Quantifying diagnostic uncertainty using item response theory: the Posterior Probability of Diagnosis Index.

Quantifying diagnostic uncertainty using item response theory: the Posterior Probability of Diagnosis Index.
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DOI:
10.1037/a0031392
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发表时间:
2013-06
影响因子:
3.6
通讯作者:
Yu L
Yu L
中科院分区:
心理学2区
文献类型:
--
作者:
Lindhiem O;Kolko DJ;Yu L

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使用传统的精神疾病诊断与统计手册(DSM)诊断标准,临床医生被迫做出分类决定(诊断与无诊断)。这种被迫的选择意味着精神和行为健康障碍是绝对的,并不能完全描述与特定诊断相关的不同程度的不确定性。使用IRT(潜在特质模型)框架,我们描述了诊断后验概率(PPOD)指数的发展,该指数回答了“患者达到或超过诊断潜在特质阈值的可能性是什么”这个问题。PPOD指数是基于每个患者症状的后验分布θ(潜在特征评分)。PPOD指数允许临床医生以概率的方式量化和传达与每个诊断相关的不确定性程度。我们在临床样本(N = 321)中说明了PPOD指数在对立违抗性障碍(ODD)儿童和青少年中的优势。
Using traditional Diagnostic and Statistical Manual of Mental Disorders (DSM) diagnostic criteria, clinicians are forced to make categorical decisions (diagnosis versus no diagnosis). This forced choice implies that mental and behavioral health disorders are categorical and does not fully characterize varying degrees of uncertainty associated with a particular diagnosis. Using an IRT (latent trait model) framework, we describe the development of the Posterior Probability of Diagnosis (PPOD) Index which answers the question, “What is the likelihood that a patient meets or exceeds the latent trait threshold for a diagnosis.” The PPOD Index is based on the posterior distribution of θ (latent trait score) for each patient’s profile of symptoms. The PPOD Index allows clinicians to quantify and communicate the degree of uncertainty associated with each diagnosis in probabilistic terms. We illustrate the advantages of the PPOD Index in a clinical sample (N = 321) of children and adolescents with Oppositional Defiant Disorder (ODD).
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