Brief Visuospatial Memory Test-Revised: normative data and clinical utility of learning indices in Parkinson's disease
Language English Country England, Great Britain Media print-electronic
Document type Journal Article, Research Support, Non-U.S. Gov't
- Keywords
- BVMT-R, Parkinson’s disease, learning curve, mild cognitive impairment, visual learning,
- MeSH
- Adult MeSH
- Cognitive Dysfunction etiology physiopathology MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Neuropsychological Tests standards MeSH
- Parkinson Disease complications physiopathology MeSH
- Memory Disorders etiology physiopathology MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Learning physiology MeSH
- Check Tag
- Adult MeSH
- Middle Aged MeSH
- Humans MeSH
- Adolescent MeSH
- Young Adult MeSH
- Male MeSH
- Aged, 80 and over MeSH
- Aged MeSH
- Female MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Introduction: The Brief Visual Memory Test-Revised (BVMT-R) is a frequently used visuospatial declarative memory test, but normative data in the Czech population are lacking. Moreover, the BVMT-R includes promising learning indexes that can be used to detect learning deficits in Parkinson's disease (PD). However, its clinical usefulness has not yet been thoroughly examined. Early detection of memory impairment in PD is essential for effective treatment. Therefore, this study aimed to provide BVMT-R Czech normative data for clinical use and to find the detection potential of the principal BVMT-R scores, including new learning indices, to capture the cognitive deficit in PD. Method: The BVMT-R were administered to a normative sample of 920 participants aged 17 to 95 years and to a clinical sample of 60 PD patients; 25 with mild cognitive impairment (PD-MCI) and 35 with normal cognition (PD-NC). In order to provide normative values, multiple regression analyses were employed, and to compare the clinical and control sample, Bayesian Hierarchical Linear Models were used. Results: The best model for regression-based norms showed to be with age + age2 + education + sex as predictors. From all learning indexes, L6 (sum of trials 1-3), followed by, L4 (sum of trials 1-3 multiplied by the difference between the highest and the lowest score) best differentiated between controls or PD-NC and PD-MCI. Conclusions: We provide regression-based normative values for BVMT-R that could be used in clinical settings and meta-analytic efforts. Furthermore, we revealed visuospatial learning and memory deficit in PD-MCI. We have also identified the most discriminative learning index adapted to BVMT-R.
Department of Psychiatry Charles University 3rd Faculty of Medicine Prague Czech Republic
Department of Science and Research Prague College of Psychosocial Studies Prague Czech Republic
References provided by Crossref.org
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