A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High-Quality Data: Development and Usability Study

J Med Internet Res. 2022 Jan 6;24(1):e28368. doi: 10.2196/28368.


Background: The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the forefront as a promising solution for the rapid mass collection of cognitive data without requiring human contact. However, a long-standing debate exists over the data quality and validity of web-based studies. This study examines the opportunities and challenges afforded by the societal shift toward web-based testing and highlights an urgent need to establish a standard data quality assurance framework for online studies.

Objective: This study aims to develop and validate a new supervised online testing methodology, remote guided testing (RGT).

Methods: A total of 85 healthy young adults were tested on 10 cognitive tasks assessing executive functioning (flexibility, memory, and inhibition) and learning. Tasks were administered either face-to-face in the laboratory (n=41) or online using remote guided testing (n=44) and delivered using identical web-based platforms (Cambridge Neuropsychological Test Automated Battery, Inquisit, and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, and response times) and overall task performance measures.

Results: The results indicated that, across all data quality and performance measures, RGT data was statistically-equivalent to in-person data collected in the lab (P>.40 for all comparisons). Moreover, RGT participants out-performed the lab group on measured verbal intelligence (P<.001), which could reflect test environment differences, including possible effects of mask-wearing on communication.

Conclusions: These data suggest that the RGT methodology could help ameliorate concerns regarding online data quality-particularly for studies involving high-risk or rare cohorts-and offer an alternative for collecting high-quality human cognitive data without requiring in-person physical attendance.

Keywords: COVID-19; executive functions; learning; neurocognitive assessment; web-based testing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • COVID-19*
  • Humans
  • Internet
  • Neuropsychological Tests
  • Pandemics*
  • SARS-CoV-2
  • Young Adult