Assessing predictions of violence: Being accurate about accuracy.

Douglas Mossman·1994·Journal of Consulting and Clinical Psychology

Abstract

The prediction of violence occupies a prominent and controversial place in public mental health practice. Productive debate about the validity of violence predictions has been hampered by the use of methods for quantifying accuracy that do not control for base rates or biases in favor of certain outcomes. This article describes these problems and shows how receiver-operating characteristic analysis can be used to solve them. The article also reanalyzes 58 data sets from 44 published studies of violence prediction. Taken together, these data strongly suggest that mental health professionals' violence predictions are substantially more accurate than chance. Short-term (1-7 day) clinical predictions seem no more accurate than long-term (> 1 year) predictions. Past behavior alone appears to be a better long-term predictor of future behavior than clinical judgments and may also be a better indicator than cross-validated actuarial techniques.

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How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Assessing predictions of violence: Being accurate about accuracy. https://app.cochat.ai/papers/10.1037//0022-006x.62.4.783
The paper
Mossman, D. (1994). Assessing predictions of violence: Being accurate about accuracy. Journal of Consulting and Clinical Psychology. https://doi.org/10.1037//0022-006x.62.4.783

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.