US Department 

0 

d lazportahon 

Nc3mkx r Trafft Safety 

Admkdshotlon 

DOT HS 808 078 November 1993 

Final Report 

Marijuana and Actual

Driving Performance

This document is availalbe to the public from the Nftional Technical Information Service, Springfield, Virginia 22161 
This publication is distributed by the U.S. Department of 

Transportation, National Highway Traffic Safety Administration, in the interest of information exchange. The opinions, 

fmdings and conclusions expressed in this publication are those 

of the author(s) and not necessarily those of the Department 

of Transportation or the National Highway Traffic Safety 

Administration. The United States Government assumes no 

liability for its contents or use thereof. If trade or manufacturers' name or products are mentioned, it is because they are 

considered essential to the object of the publication and should 

not be construed as an endorsement. The United States 

Government does not endorse products or manufacturers. 
Technical Report Documentation Page 

Report No. 2. Government Accession No. 3. Recipient's Catalog No. 

DOT HS 808 078 

I. Title and Subtitle Report Date 

Marijuana and actual driving performance November 1993

Performing Organization Code 

8. Performing Organization Report No. 

7.

Author's) 

IGVG 92-15 Hindrik W.J. Robbe and James F. O'Hanlon 

9.

Performing Organization Name and Address 10. Work Unit No. (TRAIS) 

Institute for Human Psych opharmacology 

University of Limburg

11. Contract or Grant No. 

Abtstraat 2A

DTNH22-89-X-07722 

6211 LS Maastricht - The Netherlands13. Type of Report and Period Covered 

12.

Sponsoring Agency Name and Address Final Report (11/89-11/93) 

U.S. Department of Transportation 

National Highway Traffic Safety Administration 

14. 400 Seventh Street, S.W. Sponsoring Agency Code 

Washington. DC 20590 

15.

Supplementary Notes 

16.

Abstract 

This report concerns the effects of marijuana smoking on actual driving performance. It presents the results of one 

pilot and three actual driving studies. The pilot study's major purpose was to establish the THC dose current marijuana 

users smoke to achieve their desired "high". From these results it was decided that the maximum THC dose for 

subsequent driving studies would be 300 μg/kg. The first driving study was conducted on a closed section of a primary 

highway. After smoking marijuana delivering THC doses of 0, 100, 200, and 300 pg kg, subjects drove a Far while 

maintaining a constant speed and lateral position. This study was replicated with a new group of subjects, but now in 

the presence of other traffic. In addition, a car following test was executed. The third driving study compared the 

effects of a modest dose of THC (100 p.g/kg) and alcohol (BAC of 0.04 g%) on city driving performance. This program 

of research has shown that marijuana, when taken alone, produces a moderate degree of driving impairment which 

is related to the consumed THC dose. The impairment manifests itself mainly in the ability to maintain a steady lateral 

position on the road, but its magnitude is not exceptional in comparison with changes produced by many medicinal 

drugs and alcohol. Drivers under the influence of marijuana retain insight in their performance and will compensate 

where they can, for example, by slowing down or increasing effort. As a consequence, THC's adverse effects on driving 

performance appear relatively small. 

17.

Key Words 18. Distribution Statement 

Marijuana 

Actual Driving Performance Unlimited 

THC 

Alcohol 

T9. Security Classif. (of this report) 20. Security Clossil. (of this page) 21. No. of Pages 22. Price 

Unclassified

Unclassified 

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized 
CONTENTS

List of Abbreviations i . .................................... VII

Aclmowledgements .......................................... IX

Executive Summary ..................... . ............... .XI

Chapter 1 Marijuana and Driving: A Review .......................... 1

The Drug and Its Pharmacological Properties .......................... 'I

Prevalence of Marijuana Use ............ .......... :........... 3

Marijuana and Traffic Safety .................................... 3

Epidemiological Research ..... . ........... .... _ ............ . 3

Marijuana's Effects upon Driving Simulator Performance .............. 5

Marijuana's Effects upon Actual Driving Performance ................. 6

General Conclusion ....................................... 9

Chapter 2 General Methods ..................................... 11

Description of a 4-Study Program ................................ 11

Subjects ................................................. 12

Compliance with Ethical and Legal Standards ......................... 14

Screening for the Presence of Other Illicit Drugs and Alcohol ............... 14

Blood Sampling and Quantitative Analyses ........................... 15

Chapter 3 Pilot Study to Select THC Doses ............... ; 17

Introduction ...... ........ ..............................17

Methods ................................................ 17

Subjects ........ .................................... .. 17­

Smoking Procedures ...................................... 18

Measurements ........ .......... ..................... 18

Data Analysis .......................................... 19

Results ............... ...............................21

Consumed THC ....................... ... ..... ......21

Plasma Concentrations of the Drug ...... ... ................. 21

Perceived "high" ........................................ 22

Willingness to Drive ...................................... 23

Perceived Alertness, Contentedness and Calmness .................... 24

Critical Tracking Test ................ ........... ... ... 24

Hand Steadiness Test ...................................... 26

Heart Rate ........................................... 26

Intra-Subject Relations between Variables ......................... 26

Inter-Subject Relations between Variables ......................... 28

Discussion ........................ .......... .......... 28
Chapter 4 Marijuana and Driving on a Restricted Highway ................ 31

Introduction ... . .......................................... 31

Methods ................................................. 31

Subjects ..............................................31

Design, Doses and Administration .............................. 31

Testing Procedures ....................................... 32

Driving Test ....................... ........: ........... 32

Questionnaires .......................................... 33

Laboratory Tests ........................................ 33

Physiological Assessments ................................... 33

Blood Sampling ....................................... . . 34

Data Analysis .......................................... 34

Results ............. ... .....34

Plasma Concentrations of the Drug ..... ................. . ..... 34

Perceived "high" ....................................... 35

Driving Performance ...................................... 36

Perceived Driving Quality and Effort ............................ 37

Willingness to Drive ...................................... 39

Perceived Alertness, Contentedness and Calmness .................... 39

Critical Tracking Test ...................................... 40

Hand Steadiness Test ........................... .... 40

Heart Rate and Blood Pressure .................... . ............ 41

Intra-Subject Relations between Variables ...... :........... ......... 42

Inter-Subject Relations between Variables ......................... 42

Discussion ............................................... 44

;T r 

Chapter 5 Marijuana and Driving on a Normal Highway in Traffic ........... 49

Introduction .................................... ........49

Methods ..............................................:.49

Subjects ..............................................49

Design, Doses and Administration .............................. 50

Testing Procedures ........................................ 50

Driving Tests ...................... ................... 51

Questionnaires ........................................... 53

Laboratory Tests ...................................... 53

Physiological Assessments ..................................... 54

Blood Sampling ............... ' ........ ................ 54

Data Analysis ............................................ 55

Results ............................................. .56

Test-Retest Correlations and Consistency of Performance :............... 56

Plasma Concentrations of the Drug ........................... 57'

Perceived "high" .......................... 58

Driving Performance in the Standard Driving Test .................... 59

Driving Performance in the Car Following Test ..................... 61

Willingness to Drive ...................................... 64

Perceived Alertness, Contentedness and Calmness .................... 65
Critical Tracking Test ................. '..................... 66

Hand Steadiness Test ... ...... .... . ..................... 67

Body Sway .................... '........................ 67

Heart Rate ....... ................................... 68

Intra-Subject Relations between Variables ......................... 70

Inter-Subject Relations between Variables ......................... 70

Discussion ...................... .... .................. 72

Chapter 6 Marijuana, Alcohol and Urban City Driving ................... 77

Introduction ............................................. 77

Methods ..... :...................................... :....79

Subjects ....................................... ..... 79

Design, Doses and Administration ........................... .. .79

Testing Procedures ..... ....... ... ....................... 80

Driving Test and Scoring Methods ........ ..... .......:... . . 81

Questionnaires ............................................ 84

Laboratory Tests ......................................... 85

Blood Sampling ...............................

.......................... 85

Data Analysis ............................................ 85

Results ...........................

.....................

Plasma Concentrations of the Drugs ............................. 86

Perceived "high" and "drunkness............................... 86

Driving Performance Measured by the Molecular Approach ........... :.. 87

Driving Performance Measured by the Molar Approach ................ 87

Perceived Driving Quality and Effort to Accomplish the Test ............. 89

Willingness to Drive ...................................... 90

Perceived Alertness, Contentedness and Calmness .................... 90

Hand Steadiness Test ... -....... ......................... 90

Time Perception Test ......... . ............................. 92

Inter-Subject Relations between Variables ......................... 92

Discussion . ......................... . ..................... 93

Chapter 7 General Discussion, Conclusions and Recommendations ............. 97

Introduction ............................................. 97

THC Doses ......................... ...................98

The Driving Tests ........................................ . . 100

Effects of THC on Driving Performance ......:........ •.......... 102

Drug Plasma Concentrations and Driving Performance ...:............... 107

Conclusions ..................................... _ .:.... 108

Recommendations for Future Research ............................ 109

• References ............................................... 111

Appendix A. Questionnaires .................................... 117

Appendix B. Driving Proficiency Tests ............................. 123
LIST OF ABBREVIATIONS 

11-OH-THC 11-Hydroxy-A9-Tetrahydrocannabinol 

ANWB Algemene Nederlandse Wielrijders Bond (Royal Dutch Tourist Association) 

BAC Blood Alcohol Concentration 

CS-C Curve Surface in Body Sway Test with Eyes Closed 

CS-O Curve Surface in Body Sway Test with Eyes Open 

CTT Critical Tracking Test 

CV-H 'Coefficient of Variation (SDIM) of Headway 

CV-IBI Coefficient of Variation (SD/M) of Interbeat Interval Times 

DOT Department of Transportation 

ECG Electrocardiogram 

EtOH Ethanol 

IBI Interbeat Interval Time 

MANOVA Multivariate Analysis of Variance 

NHTSA National Highway Traffic Safety Administration 

NIDA National Institute on Drug Abuse 

PWR-HR Relative Amplitude in the Power Density Spectrum of Heart Rate between the 

Frequencies of .01and .14 Hz 

RT Reaction Time 

SD Standard Deviation 

SDLP Standard Deviation of Lateral Position 

SDSP Standard Deviation of Speed 

SDST Standard Deviation of Steering Wheel Angle 

SE Standard Error (i.e. SD divided by the Square Root of the Number .of Observations) 

SED Standard Error of the Mean Difference 

SP Mean Speed 

THC W-Tetrahydrocannabinol 

THC-COOH 11-Nor-b9-Tetrahydrocannabinol-9-Carboxylic Acid 

VU
ACKNOWLEDGEMENTS

This research program was sponsored by the Office of Program Development and -Evaluation, 

National Highway Traffic Safety Administration (NHTSA), of the U.S. Department of 

Transportation (DOT). We are grateful to T.E. Alderson for initiating the program and to 

J. Frank for sharing the duties of monitoring it. The Road Safety Department of the Dutch 

Ministry of Transport, Public Works and Watermanagement functioned as an intermediary 

regarding technical and financial affairs between DOT and the official contractor, the University 

of Limburg. Furthermore, the alcohol part of the city driving study (Chapter 6) was sponsored 

by the Dutch Ministry. We thank Drs. J.T. Busstra for monitoring the project locally. ­

Before the program started an Independent Advisory Committee was formed whose function 

was to ensure that the program proceeded in accordance with all medical and legal safety 

standards. This committee comprised: Mr. J. Oosterhof, Assistant District Attorney and 

J. Bardoul, Municipal Traffic Attorney, for the City of Maastricht; Dr. H.C. Milius, psychiatrist 

and member of the University's Medical Ethics Committee; and Drs. J. Tjoeng, Dutch Regional 

Inspector for Public Health (Drugs). ­

Approvals for individual studies were separately obtained from the University's Medical 

Ethics Committee. A permit for obtaining, storing and administering marijuana was obtained 

from the Dutch Drug Enforcement Administration. 

We are very grateful to'P.G.S.M. Geurts, Chief Traffic Administrator for the Dutch Federal 

Police, District Limburg, Ing. F.V.J.M. Schepers, Head, Highway Administration South, 

Department Traffic and' Transportation, and Ing. H.P.A. Thegels, Head, Technical Services, 

Department of Public Works, District Limburg for their cooperation and readiness to close part 

of a primary highway in Southern Limburg for the first driving study. We thank all those 

involved in closing and opening the highway every evening during the study. 

Plasma samples were analyzed by Prof. Dr. M.R. Moller - and his colleagues from the 

Institute of Legal Medicine from the Department of Forensic Toxicology, University of 

Homburg, Germany. We thank them very much for their important collaboration. 

