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Reliability and Minimal Detectable Change for a Smartphone-Based Motor-Cognitive Assessment: Implications for Concussion Management.

Authors :
Howell, David R.
Seehusen, Corrine N.
Wingerson, Mathew J.
Wilson, Julie C.
Lynall, Robert C.
Lugade, Vipul
Source :
Journal of Applied Biomechanics; Aug2021, Vol. 37 Issue 4, p380-387, 8p, 1 Diagram, 3 Charts, 1 Graph
Publication Year :
2021

Abstract

Our purpose was to investigate the reliability and minimal detectable change characteristics of a smartphone-based assessment of single- and dual-task gait and cognitive performance. Uninjured adolescent athletes (n = 17; mean age = 16.6, SD = 1.3 y; 47% female) completed assessments initially and again 4 weeks later. The authors collected data via an automated smartphone-based application while participants completed a series of tasks under (1) single-task cognitive, (2) single-task gait, and (3) dual-task cognitive-gait conditions. The cognitive task was a series of continuous auditory Stroop cues. Average gait speed was consistent between testing sessions in single-task (0.98, SD = 0.21 vs 0.96, SD = 0.19 m/s; P =.60; r =.89) and dual-task (0.92, SD = 0.22 vs 0.89, SD = 0.22 m/s; P =.37; r =.88) conditions. Response accuracy was moderately consistent between assessments in single-task standing (82.3% accurate, SD = 17.9% vs 84.6% accurate, SD = 20.1%; P =.64; r =.52) and dual-task gait (89.4% accurate, SD = 15.9% vs 85.8% accurate, SD = 20.2%; P =.23; r =.81) conditions. Our results indicate automated motor-cognitive dual-task outcomes obtained within a smartphone-based assessment are consistent across a 1-month period. Further research is required to understand how this assessment performs in the setting of sport-related concussion. Given the relative reliability of values obtained, a smartphone-based evaluation may be considered for use to evaluate changes across time among adolescents, postconcussion. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10658483
Volume :
37
Issue :
4
Database :
Complementary Index
Journal :
Journal of Applied Biomechanics
Publication Type :
Academic Journal
Accession number :
151778775
Full Text :
https://doi.org/10.1123/jab.2020-0391