The Quality Assurance and Quality Control Protocol for Neuropsychological Data Collection and Curation in the Ontario Neurodegenerative Disease Research Initiative (ONDRI) Study

Paula M. McLaughlin*, Kelly M. Sunderland, Derek Beaton, Malcolm A. Binns, Donna Kwan, Brian Levine, Joseph B. Orange, Alicia J. Peltsch, Angela C. Roberts, Stephen C. Strother, Angela K. Troyer

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

6 Scopus citations

Abstract

As large research initiatives designed to generate big data on clinical cohorts become more common, there is an increasing need to establish standard quality assurance (QA; preventing errors) and quality control (QC; identifying and correcting errors) procedures for critical outcome measures. The present article describes the QA and QC approach developed and implemented for the neuropsychology data collected as part of the Ontario Neurodegenerative Disease Research Initiative study. We report on the efficacy of our approach and provide data quality metrics. Our findings demonstrate that even with a comprehensive QA protocol, the proportion of data errors still can be high. Additionally, we show that several widely used neuropsychological measures are particularly susceptible to error. These findings highlight the need for large research programs to put into place active, comprehensive, and separate QA and QC procedures before, during, and after protocol deployment. Detailed recommendations and considerations for future studies are provided.

Original languageEnglish (US)
Pages (from-to)1267-1286
Number of pages20
JournalAssessment
Volume28
Issue number5
DOIs
StatePublished - Jul 2021

Keywords

  • data quality
  • neuropsychology
  • quality assurance
  • quality control

ASJC Scopus subject areas

  • Clinical Psychology
  • Applied Psychology

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