OBJECTIVES: This study performed meta-analysis on the literatures that surveyed cognitive test to forecast unsafe driving by older drivers and identified objective and consistent cognitive test for predicting unsafe driving of older drivers. SELECTION CRITERIA: The study of RCT (Randomized Control Trial) that conducted cognitive test by classifying older drivers into safe-drivers and unsafe-drivers was done and a total of nine studies suitable for the selection criteria were chosen. SEARCH STRATEGY: To meet subject selection, online search was performed by keyword such as "Older", "Driving", "Safe", "Cognition", etc. Qualitative analysis of the study was conducted using Jadad evaluation. Quantitative analysis also conducted statistical heterogeneity, effect size, sensitivity and publication bias every cognitive assessment tool. RESULT: The Jadad evaluation grade of the studies was assessed on papers of a high quality -all study received over 3 points. The result of the effect sizes was that TMT-B, TMT-A, UFOV-subtest 2 and MMSE were statistically significant (P < .05). As a result, TMT-B was "Big effect size", TMT-A and UFOV-subtest 2 were "Medium effect sizes" and MMSE was "Small effect size." CONCLUSION: TMT-A, TMT-B and UFOV-subtest 2 were found to be useful as cognitive test tools to forecast unsafe driving of older drivers.

[Purpose] This study examined the cut-off point of the Trail Making Test in predicting the risk of unsafe driving in stroke patients. [Subjects and Methods] A total of 81 stroke patients with a driver’s license participated in this study. The DriveABLE Cognitive Assessment Tool, Trail Making Test-A, and Trail Making Test-B evaluations were conducted in all participants. All participants were classified into the safety or risk groups based on the DriveABLE Cognitive Assessment Tool evaluation results. The Trail Making Test results underwent a receiver operating characteristic analysis in each group. [Results] The results of the receiver operating characteristic curve analysis showed that the cut-off point for Trail Making Test-A was 32 seconds and the cut-off point for Trail Making Test-B was 79 seconds. The positive predictive values of the Trail Making Test-A and Trail Making Test-B were 98.3% and 98.3%, respectively, and the negative predictive values of the Trail Making Test-A and Trail Making Test-B were 81.0% and 73.9%, respectively. [Conclusion] The Trail Making Test is a useful tool for predicting the risk of unsafe driving in stroke patients. This tool is expected to be used more actively for screening stroke drivers with respect to their cognitive function.

[Purpose] This study examined the usefulness of the DriveABLE cognitive assessment tool (DCAT) in predicting the driving risk factor of stroke patients, and compared the cognitive and driving functions of two groups discriminated by DCAT. [Subjects and Methods] A total of forty-two stroke patients with a driver’s license participated in this study. Two participants with communication problems were excluded. DCAT was used to evaluate the risk potential to the driver, and the subjects were classified into two groups according to the probability of driving risk estimated by the DCAT evaluation. The safe driver group (SDG) and unsafe driver group (USDG) underwent a driving simulator and cognitive function assessments. [Results] The results of the SDG and USDG were compared. The SDG showed higher cognitive function than the USDG. In addition, the SDG showed higher ability than the USDG in most of the tests associated with the driving function (pedal reaction time, average reaction time, centerline crossing, road edge excursion, off-road accidents, collisions). [Conclusion] DCAT is a useful tool for predicting the risk of driving. In addition, it can predict the driving ability of stroke patients related to the cognitive function. Nevertheless, a multi-faceted study of associated with driving and cognitive functions for safe driving will be needed.

Introduction: Virtual reality (VR)-based training for functions such as cognition, upper extremities, balancing, and activities of daily living (ADL) has been used on stroke patients, and its efficacy has been reported. However, no comparison has been made between the efficacy of VR-based training for daily activities that exactly reproduces ADL and functional training. Therefore, this study sought to analyze the difference in independency enhancement of VR-based training for daily activities compared to cognitive and motor functional training. Patient concerns and diagnosis: This study was conducted on 4 patients who have been diagnosed with stroke and are currently receiving rehabilitation therapy in G hospital located in the city of Gwangju, using A-B-A’-B’ design from single-subject experimental designs. Interventions: Intervention was performed in 2 ways: application of VR-based training for daily activities after the application of cognitive and motor function training; and application of cognitive and motor function training after the application of VR-based training for daily activities. The Assessment of Motor and Process Skills, Computer Cognitive Screening Assessment System, Box and Block Test, and Grip and Pinch Strength Test were used to measure the changes in the performance of daily activities, cognitive function, and upper extremities function. Outcomes: The results confirmed that the performance of daily activities, cognitive function, and upper extremities function was improved after the application of VR-based intervention. In addition, the efficacy of independency enhancement was maximized by the early approach of training for daily activities at the time of VR-based intervention in stroke patients. Conclusions: VR-based intervention of training for daily activities and functional training can be considered to benefit the improvement of the performance of daily activities, cognitive function, and upper extremities function in stroke patients. In addition, although functional training was also effective in enhancing independency and functional improvement in stroke patients, an early approach to training for ADL based on tasks with objectives was deemed to be more effective.

BACKGROUND Self-report assessments for elderly drivers are used in various countries for accessible, widespread self-monitoring of driving ability in the elderly population. Likewise, in South Korea, the paper-based Self-report Assessment for Elderly Driving Risk (SAFE-DR) has been developed. Here, we implemented the SAFE-DR in an Android application, which has the advantages of accessibility, convenience, and provision of diverse information, and verified its reliability and validity. OBJECTIVE This study was tested validity and reliability of a mobile version of a self-report assessment application for elderly persons contextualized to the South Korean culture with comparing paper-based test. METHODS In this mixed-methods study, we recruited and interviewed 567 elderly drivers (≥65 years) between August 2018 and May 2019. For participants who provided consent, the application-based test was repeated after 2 weeks, and an additional paper-based Driver 65 Plus test was also administered. Using the collected data, we analyzed the reliability and validity of the application-based SAFE-DR. In the reliability analysis, exploratory factor analysis on 40 of the 44 items established five subdomains: On-road (8 items), Coping (16 items), Cognitive Functions (5 items), General Conditions (8 items), and Medical Health (3 items). In the retest after 2 weeks, the mean correlation coefficient across all items was r=0.951, showing a very high reliability. RESULTS A very strong negative correlation of -0.864 was observed between the total score for the application-based SAFE-DR and the paper-based Driver 65 Plus with decorrelation scales. The application-based test was reliable. CONCLUSIONS This assessment can be applied to the education and preventive screening of elderly drivers’ license renewal policy in South Korea and can contribute to safe driving among elderly drivers.