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Accepted for/Published in: Journal of Medical Internet Research

Date Submitted: Mar 6, 2021
Date Accepted: Jul 27, 2021

The final, peer-reviewed published version of this preprint can be found here:

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

Leong V, Raheel K, Sim JY, Kacker K, Karlaftis VM, Vassiliu C, Chen SA, Robbins TW, Sahakian BJ, Kourtzi Z

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;24(1):e28368

DOI: 10.2196/28368

PMID: 34989691

PMCID: 8778570

A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High Quality Data

  • Victoria Leong; 
  • Kausar Raheel; 
  • Jia Yi Sim; 
  • Kriti Kacker; 
  • Vasilis M Karlaftis; 
  • Chrysoula Vassiliu; 
  • S.H. Annabel Chen; 
  • Trevor W. Robbins; 
  • Barbara J. Sahakian; 
  • Zoe Kourtzi

ABSTRACT

Background:

The global COVID-19 pandemic has triggered a fundamental reexamination of how human psychological research can be conducted both safely and robustly in a new era of digital working and physical distancing. Online web-based testing has risen to the fore as a promising solution for 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.

Objective:

Here, we examine the opportunities and challenges afforded by the societal shift toward web-based testing, highlight an urgent need to establish a standard data quality assurance framework for online studies, and 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), delivered using identical web-based platforms (CANTAB, Inquisit and i-ABC). Data quality was assessed using detailed trial-level measures (missed trials, outlying and excluded responses, response times), as well as overall task performance measures.

Results:

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

Conclusions:

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


 Citation

Please cite as:

Leong V, Raheel K, Sim JY, Kacker K, Karlaftis VM, Vassiliu C, Chen SA, Robbins TW, Sahakian BJ, Kourtzi Z

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;24(1):e28368

DOI: 10.2196/28368

PMID: 34989691

PMCID: 8778570

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