Beyond Diagnosis: Virtual Reality Driving Simulation and a Transdiagnostic Approach to the Cognitive Demands of Driving Behaviors
Research Essay:
Driving is a crucial everyday activity for many individuals, providing them with transportation, freedom, and even a means of living. For patients with brain injuries and illnesses such as multiple sclerosis (MS) and traumatic brain injury (TBI), the loss of driving rights affects people emotionally, socially, and monetarily. This loss of rights is often necessary to ensure safety, as the capacity to drive a vehicle is a complicated skill comprising several cognitive, perceptual, and behavioral factors. Since driving involves the combination of these numerous components, it is a skill that frequently proves to be challenging for those with neurologic conditions.
Driving recommendations after brain injury or illness involve a delicate balance between safety and independence and thus require precise, ecologically valid tools. To evaluate the many integrated demands of driving, virtual reality driving simulators (VRDS) may be an invaluable tool. Virtual reality driving simulators enable the utilization of realistic driving conditions with varying degrees of challenge and provide many objective, sensitive metrics of driving ability, not provided by traditional driving evaluation tools.
My recent work in this area used VRDS to determine differences in stopping and turning behavior between adults with and without MS, and also identify cognitive demands of stopping and turning behavior in these two populations. According to prior literature, most accidents happen at a stop intersection and left turns, yet turning and stopping are two understudied components of driving behavior. The results of the study were quite intriguing and provided significant evidence that MS patients exhibit largely similar stopping and turning behavior to healthy controls, with some subtle differences; namely, they show more careful stopping behavior and turning behavior in select situations. By comparison, there were numerous significant associations of stopping and turning behavior with cognitive and motor functions. These findings emphasize the importance of evaluating cognitive and motor capabilities for driving rather than relying solely on diagnostic status. The ultimate goal is to shift the focus from mere diagnosis to the development of personalized rehabilitation procedures that are tailored to a person's cognitive strengths and weaknesses.
It is crucial to recognize that many individuals with MS may only experience mild difficulties and are aware of their deficits. This is not the case with other types of neurologic conditions. TBI involves a wide range of severity levels and often affects an individual’s insight into their difficulties. A recent study found that 63% of individuals with severe TBI who returned to driving were involved in subsequent car crashes. Therefore, to further expand on this important research, the next logical step is to apply similar methods and principles to individuals with TBI who have a range of cognitive difficulties. By doing so, we can validate the results obtained in the MS population and gain a better understanding of how different cognitive profiles affect driving behavior. Moreover, expanding this work to a new population will increase its generalizability and clinical impact.
Objective: This study will use virtual reality driving simulation (VRDS) to
Aim 1) Investigate how stopping/turning behaviors differ in adults with TBI in comparison to those with MS and those without a neurological diagnosis.
Aim 2) Identify cognitive demands of stopping and turning driving behaviors.
Aim 3) Examine whether diagnostic status (TBI vs. MS vs. control) influences these demands.
Participants and Methods: The present study will integrate archival data from multiple prior studies (23 drivers with TBI, 40 drivers with MS, and 55 healthy control (HC) drivers). Participants completed neuropsychological tests and a VRDS drive with multiple stops and turns of varying cognitive complexity. Key stopping variables will include failing to stop, minimum speed, distance from the stop line, and wait time. Key turning variables will include lane position, speed, acceleration, and braking. Data will be extracted from existing spreadsheets and imported into SPSS for analysis.
Analyses and Anticipated Results: Neuropsychological correlates of stopping/turning behaviors will be examined using Pearson and Spearman's correlations. Group differences will be examined using analysis of variance, Mann-Whitney U, chi-square, and Fisher exact tests. Linear and logistic regressions will be used to evaluate interactions between neurologic status and neuropsychological measures on driving behavior.
Implications and Future Work: This work will evaluate the utility of VRDS as a clinical tool for assessing complex driving behavior, identifying patients at risk of unsafe driving behavior, and informing individualized driving interventions targeting specific turning difficulties and their cognitive correlates. These results are expected to emphasize the importance of evaluating specific cognitive and motor capabilities for driving rather than relying solely on diagnostic status.
