Clinical predictors of driving simulator performance in drivers with multiple sclerosis.

Multiple sclerosis automobile driving cognitive impairment computer simulation driving performance outcome measurement

Journal

Multiple sclerosis (Houndmills, Basingstoke, England)
ISSN: 1477-0970
Titre abrégé: Mult Scler
Pays: England
ID NLM: 9509185

Informations de publication

Date de publication:
11 2021
Historique:
pubmed: 11 2 2021
medline: 28 1 2022
entrez: 10 2 2021
Statut: ppublish

Résumé

Drivers with multiple sclerosis (MS) may experience visual-cognitive impairment that affects their fitness to drive. Due to limitations associated with the on-road assessment, an alternative assessment that measures driving performance is warranted. Whether clinical indicators of on-road outcomes can also predict driving performance outcomes on a driving simulator are not fully understood. This study examined if deficits in immediate verbal/auditory recall (California Verbal Learning Test-Second Edition; CVLT2-IR) and/or slower divided attention (Useful Field of View™; UFOV2) predicted deficits in operational, tactical, or strategic maneuvers assessed on a driving simulator, in drivers with and without MS. Participants completed the CVLT2-IR, UFOV2, and a driving simulator assessment of operational, tactical, and strategic maneuvers. Deficits in immediate verbal/auditory recall and slower divided attention predicted adjustment to stimuli errors, pertaining to tactical maneuvers only, in 36 drivers with MS (vs 20 drivers without MS; The CVLT2-IR and UFOV2 capture the visual and verbal/auditory recall, processing speed, and divided attention required to appropriately adjust to stimuli in a simulated driving environment. Clinicians may use the CVLT2-IR and UFOV2 as precursors to driving performance deficits in drivers with MS.

Sections du résumé

BACKGROUND
Drivers with multiple sclerosis (MS) may experience visual-cognitive impairment that affects their fitness to drive. Due to limitations associated with the on-road assessment, an alternative assessment that measures driving performance is warranted. Whether clinical indicators of on-road outcomes can also predict driving performance outcomes on a driving simulator are not fully understood.
OBJECTIVE
This study examined if deficits in immediate verbal/auditory recall (California Verbal Learning Test-Second Edition; CVLT2-IR) and/or slower divided attention (Useful Field of View™; UFOV2) predicted deficits in operational, tactical, or strategic maneuvers assessed on a driving simulator, in drivers with and without MS.
METHODS
Participants completed the CVLT2-IR, UFOV2, and a driving simulator assessment of operational, tactical, and strategic maneuvers.
RESULTS
Deficits in immediate verbal/auditory recall and slower divided attention predicted adjustment to stimuli errors, pertaining to tactical maneuvers only, in 36 drivers with MS (vs 20 drivers without MS;
CONCLUSION
The CVLT2-IR and UFOV2 capture the visual and verbal/auditory recall, processing speed, and divided attention required to appropriately adjust to stimuli in a simulated driving environment. Clinicians may use the CVLT2-IR and UFOV2 as precursors to driving performance deficits in drivers with MS.

Identifiants

pubmed: 33565905
doi: 10.1177/1352458521992507
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

2085-2092

Auteurs

Sarah Krasniuk (S)

Health and Rehabilitation Sciences, University of Western Ontario, London, ON, Canada.

Sherrilene Classen (S)

Department of Occupational Therapy, College of Public Health and Health Professions, University of Florida, Gainesville, FL, USA.

Sarah A Morrow (SA)

Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada/London Health Sciences Centre, London, ON, Canada.

Liliana Alvarez (L)

School of Occupational Therapy, University of Western Ontario, London, ON, Canada.

Wenqing He (W)

Department of Statistical and Actuarial Sciences, University of Western Ontario, London, ON, Canada.

Sivaramakrishnan Srinivasan (S)

Department of Civil and Coastal Engineering, University of Florida, Gainesville, FL, USA.

Miriam Monahan (M)

Driver Rehabilitation Institute, Petaluma, CA, USA.

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Classifications MeSH