Risk Assessment in Criminal Sentencing Annual Review of Clinical Psychology
The predictive performance of criminal take chances assessment tools used at sentencing: Systematic review of validation studies
Abstract
Although risk cess tools have been widely used to inform sentencing decisions, there is incertitude about the extent and quality of evidence of their predictive performance when validated in new samples. Following PRISMA guidelines, we conducted a systematic review of validation studies of 11 commonly used adventure assessment tools for sentencing. We identified 36 studies with 597,665 participants, among which were 27 independent validation studies with 177,711 individuals. Overall, the predictive operation of the included run a risk assessment tools was mixed, and ranged from poor to moderate. Tool operation was typically overestimated in studies with smaller sample sizes or studies in which tool developers were co-authors. Most studies only reported area under the curve (AUC), which ranged from 0.57 to 0.75 in independent studies with more 500 participants. The bulk did not report cardinal performance measures, such as scale and rates of fake positives and negatives. In addition, about validation studies had a high risk of bias, partly due to inappropriate analytical approach used. We conclude that the research priority is for future investigations to address the key methodological shortcomings identified in this review, and policy makers should enable this research. More sufficiently powered contained validation studies are necessary.
Introduction
Chance cess tools are widely used to inform sentencing decisions for individuals convicted of crimes in many high-income countries (van Ginneken, 2019). These tools tin influence decisions on whether someone receives a prison or community-based judgement, sentence length, and associated restrictions, such equally electronic tagging (Monahan & Skeem, 2016). The choice between custodial and not-custodial outcomes is significant as prison is associated with many negative ramifications for accommodation, relationships, and employment (Harding, Wyse, Dobson, & Morenoff, 2014; Keene, Smoyer, & Blankenship, 2018; Western, Braga, Davis, & Sirois, 2015). Sentence length is determined past legislation and provides a range of judgement length options, which is typically based on certain individual factors, including the previous criminal history and take chances of hereafter serious offending. These tools can also assist with treatment decisions, especially for people with mental health issues, and atomic number 82 to referrals to diversion services. Risk cess tools need to be high quality because of the potential consequences for individuals in the criminal justice arrangement and public health and safe. For people in the criminal justice system, the utilize of inaccurate take chances assessment tools can lead to longer periods of time in custody. For public wellness and safety, it can lead to wasteful and poor allocation of resources if people remain in custody who could be released based on risk levels, and the consequences of repeat offending in people released without appropriate supervision and treatment. Furthermore, the wider ethical implications on public trust in criminal justice are relevant in that such tools should be transparently designed and reported, and not lead to amplification of systemic biases and also potentially mitigate against them.
Previous work reviewing these tools has combined different samples and settings, including forensic psychiatric hospitals, intra-institutional outcomes, and non-offending samples (Campbell, French, & Gendreau, 2009; Fazel, Singh, Doll, & Grann, 2012; Ramesh, Igoumenou, Vazquez Montes, & Fazel, 2018; Singh, Serper, Reinharth, & Fazel, 2011). In addition, it has combined development (likewise known every bit discovery) samples with validation ones, which does not reflect real-world performance every bit the development samples tend to overestimate predictive functioning (Pavlou et al., 2015). Furthermore, validation studies may accept been conducted by the tool developers, which tin can atomic number 82 to authorship bias (Singh, Grann, & Fazel, 2013), and separately examining such investigations conducted by independent groups needs consideration. Finally, previous reviews have used performance measures such as correlation coefficients and effect sizes that are not informative on their ain and not recommended in standard guidelines for systematic reviewing of prediction models (Moons et al., 2014). Rather, measures of discrimination (including truthful and faux positives and negatives), and calibration (how estimated and predicted risk scores compare) are necessary for any tool to be evaluated (Collins, Reitsma, Altman, & Moons, 2015).
To address these limitations, we have conducted a systematic review of validation studies of risk cess tools that are used to inform controlling in the criminal justice organization. Our primary outcomes were measures of predictive performance from independent validations, where tool developers are non co-authors. In so doing, we aim to provide a focused overview that will inform criminal justice and linked mental health services.
Department snippets
Protocol and registration
This systematic review was pre-registered under the Open up Science Framework (OSF). The protocol can be retrieved from: https://osf.io/59szj
Literature search
Equally a first step, we identified risk cess tools commonly used at the sentencing phase for criminal offences to estimate take chances of recidivism by searching PsycINFO, Medline, and EMBASE with the following keywords: (psychiatry OR forensic OR psychology) AND (sentencing OR sanctioning OR sanction OR violence) AND (backsliding OR re-criminal offence) AND risk assessment
Results
Overall, we identified 36 studies with 597,665 participants (PRISMA flowchart in Supplementary Fig. one), which were based in seven countries (Table ii). Of these, 27 were independent validation studies with 177,711 participants, reporting on 7 tools: COMPAS, HCR-20, LS/CMI, LSI-R, PCL-R, PCRA, and Static-99. No eligible validation studies were identified for IRAS and NVRA. The ORAS and OASys were but validated by the developers of these tools. The most common operation statistic reported was the
Discussion
In this systematic review of 36 studies of risk assessment tools used to inform decision-making in the criminal justice system that followed upwardly 597,665 participants for repeat offending, we identified functioning measures for nine tools. In the sixteen contained investigations with more than than 500 participants each, the nigh common reported outcome statistic was the AUC, which ranged from 0.57 to 0.75.
Overall, the extent and quality of evidence in back up of these tools is typically poor to
Conclusion
In this systematic review of external validation studies of 11 mutual run a risk assessment tools, most investigations solely reported the AUC equally an indication of model performance, just did not present other key measures including rates of false positives and negatives, and scale. Equally such, based on the current published evidence, the highest priority is for researchers to work towards addressing the primal methodological limitations identified in previous work. Jurisdictions that are because
Funding
SF is funded by a Wellcome Trust Senior Enquiry Fellowship (Grant no. 202836/Z/16/Z).
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