Toward a more parsimonious approach to drug recognition expert evaluations.
OBJECTIVE
The purpose of this study is to statistically identify the set of drug-related cues from Drug Evaluation and Classification (DEC) evaluations that significantly predict the substance used by suspected drug-impaired drivers.


METHODS
Data from 742 completed Canadian DEC evaluations of central nervous system (CNS) stimulant, narcotic analgesic, and cannabis cases were analyzed using a multinomial logistic regression procedure.


RESULTS
Nine clinical indicators from the DEC evaluations significantly enhanced the prediction of drug category, including pulse rate, condition of the eyes and eyelids, lack of convergence, hippus, reaction to light, rebound dilation, systolic blood pressure, and the presence of injection sites.


CONCLUSIONS
The findings from this study will facilitate the process of identifying the correct category of drug ingested by focusing on critical signs and symptoms of drug influence. This work will have direct and immediate relevance to the training of drug recognition experts (DREs) by providing the foundation for an innovative, statistically based approach to drug classification decisions by DREs.
Porath-Waller
Amy J
AJ
Canadian Centre on Substance Abuse, Ottawa, Ontario K1P 5E7, Canada. aporath-waller@ccsa.ca
Beirness
Douglas J
DJ
Beasley
Erin E
EE
D001334:Automobile Driving / Q000331:legislation & jurisprudence*; D002170:Canada; D002188:Cannabis; D000697:Central Nervous System Stimulants; D006801:Humans; D035846:Law Enforcement; D016015:Logistic Models; D015999:Multivariate Analysis; D009294:Narcotics; D015813:Substance Abuse Detection / Q000379:methods*; D019966:Substance-Related Disorders / Q000175:diagnosis*
D000697:Central Nervous System Stimulants; D009294:Narcotics