The Study of Possible Influences of Licit and Illicit Drugs on Driver Behavior

Berg, S. William; Fryback, John T.; Goldenbaum, Donald M.; Joscelyn, Kent B.; Maickel, Roger P.; Potter, William Z.; Zabik, Joseph; Jones, Ralph K. · 1971 · ROSA P / United States. National Highway Traffic Safety Administration

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Summary

This 1971 study, conducted by the Institute for Research in Public Safety at Indiana University for the National Highway Traffic Safety Administration, investigated the relationship between psychotropic drug usage and motor vehicle accidents among college students. The research was motivated by the increasing prevalence of both licit (e.g., antihistamines, tranquilizers) and illicit (e.g., marijuana, amphetamines) drug use among young adults, a demographic with high accident rates, and a lack of scientific evidence linking drug use to driving impairment. The study aimed to determine if drug presence in the blood or drug usage patterns correlated with accident involvement. The methodology employed a comparative design involving an experimental group (E) of 24 college students who had just been involved in motor vehicle accidents and three control groups (C) totaling 54 students who were not involved in accidents but were selected to approximate the general student driving population. Data collection included blood serum analysis using thin-layer chromatography to detect psychotropic drugs and comprehensive interviews assessing driving history, drug usage patterns, and psychological traits using instruments such as the Michigan Alcoholism Screening Test, the Impulse Expression Scale, and the Personality Research Form. Statistical analyses, including chi-square tests, analysis of variance, and stepwise regression, were used to compare drug presence between groups and identify predictors of accident history. The results indicated no statistically significant difference in the incidence of drug presence in the blood between the accident-involved group and the control groups. Specifically, two of 24 E-group subjects and five of 54 C-group subjects tested positive for psychotropic drugs, with the probability of equal frequency exceeding 0.75. Furthermore, multivariate analysis revealed that drug usage variables—whether licit or illicit—were statistically unrelated to the number of traffic accidents or moving violations incurred by subjects. In contrast, driving history, particularly the number of prior moving violations, was the strongest predictor of future accidents, with a pairwise correlation coefficient of 0.59. Psychological and demographic factors also showed stronger relationships to accident rates than drug use. The study concluded that, within this sample, there was no evidence that drug usage played a significant causal role in motor vehicle accidents compared to other factors. The authors recommended that a large-scale survey be conducted to develop statistically reliable data on the drug-impaired driver problem, as the current pilot study’s sample size was insufficient for broad generalizations. The findings suggest that driving history and behavioral factors are more critical indicators of accident risk than the mere presence of drugs in the bloodstream.

Key finding

Drug usage was statistically unrelated to the number of traffic accidents subjects had incurred in their driving lifetimes, and subjects involved in accidents did not have a greater proportion of positive blood drug readings than the control group.

Methodology

mixed_methods

Sample size: 107

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• illicit drugs
• polydrug
• cannabis
• prescription meds
• sex gender
• dbq psychometrics

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: observational prevalence, behavioral performance data
• Methodological Resource: validation psychometrics