/statistics/proven-reoffending-statistics-july-2012-to-june-2013.

  2. One year reoffending data for seven of the prisons were provided by Justice Statistics Analytical Services (JSAS); some prisons were excluded due to missing data.

  3. This analysis differs from that used by JSAS, who compare full calendar year data against a selected baseline year, whereas data in the current study were taken from a selected subset to fit the stepped-wedge design, centered on PSS installation.

  4. The Offender Group Reconviction Scale (OGRS) is a predictor of reoffending based on static risk factors: age, gender, and criminal history.

  5. rx 1 = rx − (gx − G), where rx 1 = adjusted reoffending rate in period x, rx = original reoffending rate in period x, gx = OGRS in period x, and G = OGRS in the baseline year (2011).

  6. An example of a typical prison survey response rate is 4% to 25% across eight prisons, e.g., published in Third Sector Research Centre Working Paper 61, 2011, a report on “Offender engagement with third sector organisations: a national prison-based survey”.

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Acknowledgements

The authors would like to commend Francis Toye, Director of Unilink, who, having funded the project, deliberately abstained from trying to influence the research and the outcomes, and Roger Holding, whose original idea it was to seek a rigorous independent evaluation. Neither of the above was known to the authors prior to the commission.

Thanks are due to HM National Offender Management Service (NOMS) National Research Committee, who critically appraised the research application for quality of design and ethical issues, and made helpful suggestions to improve the research.

Thanks are also due to NOMS Statistical Departments, who advised on availability and provided data to assist the evaluation, and to the Ministry of Justice, Justice Statistics Analytical Services, who provided us with selected samples of proven reoffending data and helpfully commented on the analysis.

We are grateful to the unnamed prisons in England, Scotland, and Wales, and to their executive directors, who willingly helped with our research and entrusted us with commercially sensitive data to assist the evaluation.

Finally, we also thank Dr. Mona Kanaan, statistician in the Health Sciences Department at the University of York, for her valuable comments on the statistical analyses.

Funding

This work was funded via the universities of York and Portsmouth by Unilink Software Ltd. The sponsor specifically requested an independent university evaluation and made no interventions in the research design, analysis, interpretation, or conclusions.

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Authors and Affiliations

  1. University of York, Heslington, York, YO10 5DD, UK

    Cynthia McDougall, David J. Torgerson & Maria Garcia-Reyes

  2. University of Portsmouth, King Henry Building, King Henry I Street, Portsmouth, PO1 2DY, UK

    Dominic A. S. Pearson

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  1. Cynthia McDougall
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Correspondence to Cynthia McDougall.

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McDougall, C., Pearson, D.A.S., Torgerson, D.J. et al. The effect of digital technology on prisoner behavior and reoffending: a natural stepped-wedge design. J Exp Criminol 13, 455–482 (2017). https://doi.org/10.1007/s11292-017-9303-5

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