Validity of the SKILLCOURT® technology for agility and cognitive performance assessment in healthy active adults.
J Exerc Sci Fit
; 21(3): 260-267, 2023 Jul.
Article
en En
| MEDLINE
| ID: mdl-37497363
ABSTRACT
Background/Objectives:
Agility and cognitive abilities are typically assessed separately by different motor and cognitive tests. While many agility tests lack a reactive decision-making component, cognitive assessments are still mainly based on computer-based or paper-pencil tests with low ecological validity. This study is the first to validate the novel SKILLCOURT technology as an integrated assessment tool for agility and cognitive-motor performance.Methods:
Thirty-two healthy adults performed agility (Star Run), reactive agility (Random Star Run) and cognitive-motor (executive function test, 1-back decision making) performance assessments on the SKILLCOURT. Cognitive-motor tests included lower limb responses in a standing position to increase the ecological validity when compared to computer-based tests. Test results were compared to established motor and agility tests (countermovement jump, 10 m linear sprint, T-agility tests) as well as computer-based cognitive assessments (choice-reaction, Go-NoGo, task switching, memory span). Correlation and multiple regression analyses quantified the relation between SKILLCOURT performance and motor and cognitive outcomes.Results:
Star Run and Random Star Run tests were best predicted by linear sprint (r = 0.68, p < 0.001) and T-agility performance (r = 0.77, p < 0.001), respectively. The executive function test performance was well explained by computer-based assessments on choice reaction speed and cognitive flexibility (r = 0.64, p < 0.001). The 1-back test on the SKILLCOURT revealed moderate but significant correlations with the computer-based assessments (r = 0.47, p = 0.007).Conclusion:
The results support the validity of the SKILLCOURT technology for agility and cognitive assessments in more ecologically valid cognitive-motor tasks. This technology provides a promising alternative to existing performance assessment tools.
Texto completo:
1
Banco de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
Idioma:
En
Año:
2023
Tipo del documento:
Article