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Journal ArticleDOI

Rates of violence in patients classified as high risk by structured risk assessment instruments

01 Mar 2014-British Journal of Psychiatry (Royal College of Psychiatrists)-Vol. 204, Iss: 3, pp 180-187
TL;DR: After controlling for time at risk, the rate of violence in individuals classified as high risk by SRAIs shows substantial variation and assigning predetermined probabilities to future violence risk on the basis of a structured risk assessment is not supported by the current evidence base.
Abstract: Background Rates of violence in persons identified as high risk by structured risk assessment instruments (SRAIs) are uncertain and frequently unreported by validation studies. Aims To analyse the variation in rates of violence in individuals identified as high risk by SRAIs. Method A systematic search of databases (1995-2011) was conducted for studies on nine widely used assessment tools. Where violence rates in high-risk groups were not published, these were requested from study authors. Rate information was extracted, and binomial logistic regression was used to study heterogeneity. Results Information was collected on 13 045 participants in 57 samples from 47 independent studies. Annualised rates of violence in individuals classified as high risk varied both across and within instruments. Rates were elevated when population rates of violence were higher, when a structured professional judgement instrument was used and when there was a lower proportion of men in a study. Conclusions After controlling for time at risk, the rate of violence in individuals classified as high risk by SRAIs shows substantial variation. In the absence of information on local base rates, assigning predetermined probabilities to future violence risk on the basis of a structured risk assessment is not supported by the current evidence base. This underscores the need for caution when such risk estimates are used to influence decisions related to individual liberty and public safety.

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Citations
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Journal ArticleDOI
TL;DR: Investigations conducted to date indicate that using objective markers is a promising strategy to predict clinically significant outcomes and may be a useful strategy for predicting outcomes.
Abstract: This systematic review aimed to examine whether neurobiological methods, or other methods independent of clinical judgment, have been investigated to assist decision making in forensic mental health services and, if so, whether this may be a useful strategy for predicting outcomes. OVID-Medline, Embase, and PsychInfo (inception-January 2015) were searched, limiting to English and human studies, using terms relating to "predict," "outcome," "psychiatry," and "forensic" to identify primary research articles reporting on predictors of outcome in forensic mental health services not reliant on clinical judgment/self-report. Fifty studies investigating demographic, neuropsychological/neurophysiological, and biological predictors were identified, reporting on 3 broad outcomes: (i) inpatient violence, (ii) length of stay, (iii) reoffending. Factors associated positively, negatively, and showing no relationship with each outcome were extracted and compiled across studies. Of various demographic predictors examined, the most consistent associations were between previous psychiatric admissions and inpatient violence; a more "severe" offense and a longer length of stay; and young age and reoffending. Poor performance on tests of cognitive control and social cognition predicted inpatient violence while a neurophysiological measure of impulsivity showed utility predicting reoffending. Serum cholesterol and creatine kinase emerged as biological factors with potential to predict future inpatient violence. Research in this field is in its infancy, but investigations conducted to date indicate that using objective markers is a promising strategy to predict clinically significant outcomes.

18 citations

Journal Article
TL;DR: In this article, the authors show how group data can have an obvious application to individual decisions, and explain how misunderstanding the aims of risk assessment has led to mistakes about how, when, and why group data apply to individual instances.
Abstract: Probability plays a ubiquitous role in decision-making through a process in which we use data from groups of past outcomes to make inferences about new situations. Yet in recent years, many forensic mental health professionals have become persuaded that overly wide confidence intervals render actuarial risk assessment instruments virtually useless in individual assessments. If this were true, the mathematical properties of probabilistic judgments would preclude forensic clinicians from applying group-based findings about risk to individuals. As a consequence, actuarially based risk estimates might be barred from use in legal proceedings. Using a fictional scenario, I seek to show how group data have an obvious application to individual decisions. I also explain how misunderstanding the aims of risk assessment has led to mistakes about how, when, and why group data apply to individual instances. Although actuarially based statements about individuals' risk have many pitfalls, confidence intervals pose no barrier to using actuarial tools derived from group data to improve decision-making about individual instances.

18 citations

Journal ArticleDOI
TL;DR: The furtive influences that shape both the (mis)interpretation and miscommunication of risk instruments in legal settings necessitate discussion.
Abstract: Forensic mental health practitioners are frequently asked to estimate the risk of future violence. Legal decisions concerning the sentencing, management and disposition of offenders often rely on the advice of such testimony. The burgeoning use of violence risk instruments in these settings undoubtedly injects a level of scientific rigour into forensic evaluations for courts and tribunals. Yet scrutiny of the inherent limitations of both risk instruments and the inferences and formulations drawn from them are often veiled by the discipline's endorsement for such approaches. Misconceptions about the validity and dependability of present-day risk assessments and expert infallibility persist. The furtive influences that shape both the (mis)interpretation and miscommunication of risk instruments in legal settings necessitate discussion.

