Understanding cognitive domains in Parkinson’s disease: A Scoping Review of empirical studies

Background: To assess cognitive performance of individuals with Parkinson’s Disease (PD), the Movement and Disorders Society’s guidelines for diagnosing Mild Cognitive Impairment (MCI) in individuals with Parkinson’s Disease (PD) recommend to use at least two tests per cognitive domain (memory, attention & working memory, executive function, language, visuospatial function) in the test battery. However, assignments of specific tests to cognitive domains are usually conceptually based and sometimes controversial. Methods to differentiate cognitive domains like factor or dimensionality analysis methods based on cognitive test scores may provide insights into that matter, as failure to reproduce assumed cognitive domains by empirical data could undermine the validity of PD-MCI diagnoses. Objectives: This scoping review aims to provide an overview of the existing research that has been empirically evaluating the differentiation of the above-mentioned cognitive domains and assignment of cognitive tests to cognitive domains in individuals with PD by dimensionality analysis methods such as principal component analysis, principal axis analysis, and structural equation modelling. Further, we seek to evaluate the results of eligible research works and to identify the statistical methods employed. Eligibility criteria: We will include sources of evidence that conducted a statistical analysis on cognitive test data from PD patients to extract factor or dimensionality structures of cognitive functions. Sources of evidence: We will conduct the systematic search in the bibliographic data bases MEDLINE and PsycInfo. Charting methods: Two reviewers will independently screen titles and abstracts and subsequently review full-text publications. A third reviewer will be involved to solve any conflicts. For eligible sources of evidence, one reviewer will extract predefined data of interest into a digital data charting form, with another reviewer double-checking data to ensure accuracy. Data will be summarized quantitatively (e.g. frequencies and proportions) and qualitatively. unknown other