A Frontal Neuropsychological Profile in Fitness to Drive.

Traffic accidents are a global concern due to the elevated mortality rates of both drivers and pedestrians. The World Health Organization declared 2011-2020 as the Decade of Action for Road Safety, endorsing initiatives to reduce traffic-related deaths. Yet, despite these incentives, fatal accidents still occur. Different studies have linked deficits in executive functions to risky driving attitudes and crashes. The present study focuses on demographic, cognitive and personality factors, related to the prefrontal cortex, that are characteristic of drivers prone to risky behavior behind the wheel. The penalty Points System was used to classify drivers as "safe", with no point loss over a two-year period, or "risky", with full point loss during the same interval. A neuropsychological assessment of prefrontal cognitive functions was carried out on each group to identify variables associated with safe and risky behavior. Neuropsychological indexes were obtained from a continuous performance task without cue (Simple Attention), a continuous performance task with cue (Conditioned Attention), the Tower of Hanoi test and the Neurologically-related Changes in Personality Inventory (NECHAPI). A Discriminant Analysis (DA) found that education level, reaction times in Simple and Conditioned Attention, learning errors in the Tower of Hanoi and vulnerability in the personality test, best predicted whether drivers were likely to be in the safe or risky group. Finally, a cross-validation analysis performed on the same sample correctly classified 87.5% of the drivers. These data suggest that prefrontal dysfunction contributes to risky behavior behind the wheel. The inclusion of cognitive programs to identify and train drivers with this propensity could reduce risky driving, and consequently, save lives on the road.

A QEEG index of level of functional dependence for people sustaining acquired brain injury: the Seville Independence Index (SINDI).

PRIMARY OBJECTIVE: To find an easy-to-use, valid and reliable tool for evaluating the level of functional dependence of an individual with brain damage who seeks a diagnosis of his/her functional dependence in daily activities. METHODS: Eighty-one patients with acquired brain injury (ABI) in post-acute phase, 40 traumatic brain injury (TBI) and 41 cerebral vascular accident (CVA), were assessed using quantitative electroencephalography (QEEG) and grouped according to the FIM + FAM scale. Discriminant analysis was performed on QEEG variables to obtain a discriminant function with the best discriminative capacity between functionality groups. RESULTS: Discriminant analysis showed classification accuracy of 100% in the training set sample and 75% in an external cross-validation sample; 100% sensitivity and 100% specificity were reached. Coherence measures were the most numerous variables in the function. CONCLUSIONS: These results point out that the discriminant function may be a useful tool in objective evaluations of patients seeking a diagnosis of their level of dependence and that it could be included in current functionality assessment protocols.