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Int J Methods Psychiatr Res. 2017 Sep;26(3). doi: 10.1002/mpr.1534. Epub 2017 Feb 17.

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

Author information

1
Department of Neurology, Vanderbilt Medical Center, Nashville, TN, USA.
2
Department of Psychiatry, Rhode Island Hospital, Providence, RI, USA.
3
Department of Psychology, Pennsylvania State University, University Park, PA, USA.
4
Graduate School of Nursing, University of Massachusetts Medical School, Worcester, MA, USA.
5
Department of Neurology, Butler Hospital, Providence, RI, USA.
6
Department of Psychiatry, Carver College of Medicine, The University of Iowa, Iowa City, IA, USA.
7
Advanced Biomedical Informatics Group, LLC, Coralville, IA, USA.
8
Department of Biostatistics, College of Public Health, The University of Iowa, Iowa City, IA, USA.
9
Department of Neurology, Carver College of Medicine, The University of Iowa, Iowa City, IA, USA.
10
Department of Psychology, The University of Iowa, Iowa City, IA, USA.

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.

KEYWORDS:

cognitive assessment; quality assurance; quality control

PMID:
28211597
DOI:
10.1002/mpr.1534
[Indexed for MEDLINE]

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