Work

Data quality assurance and control in cognitive research: Lessons learned from the PREDICT‐HD study

Year: 2017

Type: article

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.

Source: International Journal of Methods in Psychiatric Research

DOI: 10.1002/mpr.1534

Authors: Holly James Westervelt, Rachel A. Bernier, Melanie Faust, Mary Gover, H. Jeremy Bockholt, Roland Zschiegner, Jeffrey D. Long, Jane S. Paulsen, The PREDICT‐HD Investigators, Coordinators of the Huntington Study Group

Institutions: Vanderbilt University, Rhode Island Hospital, Vanderbilt University Medical Center, Pennsylvania State University, University of Massachusetts Chan Medical School, Butler Hospital, University of Iowa, University of Iowa Health Care

Language: English

Topic: Genetic Neurodegenerative Diseases

Subfield: Cellular and Molecular Neuroscience

Field: Neuroscience

Domain: Life Sciences

SDG: Good health and well-being

Open Access status: green

Funders: National Institutes of Health, National Institute of Neurological Disorders and Stroke, National Center for Advancing Translational Sciences

Awards: G2720536729, G424335420, G6340235114, The University of Iowa Clinical and Translational Science Award

OpenAlex ID: W2588099735

FWCI: 0.352

Cites: 11

Cited by: 7

Related to: 10