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

Westervelt Holly James | Zendy; Bernier Rachel A. | Zendy; Faust Melanie | Zendy; Gover Mary | Zendy; Bockholt H. Jeremy | Zendy; Zschiegner Roland | Zendy; Long Jeffrey D. | Zendy; Paulsen Jane S. | Zendy

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

Author(s) -

Westervelt Holly James,

Bernier Rachel A.,

Faust Melanie,

Gover Mary,

Bockholt H. Jeremy,

Zschiegner Roland,

Long Jeffrey D.,

Paulsen Jane S.

Publication year - 2017

Publication title -

international journal of methods in psychiatric research

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.275

H-Index - 73

eISSN - 1557-0657

pISSN - 1049-8931

DOI - 10.1002/mpr.1534

Subject(s) - cognition , quality assurance , observational study , psychology , control (management) , quality (philosophy) , huntington's disease , clinical psychology , cognitive psychology , applied psychology , disease , medicine , computer science , artificial intelligence , psychiatry , pathology , philosophy , external quality assessment , epistemology

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.

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