17 citations

Journal ArticleDOI
TL;DR: In this article, the authors provide an overview of the Historical Clinical Risk (HCR) version 3, exploring its psychometric properties, considering its clinical and research applications, while al.
Abstract: The aim of this critique is to provide an overview of the Historical Clinical Risk–20, version 3, exploring its psychometric properties, considering its clinical and research applications, while al...

16 citations

Journal ArticleDOI
TL;DR: The development and pilot testing of a novel, web-based, violence risk monitoring instrument for use in community patients with psychoses, including drawing on systematic reviews of the field, and its subsequent piloting are described.
Abstract: We describe the development and pilot testing of a novel, web-based, violence risk monitoring instrument for use in community patients with psychoses. We describe the development of the tool, including drawing on systematic reviews of the field, how item content was operationalized, the development of a user interface, and its subsequent piloting. Sixty-eight patients were included from three English counties, who had been discharged from forensic psychiatric services. Over 12 months, 310 questionnaires were completed on the sample by professionals from several disciplines and qualitative feedback collected relating to the use of the tool using an electronic survey. Strengths of this approach for risk assessment, and potential limitations and areas for future research, are discussed.

16 citations

References
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Journal ArticleDOI
TL;DR: A general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies is presented and tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interob server agreement are developed as generalized kappa-type statistics.
Abstract: This paper presents a general statistical methodology for the analysis of multivariate categorical data arising from observer reliability studies. The procedure essentially involves the construction of functions of the observed proportions which are directed at the extent to which the observers agree among themselves and the construction of test statistics for hypotheses involving these functions. Tests for interobserver bias are presented in terms of first-order marginal homogeneity and measures of interobserver agreement are developed as generalized kappa-type statistics. These procedures are illustrated with a clinical diagnosis example from the epidemiological literature.

64,109 citations

Book
01 Jan 1974
TL;DR: The authors described three heuristics that are employed in making judgements under uncertainty: representativeness, availability of instances or scenarios, and adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available.
Abstract: This article described three heuristics that are employed in making judgements under uncertainty: (i) representativeness, which is usually employed when people are asked to judge the probability that an object or event A belongs to class or process B; (ii) availability of instances or scenarios, which is often employed when people are asked to assess the frequency of a class or the plausibility of a particular development; and (iii) adjustment from an anchor, which is usually employed in numerical prediction when a relevant value is available. These heuristics are highly economical and usually effective, but they lead to systematic and predictable errors. A better understanding of these heuristics and of the biases to which they lead could improve judgements and decisions in situations of uncertainty.

31,082 citations

Journal ArticleDOI
Nancy R. Cook1
TL;DR: The c statistic, or area under the receiver operating characteristic (ROC) curve, achieved popularity in diagnostic testing, in which the test characteristics of sensitivity and specificity are relevant to discriminating diseased versus nondiseased patients, may not be optimal in assessing models that predict future risk or stratify individuals into risk categories.
Abstract: The c statistic, or area under the receiver operating characteristic (ROC) curve, achieved popularity in diagnostic testing, in which the test characteristics of sensitivity and specificity are relevant to discriminating diseased versus nondiseased patients. The c statistic, however, may not be optimal in assessing models that predict future risk or stratify individuals into risk categories. In this setting, calibration is as important to the accurate assessment of risk. For example, a biomarker with an odds ratio of 3 may have little effect on the c statistic, yet an increased level could shift estimated 10-year cardiovascular risk for an individual patient from 8% to 24%, which would lead to different treatment recommendations under current Adult Treatment Panel III guidelines. Accepted risk factors such as lipids, hypertension, and smoking have only marginal impact on the c statistic individually yet lead to more accurate reclassification of large proportions of patients into higher-risk or lower-risk categories. Perfectly calibrated models for complex disease can, in fact, only achieve values for the c statistic well below the theoretical maximum of 1. Use of the c statistic for model selection could thus naively eliminate established risk factors from cardiovascular risk prediction scores. As novel risk factors are discovered, sole reliance on the c statistic to evaluate their utility as risk predictors thus seems ill-advised.

1,815 citations

Journal ArticleDOI
Kirk Heilbrun1
TL;DR: Federal Abortion Policy and Politics: 1973-1996 Why is Abortion Such a Controversial issue in the United States Barriers to Access to Abortion Services The Impact of Anti-abortion Activities on Women Seeking Abortions
Abstract: Federal Abortion Policy and Politics: 1973-1996 Why is Abortion Such a Controversial issue in the United States Barriers to Access to Abortion Services The Impact of Anti-abortion Activities on Women Seeking Abortions Black Women and the Question of Abortion Latinos and Abortion Abortion and Asian Pacific Islander Americans The Acceptability of Medical Abortion to Women Understanding the Relationship of Violence Against Women to Unwanted Pregnancy and it's Resolution Testing a Model of the Psychological Consequences of Abortion Men and Abortion: The Gender Politics of Pregnancy Resolution Abortion Among Adolescents A Cognitive Approach to Patient-Centered Abortion Care Abortion Issues in Psychotherapy Bringing Lessons Learned to the United States Improving Access to Abortion Services Abortion Practice, Policy, and Research: Recommendations for the 21st Century

1,564 citations