Data quality assurance and control in cognitive research: Lessons learned from the PREDICT-HD study
Graduate School of Nursing
Biostatistics | Nursing | Psychiatry and Psychology | Quantitative, Qualitative, Comparative, and Historical Methodologies | Research Methods in Life Sciences
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.
cognitive assessment, quality assurance, quality control
DOI of Published Version
Int J Methods Psychiatr Res. 2017 Sep;26(3). doi: 10.1002/mpr.1534. Epub 2017 Feb 17. Link to article on publisher's site
International journal of methods in psychiatric research
Westervelt, Holly James; Bernier, Rachel A.; Faust, Melanie; Gover, Mary; Bockholt, H. Jeremy; Zschiegner, Roland; Long, Jeffrey D.; and Paulsen, Jane S., "Data quality assurance and control in cognitive research: Lessons learned from the PREDICT-HD study" (2017). Graduate School of Nursing Publications and Presentations. 87.