Literature DB >> 26933140

Characterizing Information Processing With a Mobile Device: Measurement of Simple and Choice Reaction Time.

Daniel Burke1, Susan Linder1, Joshua Hirsch1, Tanujit Dey1, Daniel Kana1, Shannon Ringenbach2, David Schindler1, Jay Alberts1.   

Abstract

Information processing is typically evaluated using simple reaction time (SRT) and choice reaction time (CRT) paradigms in which a specific response is initiated following a given stimulus. The measurement of reaction time (RT) has evolved from monitoring the timing of mechanical switches to computerized paradigms. The proliferation of mobile devices with touch screens makes them a natural next technological approach to assess information processing. The aims of this study were to determine the validity and reliability of using of a mobile device (Apple iPad or iTouch) to accurately measure RT. Sixty healthy young adults completed SRT and CRT tasks using a traditional test platform and mobile platforms on two occasions. The SRT was similar across test modality: 300, 287, and 280 milliseconds (ms) for the traditional, iPad, and iTouch, respectively. The CRT was similar within mobile devices, though slightly faster on the traditional: 359, 408, and 384 ms for traditional, iPad, and iTouch, respectively. Intraclass correlation coefficients ranged from 0.79 to 0.85 for SRT and from 0.75 to 0.83 for CRT. The similarity and reliability of SRT across platforms and consistency of SRT and CRT across test conditions indicate that mobile devices provide the next generation of assessment platforms for information processing.

Entities:  

Keywords:  cognitive assessment; information processing; mobile technology; reaction time

Mesh:

Year:  2016        PMID: 26933140     DOI: 10.1177/1073191116633752

Source DB:  PubMed          Journal:  Assessment        ISSN: 1073-1911


  6 in total

1.  Comparison of PC and iPad administrations of the Cogstate Brief Battery in the Mayo Clinic Study of Aging: Assessing cross-modality equivalence of computerized neuropsychological tests.

Authors:  Nikki H Stricker; Emily S Lundt; Kelly K Edwards; Mary M Machulda; Walter K Kremers; Rosebud O Roberts; David S Knopman; Ronald C Petersen; Michelle M Mielke
Journal:  Clin Neuropsychol       Date:  2018-11-10       Impact factor: 3.535

2.  High intensity aerobic exercise improves information processing and motor performance in individuals with Parkinson's disease.

Authors:  Anson B Rosenfeldt; Mandy Miller Koop; Hubert H Fernandez; Jay L Alberts
Journal:  Exp Brain Res       Date:  2021-01-04       Impact factor: 1.972

3.  MILO Mobile: An iPad App to Measure Search Performance in Multi-Target Sequences.

Authors:  Ian M Thornton; Todd S Horowitz
Journal:  Iperception       Date:  2020-06-20

4.  Use of a Smartphone to Gather Parkinson's Disease Neurological Vital Signs during the COVID-19 Pandemic.

Authors:  Jay L Alberts; Mandy Miller Koop; Marisa P McGinley; Amanda L Penko; Hubert H Fernandez; Steven Shook; Robert A Bermel; André Machado; Anson B Rosenfeldt
Journal:  Parkinsons Dis       Date:  2021-04-08

5.  Is conduct after capture training sufficiently stressful?

Authors:  Niclas Wisén; Gerry Larsson; Mårten Risling; Ulf Arborelius
Journal:  Front Psychol       Date:  2022-07-29

6.  A Novel Neuropsychological Tool for Immersive Assessment of Concussion and Correlation with Subclinical Head Impacts.

Authors:  Tamara R Espinoza; Kristopher A Hendershot; Brian Liu; Andrea Knezevic; Breanne B Jacobs; Russell K Gore; Kevin M Guskiewicz; Jeffery J Bazarian; Shean E Phelps; David W Wright; Michelle C LaPlaca
Journal:  Neurotrauma Rep       Date:  2021-05-26
  6 in total

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