Wonderlich Stephen A, Joiner Thomas E, Keel Pamela K, Williamson Donald A, Crosby Ross D
Department of Clinical Neuroscience, University of North Dakota School of Medicine & Health Sciences, Fargo, ND 58107-1415, USA.
Am Psychol. 2007 Apr;62(3):167-80. doi: 10.1037/0003-066X.62.3.167.
Decisions about the classification of eating disorders have significant scientific and clinical implications. The eating disorder diagnoses in the Diagnostic and Statistical Manual of Mental Disorders (4th ed.; DSM-IV; American Psychiatric Association, 1994) reflect the collective wisdom of experts in the field but are frequently not supported in empirical studies and do not capture the disorders of eating experienced by most people with an eating disorder. Statistical approaches to classification such as latent class analysis and taxometrics can help to create a classification system with greater scientific validity and clinical utility. The field would benefit from direct empirical comparisons of different classification schemes with various clinical and scientific validators. Such studies would enable the creators of the next DSM eating disorder classification to increase understanding of the advantages and disadvantages associated with choosing various diagnostic criteria sets for the eating disorders.
关于饮食失调分类的决策具有重大的科学和临床意义。《精神疾病诊断与统计手册》（第4版；DSM-IV；美国精神病学协会，1994年）中的饮食失调诊断反映了该领域专家的集体智慧，但在实证研究中往往得不到支持，也未能涵盖大多数饮食失调患者所经历的饮食紊乱情况。诸如潜在类别分析和分类测量学等统计分类方法有助于创建一个具有更高科学效度和临床实用性的分类系统。通过使用各种临床和科学验证指标对不同分类方案进行直接实证比较，该领域将从中受益。此类研究将使下一版DSM饮食失调分类的制定者能够更深入地了解选择各种饮食失调诊断标准集的优缺点。
