Sleepiness at the wheel is widely believed to be a cause of motor vehicle accidents. Nevertheless, a systematic review of studies investigating this relationship has not yet been published. The objective of this study was to quantify the relationship between sleepiness at the wheel and motor vehicle accidents. A systematic review was performed using Medline, Scopus and ISI Web of Science. The outcome measure of interest was motor vehicle accident defined as involving four or two wheeled vehicles in road traffic, professional and non-professional drivers, with or without objective consequences. The exposure was sleepiness at the wheel defined as self-reported sleepiness at the wheel. Studies were included if they provided adjusted risk estimates of motor vehicles accidents related to sleepiness at the wheel. Risk estimates and 95% confidence intervals (95%CI) were extracted and pooled as odds ratios (OR) using a random-effect model. Heterogeneity was quantified using Q statistics and the I² index. The potential causes of heterogeneity were investigated using meta-regressions. Ten cross-sectional studies (51,520 subjects), six case-control studies (4,904 subjects), and one cohort study (13,674 subjects) were included. Sleepiness at the wheel was associated with an increased risk of motor vehicle accidents (pooled OR 2.51 [95%CI 1.87; 3.39]). A significant heterogeneity was found between the individual risk estimates (Q =93.21; I² = 83%). Sleepiness at the wheel increases the risk of motor vehicle accidents and should be considered when investigating fitness to drive. Further studies are required to explore the nature of this relationship.

Objective We undertook a meta-analysis of published Randomized Controlled Trials (RCT) with semi-active control and sham-NF groups to determine whether EEG-NF significantly improves the overall symptoms, inattention and hyperactivity/impulsivity dimensions for probably unblinded assessment (parent assessment) and probably blinded assessment (teacher assessment) in children with Attention Deficit Hyperactivity Disorder (ADHD). Data Sources A systematic review identified independent studies that were eligible for inclusion in a random effects meta-analysis. Data Extraction Effect sizes for ADHD symptoms were expressed as standardized mean differences (SMD) with 95% confidence intervals. Results Five identified studies met eligibility criteria, 263 patients with ADHD were included, 146 patients were trained with EEG-NF. On parent assessment (probably unblinded assessment), the overall ADHD score (SMD=-0.49 [-0.74, -0.24]), the inattention score (SMD=-0.46 [-0.76, -0.15]) and the hyperactivity/impulsivity score (SMD=-0.34 [-0.59, -0.09]) were significantly improved in patients receiving EEG-NF compared to controls. On teacher assessment (probably blinded assessment), only the inattention score was significantly improved in patients receiving EEG-NF compared to controls (SMD=-0.30 [-0.58, -0.03]). Conclusions This meta-analysis of EEG-NF in children with ADHD highlights improvement in the inattention dimension of ADHD symptoms. Future investigations should pay greater attention to adequately blinded studies and EEG-NF protocols that carefully control the implementation and embedding of training.

Embodied Conversational Agents (ECAs) are promising software to communicate with patients but no study has tested them in the diagnostic field of mental disorders. The aim of this study was 1) to test the performance of a diagnostic system for major depressive disorders (MDD), based on the identification by an ECA of specific symptoms (the MDD DSM 5 criteria) in outpatients; 2) to evaluate the acceptability of such an ECA. Patients completed two clinical interviews in a randomized order (ECA versus psychiatrist) and filled in the Acceptability E-scale (AES) to quantify the acceptability of the ECA. 179 outpatients were included in this study (mean age 46.5 ± 12.9 years, 57.5% females). Among the 35 patients diagnosed with MDD by the psychiatrist, 14 (40%) patients exhibited mild, 12 (34.3%) moderate and 9 (25.7%) severe depressive symptoms. Sensitivity increased across the severity level of depressive symptoms and reached 73% for patients with severe depressive symptoms, while specificity remained above 95% for all three severity levels. The acceptability of the ECA evaluated by the AES was very good (25.4). We demonstrate here the validity and acceptability of an ECA to diagnose major depressive disorders. ECAs are promising tools to conduct standardized and well-accepted clinical interviews.