Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 915

The DOI matches its Crossref record.

Rethinking Risk Assessment: The MacArthur Study of Mental Disorder and Violence

·2001

Abstract

The presumed link between mental disorder and violence has been the driving force behind mental health law and policy for centuries. Legislatures, courts, and the public have come to expect that mental health professionals will protect them from violent acts by persons with mental disorders. Yet for three decades research has shown that clinicians’ unaided assessments of “dangerousness” are barely better than chance. Rethinking Risk Assessment: The MacArthur Study of Mental Disorder and Violence tells the story of a pioneering investigation that challenges preconceptions about the frequency and nature of violence among persons with mental disorders, and suggests an innovative approach to predicting its occurrence. The authors of this massive project—the largest ever undertaken on the topic—demonstrate how clinicians can use a “decision tree” to identify groups of patients at very low and very high risk for violence. This dramatic new finding, and its implications for the every day clinical practice of risk assessment and risk management, is thoroughly described in this remarkable and long-anticipated volume. Taken to heart, its message will change the way clinicians, judges, and others who must deal with persons who are mentally ill and may be violent will do their work.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/oso/9780195138825.001.0001

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 915

Metadata

Published
2001-03-01
OpenAlex
W4388361532
Cited by
915
References
0
FWCI
35.73
Type
book
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

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

This page
CoChat. (2026). Citation check: Rethinking Risk Assessment: The MacArthur Study of Mental Disorder and Violence. https://app.cochat.ai/papers/10.1093/oso/9780195138825.001.0001
The paper
Rethinking Risk Assessment: The MacArthur Study of Mental Disorder and Violence. (2001). https://doi.org/10.1093/oso/9780195138825.001.0001

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.