Steadman H J, Silver E, Monahan J, Appelbaum P S, Robbins P C, Mulvey E P, Grisso T, Roth L H, Banks S
Policy Research Associates, Inc., Delmar, NY 12054, USA.
Law Hum Behav. 2000 Feb;24(1):83-100. doi: 10.1023/a:1005478820425.
Since the 1970s, a wide body of research has suggested that the accuracy of clinical risk assessments of violence might be increased if clinicians used actuarial tools. Despite considerable progress in recent years in the development of such tools for violence risk assessment, they remain primarily research instruments, largely ignored in daily clinical practice. We argue that because most existing actuarial tools are based on a main effects regression approach, they do not adequately reflect the contingent nature of the clinical assessment processes. To enhance the use of actuarial violence risk assessment tools, we propose a classification tree rather than a main effects regression approach. In addition, we suggest that by employing two decision thresholds for identifying high- and low-risk cases--instead of the standard single threshold--the use of actuarial tools to make dichotomous risk classification decisions may be further enhanced. These claims are supported with empirical data from the MacArthur Violence Risk Assessment Study.
自20世纪70年代以来，大量研究表明，如果临床医生使用精算工具，暴力行为临床风险评估的准确性可能会提高。尽管近年来用于暴力风险评估的此类工具在开发方面取得了相当大的进展，但它们仍然主要是研究工具，在日常临床实践中基本被忽视。我们认为，由于大多数现有的精算工具基于主效应回归方法，它们没有充分反映临床评估过程的偶然性。为了加强精算暴力风险评估工具的使用，我们提出一种分类树方法而非主效应回归方法。此外，我们建议通过采用两个决策阈值来识别高风险和低风险案例，而不是标准的单一阈值，可以进一步加强使用精算工具进行二分法风险分类决策。这些主张得到了麦克阿瑟暴力风险评估研究的实证数据支持。