Medical, technical and administrative support was obtained from our respective colleagues, 

M. van Boxtel, MD, A. van Houte, MD, Ing. M. Hendrickx, Mrs. V. van der Varst and Mrs. 

S. Aldenhoff. We are also grateful to all those who assisted the program manager during data 

collection: B. Bekkers, L. de Beukelaar, Ph. Bouwmeester, A. Casteleyn, J. Dorr, R. van 

Drumpt, A. Gresnigt, M. Heeres, A. van Houte, MD, R. Koppers, C. van Leeuwen, MD, 

B. Liederkerken, W. Linders, I. Movig, J. Van Oostrum, A. Rademaker and M. Uiterwijk. 

Mr. H. Brauers, our licensed driving instructor, was chiefly responsible for safety during 

driving tests. We deeply respect the care with which he and his colleagues, Mr. and Mrs. Godt, 

F. Herzberg, and W. Jennissen, ensured the subjects' safety throughout the entire program. 

Finally, we gratefully appreciate all of the effort devoted by the subjects, more than seventy 

in total, during their participation in the study. 
EXECUTIVE SUMMARY

This report concerns the effects of marijuana smoking on actual driving performance. It presents 

the results of one pilot and three actual driving studies which were conducted between april 1990 

and march 1992. The program was funded by the U.S. National Highway Traffic Safety Administration (NHTSA), with the exception of the alcohol part of the city driving study which was 

sponsored by the Dutch Road Safety Directorate of the Dutch Ministry of Transport and Public 

Works.. The project was conducted by the Institute for Drugs, Safety and Behavior of the 

University of Limburg, Maastricht, The Netherlands. The major objectives of the program were 

to determine the dose-response relationship between Y-tetrahydrocannabinol (THC), marijuana's 

main constituent, and objectively and subjectively measured aspects of real-world driving; and, 

to determine whether it is possible to correlate driving performance impairment with plasma concentrations of the drug or a metabolite. A variety of driving tests were employed, including: 

maintenance of a constant speed and lateral position during uninterrupted highway travel, 

following a leading car with varying speed on a highway, and city driving. The purpose of 

applying different tests was to determine whether similar changes in performance under the 

influence of THC occur in all, thereby indicating a general drug effect on driving ability. 

Chapter One provides background information about the drug, its pharmacological 

properties, the prevalence of its use, and a review of marijuana smoking and traffic safety. 

THC's effects on the ability of drivers to operate safely in traffic situations have traditionally 

been determined in two ways: from -epidemiological surveys of users' involvement in traffic 

accidents and from empirical studies to measure the drug's influence on skills related to driving, 

or driving itself. Epidemiology shows that people drive after marijuana use and that drivers 

involved in accidents often show the drug's presence. The results are, however, inconclusive 

because of the high proportion of cases which also involve alcohol use and the lack of proper 

control groups. Therefore, the extent marijuana contributes to traffic accident causality remains 

obscure. Results from driving simulator and closed-course tests show that THC in single inhaled 

doses up to about 250 tig/kg has relatively minor effects on. driving performance, certainly less 

.than blood alcohol concentrations (BACs) in the range of 0.08-0.10 g%. 

Chapter Two describes the studies of the program and certain procedures that were common 

to all. These were subject recruiting, compliance with ethical and legal standards, screening for 

the presence of other illicit drugs and alcohol, blood sampling procedures and quantitative 

analyses. Subjects in all studies were recreational users of cannabis, i.e.-smoking marijuana or 

hashish more than once a month but not daily. They were all healthy, between 21 and 40 years 

of age, had normal weight and binocular acuity, and were licensed to drive an automobile. 

Subjects were accompanied in every driving test by an licensed driving instructor, experienced 

in supervising subjects who operated under the influence of medicinal drugs in previous studies. 

Redundant control system in the test vehicle was available for controlling the car if emergency 

situations should arise. Marijuana and placebo marijuana cigarettes were supplied by the U.S. 

National Institute on Drug Abuse (NIDA). 

Chapter Three presents the results of the pilot study. It was conducted in a hospital under 

strict medical supervision to identify THC doses that recreational marijuana users were likely 

to consume before driving. Twenty-four subjects, twelve males and twelve females, participated. 
They were allowed to smoke part or all of the THC. content in three cigarettes until achieving 

the desired psychological effect. Cigarettes were smoked through a plastic holder in a manner 

determined by the subjects. The only requirement was to smoke continuously for a period not 

exceeding 15 minutes. When subjects voluntarily stopped smoking, cigarettes were carefully 

extinguished and retained for subsequent gravimetric estimation of THC consumed. Six subjects 

consumed one cigarette, thirteen smoked two and four smoked three. The average amount of 

THC consumed was 20.8 mg, after adjustment for body weight, 308 μg/kg. There was no 

significant difference between males and females with respect to the weight adjusted preferred 

dose. It was decided that the maximum dose for subsequent driving studies would be 300 μg/kg. 

This is considerably higher than doses that have usually been administered to subjects in 

experimental studies (typically, 100-200 μg/kg THC). 

The study provided the opportunity for obtaining valuable information about THC's pharmacokinetics. and its pharmacodynamic effects after marijuana smoking: Blood samples were 

repeatedly taken for measuring plasma concentrations of THC and its major inactive metabolite, 

THC-COOH. The subjects repeatedly performed certain simple laboratory tests, estimated their 

levels of intoxication and indicated their willingness to drive under several specified conditions 

of urgency. Heart rate was measured at these fumes. The secondary purpose of the pilot study 

was that of specifying relationships between [THCJ and [THC-COOH] with changes in- the other 

physiological, performance or subjective variables. Other results from the pilot study showed 

that perceived "high" and heart rate are very sensitive measures of marijuana intoxication which 

confirms prior findings. Impairments in laboratory tests performance were found at the time of 

peak subjective feelings but generally, objective impairment dissipated more rapidly than the 

feelings themselves. 

The first driving study, described in Chapter Four, was conducted on a highway closed to 

other traffic. One objective. of the study was to determine whether it would be safe to repeat the 

study on a normal highway in the presence of other traffic. The second objective was to define 

the dose-effect relationship between inhaled THC dose and driving performance. The same 

twelve men and twelve women who participated in the pilot study served again as the subjects. 

They were treated on separate occasions with THC doses of 0, 100, 200, 300 μg/kg. Treatments 

were administered double-blind and in a counterbalanced order. On each occasion, subjects 

performed a road tracking test beginning 40 minutes after initiation of smoking and repeated one 

hour later. The test, developed and standardized by O'Hanlon et al. (1982, 1986), involved 

maintaining a constant speed at 90 km/h (56 mph) and a steady lateral position between the 

delineated boundaries of the traffic lane. Subjects drove 22 km (13.6 mi) on a primary highway 

and were accompanied by a licensed -driving instructor. The latter was charged with 

responsibility for ensuring safety at all times and was able to intervene, if necessary, using 

redundant vehicular controls. The primary dependent variable was the standard deviation of 

lateral position (SDLP), which has been shown to be both highly reliable and very sensitive to 

the influence of sedative drugs and alcohol. Other dependent variables were mean speed,. and 

standard deviation of speed and steering wheel angle. Blood samples were taken prior to each 

driving test; and, performance in critical tracking and hand steadiness tests, heart rate, and blood 

pressure were measured after its, termination. Questionnaires were repeatedly administered to 

estimate the "high" and other, subjective feelings. 

All subjects were willing and able to finish the driving tests without great difficulty. The 

study demonstrated that marijuana impairs driving performance as measured by an increase in 

SDLP; all three THC doses significantly affected SDLP relative to placebo. The driving 

-7HI­
performance decrement after smoking marijuana persisted almost undiminished for two hours 

after smoking while drug plasma concentrations, perceived "high" and heart rate elevation had 

decreased. Marijuana's effects on SDLP were compared to those of alcohol obtained in a very 

similar study by Louwerens er al. (1985, 1987). It appeared that THC's effects on SDLP were 

equivalent to those associated with BACs in the range of 0.03-0.07 g%. Other driving 

performance measures were not significantly affected by THC. Intersubject correlations between 

plasma concentrations of the drug and driving performance after every dose were essentially nil. 

Thus, driving impairment cannot be predicted 'by prevailing plasma concentrations of THC or 

THC-COOH. Driving impairment was also not related to performance in the laboratory tests. 

Both the observed degree of driving impairment, and what subjects said`-and did, indicated that 

normal safeguards would be sufficient for ensuring safety in further testing. Hence, the final 

conclusion was to repeat this study on a normal highway in the presence of other traffic. 

The second driving study, described in Chapter Five, was conducted to come a step closer 

to driving reality than its predecessor., Driving tests were now conducted on a highway in the 

presence of other traffic. The major objective of this study was to confirm the relationship 

between inhaled THC dose and lateral position variability in the context of a standard road 

tracking test. A secondary objective was to measure performance in another actual driving test, 

i.e.-car following. The third objective was to continue efforts to correlate plasma concentrations 

of THC and THC-COOH with driving performance impairment as measured in both tests. 

A new group of sixteen subjects, equally comprised of men and-women, participated in this 

study. A conservative approach was chosen in designing the present study in order to satisfy the 

strictest safety requirements. That is, the study was conducted according to an ascending dose 

series design where both active drug and placebo conditions were administered, double-blind, 

at each- of three THC dose levels. THC doses were the same as those used in the previous study, 

namely 100, 200, and 300 ug/kg. Cigarettes appeared identical at each level of treatment 

conditions and were smoked through a plastic holder in a fashion determined by the subject 

within a time limit of 10 minutes. If any subject would have reacted in an unacceptable manner 

to a lower. dose, he/she would not have been permitted to receive'a higher dose. 

Two subjects at a time commenced smoking. Thirty minutes after onset of smoking the 

-subjects performed i battery of laboratory tests (tracking, hand steadiness and body sway), 

yielded a blood sample, and rated their "high" and other subjective feelings. They were then 

transported to a primary highway were the driving tests were performed. Two instrumented 

vehicles were employed. The subjects performed the car following test on a 16 km (9.9 mi) 

segment of the highway for about twelve minutes. After conclusion of the car following test, 

both subjects then commenced the road tracking test in separate 'instrumented vehicles. The 

highway was the same as for the car following. test. Subjects drove 64 km (40 mi) without 

stopping in about 50 minutes. At the conclusion of this test, both subjects participated again in 

the car following test. Subjects were then transported back to the laboratory where they rated 

subjective feelings, yielded a blood sample, and repeated the test battery. The subjects' heart rate 

was registered continuously during both driving tests. 

The road tracking test was the same as in the previous study except for its duration and the 

presence of other traffic. Subjects were instructed to maintain a constant speed of 95 km/h 

(59 mph) and a steady lateral position between lane boundaries in the right traffic lane. They 

were allowed to deviate from this only if it would become necessary to pass a slower vehicle 

in the same lane. Data from the standard test were analyzed to yield the same performance 

measures as in the previous study; i.e. SDLP', mean and standard deviation of speed, and 
standard deviation of steering wheel angle. The car following test measures drivers' ability to 

perceive changes in a preceding vehicle's speed and to react in a manner maintaining a constant 

headway. It began as the preceding and the following vehicle, respectively driven by one of the 

driving instructors and the subject, operated in tandem on the slower traffic lane while travelling 

at a speed of 100 km/h (62 mph). The subject was instructed to maintain a 50, m (164 ft) 

headway however the preceding vehicle's speed might vary. After driving in this manner for 

about one minute, the operator of the preceding vehicle released the accelerator pedal allowing 

its speed to fall to 80 km/h (50 mph). Immediately thereafter, the operator of the preceding 

vehicle accelerated to 100 km/h (62 mph). The duration of one deceleration and acceleration 

maneuver was approximately 50 seconds and six to eight, depending upon traffic density, were 

executed during one -test. The subject's average reaction time to the movements of the leading 

vehicle, mean headway and coefficient of variation of headway during maneuvers were taken 

as the dependent variables from this. 

All subjects were able to complete the series without suffering any untoward reaction while 

driving. Road tracking performance in the standard test was impaired in a dose-related manner 

by THC and confirmed the results obtained in the previous closed highway study. The 100 μg/kg 

dose produced a slight elevation in mean SDLP, albeit nearly significant. The 200 μg/kg dose 

produced a significant elevation, of dubious practical relevance. The 300 gg/kg dose produced 

a highly significant elevation which may be viewed as practically relevant but unexceptional in 

comparison with similarly measured effects of many medicinal drugs. Following marijuana 

smoking subjects drove with an average speed that was only slightly lower than after placebo 

and very close to the prescribed level. 

