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A New Remote Guided Method for Supervised Web-Based Cognitive Testing to Ensure High-Quality Data: Development and Usability Study.
Leong, Victoria; Raheel, Kausar; Sim, Jia Yi; Kacker, Kriti; Karlaftis, Vasilis M; Vassiliu, Chrysoula; Kalaivanan, Kastoori; Chen, S H Annabel; Robbins, Trevor W; Sahakian, Barbara J; Kourtzi, Zoe.
  • Leong V; Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.
  • Raheel K; Centre for Research and Development in Learning, Nanyang Technological University, Singapore, Singapore.
  • Sim JY; Lee Kong Chian School of Medicine, Nanyang Technological University, Singapore, Singapore.
  • Kacker K; Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.
  • Karlaftis VM; Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.
  • Vassiliu C; Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.
  • Kalaivanan K; Department of Psychology, University of Cambridge, Cambridge, United Kingdom.
  • Chen SHA; Faculty of Modern and Medieval Languages and Linguistics, University of Cambridge, Cambridge, United Kingdom.
  • Robbins TW; Centre for Research and Development in Learning, Nanyang Technological University, Singapore, Singapore.
  • Sahakian BJ; Psychology, School of Social Sciences, Nanyang Technological University, Singapore, Singapore.
  • Kourtzi Z; Centre for Research and Development in Learning, Nanyang Technological University, Singapore, Singapore.
J Med Internet Res ; 24(1): e28368, 2022 01 06.
Article in English | MEDLINE | ID: covidwho-1606084
ABSTRACT

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.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Humans / Young adult Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2022 Document Type: Article Affiliation country: 28368

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Pandemics / COVID-19 Type of study: Cohort study / Observational study / Prognostic study / Randomized controlled trials Limits: Adult / Humans / Young adult Language: English Journal: J Med Internet Res Journal subject: Medical Informatics Year: 2022 Document Type: Article Affiliation country: 28368