Long-lasting virtual motorcycle-riding trainer effectiveness.

This work aimed to test the long-lasting effects of learning acquired with a virtual motorcycle-riding trainer as a tool to improve hazard perception. During the simulation, the rider can interact with other road actors and experience the most common potential accident situations in order to learn to modify his or her behavior to anticipate hazards and avoid crashes. We compared performance to the riding simulator of the two groups of participants: the experimental group, which was trained with the same simulator one year prior, and the control group that had not received any type of training with a riding or driving simulator. All of the participants had ridden a moped in the previous 12 months. The experimental group showed greater abilities to avoid accidents and recognize hazards in comparison to their performance observed a year before, whereas the performance of the control group was similar to that of the experimental group 1 year before in the first two sessions, and even better in the third. We interpreted this latter result as a consequence of their prior on-road experience. Also, the fact that the performance of the experimental group at the beginning of the follow-up is better than that recorded at the end of the training-1 year before-is in line with the idea of a transfer from the on-road experience to the simulator. The present data confirm our main expectation that the effectiveness of the riding training simulator on the ability to cope with potentially dangerous situations persists over time and provides additional evidence in favor of the idea that simulators may be considered useful tools for training the ability to detect and react to hazards, leading to an improvement of this higher-order cognitive skill that persists over time. Implications for the reciprocal influence of the training with the simulator and the on-the road experience are discussed as well.

Compulsivity and Impulsivity in Pathological Gambling: Does a Dimensional-Transdiagnostic Approach Add Clinical Utility to DSM-5 Classification?

Although the phenomenology of Pathological Gambling (PG) is clearly characterized by impulsive features, some of the Diagnostic and Statistical Manual of Mental Disorder (DSM-5) criteria for PG are similar to those of Obsessive Compulsive Disorder (OCD). Therefore, the compulsive-impulsive spectrum model may be a better (or complementary) fit with PG phenomenology. The present exploratory research was designed to further investigate the compulsive and impulsive features characterizing PG, by comparing PG individuals, alcohol dependents (ADs), OCD patients, and healthy controls (HCs) on both self-report and cognitive measures of compulsivity and impulsivity. A better understanding of the shared psychological and cognitive mechanisms underlying differently categorized compulsive and impulsive disorders may significantly impact on both clinical assessment and treatment strategies for PG patients. With respect to self-report measures, PG individuals reported more compulsive and impulsive features than did HCs. As regards motor inhibition ability indices, PG individuals and HCs performed similarly on the Go/No-go task and better than AD individuals and OCD patients. Results from the Iowa Gambling Task highlighted that PG, AD, and OCD participants performed worse than did HCs. An in-depth analysis of each group's learning profile revealed similar patterns of impairment between PG and AD individuals in decision-making processes. Current findings support the utility of adopting a dimensional-transdiagnostic approach to complement the DSM-5 classification when working with PG individuals in clinical practice. Indeed, clinicians are encouraged to assess both compulsivity and impulsivity to provide individualized case conceptualizations and treatment plans focusing on the specific phenomenological features characterizing each PG patient.

A functional measurement study on averaging numerosity

In two experiments, participants judged the average numerosity between two sequentially presented dot patterns to perform an approximate arithmetic task. In Experiment 1, the response was given on a 0-20 numerical scale (categorical scaling), and in Experiment 2, the response was given by the production of a dot pattern of the desired numerosity (numerosity production). The experiments found that the responses were shaped according to an averaging integration model. This suggests the linearity in the response scale of both of the response methods in the approximate arithmetic task (AU)

No disponible