| Literature DB >> 28211597 |
Holly James Westervelt1,2, Rachel A Bernier2,3, Melanie Faust2,4,5, Mary Gover2, H Jeremy Bockholt6,7, Roland Zschiegner6, Jeffrey D Long6,8, Jane S Paulsen6,9,10.
Abstract
We discuss the strategies employed in data quality control and quality assurance for the cognitive core of Neurobiological Predictors of Huntington's Disease (PREDICT-HD), a long-term observational study of over 1,000 participants with prodromal Huntington disease. In particular, we provide details regarding the training and continual evaluation of cognitive examiners, methods for error corrections, and strategies to minimize errors in the data. We present five important lessons learned to help other researchers avoid certain assumptions that could potentially lead to inaccuracies in their cognitive data.Entities:
Keywords: cognitive assessment; quality assurance; quality control
Mesh:
Year: 2017 PMID: 28211597 PMCID: PMC6258197 DOI: 10.1002/mpr.1534
Source DB: PubMed Journal: Int J Methods Psychiatr Res ISSN: 1049-8931 Impact factor: 4.035