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A scoping review and meta-analyses of clinical override use in structured risk assessments: Clinical and training implications for field practice.

Psychology, Public Policy, and Law, Vol 31(3), Aug 2025, 217-233; doi:10.1037/law0000448

Clinical override is a feature in actuarial risk assessment tools that allows assessors to alter predetermined risk levels for offenders. Although the body of research has focused on improving the predictive validity of risk classification, no comprehensive understanding of the use or impacts of clinical override has yet to be achieved. In this article, we first conduct a scoping review to examine override use in actuarial risk assessment tools. Primary sources from the academic and gray literatures were included in the review if available in English and focused on predictive validity and override. Twenty-one studies evaluating the use of an override across eight risk assessment tools in the adult and youth offender populations were included. Data charting followed an iterative process, was organized in Google Sheets, and was validated by two authors. Given the rich pool of data collected in the scoping review, in Study 2, meta-analyses were conducted to obtain precise predictive validity estimates before and after an override. In studies where overridden offenders were analyzed separately, the area under the curve value before an override was .674 (95% confidence interval = [.638, .711]) and after was .593 (95% confidence interval = [.540, .646]). Overall, the results indicate that override is used frequently, does not enhance predictive validity, and, in many cases, appears to compromise the accuracy of risk classification judgments. These results are used to generate clinical, policy, and research-based recommendations for the field, with attention given to better aligning the use of clinical override with current knowledge and empirical science. (PsycInfo Database Record (c) 2025 APA, all rights reserved)

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Posted in: Journal Article Abstracts on 09/02/2025 | Link to this post on IFP |
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