Brendan McLaren1, Sophie C Andrews1,2,3, Yifat Glikmann-Johnston1, Emily-Clare Mercieca1, Nicholas W G Murray4, Clement Loy5,4, Mark A Bellgrove1, Julie C Stout6. 1. Turner Institute for Brain and Mental Health. School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC, 3800, Australia. 2. Neuroscience Research Australia, Sydney, NSW, Australia. 3. School of Psychology, University of New South Wales, Sydney, NSW, Australia. 4. Huntington Disease Service, Westmead Hospital, Sydney, NSW, Australia. 5. Brain and Mind Centre, The University of Sydney, Sydney, NSW, Australia. 6. Turner Institute for Brain and Mental Health. School of Psychological Sciences, Monash University, 18 Innovation Walk, Clayton, VIC, 3800, Australia. Julie.stout@monash.edu.
Abstract
OBJECTIVE: Smartphone-based cognitive assessment measures allow efficient, rapid, and convenient collection of cognitive datasets. Establishment of feasibility and validity is essential for the widespread use of this approach. We describe a novel smartphone application (HD-Mobile) that includes three performance-based cognitive tasks with four key outcome measures, for use with Huntington's disease (HD) samples. We describe known groups and concurrent validity, test-retest reliability, sensitivity, and feasibility properties of the tasks. METHODS: Forty-two HD CAG-expanded participants (20 manifest, 22 premanifest) and 28 healthy controls completed HD-Mobile cognitive tasks three times across an 8-day period, on days 1, 4, and 8. A subsample of participants had pen-and-paper cognitive task data available from their most recent assessment from their participation in a separate observational longitudinal study, Enroll-HD. RESULTS: Manifest-HD participants performed worse than healthy controls for three of four HD-Mobile cognitive measures, and worse than premanifest-HD participants for two of four measures. We found robust test-retest reliability for manifest-HD participants (ICC = 0.71-0.96) and with some exceptions, in premanifest-HD (ICC = 0.52-0.96) and healthy controls (0.54-0.96). Correlations between HD-Mobile and selected Enroll-HD cognitive tasks were mostly medium to strong (r = 0.36-0.68) as were correlations between HD-Mobile cognitive tasks and measures of expected disease progression and motor symptoms for the HD CAG-expanded participants (r = - 0.34 to - 0.54). CONCLUSIONS: Results indicated robust known-groups, test-retest, concurrent validity, and sensitivity of HD-Mobile cognitive tasks. The study demonstrates the feasibility and utility of HD-Mobile for conducting convenient, frequent, and potentially ongoing assessment of HD samples without the need for in-person assessment.
OBJECTIVE: Smartphone-based cognitive assessment measures allow efficient, rapid, and convenient collection of cognitive datasets. Establishment of feasibility and validity is essential for the widespread use of this approach. We describe a novel smartphone application (HD-Mobile) that includes three performance-based cognitive tasks with four key outcome measures, for use with Huntington's disease (HD) samples. We describe known groups and concurrent validity, test-retest reliability, sensitivity, and feasibility properties of the tasks. METHODS: Forty-two HD CAG-expanded participants (20 manifest, 22 premanifest) and 28 healthy controls completed HD-Mobile cognitive tasks three times across an 8-day period, on days 1, 4, and 8. A subsample of participants had pen-and-paper cognitive task data available from their most recent assessment from their participation in a separate observational longitudinal study, Enroll-HD. RESULTS: Manifest-HDparticipants performed worse than healthy controls for three of four HD-Mobile cognitive measures, and worse than premanifest-HDparticipants for two of four measures. We found robust test-retest reliability for manifest-HDparticipants (ICC = 0.71-0.96) and with some exceptions, in premanifest-HD (ICC = 0.52-0.96) and healthy controls (0.54-0.96). Correlations between HD-Mobile and selected Enroll-HD cognitive tasks were mostly medium to strong (r = 0.36-0.68) as were correlations between HD-Mobile cognitive tasks and measures of expected disease progression and motor symptoms for the HD CAG-expanded participants (r = - 0.34 to - 0.54). CONCLUSIONS: Results indicated robust known-groups, test-retest, concurrent validity, and sensitivity of HD-Mobile cognitive tasks. The study demonstrates the feasibility and utility of HD-Mobile for conducting convenient, frequent, and potentially ongoing assessment of HD samples without the need for in-person assessment.
Authors: Sarah J Tabrizi; Ralf Reilmann; Raymund A C Roos; Alexandra Durr; Blair Leavitt; Gail Owen; Rebecca Jones; Hans Johnson; David Craufurd; Stephen L Hicks; Christopher Kennard; Bernhard Landwehrmeyer; Julie C Stout; Beth Borowsky; Rachael I Scahill; Chris Frost; Douglas R Langbehn Journal: Lancet Neurol Date: 2011-12-02 Impact factor: 44.182
Authors: Russell M Bauer; Grant L Iverson; Alison N Cernich; Laurence M Binder; Ronald M Ruff; Richard I Naugle Journal: Arch Clin Neuropsychol Date: 2012-03-01 Impact factor: 2.813
Authors: Stephane Dufau; Jon Andoni Duñabeitia; Carmen Moret-Tatay; Aileen McGonigal; David Peeters; F-Xavier Alario; David A Balota; Marc Brysbaert; Manuel Carreiras; Ludovic Ferrand; Maria Ktori; Manuel Perea; Kathy Rastle; Olivier Sasburg; Melvin J Yap; Johannes C Ziegler; Jonathan Grainger Journal: PLoS One Date: 2011-09-28 Impact factor: 3.240
Authors: Florian Lipsmeier; Cedric Simillion; Atieh Bamdadian; Rosanna Tortelli; Lauren M Byrne; Yan-Ping Zhang; Detlef Wolf; Anne V Smith; Christian Czech; Christian Gossens; Patrick Weydt; Scott A Schobel; Filipe B Rodrigues; Edward J Wild; Michael Lindemann Journal: J Med Internet Res Date: 2022-06-28 Impact factor: 7.076
Authors: Xavier Montalban; Jennifer Graves; Luciana Midaglia; Patricia Mulero; Laura Julian; Michael Baker; Jan Schadrack; Christian Gossens; Marco Ganzetti; Alf Scotland; Florian Lipsmeier; Johan van Beek; Corrado Bernasconi; Shibeshih Belachew; Michael Lindemann; Stephen L Hauser Journal: Mult Scler Date: 2021-07-14 Impact factor: 6.312