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      MICK (Mobile Integrated Cognitive Kit) app: Feasibility of an accessible tablet-based rapid picture and number naming task for concussion assessment in a division 1 college football cohort.

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          Abstract

          Although visual symptoms are common following concussion, quantitative measures of visual function are missing from concussion evaluation protocols on the athletic sideline. For the past half century, rapid automatized naming (RAN) tasks have demonstrated promise as quantitative neuro-visual assessment tools in the setting of head trauma and other disorders but have been previously limited in accessibility and scalability. The Mobile Interactive Cognitive Kit (MICK) App is a digital RAN test that can be downloaded on most mobile devices and can therefore provide a quantitative measure of visual function anywhere, including the athletic sideline. This investigation examined the feasibility of MICK App administration in a cohort of Division 1 college football players. Participants (n = 82) from a National Collegiate Athletic Association (NCAA) Division 1 football team underwent baseline testing on the MICK app. Total completion times of RAN tests on the MICK app were recorded; magnitudes of best time scores and between-trial learning effects were determined by paired t-test. Consistent with most timed performance measures, there were significant learning effects between the two baseline trials for both RAN tasks on the MICK app: Mobile Universal Lexicon Evaluation System (MULES) (p < 0.001, paired t-test, mean improvement 13.3 s) and the Staggered Uneven Number (SUN) (p < 0.001, mean improvement 3.3 s). This study demonstrated that the MICK App can be feasibly administered in the setting of pre-season baseline testing in a Division I environment. These data provide a foundation for post-injury sideline testing that will include comparison to baseline in the setting of concussion.

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          Author and article information

          Journal
          J Neurol Sci
          Journal of the neurological sciences
          Elsevier BV
          1878-5883
          0022-510X
          Nov 15 2022
          : 442
          Affiliations
          [1 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: carter.bell@nyulangone.org.
          [2 ] Michigan State University, East Lansing, MI, USA. Electronic address: ricel@ath.msu.edu.
          [3 ] Model Compilers Inc., San Francisco, CA, USA. Electronic address: marc@modelcompilers.com.
          [4 ] Michigan State University, East Lansing, MI, USA. Electronic address: pearson@msu.edu.
          [5 ] Michigan State University, East Lansing, MI, USA. Electronic address: penningb@ath.msu.edu.
          [6 ] Michigan State University, East Lansing, MI, USA. Electronic address: aubrey.alexander@hc.msu.edu.
          [7 ] Michigan State University, East Lansing, MI, USA. Electronic address: jensynb@ath.ms.edu.
          [8 ] Michigan State University, East Lansing, MI, USA. Electronic address: nogle@ath.msu.edu.
          [9 ] Michigan State University, East Lansing, MI, USA. Electronic address: tomczykc@msu.edu.
          [10 ] Michigan State University, East Lansing, MI, USA. Electronic address: traceyaj@msu.edu.
          [11 ] Michigan State University, East Lansing, MI, USA. Electronic address: loftinme@msu.edu.
          [12 ] Michigan State University, East Lansing, MI, USA. Electronic address: pollar77@msu.edu.
          [13 ] Michigan State University, East Lansing, MI, USA. Electronic address: zyndaaar@msu.edu.
          [14 ] Michigan State University, East Lansing, MI, USA. Electronic address: covassin@msu.edu.
          [15 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: george.park@nyulangone.org.
          [16 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA; Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: john-rossrizzo@nyulangone.org.
          [17 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA; Department of Rehabilitation Medicine, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: todd.hudson@nyulangone.org.
          [18 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA; Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: janet.rucker@nyulangone.org.
          [19 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA; Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: steven.galetta@nyulangone.org.
          [20 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA; Department of Ophthalmology, New York University Grossman School of Medicine, New York, NY, USA; Department of Population Health, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: laura.balcer@nyulangone.org.
          [21 ] Michigan State University, East Lansing, MI, USA. Electronic address: kaufman1@msu.edu.
          [22 ] Department of Neurology, New York University Grossman School of Medicine, New York, NY, USA. Electronic address: scott.grossman@nyulangone.org.
          Article
          S0022-510X(22)00307-0
          10.1016/j.jns.2022.120445
          36208585
          fd331838-29b7-45b6-8752-774b8cccbc0d
          History

          Staggered Uneven Number (SUN) test,Mobile Integrated Cognitive Kit (MICK),Mobile Universal Lexicon Evaluation System (MULES),Neuro-ophthalmology,Rapid Automatized Naming (RAN) tasks,Vision

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