期刊
NEUROSCIENCE LETTERS
卷 745, 期 -, 页码 -出版社
ELSEVIER IRELAND LTD
DOI: 10.1016/j.neulet.2020.135620
关键词
Pain; Parkinson's disease; Validity; Reliability
The study confirmed the acceptability and efficacy of the Persian version of KPPS-P for assessing pain in patients with Parkinson's disease. Cut-off points for pain severity levels were identified as 0, 17, and 68, with high sensitivity and specificity.
Background: Pain is one of the most common non-motor symptoms in Parkinson's disease (PD). Using an appropriate and specific measuring tool would be helpful in managing the pain. King's Parkinson's disease Pain Scale (KPPS) is an instrument designed to specifically measure pain in people with PD. Purpose: This study aimed to examine the psychometric properties of the Persian version of KPPS (KPPS-P) and its cut-off points for pain severity levels. Methods: A total of 480 people with PD (with a mean (SD) age of 60.89 (10.98)) were recruited. The acceptability of KPPS-P was calculated. The structural validity and discriminant validity for different levels of pain was explored via the factor analysis, and Receiver Operating Characteristics (ROC) curves, respectively. Internal consistency, test-retest, and inter-rater reliability were estimated by Cronbach's alpha and Interclass Correlation coefficient (ICC). Convergent validity was established between KPPS-P and other scales including Visual Analog Scale-Pain, Douleur Neuropathic 4, Brief Pain Inventory, Short-form McGill Pain Questionnaire-2, and Parkinson's Disease-8. Results: A significant floor effect was observed. The exploratory factor analysis revealed 4 factors. Cronbach's alpha and ICC values were higher than 0.80. The correlation range between KPPS-P and other scales was 0.35-0.76. Cut-off points of 0, 17, and 68 were obtained to discriminate pain severity levels between no pain, mild, moderate, and severe pain, respectively, with sensitivity and specificity above 0.80. Conclusion: Our results indicate that the Persian version of KPPS not only has acceptable psychometric properties to assess pain in PD but also has the ability to distinguish between different levels of pain severity.
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