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Observational Study
. 2017 Sep;26(3):e1534.
doi: 10.1002/mpr.1534. Epub 2017 Feb 17.

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

Holly James Westervelt  1   2 , Rachel A Bernier  2   3 , Melanie Faust  2   4   5 , Mary Gover  2 , H Jeremy Bockholt  6   7 , Roland Zschiegner  6 , Jeffrey D Long  6   8 , Jane S Paulsen  6   9   10 ; PREDICT-HD Investigators; Coordinators of the Huntington Study Group
Affiliations
Observational Study

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

Holly James Westervelt et al. Int J Methods Psychiatr Res. 2017 Sep.

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.

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Figures

Figure 1
Figure 1
Examiner error rate by number of participants examined
Figure 2
Figure 2
Average examiner error rate across quality assurance/quality control (QA/QC) review periods. Each review period = six months
Figure 3
Figure 3
Comparison of errors rates between computer tasks and traditional task
See this image and copyright information in PMC

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