In the car following test, subjects maintained a headway of 45-50 m (148-164 ft) .while 

driving in the successive placebo conditions. They lengthened mean headway by 8, 6 and 2 m 

(26.2, 19.7 and 6.6 ft) in -the corresponding THC conditions after 100, 200 and 300 μg/kg, 

respectively. The initially large drug-placebo difference and its subsequent decline is a surprising 

result. Our explanation for this observation is that the subjects' caution was greatest the first 

time they undertook the test under the influence of THC and progressively less thereafter. 

Reaction time to changes in the preceding vehicle's speed increased following THC treatment, 

relative-to placebo. -The administered THC dose was inversely related to the change in reaction 

time, as it was to headway. However, increased reaction times were partly due to -longer 

headway. Statistical adjustment for this confounding resulted in smaller and non-significant 

increases in reaction time following marijuana treatment, the greatest impairment (0.32 s) being 

observed in the first test following the lowest THC dose. Headway variability followed a similar 

pattern as mean headway and reaction time; the greatest impairment was found following the 

lowest dose. 

An important practical objective of this study was to determine whether degrees of driving 

impairment can be accurately predicted from either measured concentrations of THC in plasma 

or performance measured in potential roadside "sobriety" tests of tracking ability or hand and 

posture stability. The results, like many reported before, indicate that none of these measures 

accurately predicts changes in actual driving performance under the influence of THC. 

The program then proceeded into the third driving study, presented in Chapter Six, which 

involved tests conducted in high-density urban traffic. There were logical and safety reasons for 

restricting the THC dose to 100 ug/kg. It was given to a group of regular cannabis users, along 

with placebo. For comparative purposes another group of regular alcohol users were treated with 

a modest dose of their preferred recreational drug, and again placebo, before undertaking the 
same city driving test. Two groups of sixteen new subjects apiece, equally comprised of men 

and women, participated. Subjects in.the alcohol group were regular users of alcohol but not 

marijuana. Both groups were treated on separate occasions with active drug and placebo. Active 

marijuana was administered to deliver 100 μg/kg THC. The driving test commenced 30 minutes 

after smoking. The alcohol dose was chosen to yield a BAC approaching 0.05 g% when the 

driving test commenced 45 minutes after onset of drinking. Active drug and placebo conditions 

were administered double-blind and in a counterbalanced order in each group. 

Driving tests were conducted in daylight over a constant 17.5 km (10.9 mi) route within the 

city limits of Maastricht. Subjects drove their placebo and active drug rides through heavy, 

medium and low density traffic on the same day of the week, and at the same time of day. Two 

scoring methods were employed in the present study. The first, "molar" approach, required the 

driving instructor acting as the safety controller during the tests to retrospectively rate the 

driver's performance using a standard scale. The second, a more "molecular" approach, involved 

the employment of a specially trained observer who applied simple and strict criteria for 

recording when the driver made or failed to. make each in a series of observable responses at 

predetermined points along a chosen route. Immediately prior to and following the driving tests 

subjects performed hand steadiness and time perception tests, yielded a blood sample, and were 

administered the same subjective questionnaires used in the previous studies. 

The study showed that a modest dose of alcohol (BAC=0.04 g%) produced a significant 

impairment in city driving as measured by the molar approach, relative to placebo. More 

specifically, alcohol impaired vehicle handling and traffic maneuvers.. Marijuana, administered 

in a dose of 100,ug/kg . THC, on the other hand, did not significantly change mean driving 

performance as measured by this approach. Neither alcohol nor marijuana significantly affected 

driving performance measures obtained by the molecular approach indicating that it may be 

relatively, insensitive to drug-induced changes. 

Driving quality as rated by the subjects contrasted with observer ratings. Alcohol impaired 

driving performance according to the driving instructor but subjects did not perceive it; 

marijuana did not impair driving performance but the subjects themselves perceived their driving 

performance as such. Both groups reported about .the same amount of effort in accomplishing 

the driving test following placebo. Yet only subjects in the marijuana group reported 

significantly higher levels of invested effort following the active drug. Thus, there was evidence 

that subjects in the marijuana group were not only aware of their intoxicated condition but were 

also attempting to compensate for it. These seem to be important findings. They support both 

the common belief that drivers become overconfident after drinking alcohol and investigators' 

suspicions that they become more cautious and self-critical after consuming low THC doses by 

smoking marijuana. 

The laboratory performance tests also discriminated between the drugs' effects. Hand 

steadiness was impaired following THC and improved following alcohol, relative to placebo. 

The difference between the drugs' effects was significant, both before and after the driving test. 

Impairment after THC was about as much as that produced by the same dose in the previous 

study, indicating equivalent sensitivities of the present and previous groups. Production of time 

intervals was not affected by alcohol, but THC significantly shortened interval production, 

relative to placebo. 

Drug plasma concentrations were neither related to absolute driving performance scores nor 

to the changes that occurred from placebo to. drug conditions. With respect to THC, these results 

xv 
confirm the findings in previous studies. They are somewhat surprising for alcohol but may be 

due to the restricted range of ethanol.concentrations in the plasma of different subjects. 

Chapter Seven concludes the report with a general discussion of the results of the program 

and ends with a list of conclusions and recommendations. It starts with a discussion of the THC 

dose which marijuana users actually prefer for achieving their desired "high". Several questions 

are raised and discussed, such as: how do people regulate their THC consumption, what role 

plays familiarization with the drug, and what would the preferred dose have been if marijuana 

of much higher potency were smoked. The discussion then continues with a description of the 

differences between the driving tests in terms of the type of information processing each 

requires, automatic vs controlled, and the relevance of each to traffic safety. 

Attention-is further focussed on the effects of THC on driving performance. The results of 

the studies corroborate those of previous driving simulator and closed-course tests by indicating. 

that THC in single inhaled doses up to 30Q μg/kg has significant, yet not dramatic, dose-related 

impairing effects on driving performance. Standard deviation of lateral position in the road 

tracking test was the most sensitive measure for revealing THC's adverse effects. This is 

because road tracking is primarily controlled by an automatic information processing system 

which operates outside of conscious control. The process is relatively impervious to environmental changes but highly vulnerable to internal factors that retard the flow of information 

through the system. THC and many other drugs are among these factors. When they interfere 

with the process that restricts SDLP, there is little the afflicted individual can do by way of 

compensation to restore the situation. Car following and, to a greater extent, city driving 

performance depend more on controlled information processing and are therefore more 

accessible for compensatory mechanisms that reduce the decrements or abolish them entirely. 

It appears that performance is more affected by THC in laboratory than actual driving tests. 

Several reasons that may account for the apparent discrepancy are discussed. First, laboratory 

tests. are experimentally controlled by drastic simplification which may -affect a subject's 

motivation to perform the test by making it appear "unreal". Secondly, the restriction of 

response options in laboratory performance tests leave fewer possibilities for compensation. -In 

real life, drivers always apply numerous skills in parallel and series. Should one become 

deficient, they are often able to compensate in a number of ways to achieve a satisfactory level 

of proficiency. Finally, after learning to drive, subjects possess such skills in abundance and one 

can only demonstrate how they vary with drug effects in the real task or a very close 

approximation thereof. Profound drug impairment constituting an obvious traffic safety hazard 

could as easily be demonstrated in a laboratory performance test as anywhere else. But THC is 

not a profoundly impairing drug. It does affect automatic information processing, even after low 

doses, but not to any great extent after high doses. It apparently affects- controlled - information 

processing in a variety of laboratory tests, but not to the extent which is beyond the individual's 

ability to control when he is motivated and permitted to do so in real, driving. . 

Marijuana's effects on driving performance were compared to those of many other drugs. 

It was concluded that THC's effects after doses up to 300 μg/kg never exceed alcohol's at BACs 

of 0.08 g%; and, were in no way unusual compared to many medicinal drugs'. Yet THC's 

effects differ qualitatively from many other drugs, especially alcohol. Evidence from the present 

and previous studies strongly suggests that alcohol encourages risky driving whereas THC 

encourages greater caution, at least in experiments. Another way THC seems to differ 

qualitatively from many other drugs is that the former's users seem better able to compensate 

for its adverse effects while driving under the influence. Still one can easily imagine situations 

-XVI­
where the influence of marijuana smoking might have an exceedingly dangerous effect; i.e., 

emergency situations which put high demands on the driver's information processing capacity, 

prolonged monotonous driving, and after THC has been taken with other drugs, especially 

alcohol. 

Finally, the relation between driving impairment following marijuana smoking and plasma 

concentrations of THC and THC-COOH is discussed. It appears not possible to conclude 

anything about a driver's impairment on the basis of his/her plasma concentrations of THC and 

THC-COOH determined in a single sample. 

-
CHAPTER 1 - MARIJUANA AND DRIVING: A REVIEW

Marijuana's effects on the ability of drivers to operate safely in traffic situations have 

traditionally been determined in two ways: from epidemiological surveys of users' involvement 

in traffic accidents and from empirical studies to measure the drug's influence on skills related 

to driving and driving itself. A review of results obtained from both approaches, partly relying 

upon previously published reviews, is provided. Its purpose is providing the reader a broader 

context in which the present report should be viewed. First, however, the drug • and its 

pharmacological properties, and the prevalence of its use, will be discussed. 

THE DRUG AND ITS PHARMACOLOGICAL PROPERTIES 

Marijuana is the common name for any part of the hemp plant, cannabis sativa, or extracts 

which possess characteristic psychoactive properties in man. The plant contains more than 400 

compounds. More than 60, the cannabinoids, are-specific to that plant. The majority of the 

cannabinoid products are pharmacologically inactive. The major active product and that 

primarily responsible for the physiological and psychological effects of marijuana smoking is 

A9-tetrahydrocannabinol (THC). 

Besides being used as an intoxicant to produce a psychological "high" or euphoria, marijuana 

has been used as a sedative and analgesic (Maykut, 1985) but also, in Eastern countries, for 

relieving fatigue and stimulating appetite (Murray, 1985). It reliably produces both tachycardia 

and marked conjunctivitis. The mechanisms by which THC produces these physiological effects 

or the psychological effects sought by its users are still poorly understood (Jaffe, 1990). As a 

therapeutic agent, marijuana has been successfully applied in some cases of glaucoma (Reiman, 

1982) and anorexia nervosa (Zinberg, 1979). The most promising potential clinical use of 

marijuana is in the treatment of nausea and vomiting caused by cancer chemotherapy (Relman, 

1982; Vinciguerra et al., 1988; Randall, 1990). Synthetically formulated THC was approved in 

1985 by the U.S. Food and Drug_ Administration (FDA) for use in the treatment of emesis, and 

is now marketed under the trade name Marinol (Unimed, Somerville, NJ). Patients suffering 

from AIDS may also benefit from marijuana because of its antiemetic and appetite stimulating 

effects. Yet there are also reports of adverse health effects of marijuana smoking on fetal 

growth, sperm cell motility, female reproductive hormone function, immunological system, 

cardiopulmonary system and central nervous system (Jaffe, 1990; Mendelson; 1987; Maykut, 

1985). 

The THC content in marijuana cigarettes varies in the United States from about 0.5.% to 11 % 

(Jaffe, 1990). In The Netherlands, seized hemp material usually contains about 10% THC, 

though it may range from 5 to 15% and, in exceptional cases, to 25% (Dutch Forensic 

Laboratory, personal communication). The inhaled dose in marijuana smoke varies also widely, 

depending upon the smoking technique and the amount altered by pyrolysis. In general it is 

thought that no more than about 25 % of the available THC'enters_the circulation when marijuana 

is smoked in the usual manner (Davis et al., 1984; Ohlsson et al. , 1980; Agurell and Leander, 

1
1971), though if it were possible to continuously inhale smoke from an entire cigarette, up to 

70% would become available (Agurell and Hollister, 1986).. 

The metabolism of THC is exceedingly complex and more than 80 metabolites are known 

to be formed in man. After marijuana smoking or THC injection, the first metabolite, 11­

hydroxy-THC (11-OH-THC) is formed in the lungs and liver. Its peak concentration in relation 

to the parent compound's is about 1:10-20 (Wall et al., 1983). After oral THC the ratio is about 

1:1-2. Because this metabolite's psychological activity is equipotent to the parent's, it contributes 

to the total marijuana effect, particularly when the drug is ingested. 1 1-OH-THC is converted 

by the liver into a number of inactive metabolites. The primary pathway leads to the formulation 

of 11-nor-THC-9-carboxylic acid (THC-COOH), the most abundant inactive metabolite in 

plasma, and in urine where it is partially conjugated. 

