کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
6812680 | 545638 | 2016 | 5 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
The psychometric properties of the Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) and the Patient Health Questionnaire-9 (PHQ-9) in depressed inpatients in China
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موضوعات مرتبط
علوم زیستی و بیوفناوری
علم عصب شناسی
روانپزشکی بیولوژیکی
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چکیده انگلیسی
This study examined the psychometric properties of the 16-item Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) and Patient Health Questionnaire-9 (PHQ-9). The study sample comprised 297 depressed inpatients. The severity of depressive symptoms was assessed with the Hamilton Rating Scale for Depression, the QIDS-SR and the PHQ-9 in all subjects at baseline and a random sample of 50 subjects two weeks later. The internal consistency, convergent validity, factor structure and sensitivity to change of these scales were assessed. Internal consistency (Cronbach's alpha) of the PHQ-9 and QIDS-SR were 0.88 and 0.83, respectively at baseline and 0.91 and 0.87, respectively at exit. Item to total score correlations were higher for the PHQ-9 than those for the QIDS-SR at baseline and exit. Three domains at baseline and two at study exit of the QIDS-SR had a correlation less than 0.65; while only two items at baseline and no item at exit were less than 0.65 for the PHQ-9. Both the PHQ-9 and the QIDS-SR showed uni-dimensional measurement properties at baseline; the two instruments were less sensitive than the HAMD to detect changes of depressive symptoms suggesting low convergent validity. The QIDS-SR and the PHQ-9 have similar and acceptable psychometric properties in most domains as tested in depressed inpatients.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Psychiatry Research - Volume 243, 30 September 2016, Pages 92-96
Journal: Psychiatry Research - Volume 243, 30 September 2016, Pages 92-96
نویسندگان
Yuan Feng, Wei Huang, Teng-Fei Tian, Gang Wang, Chen Hu, Helen F.K. Chiu, Gabor S. Ungvari, Amy M. Kilbourne, Yu-Tao Xiang,