Citation

Marques PH, Jesus V, Olea SA, Vairinhos V, Jacinto C. Safety Sci. 2014; 68: 108-120.

Copyright

(Copyright © 2014, Elsevier Publishing)

DOI

10.1016/j.ssci.2014.03.007

PMID

unavailable

Abstract

Programmes for testing Alcohol and Drugs (A&D) at the workplace, at random and by surprise, are believed to have a positive impact on safety and to reduce individual's accident risk. Despite this perception, there is limited scientific evidence and poor statistical support of this assumption. This study aims at testing whether there is such a cause-effect relationship between A&D testing and post-accident reduction, and how to quantify it. The methodology applied data-mining techniques together with classical statistics hypothesis testing. It covers a wide range of data concerning accidents, alcohol and drug tests, biographical and occupational records of a large railway transportation company in Portugal, for a period of 5½ years.

RESULTS give sound statistical evidence of individual's accident risk decrease after being tested, by quantifying the relations between A&D testing and post-testing accidents.

RESULTS also estimate the optimal testing frequency that balances testing costs and accident reduction. Optimum rates of tests per year per worker are in the ranges ]0.5-1.0] in white-collars and professions at large, and ]0.0-0.5] in operations/technical personnel. The fraction of accident victims that are prevented by the application of optimal frequencies are around 59% for workers onboard trains, 72% for those working near trains, and 85% for white-collars. Testing at the optimal frequency generates net savings of at least 15:1, in onboard personnel. In conclusion, testing for alcohol and drugs at workplace, at random and by surprise, has a statistically significant preventive effect in overall professions, but is stronger within white-collars.