Plasma concentrations of THC peak during the smoking process and decline in sequential 

exponential phases; a redistribution (a) phase wherein the drug passes rapidly out of the plasma 

and into fatty tissues including the brain, followed by a much more prolonged elimination (B) 

phase wherein it is metabolized and excreted in urine and feces. The a-phase half life (tAa) is 

only about 30 minutes, whereas that of the B-phase (t%s) varies between 18 and 36 hours 

depending upon the individual (Wall et. al., 1983; Chiang and Barnett, 1984; Agurell et al., 

1986). 

The peak plasma concentration of 11-OH-THC is achieved within 15-30 minutes and from 

there declines according to essentially the same pharmacokinetic profile as its parent. The'rise 

in THC-COOH's plasma concentration is relatively slow, reaching an ill defined peak in 

different individuals within 1-2 hours. Its elimination follows a monoexponential profile with 

various individuals showing t%8's from less then 24 to more than 72 hours. It is interesting to 

note that the inactive metabolite's mean plasma concentration exceeds that of THC from about. 

the first hour onward. 

Though peak concentrations of THC are achieved during smoking, the maximum 

psychological effect (the "high") occurs 15-30 minutes after its cessation, suggesting that brain 

concentrations increase as plasma concentrations decrease. Both peak concentrations and 

maximum "high" are roughly proportional to the inhaled THC dose, but correlations between 

these parameters measured simultaneously at times 3-240 min after the cessation of smoking are, 

albeit significant, not especially strong. For example, Ohlsson et al. (1980) found the overall 

correlation for repeated measurements obtained from 11 experienced smokers to be r=0.53. 

After four hours the psychological "high" had vanished and plasma. THC levels were very low. 

Great interindividual variation exists in plasma levels of THC after smoking and this variation 

cannot be attributed to the regularity of marijuana use (Lindgren et al., 1981; Agurell and 

Hollister, 1986). 

Available evidence leads to the conclusion that it is usually impossible to predict the 

psychological effects of THC from its determination in a single plasma sample. But this is not 

the same as saying that no biological index of marijuana intoxication will ever be found. One 

possible candidate is THC's inactive metabolite THC-COOH. The relationship between this 

metabolite's plasma concentration and the perceived "high" after marijuana smoking has never 

been defined, although both parameters were measured in the study by Perez-Reyes et al. 

(1982). Peak and time integrated THC-COOH concentrations were proportional to the 

,,administered THC doses. Interestingly, the occurrence of the peak THC-COOH concentration 

coincided in time with the subjects' report of maximum "high". The authors failed, however, 

to measure, or at least report, the correlation between plasma THC-COOH concentration and 

-2­
subjective feelings because of the metabolite's pharmacological inactivity. Yet this coincidence 

might signify a useful epiphenomenal correlation. This possibility was repeatedly explored in this 

program. 

PREVALENCE OF MARIJUANA USE 

Marijuana usage prevalence peaked in the late 1970s and has been declining ever since. Still, 

marijuana is by far the most commonly used illicit drug in the United States (Jessor et al., 1986; 

Johnston et al. , .1992). The most recent data about marijuana usage prevalence are available 

from the 17`' National Survey of American High School Seniors, and the 121 National Survey 

of American College Students (Johnston et al., 1992). Life time prevalence among high school 

seniors declined from 60 % in 1980 to 37 % in 1991; and, among college students, from 65 % -in 

1980 to 46 % in 1991. Thirty-day prevalence declined in both groups from 34 % in 1980 to 14 % 

in 1991. About 9 % of high school seniors and 7 % of college students admitted daily use of 

marijuana in 1980. Only 2 % of both groups did in 1991. 

A 1988/1989 survey of cannabis. use among Dutch students, 10-20 years old, provided 

different results (Plomp et al., 1990): Considering only those in an age bracket comparable to 

American high school seniors and recent graduates (17-20 yrs; N=1806), the lifetime use 

prevalence of cannabis was 21 % and 13 % among males and females, respectively. Those who 

smoked at least once during the last month comprised 5.8% and 3.0% of the respective samples. 

Compared to results obtained from a similar survey executed in 1984 (Van der Wal, 1985) the 

lifetime and current prevalence of use have risen in The Netherlands by factors of 1.7 and 1.5, 

respectively. 

In short, relatively more young Americans formerly used and still use cannabis than their 

Dutch counterparts, but the .disparities between lifetime and current use prevalences are 

.narrowing due to opposite trends in the two countries. 

It is perhaps important to note in this context that possession of cannabis is prohibited by law 

in The Netherlands, as in the United States. The seriousness of the offense is, however, 

determined by the amount found in the Dutch user's possession and prosecution is unlikely to 

occur when that is less than 30 g (1 oz). 

MARIJUANA AND TRAFFIC SAFETY 

Epidemiological Research _ 

Simpson (1986) has reviewed recent epidemiological evidence regarding marijuana's role in 

traffic accident causality. His first concern was to determine the frequency of driving after 

marijuana use in order to identify the proportion of the total driving population who may be 

considered "at risk" of causing an accident for that reason. His information was derived from 

two sources: questionnaire surveys of adolescents (16-19 years), who were licensed to drive, and 

roadside surveys of recent usage among passing motorists. 

He mentioned the reasonably consistent results of. four questionnaire surveys conducted in 

the United States or Canada between 1979 and 1982. About one in six teenage drivers admitted 

driving while smoking or shortly afterward, and about 10% said they had done so between one 

and five times during the preceding month. Taken at face value, these results indicate that most 

-3­
users do not drive during or shortly after marijuana smoking which implies they do perceive 

risks associated with marijuana use and driving. Unfortunately it is not easy to generalize these 

results to older drivers in North America, nor to Europeans who are generally not licensed to 

drive until older than 18 years of age. 

Only two surveys of recent marijuana use among drivers stopped at roadside check points 

have apparently been reported. These were widely separated in place and time. The first was 

completed in Canada in 1974 (Smith et al., 1975), the second in Italy in 1982 (Ferrara and 

Rozza, 1985). Moreover, the former relied upon the drivers' admission of use and the latter 

upon detection of cannabinoids in urine samples. Nonetheless, the indications of recent marijuana 

use given by the two sets of results were not grossly different; 4% by the first and 1.2% by the 

second. 

The incidence of drivers whose recent use of marijuana resulted in their injury or death in 

motor vehicle accidents can only be estimated from the detection of THC. in plasma samples 

obtained shortly after the occurrence of the event. Hemolyzed blood samples obtained from dead 

victims provide unreliable estimates and analyseg- of urine samples to determine metabolite 

concentrations yield no indication of whether the drug was active at the time of the accident. 

Terhune (1982) tested 497 injured drivers for the presence of a wide range of drugs during 

treatment at the Rochester General Hospital in New York. THC in blood was detected in 9.5 % 

of the drivers, but more than half of them also tested positively for alcohol. Chesher and 

Starmer (1983) found THC in 6.7% of 104 injured drivers in New South Wales, Australia, but 

again about half of them showed alcohol as well. Daidrup. et al. (1987) examined 597 blood 

samples from injured drivers in the region around the German city Dusseldorf for the presence 

of alcohol. Blood samples having alcohol concentrations (BAC) below 0.13 g % were additionally 

analyzed for the presence of cannabinoids; twenty-five of the 220 blood samples (10%) were 

positive. More recently, Soderstrom et al. (1988) determined prior marijuana and alcohol use 

in 1023 patients who were injured as the result of vehicular and nonvehicular accidents and 

treated in the Shock Trauma Center in Baltimore, Maryland. THC was found in blood by 

radioimmunoassay in 34.7% of the patients, alcohol in 33.5%. Among automobile drivers, the 

numbers were 31.7% and 34.6%, respectively. Again, in about 50% of the marijuana positive 

cases alcohol was also found. It is not clear why these results contrast with those of previous 

studies. The most plausible explanation is that residents of the Baltimore area tend, in general, 

to use THC more often than those in the other regions surveyed. 

Canadian and American surveys of fatally injured drivers have generally found the incidence 

of those showing THC in plasma to be between 3 % and 11 % and . in all cases the coincidence 

of this drug and alcohol was above 70% (Cimbura et al., 1980, 1982, 1990; Donelson et al., 

1985; Owens, 1981; Mason and McBay, 1984). Disparate results were obtained by .Williams et 

al. (1985) who found THC in plasma from 37% of 440 dead drivers in California (80% in 

combination with alcohol). The reason for this disparity could be due to the greater prevalence 

of marijuana use in California but it was more probably related to these investigators' selection 

criteria: they only included male drivers younger than 35 years of age in their sample. Simpson 

estimated that if female and older male fatalities had been included in this survey, the overall 

percentage showing THC would have been about 20%. This figure is still double the estimates 

from other studies, which reinforces suspicions about the prevalence of marijuana use in 

California. However neither this nor any other survey allowed for the local and contemporary 

comparison of the fatally injured percentage of drivers showing THC plasma levels with that of 

the driving population in general. 

4 
If it is true that the population at risk from driving after marijuana smoking is 4%, or less, 

then the higher percentages of drivers injured or killed in traffic accidents while showing plasma 

THC concentrations seem to be an over-representation. However, there are obvious reasons to 

doubt whether valid estimates of the population at risk in urban North America can be derived 

from data that are more than 14 years old or were obtained at two. locations in Northern Italy. 

Even if the population at,risk is as small as estimated, the surveys of THHC incidence in injured 

or killed drivers have not provided evidence for a causal role of the drug per se in accidents. 

Alcohol was present in the vast majority of victims showing plasma concentrations of THC. The 

fact that the two drugs in combination possess a greater risk potential than either alone, is most 

likely. But the independent contribution of THC to traffic accident causality, particularly in 

concentrations which are likely to be found in most users who drive, is still questionable. 

One major problem in epidemiological research on the relationship between marijuana and 

traffic accidents is the lack of sound control groups as have been used in studies of alcohol 

involvement in accidents (e.g. Borkenstein et al., 1964). In those studies BACs derived from 

breath samples of drivers involved in accidents were compared with those of randomly selected 

drivers passing the accident site in the same direction at the same time of day and day of week. 

As Moskowitz (1985) noted, these kind of studies rely on two assumptions that do not hold well 

for investigations on marijuana. The first is that nearly all drivers will cooperate, which holds 

for alcohol studies in which typically 97% are willing to supply a breath sample, but does not 

hold for marijuana studies in which only 50-75% are willing to cooperate-due to the necessity 

of sampling blood rather than breath. A second assumption is that drug concentrations found are 

well correlated with performance impairment, which holds for alcohol but seems not to for 

marijuana. 

One way to circumvent this problem is the use of a culpability index, which reflects the 

percentage of drivers with detectable drug levels and deemed culpable compared to drug free 

drivers from the same sample who were also responsible for causing an accident. Warren et al. 

(1981) reanalyzed the data from Cimbura et al. (1980) and reported that 52% of the drug free 

fatally injured drivers were deemed culpable compared to 90% of those with evidence of 

marijuana use resulting in a culpability index of 1.7, a level also found for alcohol. Results of 

two other studies (Terhune, 1982; Donelson et al., 1985) are consistent with these findings; 

whereas Mason and McBay (1984) found no evidence of marijuana as a risk factor. In contrast 

to these studies, Williams et al. (1985) found that drivers in whom only marijuana was detected 

were less likely to be culpable (53 % vs 71 %). In contrast, dead drivers showing only alcohol 

were judged responsible in 92 % of all cases. Those showing both THC and alcohol were slightly 

more often responsible for causing the accident than those in whom only alcohol was found. It 

should be noted, however, that the frequencies of injured drivers showing THC alone are 

commonly very low and prohibit any definite conclusion. 

In summary, epidemiological literature shows that people do drive after marijuana use and 

that drivers involved in accidents often show the drug's presence, but results are inconclusive 

especially because of the high proportion of cases that also involve alcohol use. Therefore, the 

extent marijuana contributes to traffic accident causality remains obscure. 

