University of California San Diego.
Psychol Assess. 2019 Dec;31(12):1442-1455. doi: 10.1037/pas0000597. Epub 2019 Mar 14.
Item response theory (IRT) is moving to the forefront of methodologies used to develop, evaluate, and score clinical measures. Funding agencies and test developers are routinely supporting IRT work, and the theory has become closely tied to technological advances within the field. As a result, familiarity with IRT has grown increasingly relevant to mental health research and practice. But to what end? This article reviews advances in applications of IRT to clinical measurement in an effort to identify tangible improvements that can be attributed to the methodology. Although IRT shares similarities with classical test theory and factor analysis, the approach has certain practical benefits, but also limitations, when applied to measurement challenges. Major opportunities include the use of computerized adaptive tests to prevent conditional measurement error, multidimensional models to prevent misinterpretation of scores, and analyses of differential item functioning to prevent bias. Whereas these methods and technologies were once only discussed as future possibilities, they are now accessible because of recent support of IRT-focused clinical research. Despite this, much work still remains in widely disseminating methods and technologies from IRT into mental health research and practice. Clinicians have been reluctant to fully embrace the approach, especially in terms or prospective test development and adaptive item administration. Widespread use of IRT technologies will require continued cooperation among psychometricians, clinicians, and other stakeholders. There are also many opportunities to expand the methodology, especially with respect to integrating modern measurement theory with models from personality and cognitive psychology as well as neuroscience. (PsycINFO Database Record (c) 2019 APA, all rights reserved).
项目反应理论(IRT)正在成为开发、评估和评分临床测量工具的主要方法。资助机构和测试开发者通常会支持 IRT 工作,该理论已与该领域的技术进步紧密结合。因此,熟悉 IRT 对于心理健康研究和实践越来越重要。但目的是什么?本文回顾了 IRT 在临床测量中的应用进展,努力确定可以归因于该方法的切实改进。虽然 IRT 与经典测试理论和因素分析有相似之处,但当应用于测量挑战时,该方法具有某些实际优势,但也有限制。主要机会包括使用计算机化自适应测试来防止条件测量误差、多维模型来防止分数的错误解释,以及分析差异项目功能以防止偏差。虽然这些方法和技术曾经只被讨论为未来的可能性,但由于最近对以 IRT 为重点的临床研究的支持,现在已经可以实现。尽管如此,仍有许多工作需要在心理健康研究和实践中广泛传播 IRT 方法和技术。临床医生一直不愿意完全接受这种方法,尤其是在前瞻性测试开发和自适应项目管理方面。广泛使用 IRT 技术将需要心理计量学家、临床医生和其他利益相关者之间的持续合作。还有许多机会可以扩展该方法,特别是将现代测量理论与人格和认知心理学以及神经科学的模型相结合。(APA 版权所有,2019)。