Psychometric Evaluation Of A Patient-Rated Most Troubling Symptom Scale For Depression: Findings From A Secondary Analysis Of A Clinical Trial

INTERNATIONAL CLINICAL PSYCHOPHARMACOLOGY(2010)

引用 5|浏览5
暂无评分
摘要
The objective of this study was to assess the reliability and validity of the presence and severity of eight symptoms rated on the Patient-Rated Troubling Symptoms for Depression (PaRTS-D) instrument used in a risperidone augmentation trial. PaRTS-D total score (sum of four most severe symptoms) and global total score (sum of all eight symptoms) were determined weekly. Clinician-rated and patient-rated instruments were completed at selected time points. Statistical tests of reliability and validity were performed. The frequency of symptoms rated as one of the four most troubling were sadness, 73.5%; trouble concentrating, 70.9%; reduced involvement, 61.9%; tense/uptight, 56.0%; reduced sleep, 52.2%; negative thoughts, 42.9%; inability to feel emotion, 26.5%; and reduced appetite, 13.1%. Evidence of two factors (somatic-related and depression-related) was observed in the exploratory factor analysis. Baseline PaRTS-D total score correlated with the Quality of Life Enjoyment and Satisfaction Questionnaire and the Sheehan Disability Scale. PaRTS-D global total score showed high internal consistency reliability. PaRTS-D total score and global total score distinguished between patients with high and low-Hamilton Rating Scale for Depression Scores and were responsive to Patient Global Improvement Scale changes. The PaRTS-D total score minimal important difference was 4-5 points. In conclusion, PaRTS-D may be useful in symptom presence and severity assessments from the patient's perspective and as an adjunctive to other instruments in major depressive disorder diagnosis and response to treatment. Int Clin Psychopharmacol 25:51-59 (C) 2010 Wolters Kluwer Health vertical bar Lippincott Williams & Wilkins.
更多
查看译文
关键词
clinical outcome, major depressive disorder, PaRTS-D, reliability, risperidone augmentation, validity
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要