Background Background: The Apathy Scale (AS), a popular measure of apathy in Parkinson's disease (PD), has been somewhat limited for failing to characterize dimensions of apathy, such as those involving cognitive, behavioral, and emotional apathy symptoms. This study sought to determine whether factors consistent with these apathy dimensions in PD could be identified on the AS, examine the associations between these factors and disease-related characteristics, and compare PD patients and healthy control (HCs) on identified factors. Methods Methods: Confirmatory (CFA) and exploratory factor analysis (EFA) were conducted on AS scores of 157 nondemented PD patients to identify AS factors. These factors were then correlated with important diseaserelated characteristics, and PD and HC participants were compared across these factors. ResultsResults: Previously proposed AS models failed to achieve an adequate fit in CFA. A subsequent EFA revealed two factors on the AS reflecting joint cognitive-behavioral aspects of apathy (Motivation-Interest-Energy) and emotional apathy symptoms (Indifference). Both factors were associated with anxiety, depression, healthrelated quality of life, and independent activities of daily living, with Indifference associated more with the latter. In addition, only the Indifference factor was associated with cognitive functioning. PD patients reported higher levels of symptoms than HCs on both factors, with the group difference slightly larger on the Motivation-Interest-Energy factor. Conclusion Conclusion: The AS can be decomposed into two factors reflecting Motivation-Interest-Energy and Indifference symptoms. These factors are differentially associated with clinical variables, including cognition and independent activities of daily living, indicating the importance of evaluating apathy from a multidimensional perspective.Apathy is among the most common psychiatric symptoms in Parkinson's disease (PD). Prevalence estimates of apathy in PD range from 17% to 62%. Although there is a substantial overlap between apathy and depression (e.g., common symptoms of lack of energy, fatigue, and loss of interest), a growing body of literature suggests that symptoms of apathy and depression are dissociable in PD, with 5% to 33% of individuals reporting apathy in isolation from any other psychiatric symptom. 1-8 This is likely attributed to nonoverlapping symptoms, such as diminished initiation and interests in the absence of affective evaluation in apathy as opposed to depression. 9 Apathy is associated with diminished quality of life, 10 a reduction in activities of daily living, 2,11 and may be a predictor of future executive dysfunction and global cognitive decline. 4,5,12 1 Veterans Administration San Diego Healthcare System,

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Background The Geriatric Depression Scale (GDS) is recommended for screening depression in individuals with Parkinson's disease (PD). Empirical evidence, however, is limited regarding its validity and factor structure in PD. Thus, the current study sought to evaluate the convergent and divergent validity of the GDS, as well as the structure and validity of the derived factors. Method Nondemented individuals with PD (n = 158) completed the GDS‐30, and items were subjected to a principle component analysis. Geriatric Depression Scale total and factor scores were correlated with depression items from the Movement Disorder Society Unified Parkinson's disease Rating Scale (MDS‐UPDRSd) and Hamilton Rating Scale for Depression (HAMDd), as well as with the Apathy Scale (AS), State‐Trait Anxiety Inventory (STAI), Modified Fatigue Impact Scale (MFIS), Parkinson's disease Sleep Scale, and a Subjective Cognitive Function composite score. Results The GDS total score was strongly correlated with divergent neuropsychiatric measures (AS, r = 0.57; STAI, r = 0.66; MFIS, r = 0.60), while only moderately correlated with convergent measures (MDS‐UPDRSd, r = 0.36; HAMDd, r = 0.32; Ps < 0.05). Linear regression analyses revealed standardized measures of anxiety, apathy, and fatigue independently predicted the GDS total score, while depression items (MDS‐UPDRSd and HAMDd) failed to reach significance. Three independent factors were identified: Anxiety, Apathy, and Fatigue. These factors were significantly predicted by their respective convergent measures. Conclusions Taken together, our findings suggest that the GDS and its subscales appear to primarily measure anxiety, apathy, and fatigue in PD, or alternatively, these symptom dimensions may be predominant in PD‐depression. Future research with clinically diagnosed samples is needed to confirm these initial findings.

Prevalence rates for mild cognitive impairment in Parkinson’s disease (PD-MCI) remain variable, obscuring the diagnosis’ predictive utility of greater dementia risk. A primary factor of this variability is inconsistent operationalization of normative cutoffs for cognitive impairment. We aimed to determine which cutoff was optimal for classifying individuals as PD-MCI by comparing classifications against data-driven PD cognitive phenotypes. Participants with idiopathic PD (n = 494; mean age 64.7 ± 9) completed comprehensive neuropsychological testing. Cluster analyses (K-means, Hierarchical) identified cognitive phenotypes using domain-specific composites. PD-MCI criteria were assessed using separate cutoffs (−1, −1.5, −2 SD) on ≥2 tests in a domain. Cutoffs were compared using PD-MCI prevalence rates, MCI subtype frequencies (single/multi-domain, executive function (EF)/non-EF impairment), and validity against the cluster-derived cognitive phenotypes (using chi-square tests/binary logistic regressions). Cluster analyses resulted in similar three-cluster solutions: Cognitively Average (n = 154), Low EF (n = 227), and Prominent EF/Memory Impairment (n = 113). The −1.5 SD cutoff produced the best model of cluster membership (PD-MCI classification accuracy = 87.9%) and resulted in the best alignment between PD-MCI classification and the empirical cognitive profile containing impairments associated with greater dementia risk. Similar to previous Alzheimer’s work, these findings highlight the utility of comparing empirical and actuarial approaches to establish concurrent validity of cognitive impairment in PD.