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Internet Cognitive Testing of Large Samples Needed in Genetic Research

Published online by Cambridge University Press:  21 February 2012

Claire M. A. Haworth*
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom. Claire.Haworth@iop.kcl.ac.uk
Nicole Harlaar
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom.
Yulia Kovas
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom.
Oliver S. P. Davis
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom.
Bonamy R. Oliver
Affiliation:
Forensic Mental Health Science, Institute of Psychiatry, King's College London, London, United Kingdom.
Marianna E. Hayiou-Thomas
Affiliation:
Department of Psychology, University of York,York, United Kingdom.
Jane Frances
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom.
Patricia Busfield
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom.
Andrew McMillan
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom.
Philip S. Dale
Affiliation:
Department of Speech and Hearing Sciences, University of New Mexico, Albuquerque, United States of America.
Robert Plomin
Affiliation:
Social, Genetic and Developmental Psychiatry Centre, Institute of Psychiatry, King's College London, London, United Kingdom.
*
*Address for correspondence: Claire Haworth, SGDP Centre, P080, Institute of Psychiatry, King's College London, De Crespigny Park, London SE5 8AF, UK.

Abstract

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Quantitative and molecular genetic research requires large samples to provide adequate statistical power, but it is expensive to test large samples in person, especially when the participants are widely distributed geographically. Increasing access to inexpensive and fast Internet connections makes it possible to test large samples efficiently and economically online. Reliability and validity of Internet testing for cognitive ability have not been previously reported; these issues are especially pertinent for testing children. We developed Internet versions of reading, language, mathematics and general cognitive ability tests and investigated their reliability and validity for 10- and 12-year-old children. We tested online more than 2500 pairs of 10-year-old twins and compared their scores to similar internet-based measures administered online to a subsample of the children when they were 12 years old (> 759 pairs). Within 3 months of the online testing at 12 years, we administered standard paper and pencil versions of the reading and mathematics tests in person to 30 children (15 pairs of twins). Scores on Internet-based measures at 10 and 12 years correlated .63 on average across the two years, suggesting substantial stability and high reliability. Correlations of about .80 between Internet measures and in-person testing suggest excellent validity. In addition, the comparison of the internet-based measures to ratings from teachers based on criteria from the UK National Curriculum suggests good concurrent validity for these tests. We conclude that Internet testing can be reliable and valid for collecting cognitive test data on large samples even for children as young as 10 years.

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