An investigation on the risk factors associated with driving errors under the influence of alcohol using structural equation modeling.

Conclusion: This study highlights a novel approach to investigate driving error by modeling it as a latent variable instead of modeling individual performance measures. The successful execution of SEM in alcohol impairment research may serve as a significant step in the human factors field moving from piecemeal analysis to a combined analysis where interrelationships among numerous risk factors and driving error can be established. The study outcomes may serve as a reference while developing strategies to enhance road traffic safety where special emphasis can be given to the critical risk factors influencing driving error identified in the study. PMID: 32364839 [PubMed - as supplied by publisher]
Source: Traffic Injury Prevention - Category: Accident Prevention Authors: Tags: Traffic Inj Prev Source Type: research