Marijuana's Effects upon Driving Simulator Performance 

Early studies by Crancer et al. (1969), Rafaelsen et al. (1973), Ellingstad et al. (1973) and 

Moskowitz et al. (1976) utilized the filmed ride'approach where subjects had little or no control 

-5­
over the presented imagery. Don (1972) used a different approach for measuring subjects' 

decisions to pass a preceding car, or not, in the presence of an opposing vehicle portrayed as 

models on a continuous belt. Doses of inhaled THC varied from about 3 to 22.5 mg 

(43-321 μg/kg for 70 kg, or 154 Ib, persons). Smiley (1986) reviewed these early studies to 

conclude that THC had (1) not affected vehicle control, (2) increased decision latency before 

starting, stopping or overtaking, (3) reduced the willingness to accept a risk during passing 

maneuvers, and (4) impaired speedometer monitoring. Except in the case of one individual who, 

after inhaling 12 mg THC, repeatedly drove through stop lights during a filmed ride, no 

particular sign of dangerous driving behavior was observed. 

Smiley et al. (1981) conducted the first study using an interactive simulator with accurate 

visual imagery, though not moving base dynamics. The simulated tasks contained in a 45-minute 

scenario included curve following, reacting to wind gusts, car following, route selection from 

signs, avoiding an obstacle which appeared in front of the simulated vehicle and passing. A 

visual choice reaction time was also superimposed on driving. Three groups of marijuana users 

smoked cigarettes containing 0, 100 and 200 μg/kg THC on two occasions per dose, once with 

and once without alcohol. The quantity of alcohol consumed varied between groups to reach 

intended blood concentrations of 0.00, 0.05 and 0.08 g%, respectively. To ensure high 

motivation, good driving was rewarded and blatant errors, such as crashes, were penalized 

financially. The test began 15 minutes after the cessation of smoking. Both THC doses increased 

lateral position variability and the highest dose increased speed variability during curve 

following. Both increased headway variability, and the highest, lateral position variability during 

car following. Both doses caused the subjects to miss more signs indicating the need to follow 

another route. The high dose caused the subjects to hit the roadway obstacle more often thanplacebo, and also, to react-slower to the subsidiary task. Yet both THC doses caused the subjects 

to drive in a more conservative manner. They maintained a longer headway while car following, 

refused more opportunities. to pass, and when they did, began this maneuver at a greater distance 

from the approaching vehicle. Alcohol's effects in this study were generally less than THC's. 

Chesher (1986) was puzzled by this, calling the alcohol effect' "surprisingly small" and its 

interactive effect with THC, "unclear". Certainly it is so that BACs-of 0.08 g% and below have 

been enough to substantially degrade drivers' control of vehicular lateral position in real driving 

tests (Louwerens et al., 1987; Ramaekers et al., 1992a). 

Stein et al. (1983) conducted two studies of alcohol and marijuana effects using a driving 

simulator and a 15-minute test scenario that were very similar to those employed by Smiley et 

al: (1981). The former administered the two drugs in complete crossover designs. THC doses 

of 0, 50 and 100 μg/kg THC were combined with BACs of 0.00 and 0.10 g% in the first study. 

The same BACs were combined with 100 and 200 μg/kg in the second. This time alcohol had 

the expected adverse effect on practically-every performance parameter, THC had little effect 

in the first study and little in the second in spite of the higher dose. The latter did cause the 

subjects to operate at generally lower speeds, however. The combination of drugs produced 

widely different individual reactions. After the highest THC dose, the combination produced 

more adverse reactions than alcohol alone. 

Marijuana's Effects upon Actual Driving Performance 

A number of studies on marijuana's effects upon actual car driving have been reported since 

1974. All studies but one were carried out on courses closed to other traffic. Klonoff (1974) 
conducted the exceptional study wherein 64 subjects drove on a closed course and 38 also 

participated in a city driving test. In his first study subjects were assigned to one of three groups 

that were treated with (1) placebo, (2) 4.9 mg THC, and (3) 8.4 mg THC. They undertook eight 

tests: a slalom, two tunnel tests, a funnel test, a backing up, turning in a corner, a risk judgment 

test and' an emergency braking test. Except for the latter two, the performance measure was 

number of cones hit. Subjects performed 20 trials in four blocks of five. Treatments were 

administered between the third and fourth block and each subject's performance was related to 

his/her performance predicted by means of regression analysis over the first three blocks. 

Performance after placebo was as predicted, but after marijuana, significantly worse, though not 

much. The low dose impaired performance in two tests (tunnel and confer) and the high dose 

in five (slalom, both tunnel tests, funnel and risk judgment). 

Subjects in the city driving test were divided among four groups who were treated with 

placebo and marijuana, on separate occasions a week apart. The respective groups' treatments 

were (i) placebo followed by 4.9 mg THC, (2) the same in reverse order, (3) placebo followed 

by 8.4 mg THC, and (4) the same in reverse order. After smoking a placebo or marijuana 

cigarette, the subjects drove for 45 minutes over a 16.8 mi (27.0 km) route on city streets while 

aspects of their performance were rated by a professional examiner using an abbreviated version 

of the British Columbia Department of Motor Vehicles' standard driver's licensing test. All 

subjects were allowed to complete the test which indicates that their performance never became 

dangerously -unsafe under the drug's influence. Nonetheless, the examiner rated the subjects' 

performance as significantly worse on scales of judgement and concentration following the 

highest but not the lowest dose. The majority showed some impairment, but 32% after the low 

dose and 16 % after the high dose performed significantly better than they had following placebo 

suggesting qualitative differences between the drug's effects in different subjects. 

Hansteen et al. (1976) tested sixteen subjects in four conditions, (1) placebo alcohol + 

placebo marijuana, (2) placebo alcohol + marijuana (THC dose of 21 μg/kg), (3) placebo 

alcohol + marijuana (THC dose of 88 μg/kg), and (4) alcohol (BAC 0.07 g%) + placebo 

marijuana. Subjects were instructed to drive through a 1.1 mi (0.7 km) course delineated by 

traffic cones as quickly as possible but without exceeding 30 mph (19 km/h). Performance was 

measured shortly after smoking and three hours later. Number of cones hit, "rough handling" 

(superfluous and/oi` awkward movements as observed by an accompanying investigator), and 

driving time were scored. More cones were hit and more time was taken to complete each-lapafter consuming the higher THC dose, but no increase in rough handling was observed. Alcohol, 

on the other hand, adversely affected both performance measures and diminished the time taken 

to complete each lap. The authors concluded that the drug effects on performance were not 

dramatic since=no major differences were found between conditions with respect to observer 

ratings. 

Casswell (1979) was the first who included a subsidiary task to simulate the demands for 

monitoring the environment. Thirteen males were tested in three treatment sessions receiving 

alcohol and marijuana treatments twice in each session and drove for 35 minutes after each 

treatment. Treatments included (1a) alcohol (0.10 g% BAC) + placebo marijuana, (1b) placebo 

alcohol + marijuana (6.25 mg THC), (2a) double placebo, (2b) placebo alcohol + marijuana 

(6.25 mg THC), (3a) alcohol (0.05 g% BAC) + marijuana (3.12 mg THC), and (3b) alcohol 

(0.05 g% BAC) + marijuana (3.12 mg THC). Subjects' tasks included overtaking, driving on 

straight sections, through a hairpin bend, and through narrow gaps, while responding to road 

signals, traffic signals, and auditory signals in the subsidiary task. Alcohol alone and in 

-7­
combination with marijuana produced more coarse steering corrections, higher speed and 

increased lateral position variability. Marijuana alone was associated with lower driving speed 

and prolonged reaction times in the subsidiary task. Reaction times were also prolonged by the 

combination of marijuana and alcohol. The authors said that drivers under the influence of 

marijuana appeared to compensate for what they felt were the adverse effects of the drug by 

maintaining control effort, and decreasing speed to reduce the required rate of information 

processing. Alcohol, in contrast, appeared to produce more risky behavior. 

Attwood et al. (1981) also employed normal driving tasks on a closed course. Eight males 

participated in a within-subjects design, receiving (1) double placebo, (2) alcohol (0.08 g% 

BAC) + placebo marijuana, (3) placebo alcohol + marijuana (150 μg/kg THC), and (4) alcohol 

(0.04 g% BAC) + marijuana (75 μg/kg THC). The driving tasks were performed on an airfield 

runway and included: maintenance of a constant lateral position and velocity, maintenance of 

a constant headway while following a lead car that varied in speed, bringing the car to a smooth 

stop at a traffic signal, and deciding whether or not to overtake a preceding vehicle in the 

presence of. an approaching car. The latter maneuver was, however, not actually undertaken. 

Various measures, as speed, lateral position, acceleration and headway, were taken but the 

number of significant comparisons were no more than expected by chance. All measures were 

then subjected to a discriminant analysis that separated overall treatment effects. Overall driving 

performances after all drug treatments were significantly worse than following placebo when 

tested in this multivariate analysis. Smiley (1986) suspected that the lack of univariate effects 

was attributable to the low number of subjects and the lack of a subsidiary task. 

Peck et al. (1986) assigned 84 subjects in equal proportions to four treatment conditions: 

(1) double placebo, (2) alcohol (0.08 g% BAC) + marijuana placebo, (3) marijuana (19 mg 

THC) + alcohol placebo, and (4) both drugs combined. If these subjects could have inhaled all 

of the drug available in the cigarette, one weighing 70 kg (154 lb; population average) would 

have received a dose of about 270 ug/kg. Because of the remaining butt, the actual THC dose 

probably never exceeded 250 μg/kg. The subjects were tested four times in complete replications 

of a driving test battery beginning shortly after drug administration and continuing at hourly 

intervals thereafter. Ratings of the subjects' driving proficiency were obtained from driving 

licence examiners who rode with the subjects or observed them from static positions at points 

along the course; and, by California Highway Patrol officers who followed the subjects' vehicle 

in a police car. A computerized system within the subjects' vehicle. recorded their use of 

controls, speed and lateral position relative to course delineation. A risk.acceptance test was 

included to measure the subjects' willingness and ability to drive through gaps wider and 

narrower than the vehicle. Other tasks involved stopping in response to signals,, making a forced 

lane change and driving through pylons in a chicane. Finally, a standard police field sobriety 

examination and two standard laboratory tests (tracking and time estimation) were administered 

to the subjects outside of the vehicle. Several hundred measures of performance were obtained. 

No dramatic performance failures were reported as an effect of either drug or their combination. 

In general, the number of significant drug effects on particular measures were about what one 

might expect given the total- number,of statistical tests. 

The investigators resorted, like Attwood et al., to multivariate statistical analysis of their 

data. Twelve performance measures were combined in discriminant-analysis, which significantly 

separated the effects of each drug or their combination from placebo's. The THC effect was 

significant over all four replications of the tests, being greatest in the first trial. Alcohol's effect 

was greatest in the second trial and slightly greater than THC in every one. The combination 

-8­
of THC and alcohol produced significantly more impairment then did either drug alone in the 

first and third trials. Field sobriety checks by the police and ratings of the subjects' driving 

proficiency by experts failed to show any effect of THC, though these did reveal the effects of 

that drug in combination with alcohol. Practically the only indication of a serious effect of THC 

was provided by the officers following the subject's vehicle in a police car. They reported that 

they would have stopped the subject for suspicion of being intoxicated on 32 % of all THC trials 

(alcohol 50%, both drugs 60%). But they also said they would have stopped 15% of the placebo 

treated subjects. This either indicates that the subjects were exceptionally poor drivers, or were 

made to appear so under conditions of the test, or that the officers were responding to cues that 

they ordinarily would have ignored in real driving conditions. 

Smiley et al. (1987) tested the effects of marijuana (0, 100 and 200 μg/kg THC) in 

combination with alcohol (0.00 and 0.05 g % BAC) and alcohol alone (0.08 g% BAC) on driving 

in a closed-course study. Treatments were administered to groups of nine males over a three 

hour period in a party-like atmosphere in the evening. Subjects drove shortly after smoking as 

well as on the following morning. Driving tasks included maintenance of a constant lateral 

position at 80 km/h (50 mph), curve following, car following, route navigation, obstacle 

avoidance, and emergency decision making. Additionally, subjects had to perform a subsidiary 

task requiring visual monitoring. The high THC dose resulted in increased headway and 

headway variability. Alcohol alone at the 0.05 g% BAC level produced increased speed. Number 

of subsidiary task detections decreased at 0.05 g% BAC but increased at 0.08 g% BAC. 

Smiley's (1986) conclusion from her own and previous studies was as follows: 

".... , marijuana does appear to impair driving' behaviour. However, this impairment is mediated in. that subjects under marijuana treatment appear to perceive 

that they are indeed impaired. Where they can compensate, they do, for example, 

by not overtaking, by slowing down and by focusing their attention when they 

know a response -will be required.. Unfortunately, such compensation is not 

possible where events are unexpected or where continuous attention is required. 

