Towards the Validation of an Observational Tool to Detect Impaired Drivers-An Online Video Study

Int J Environ Res Public Health. 2022 Jun 20;19(12):7548. doi: 10.3390/ijerph19127548.

Abstract

Abuse of alcohol and other drugs is a major risk factor at work. To reduce this risk, workplace drug testing is performed in transportation and other industries. VERIFY, an observational method, is one of the key elements in a procedure adopted by the police of the canton of Zurich, Switzerland, for detecting impaired drivers. The observational method has been successfully applied by adequately trained police officers since 2014. The aim of this study is to examine the interrater reliability of the observational method, the effect of training in use of the method, and the role of having experience in the police force and traffic police force on the outcome when rating a driver's impairment. For this purpose, driver impairment in staged road traffic controls presented in videos was rated by laypeople (n = 81), and police officers without (n = 146) and with training (n = 172) in the VERIFY procedure. In general, the results recorded for police officers with training revealed a moderate to very good interrater reliability of the observational method. Among the three groups, impaired drivers were best identified by officers with training (ranging between 82.6% and 89.5% correct identification). Trained officers reported a higher impairment severity of the impaired drivers than the other two groups, indicating that training increases sensitivity to signs of impairment. Our findings also suggest that online video technology could be helpful in identifying impaired drivers. Trained police officers could be connected to a road traffic control to make observations via live video. By this method efficiency and reliability in detecting abuse of alcohol and other drugs could be improved. Our findings also apply to workplace drug testing in general.

Keywords: accident prevention; impaired driving; video-based training; workplace drug testing.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidents, Traffic
  • Automobile Driving*
  • Ethanol
  • Humans
  • Police
  • Reproducibility of Results
  • Substance Abuse Detection

Substances

  • Ethanol

Grants and funding

This work was supported by the Zurich Cantonal Police, Switzerland.