Kent State University, Kent, OH 44242, USA.
Behav Ther. 2010 Sep;41(3):423-31. doi: 10.1016/j.beth.2009.12.002. Epub 2010 Apr 1.
Major depressive disorder (MDD) is a serious and prevalent mental health issue. As the majority of MDD cases are identified and treated by one's primary care physician, it is imperative that care providers utilize accurate and efficient methods for diagnosing MDD in primary care settings. The present study is the first to investigate the accuracy of the Quick Inventory of Depressive Symptomatology-Self Report (QIDS-SR(16)) as a screen for MDD. A heterogeneous sample of 155 primary care patients completed the QIDS-SR(16) prior to attending a primary care appointment. Participants were then assessed for psychopathology using the Structured Clinical Interview for DSM-IV-TR Axis I Disorders (SCID) by clinicians who were blind to QIDS-SR(16) scores. Scores on the QIDS-SR(16) were compared to clinician-assessed current and lifetime diagnoses derived from the SCID, which represented the gold-standard criterion measure. Receiver operator characteristic analysis was utilized to determine the optimal QIDS-SR(16) cut score to correctly classify participants based on their MDD status as assessed by the SCID. The test revealed a robust area under the curve (.82, p<0.00001) and suggested that a cut score of 13 or 14 provided the best balance of sensitivity (76.5%) and specificity (81.8%) in this primary care sample. Over 80% of participants were correctly classified. Separate analyses by race were conducted to address the possibility that different cut scores may be more accurate for African American and Caucasians. Findings from the present study provide support for the use of the QIDS-SR(16) as a screening measure for identifying primary care patients who will meet diagnostic criteria for MDD based on clinician assessment.
重度抑郁症（MDD）是一种严重且普遍的心理健康问题。由于大多数 MDD 病例是由初级保健医生识别和治疗的，因此护理提供者必须在初级保健环境中使用准确且有效的方法来诊断 MDD。本研究首次调查了 Quick Inventory of Depressive Symptomatology-Self Report（QIDS-SR(16)）作为 MDD 筛查工具的准确性。155 名初级保健患者在参加初级保健预约之前完成了 QIDS-SR(16)。然后，参与者由对 QIDS-SR(16)评分盲的临床医生使用 DSM-IV-TR 轴 I 障碍的结构临床访谈 (SCID) 进行精神病理学评估。将 QIDS-SR(16)的评分与来自 SCID 的临床医生评估的当前和终生诊断进行比较，后者代表了黄金标准的标准衡量标准。利用接收器工作特性分析来确定最佳的 QIDS-SR(16)切点，以便根据 SCID 评估的 MDD 状态正确分类参与者。测试结果显示出强大的曲线下面积（.82，p<0.00001），表明在这个初级保健样本中，13 或 14 的切点得分在灵敏度（76.5%）和特异性（81.8%）之间提供了最佳平衡。超过 80%的参与者被正确分类。通过种族进行了单独的分析，以解决不同的切点分数可能对非裔美国人和白种人更准确的可能性。本研究的结果为使用 QIDS-SR(16)作为识别将根据临床医生评估符合 MDD 诊断标准的初级保健患者的筛查措施提供了支持。