Effects on driving behaviour are present shortly after smoking but do not continue 

for extended periods." (p. 133). 

General Conclusion 

The foremost impression one gains from reviewing the literature is that no clear relationship has 

ever been demonstrated between marijuana smoking and either seriously impaired driving 

performance or the risk of accident involvement. The epidemiological evidence, as limited as 

it is, shows that the combination of THC and alcohol is over-represented in injured and dead 

drivers and more so in those who actually caused the accidents to occur. Yet there is little if any 

evidence to indicate that drivers who have used marijuana alone are any more likely to cause 

serious accidents than drug free drivers. To a large extent, the results from driving simulator 

and closed-course tests corroborate the epidemiological findings by indicating that THC in single 

inhaled doses up to 250 Mg/kg has relatively minor effects on driving performance, certainly less 

than BACs in the range 0.08-0.10 g%. 

9
CHAPTER 2 - GENERAL METHODS

Before presenting the designs and results of the individual studies in separate chapters, it seems 

appropriate to describe the studies of the program and certain procedures that were common to 

all. These were subject recruiting, compliance with ethical and legal standards, screening for the 

presence of other illicit drugs and alcohol, and blood sampling procedures and quantitative 

analyses. 

DESCRIPTION OF A 4-STUDY PROGRAM 

The present relationship between drivers' use of marijuana and other substances containing the 

psychoactive drug (THC) and their involvement in traffic accidents is exceedingly obscure. For 

a variety of practical reasons, epidemiological research has failed to define that relationship in 

a manner approximating the demonstration of alcohol's effects on traffic safety (Terhune, 1986). 

The classical approach of first showing that a drug is actually causing traffic accidents before 

determining how has simply failed for THC. 

Yet abundant experimental evidence exists to show that some doses of THC can impair skills 

deemed important for safe driving. Unfortunately, most of it is of dubious relevance to the actual 

driving situation: nearly all of the studies on THC's behavioral effects were accomplished using 

laboratory tests that are not directly related to actual car driving. If previous experience is any 

guide, little of crucial importance will emerge from experimental research until it is conducted 

in a more "real world". 

Closed-course driving studies have shown that marijuana can impair driving performance but 

it is unknown to what extent these effects translate into driving performance in the real world. 

Only one study has been conducted in real world (city driving; Klonoff, 1974). This study 

demonstrated that subjects perform less competently when under the influence of marijuana, but 

the scoring method was questioned by others as regards its relationship to safe driving 

performance. 

Bearing these limitations of previous studies in mind a program was set up to determine the 

dose-response relationship between marijuana and objectively and subjectively measured aspects 

of real world driving; and, to determine whether it is possible to correlate driving performance 

impairment with plasma concentrations of the drug or a metabolite. These goals are the same 

as those of many unsuccessful investigations in the past. Yet none before has gone so far in 

seeking to achieve them in the environment where the "drugs and driving" problem actually 

exists. In the present studies, a variety of driving tasks were employed, including: maintenance 

of a constant speed and lateral position during uninterrupted highway travel, following a leading 

car with varying speed on a highway, and city driving. The-purpose of applying different tests 

was to determine whether similar changes in performance under the influence of THC occurs 

in all thereby indicating a general drug effect on driving safety. 

The program consisted of one minor and three major studies; a series of separate but 

interdependent experiments that successively 'approached driving reality. This approach was 

necessary to ensure subject safety throughout the program. The program started with a pilot 

- 11 ­
study (Chapter 3), conducted in a hospital under strict medical supervision, to identify THC 

doses that recreational marijuana users were likely to consume before driving. 

The first driving study (Chapter 4) was executed on a closed section of a public highway. 

The major goal was to determine the dose-response and dose-response-time relationship between 

marijuana (three different THC doses, and placebo) and road tracking precision as measured by 

the "weaving" motion of the subject's vehicle during uninterrupted highway travel. Results of 

this are compared to those from a previous study, undertaken by the investigators to measure the 

effects of different blood alcohol concentrations on driving performance in essentially the same 

test situation (Louwerens et al., 1987). A practical purpose was to determine whether the drug's 

effects as measured in a standard driving test were of a magnitude that would safely allow 

application of the same test and others on public roads in traffic. 

Upon completion of this study with the demonstration that THC's effects could be safely 

controlled, a second driving study (Chapter 5) was conducted to come a step closer to driving 

reality than its predecessor. The methods applied were, with the addition of 'a car following test, 

the same as those used in the first driving study. However, driving tests were now conducted 

on a highway in the presence of other traffic. The greatest discretion was -employed in designing 

this study to reach limited objectives. We choose a conservative approach which closely follows 

that used to determine the tolerability of medicinal drugs in human pharmacological research. 

It is to test THC's effects on actual driving performance in an ascending dose series. The 

ultimate goal was to define the THC dose (or plasma concentration) limit which separates low 

and high risk driving performance impairment by approaching it from the bottom up. 

Yet normal driving is far more complex and varied than simply to: maintain a safe lateral 

position and headway during uninterrupted travel on a highway. A THC dose having no effect 

on these parameters might still impair driving performance in more complex urban driving 

situations.. For this reason the program then proceeded into the third and final driving study 

(Chapter 6) which involved tests conducted in high density urban traffic. The highest dose which 

had no significant effect on highway driving in the previous study was given to subjects who 

would now operate in an urban driving test. This provided an opportunity to measure a far 

broader range of driving performance. If no effect were again observed, the generality of the 

dose-effect relationship would be strengthened. But if a new kind of impairment were observed, 

the conclusion would have to be that the dose effect relationship can not be validly used to 

define the effects of THC on driving performance, in general. The nature of the new impairment 

would provide insight into the kinds of traffic safety problems that may be first to appear as a 

consequence of the drug's effects. A second group also participated in this study and undertook 

the same driving test, but then after drinking alcohol (reaching an average BAC of 0.04 g%), 

and a placebo. This was done for two reasons; first, the alcohol condition served as a control 

whether the employed tools to assess driving performance were sensitive; and, secondly, it made 

a comparison possible between low doses of alcohol and THC. 

SUBJECTS 

The ideal subjects would be male and female marijuana users whose consumption of the drug 

represents that of the majority in that particular population. Van der Wal's (1985) data for the 

oldest group (17-18 years) in his sample of present Dutch cannabis users indicate that about 56% 

- 12­
of the males and females have a usage frequency of more than once per month and less than 

daily. This usage frequency was considered as the first selection criterion. 

The second criterion was that the users should also be experienced drivers in possession of 

a driver's licence. Subjects must have driven at least 5,000 km (3,108 mi) per year over the 

previous three years. This criterion was, however, not always met because of the difficulties in 

recruiting subjects. 

As the third criterion the users should have indicated on a questionnaire that they had driven 

within one hour after smoking cannabis at least once within the preceding year. These users not 

only possess the requisite driving experience under the influence of marijuana, they also 

constitute the "drivers at risk". In addition, the application of this criterion avoided the ethical 

dilemma of requiring subjects to accept a risk which they would otherwise avoid. 

. As a fourth criterion, the subjects should agree to refrain from their normal marijuana use. 

for at least five days prior to their participation in any test. 

Other inclusion criteria were as follows: age 21-40 years; normal (corrected or uncorrected) 

binocular acuity (i.e. 20/25 Snellen acuity, or better); body weight within the 85th - 115' 

percentile range according to the 1983 table from the Metropolitan Life Insurance. Company; 

and, Dutch nationality. The latter criterion was a condition set by the Dutch Ministry of Health 

which has no authority to permit the use of an illicit drug by foreign nationals. 

Exclusion criteria included the following: 

1.­ No history of treatment for drug or alcohol abuse or addiction and no reasonable possibility 

of dependence occurring as the result of participation in the investigation. 

2.­ No record of. arrests or conviction for drug trafficking. 

3.­ No history of psychiatric or organic brain disorders. 

4.­ No overt signs of cardiovascular, respiratory, renal, hepatic, metabolic or neuromuscular 

disorders and no history of serious disorders of this type. ­

5.­ No current use of any psychoactive medication (tranquilizers, antidepressants etc.) 

6.­ For females, no pregnancy or any reasonable probability that pregnancy might occur during 

participation in the investigation. 

Some subjects volunteered spontaneously after reading about the planned study in newspapers. 

Other volunteers for the first two studies were primarily obtained from among the local 

population of marijuana users by means of advertisements. Both the second and the third driving 

study required new samples of subjects. In these cases it was more difficult to recruit subjects 

since advertisements could not be placed where they might attract the attention of news media. 

The desire to avoid attention was fostered by a need to ensure subjects' anonymity and avoid 

the media's interference with data collection involving driving in traffic on public highways and 

city streets. Subjects were therefore recruited in the last two studies mainly by contacts obtained 

from subjects from the preceding ones. Admittedly this procedure is not the best to acquire 

independent samples but was necessary for practical reasons. 

Volunteers were screened in two stages; first from their responses to a combined cannabis 

use, driving experience and medical history questionnaire; and secondly, on the basis of an 

interview and physical examination. Furthermore law. enforcement authorities were contacted, 

with the volunteers' consent, to verify that they had no previous arrests or convictions for drug 

trafficking. 

Subjects were instructed to sleep normally on the nights before test days. Alcohol 

consumption was prohibited for 24 hours before tests, and consumption of beverages containing 

-13­
caffeine, for 2 hours beforehand. Those who smoked tobacco were advised that this would also 

be prohibited for one hour before testing until its completion. 

COMPLIANCE WITH ETHICAL AND LEGAL STANDARDS 

All studies described in this report complied with the code of ethics on human experimentation 

established by the Declaration of Helsinki (1964) as amended in Tokyo (1975), Venice (1983), 

and Hong Kong (1989). This implies that the volunteer subjects were fully informed of all 

procedures, possible adverse reactions to drug treatments, legal rights and responsibilities, 

expected benefits of a general scientific nature, and their right for voluntary termination without 

penalty or censure. All subjects gave their informed consent, in 'writing. Their anonymity was 

and will be maintained in all communications from the project. The investigators provided for 

continuous medical supervision and emergency medical treatment during the studies. Approvals 

for individual studies were separately obtained from the University's Medical Ethics Committee. 

Before the program started an Independent Advisory Committee was formed whose function 

was to ensure that the program proceeded in accordance with all medical and legal standards. 

This committee comprised the Assistant District Attorney, the Municipal Traffic Attorney for 

the City of Maastricht, a member of the University's Medical Ethical Committee, and the Dutch 

Regional Inspector for Public Health (Drugs). A permit for obtaining, storing and administering 

marijuana was obtained from the Dutch Drug Enforcement Administration. 

Subjects were accompanied on every driving test by a licensed driving instructor experienced 

iri supervising subjects who operated under the influence of medicinal drugs in previous studies. 

The instructor's sole task was that of monitoring ride safety. Redundant control system in the 

test vehicle was available for controlling the car if emergency situations should arise. However, 

the primary guarantor of the subject's safety was the subject himself/herself. The subject, like 

any licensed Dutch driver, had the legal responsibility to stop driving when feeling "under the 

influence" to the point where he/she could no longer be sure of his/her ability for safely 

controlling the vehicle. Subjects in this investigation were reminded of their responsibility and 

urged not to undertake any test, or to stop driving during a test in progress, if they felt incapable 

of driving safely. Subjects were always transported to and from their appointments and were 

strictly instructed not to operate their own vehicles for a period of 12 hours after having received 

the experimental treatment. 

SCREENING FOR THE PRESENCE OF OTHER ILLICIT DRUGS AND ALCOHOL 

Though it seemed unlikely that subjects would regularly resort to using other illicit drugs or 

alcohol prior to controlled marijuana smoking and testing, the possibility could not be definitely 

excluded without testing the subjects for the presence of these drugs. Therefore they were 

informed beforehand of the intention to.. obtain urine and breath samples which would be 

analyzed for the presence of prohibited agents. 

Each subject was required to submit a urine sample immediately upon arrival at the test site. 

Samples were later assayed qualitatively for the following drugs (or metabolites): cannabinoids, 

benzodiazepines, opiates, cocaine, amphetamines and barbiturates. In addition a breath sample 

was analyzed on the spot for the presence of alcohol using a Lion S-D3 Breath-Alcohol 

- 14­
Analyzer. The urine and breath sample screening procedures were employed in all studies in the 

program. 

Drugs other than cannabinoids were found in urine of four subjects. In the pilot study, the 

urine of two subjects was positive for benzodiazepines; and, of one subject for barbiturates. 

