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4%) and the mean age and disease onset age of the study cohort were 64.98 �� 9.19 years and 57.29 �� 9.19 years, respectively. More than half of the participants were ��65 years old (77, 57.46%). Less than half of the participants were still working either part-time or full-time jobs (65, 48.51%), and of those still working, 30 (22.39%) were ��65 years old. Table 1 Characteristics of the participants (N = 134). 2.2. Instruments The MMSE was used as a brief screening tool for cognitive impairment [17]; the disease stage and symptoms were evaluated using the Hoehn and Yahr scale (H&Y) [18] and the Unified Parkinson's Disease Rating Scale (UPDRS) [19], Apoptosis Compound Library manufacturer respectively. The patients' QOL and sleep quality were assessed using the 39-item Parkinson's Disease Questionnaire (PDQ-39) [20] and Parkinson's Disease Sleep Scale-2 (PDSS-2) [21], respectively, which were each answered on a five-point Likert scale ranging from LGK-974 research buy 0 (never) to 4 (always), with higher scores indicating poorer QOL and sleep quality, respectively. Since comorbidity of anxiety and depression can be a concern, the self-reported Beck Depression Inventory (BDI) [22] and Beck Anxiety Inventory (BAI) [23] were utilized to detect depression and anxiety, respectively. Both the BDI and BAI were answered on a four-point Likert scale ranging from 0 (not at all) to 3 (severely), with higher scores indicating higher levels of anxiety and depression [22, 23], respectively. All of the instruments we used were the validated Chinese versions. 2.3. Statistical Analysis The demographical factors and characteristics of the study participants are presented as frequencies and percentages for categorical variables or as the mean and standard AZ191 deviation for continuous variables. Participants' characteristics and variables of interest among the different depression/anxiety severity indexes were compared by using Chi-squared tests with Fisher's exact tests and one-way analyses of variance (ANOVA) followed by Bonferroni post hoc multiple comparisons tests. The relationships among participants' characteristics and other variables of interest were examined using Pearson's correlation coefficient. An multiple regression analysis (forward) was employed to assess the potential predictive variables for QOL in patients with PD. Since severe multicollinearity among independent variables may reduce the variance estimated in the regression model, prior to exploring the predictors, a multicollinearity diagnosis using variance inflation factors of less than 10 was conducted to examine whether the potential regression model violated the assumption of the regression model. Data analyses were conducted using SPSS 22 (IBM SPSS Inc., Chicago, IL) and the significance level was set at p