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Living Well Study > Blog > Technology > Fit2Drive revolutionizes the evaluation of older drivers experiencing cognitive decline
Technology

Fit2Drive revolutionizes the evaluation of older drivers experiencing cognitive decline

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Man in Brown Jacket Driving Car. Photo by Kampus Production: https://www.pexels.com/photo/man-in-brown-jacket-driving-car-7476883/
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As the global population ages, the number of elderly drivers on the road also increases. Driving safely requires robust memory, perceptual, motor skills, and executive functioning abilities. It’s well-established that individuals with severe Alzheimer’s Disease and related dementias (ADRD) cannot drive safely. However, evidence suggests that deterioration in driving abilities can begin during the preclinical stages of Alzheimer’s Disease. This situation presents a complex challenge, as the decision to cease driving due to cognitive impairments involves not only the elderly individuals themselves but also their families and healthcare providers.

Despite the availability of numerous cognitive tests and practical driving assessments, clinicians often need more training and time constraints, which impede their ability to administer these tests effectively. This issue is compounded by the difficulty in obtaining objective evidence to support decisions about an older adult’s fitness to drive. To address these challenges, researchers at Florida Atlantic University have developed an innovative tool called “Fit2Drive”. This evidence-based calculator simplifies the process for clinicians to administer and evaluate a cognitive test in their office, predicting the likelihood of an older adult passing a practical driving test based on short, straightforward cognitive assessments.

The development of Fit2Drive involved the creation of an algorithm by the team at FAU’s Christine E. Lynn College of Nursing and Charles E. Schmidt College of Science, which rapidly generates driving capability predictions for individual patients. They utilized data from 12 different cognitive assessments and practical driving tests collected from two distinct groups: patients from FAU’s Louis and Anne Green Memory and Wellness Center and older drivers from the local community. These assessments included the Mini-Mental State Exam (MMSE) and the Trail Making Tests A and B, which assess various cognitive abilities. Four hundred twelve study participants, aged between 59 and 89, underwent these cognitive tests and a practical driving assessment.

The study’s findings, published in the Journal of the American Medical Directors Association, demonstrated that the Fit2Drive algorithm achieved a remarkable predictive accuracy of 91.5%. A detailed analysis revealed that the highest MMSE score and the time to complete Trails B were the most significant predictors of driving performance. Furthermore, the study noted substantial differences in practical driving test outcomes between the two groups, with a much higher failure rate among those from the memory and wellness centre compared to the community sample.

The emotional strain on patients and the lack of objective data to support clinical recommendations were critical motivators for developing this predictive tool. The Fit2Drive results aim to provide clinicians with reliable evidence to share with patients and their families, who may be concerned about the risks of continuing to drive. This decision significantly impacts their lives and poses a challenge for primary care providers. To streamline the use of the predictive model, researchers developed a logistic regression model that evaluated the sensitivity and specificity of the predictions, using a binary pass-fail outcome from the practical driving test as the basis for assessing predictive variables.

The Fit2Drive calculator is available online and is designed for easy use on Android and iOS devices, enabling clinicians to enter data through a smartphone. As the feasibility of conducting cognitive tests online increases, there is potential for developing a completely online version of Fit2Drive, further enhancing its accessibility and ease of use. This tool represents a significant advancement in the ability to assess the driving capabilities of elderly individuals objectively, providing valuable support to clinicians, patients, and families navigating the complex issue of cognitive decline and driving.

More information: Ruth Tappen et al, Fit2Drive: Screening Older Drivers with Cognitive Concerns, Journal of the American Medical Directors Association. DOI: 10.1016/j.jamda.2024.105054

Journal information: Journal of the American Medical Directors Association Provided by Florida Atlantic University

TAGGED:algorithmsalzheimer diseasecognitive neurosciencedementiamemory disordersstatistical probabilityworking memory
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