Analyses of six urine samples obtained from these subjects during the successive driving study 

failed to show the presence of these drugs. Since all urine samples from both the pilot and first 

driving study wereanalyzed after completion of the latter, the failure to detect the drugs in 

samples obtained during the driving study indicates that they did not abuse these drugs. Upon 

questioning, all three subjects denied that they had taken these drugs. Since no urine or plasma 

was left from these subjects, it was, however, not possible to check whether the results were 

false positives. Data obtained from these subjects in the pilot study were not excluded from the 

statistical analyses. One subject's urine, obtained prior to smoking in the 200 μg/kg condition 

in the first driving study, was positive for cocaine. Upon questioning, the subject replied that 

some friends had surreptitiously administered him cannabis cake and cocaine the day before. 

Assuming that the drugs'. effects had dissipated the next day, these subject's data were also not 

excluded from statistical analyses. 

BLOOD SAMPLING AND QUANTITATIVE ANALYSES 

Blood samples were taken by venepuncture. Two 10 ml aliquots were obtained in every case. 

These were heparinized and centrifuged within 30 minutes. Plasma was placed in frozen (-20°C) 

storage prior to analysis. The quantitative chemical analysis of THC and THC-COOH in plasma 

was performed by gas chromatography/mass spectrometry (GC/MS) using deuterated 

cannabinoids as internal standards (Moller et al., 1992). Of the many analytic techniques 

available at present, GC/MS is the reference method of choice (Cook, 1986). Applying this 

method, the detection limits for THC and THC-COOH were about 0.3 and 3.0 ng/ml, 

respectively. THC and THC-COOH concentrations in plasma will further be abbreviated to 

[MCI and [THC-COO11I. 

If the urine analysis (above) was positive for cannabinoids, plasma taken before smoking was 

also analyzed to quantitatively determine [THC] and [THC-COOH]. Subjects with detectable 

THC in pre-smoking plasma are shown in Table 2.1. In the pilot and first driving study, THC 

was detected in each pre-smoking plasma sample from two subjects and. in one sample from 

another subject, namely prior to smoking in the 200 μg/kg condition. In the second driving 

study, THC was detected in one sample from one male. and in five out of six samples from 

another male. In the city driving study, THC was not detected in any pre-smoking sample. 

It seems obvious that those subjects; -who had. detectable [THCI before -smoking, did not 

comply with the instruction to abstain from cannabis consumption for'at least five days prior to 

the trial. They all had long histories (at least 7 ypars) of cannabis experience and were frequent 

(at least twice a week) users. Gieringer (1988) `reports that THC may persist in the blood of 

chronic smokers at levels up to 4.0 ng/ml after 48 hours. It therefore remains an open question 

when their latest consumption was or whether they were impaired upon arrival at the laboratory. 

The same pattern of pre- to post-smoking values as shown in Table 2.1 was observed in the 

other subjects, i.e. [THC] and [THC-COOH] -increased considerably aftbr smoking the 

administered marijuana cigarettes and not following placebo. Therefore, these subjects' data 

were not excluded from the statistical analyses. 

- 15.­
Table 2.1 Pre-smoking and post-smoking [THC] in subjects with detectable THC in pre-smoking 

plasma samples. 

[THC] before [THC] after 

Study Subject no. Condition Smoking (ng/ml) Smoking?" (ng/ml) 

Pilot study , 1513 3.0 35.5 

1525 1.2 13.3 

1s` driving study 1507 200 μg/kg 1.9 39.3 

1513

placebo 2.0 -- 1.8 

100 pg/kg 2.4 9.2 

200 tg/kg 2.7 34.7 

300 μg/kg 4.2 26.8 

1525

placebo 1.1 1.1 

100,ug/kg 1.5 19.5 

200 uglkg 1.1 6.9 

300 μg/kg 2.7 13.9 

2"d driving study 1536

1" placebo 0.5 0.6 

100 μg/kg 0.6 10.7 

2-d placebo 0.7 0.6 

3nd placebo 1.2 1.3 

300 ug/kg 1.3 30.9 

1537

lu placebo 0.6 0.5 

r

only one condition (smoking until the desired effect was achieved). 

sampling time was 40, 30 and 35 minutes after initiation of smoking in the pilot, first and second driving study, 

respectively. 

Fifty percent of the pre-smoking plasma samples obtained from subjects in the pilot and first 

driving study, whose urine tests were negative for cannabinoids, were also analyzed. These 

analyses were performed to examine whether any false negative urine analyses had occurred. 

Results showed that'none of these samples contained detectable [THC] or [THC-COOH]. From 

these results it was inferred that in subsequent studies pre-smoking blood samples need only be 

taken if the urine test for cannabinoids were positive. 
CHAPTER 3 - PILOT STUDY TO SELECT THC DOSES 

INTRODUCTION 

Doses used in all previous studies of inhaled THC have been selected without consulting the 

subjects beforehand to determine whether these realistically approximated doses they commonly 

use. In the opinion of several experts_ (Moskowitz, 1985; Chesher, 1986; Peck et al., 1986) this 

has resulted in the selection of maximum doses for experimental purposes that are considerably 

less than those used for recreational pursuits. One could arbitrarily select higher doses but with 

the risk of erring in- the opposite direction. A dose of, say 300 μg/kg, might be higher than any 

taken at onetime by street users or, at any rate, higher than one they might take and then drive. 

If we were to select unrealistically high doses these could result in bizarre and potentially 

dangerous reactions in even the most controlled driving test. To avoid arbitrarily selecting the 

wrong maximum dose, it seemed necessary to consult the subjects in the context of a "clinical" 

pilot study. 

The pilot study's major purpose was therefore to establish the maximum dose for subsequent 

driving studies. Yet it provided several opportunities for obtaining valuable information about 

THC's pharmacokinetics and its pharmacodynamic effects after marijuana smoking. Blood 

samples were repeatedly taken for measuring [THC] and [THC-000H]. The subjects repeatedly 

performed certain simple laboratory tests, estimated their levels of intoxication and indicated 

their willingness to drive under several specified conditions of urgency. In addition, heart rate 

was measured at these times. The. secondary purpose was that of specifying relationships 

between [THC] and [THC-COOH] with changes in the other physiological, performance or 

subjective variables. 

METHODS 

Subjects 

Twenty-four healthy volunteers, 12 males and, 12 females, volunteered to participate in this 

study. They were screened as described in Chapter 2. Groups of six were treated and tested per 

night. Sessions were conducted in the evening between 19.00 and 24.00 hours and subjects 

smoked and were tested. at staggered intervals of 10 minutes. GC/MS analysis of plasma 

obtained from one male revealed trivial amounts of values THC in the first, and second samples 

after smoking but none thereafter, and no THC-CO(3H in any sample. It was concluded that this 

subject had not inhaled smoke so his data were excluded from further analyses. Characteristics 

of the remaining 23 subjects are given in Table 3.1. T-tests for independent samples showed that 

males were more experienced smokers than females (p < .044). Males' driving experience was 

nearly significantly greater than females' (p<.056 & .089 for number of years and km (mi), 

respectively). 

-17­
Table 3.1 Mean±SD (range) of subjects' characteristics. 

Males Females 

(N=11) (N=12) 

Age (yrs) 27.0±4.6 (22-38) 24.6±2.9 (21-31)

Weight (kg) 69.8±10.3 (56.5-87.0) 66.6±9.1 (52.0-79.0)

Weight (lb) 154±23 (125-192) 147±20 (115-174)

Smoking Experience (yrs) 9:2±5.8 (1-23) 5.0±3.3 (2-14)

# Joints/Month 5.9±3.7 (1-14) 5.8±5.4 (1-20)

Driving Experience (yrs) 8.5±5.7 (3-23) 4.8±2.7 (1-12)

Driving Experience (lan x 1000) 121±118 (15-360) 54±54 (5-175)

Driving Experience (mi x 1000) 75 ±73. (9-224) 34±34 (3-109)

# of Subjects Having Driven within

1 Hour following Cannabis Consumption:

less than 5 times 1 9

5 times or more 10 3

Smoking Procedures 

Marijuana cigarettes were supplied by the U.S. National Institute on Drug Abuse (NIDA). The 

cigarettes had an average weight of 767 mg and contained 2.57% or about 20 mg THC. 

Cigarettes were humidified by placing them at room temperature overnight in a desiccator 

containing a small quantity of saturated sodium chloride solution. This procedure raised the 

moisture content of the cigarettes from 10% to 15%, on the average. The subjects were allowed 

to smoke part or all of the THC content in three cigarettes until achieving the desired 

psychological effect. Cigarettes were smoked through a plastic holder, in a fashion determined 

by the subject. The only requirement was to smoke continuously for a period not exceeding 15 

minutes. When subjects voluntarily stopped smoking, cigarettes were carefully extinguished and 

retained for subsequent gravimetric estimation of THC consumed (2.57% of the difference 

between the weight of the original cigarette and the remaining unsmoked portion). This method 

of estimating THC amounts consumed is based upon the assumption that THC is equally 

distributed over the entire cigarette. Perez-Reyes et al. (1982) analyzed THC concentrations in 

the unsmoked portions of marijuana cigarettes of three different potencies and indeed found that 

they were identical to those in the unlit cigarette. 

Measurements 

A test battery which lasted 20 minutes took place before smoking and was repeatedly 

administered at 30, 90, 150 and 210 minutes after initiation of smoking. The battery consisted 

of: 

1:­ The Critical Tracking Test (CTT). This test, described in detail by Jex et al. (1966), was 

implemented on a IBM-compatible MS-DOS computer and measures the subject's ability to 

control a displayed error signal in a ?-order compensatory tracking task. Error appears as 

horizontal deviation of a cursor from midpoint on a horizontal, linear scale. Compensatory 

joy-stick movements null the error by returning the cursor to the midpoint. The frequency 

-18­
of cursor deviations, and therefore its velocity, increase as a stochastic, linear function of 

time. The frequency at which the subject loses control is called the critical frequency (X, 

expressed in rad/s). Theoretically, k is the reciprocal of the operating delay lag in human 

closed-loop manual control. The test included 5 trials of which the lowest and highest score 

were removed; the average of the remaining scores was taken as the final test score. Total 

test time duration was approximately 5 minutes. 

2.­ Questionnaires. Subjects were required to rate their feeling of "high" as a percentage of the 

maximum ever experienced, and. to indicate certain feelings of present cognitive and 

emotional state using the 16-item visual-analog scale developed and standardized for drug 

research by Bond and Lader (1974). Scores on the latter scales were grouped to form three 

cluster scores for measuring the corresponding factors: alertness, contentedness and calmness 

which will be expressed as percentage of the maximum. In addition, the subjects' willingness 

to operate a motor vehicle was assessed by asking them to declare whether they would 

attempt to drive for a set distance if the reasons were: A. unimportant though gratifying, 

such as for transporting a friend to another party; B. important but avoidable, such as for 

transporting a mildly sick friend home when he would otherwise have. to call a taxi; and C. 

urgent, such as transporting a severely sick infant to the hospital. These ratings were made 

by subjects immediately after termination of smoking and after conclusion of the CIT. All`'= 

questionnaires are enclosed in Appendix A. 

3.­ Heart Rate. Heart rate was measured by counting the number of beats per minute 

immediately after completion of the questionnaires. 

4.­ Hand Steadiness Test. Thereafter, hand steadiness was measured from the number of side 

contacts occurring as the subject attempted to hold a 1 mm (004 in) stylus for 15 seconds 

within each of five circular holes with successively diminishing diameters (3.90, 3.05, 2.70, 

2.20. and 1.85 mm,' respectively; or, 0.15, 0.12, 0.11, 0.09 and 0.07 in). Subjects were 

allowed to rest their hand on the table. The test score was defined as the total number of 

contacts of the stylus with any side. Since the distribution of subjects' scores were skewed, 

a square root transformation was applied to normalize data. The test lasted about 3 minutes. 

5.­ Blood -Sampling. A blood sample was taken by means of a venepuncture ten minutes after 

the beginning of the test battery. The sample (2 aliquots containing 10 ml blood apiece) was 

heparinized and centrifuged, and plasma was placed in frozen (-20°C) storage prior to 

analysis for THC and its major metabolite THC-COOH. Blood samples were taken before 

and at 40, 100, 160 and 220 minutes after initiation smoking. 

Subjects were familiarized with the questionnaires and practiced the CTT and hand steadiness 

test on three separate occasions during the weeks prior to the test night until they reached a 

steady performance level. 

I 

Data Analysis 

Parametric data were analyzed as. follows; All data including baseline values entered a repeated 

measures multivariate analysis of variance (MANOVA) with Sex as a between-groups and Time 

as a within-subjects factor and the criterion for significance set at .05. If a significant Time effect 

was found, a repeated measures univariate analysis of variance (ANOVA) was performed to 

separately compare each post-smoking measurement with baseline. Sex was not a factor in these 

ANOVA's unless MANOVA had revealed a significant Sex by Time interaction. Individual 

-19­
comparisons with baseline were not possible for perceived "high" ratings and plasma levels of 

the drug since baseline values were zero in most cases. Instead, if MANOVA revealed a 

significant Time effect, the data were further analyzed in an ANOVA trends analysis to 

determine the significance of linear., quadratic and cubic components. In the figures, the mean 

of the variable is depicted by a point and its standard error (SE) by the height of the vertical line 

above the point. 

The subjects' expressions of willingness to drive were made on the basis of a dichotomous 

decision and could not for that reason be analyzed in the same manner as other variables. These 

data were therefore analyzed using Cochran's Q-statistic to determine if the proportion of 

subjects willing to drive changed over time. If they did significantly, separate changes from 

baseline were tested by McNemar's sign-test. 

Criterion for statistical significance in individual comparisons was adjusted by means of the 

"Sequential Bonferroni" correction (Overall and Rhoades, 1987) to retain a constant type I error 

probability of .05 across the entire set of comparisons. This means that for the largest of four 

differences tested at once, p had to be less than .05/4=.013 to be judged significant. For the 

second, it had to be <.05/3=.017; for the third, <.05/2=.025; and for the smallest difference, 

p<.05 

Significant Sex effects were generally absent. Results pertaining to differences between the 

sexes are therefore only reported for the exceptional cases where the differences were 

significant. 

Two types of correlations were calculated to determine the linear relationship between two 

variables; i.e., the inter-subject and intra-subject correlation. The first is the most commonly 

used; it is obtained from pairs of variables measured in a group of subjects. In this study, for 

example, the correlation between [THC] and ), the tracking performance score, was calculated 

for all subjects at each sampling time separately. This resulted in four correlations (one at t=40, 

100, 160 and 220 min) obtained from 23 subjects (N=23). These correlations were tested for 

significant departures from zero by t-test. 

The intra-subject correlation, on the other hand, is the correlation between pans otv&riables 

within one subject. In the present study, for example, the correlation between [THC] and ? was 

also. calculated for each subject, across all sampling times, separately. This resulted in 23 

correlations (one from each subject) obtained from four repeated measurements (N =4; baseline 

values were excluded). These were transformed into Fisher's z-scores and then averaged across 

subjects yielding z,t, which was tested for significant deviation from zero by t-test, and 

transformed back to r. 

Interpretations of these two types of correlation are not the same. If, in the present study, 

a perfect inter-subject correlation (r= ± 1.0) between [THC] and k existed, it would mean that 

one can perfectly predict k of a particular subject from the knowledge 'of his/her [THC]. 

Usually, however, inter-subject correlations are much lower; and, the closer to zero, the more 

unreliable the predictions become. 

A high average intra-subject correlation means that, on the average, scores on two variables 

are closely related within a subject, but not necessatily between subjects. Thus, a highly negative 

average intra-subject correlation between [THC] and k (lower scores indicating poorer 

performance) would mean that, within a subject, higher plasma levels of THC are associated 

with poorer tracking performance. Yet this does not imply that, if two subjects are compared, 

the one with the higher plasma levels performs worse. That would only be the case if both the 

average intrasubject and the intersubject correlations were strongly negative. 

-20­
RESULTS

Consumed THC 

Six subjects consumed one cigarette, thirteen smoked two and four smoked three. Total THC 

amounts consumed are given in Table 3.2. Statistical analyses failed to. reveal a significant 

difference between the sexes. It should be noted that these amounts of THC represent both the 

amount inhaled and the portion that was lost through pyrolysis and side-stream smoke during 

the smoking process. 

Table 3.2 Mean, median and range of amounts of THC consumed, both in absolute values and 

relative to bodyweight (BW). 

THC consumed (mg) THC consumed per kg BW (pg/kg) 

mean median range mean median range 

Males (N =11) 22.3 18.6 14.7-35.2 324 292 203-524 

Females (N =12) 19.4 18.9 11.3-28.2 293 292 194-440 

All (N=23) 20.8 18.8 11.3-35.2 308 292 194-524 

Plasma Concentrations of the Drug 

Mean, median and range of [THC] and [THC-000H] at each sampling time are shown in 

Tables. 3.3 and 3.4. Maximum [THC] was found in the first sample after smoking at t=40 

minutes. Males had somewhat higher [THC] and -much higher [THC-COOH] values than 

females; the difference between both sexes was however rather constant over time, except for 

[THC] at 1=40 where the difference was quite profound. These observations ►ere.-cbnfirmed 

by MANOVA that showed a significant Sex effect for both [THC] and [THC-000H] (F1.21 =4.3 

& 9.79; p <.05 & .005, respectively), but no significant Time by Sex interaction. Since 

consumed THC amount did not differ between both sexes, the conclusion must either be that 

males were more efficient smokers than females, or that they absorbed the active ingredient 

differently. 

There was a significant Time effect for both [THC] and [THC-COOH] (F3,19=14.79 & 11.70, 

respectively; p<.001 in both cases). Univariate trend analysis revealed that ' both linear, 

quadratic as well as cubic functions fitted the trend in [THC] over time significantly 

(F1.21=44.56, 38.95 & 29.23; p<.001, .001 & .001; p,=.017, .025 & .05, respectively) due 

to a rapid decline of [THC] in plasma after the first sample. THC-COOH changes over time 

were only significantly fitted by a linear trend (F1,21=26.92p<.001;p,=.017). 

The relation between consumed THC, relative to body weight, and [THC] was examined by 

calculation of inter-subject correlations (intra-subject correlations could not be determined from 

the data because each subject smoked only one dose of THC). These analyses showed moderate 

inter-subject correlations between both parameters at each sampling time, namely 0.42 (p < .05), 

0.34 (ns), 0.42 (p<.05) and 0.45 (p<.05). Yet inspection revealed that the apparent strength 

of these correlations was almost totally attributable to two males who had consumed the greatest 

amounts of THC (486 and 524 μg/kg) and had also very high plasma levels of THC (45.9 and 

35:5 ng/ml, respectively). When log values of [THC] and consumed THC were used, to 

-21­
normalize the distributions, the correlations were small and not significant. There were no 

differences between males and females with respect to these correlations. 

Table 3.3 Mean, median and range of [THC] in ng/ml. 

t=40 t=100 t=160 t=220 

mean 17.7 5.8 2.8 1.7 

Males (N =11) median 13.3 4.5 2.3 1.3­

range 6.7-45.9 2.5-15.2 1.2-6.8 0.7-5.1 

mean 9.9 3.0 1.4 0.7 

Females (N=12) "median 7.0 2.7 1.0 0.6 

range 3.3-19.3 0.3-6.8 0.5-3.2 0.0-1.8 

mean 13.6 4.3 2.1 1.2 

All (N=23) median 9.9 3.5 1.4 0.8 

range 3.3-45.9 0.3-15.2 0.5-6.8 0.0-5.1 

Table 3.4 Mean, median and range of [THC-COOH] in ng/ml. 

t=40 t=100 t=160 t=220 

mean 33.9 28.1 25.3 20.8 

Males (N =11) median 25.6 19.6 18.3 13.5 

range 12.9-96.4 12.8-72.4 9.5-63.5 8.0-67.0 

mean 12.4 9.5 8.3 5.6 

Females (N=12) median 9.6 8.2 7.5 5.5 

range 3.3-39.9 0.5-26.8 3.0-15.8 0.0-13.0 

mean 22.7 18.4 16.4 12.8 

All (N=23) median 17.3 13.9 13.6 10.1 

range 3.3-96.4 0.5-72.4 3.0-63.5 0.0-67.0 

These results indicate that the between-subject variability in [THC] is not related to the betweensubject variability in the consumed amount of THC; in other words; information about [THC] 

and the time of blood sampling after smoking, of a particular individual, does not reveal how 

much that subject smoked, nor vice versa. 

Perceived "high" 

Mean subjective ratings of "high" are shown in Figure 3.1. The subjects consistently reported 

their peak subjective reaction as being about 70% of the greatest ever experienced. This was 

achieved shortly after smoking. Their subjective feelings declined, again in a highly consistent 

-22­
 *

Perceived "high"

100% r

90%

80%

70%

60%

50%

407.

.30%

20%

10%

0x

0 30 60 90 120 150 180 210

Time after initiation of emokin8 (min)

Figure 3.1 Mean (+SE) perceived "high" by Time.

manner between subjects; until arriving at a level less than 15 % of the greatest ever experienced,

at a time 3'4 hours after smoking.

MANOVA revealed a significant Time effect (F4.,g=49.18; p<.001). Trend analysis

confirmed the impression from the data that the downward trend is best fitted by a linear

function (F1..1=201.92; p <.001).

Willingness to Drive.

Figure 3.2 displays percentages of the subjects that declared to be willing to drive under

different circumstances of a gradually more compelling nature (A. unimportant though

gratifying; B. important but avoidable; and, C. urgent). Only about 20% of the subjects declared

their willingness to drive for relatively unimportant reasons (A and B), but approximately 80%

declared that they would do so for an urgent reason (C), while experiencing the peak subjective * 

reaction. Willingness to drive gradually rose to about 70% for unimportant reasons, and 100%

for an urgent reason, by the end of the test session.

Cochran's test revealed that time-related changes in willingness to drive were statistically

significant in all three circumstances (Qdf .5 =46.62, 44.62 & 15.17; p<.001, .001 & .01 for

situations A, B & C, respectively). McNenzar's test showed that the percentage of subjects

willing to drive under circumstance A was significantly different from baseline until the end of

the test session (p <.001, .001, .001, .002 & .02; p,,=.01, .013, .017, .025 & .05), while under

circumstance B changes were only significant until 21 hours after smoking (p<.001, .001 &

-23-
 *

.004; p,=.01, .013 & .017). McNemar's test failed to detect any significant change after

smoking relative to baseline for circumstance C.

Subjects willing to drive 100% r

90%

807.

70%

60%

50%

40%

30%

20%

10%

0% I 1 1 I 1 1 1 1 1

-30 0 90 60 90 120 150 180 210

Time after initiation of smoking (min.)

Figure 3.2 Percentage of subjects willing to drive under circumstances A, B

& C (see text) by Time.

Perceived Alertness, Contentedness and Calmness

Figure 3.3 shows subjects' ratings of perceived alertness, contentedness and calmness. Scores

on these factors changed significantly over time (F5.17=8.19, 5.79. & 7.02; p<.001, .003 &

.001, respectively). Subjects felt significantly less alert relative to baseline until about 11 hours

after smoking (• 1.22=34.67, 20.03 & 16.97; all p<.001; p,=.01, .013 & .017). Separate

sequential comparisons of subjective feelings of contentedness provided the same results

(F,==27.24,19.98&9.99;p<.001,.001 &.004;p,=.0l,.013 &.017). Feelings of calmness

followed a different profile over time. Separate sequential comparisons showed that no

significant change occurred during the first few hours after smoking, but at the end of the

session subjects felt calmer than they had at baseline (F= 12.25; p < .002; pp= .01). * 

Critical Tracking Test

The average frequency at which the subjects lost control (XJ was 4.40 rad/s before smoking and

fell to 4.15 rad/s in the first test after smoking and gradually rose to baseline level in later tests.

MANOVA however failed to show a significant Time effect. _

-24-
 *

Subjective feelings

100% r

90%

Calm

807 Content

707

Alert

60%

507

407 * 

-30 0 30 60 90 120 150 180 210

Time after initiation of smoking (min)

Figure 3.3 Mean (+SE) perceived alertness, contentedness and calmness by

Time.

Square root of total side contacts 8.0 r

7.5

7.0

6.5

6.0

5.5

5.0

4.5

4.0

3.5 *

3.01

-30 0 30. 60 • 90 120 150 160 210

Time after initiation of smoking (min)

Figure 3.4 Mean (+SE) square root of total number of side contacts in the

hand steadiness test by Time.

-25-
 *

Hand Steadiness Test

Figure 3.4 demonstrates that subjects' hand steadiness diminished after smoking marijuana, but

this effect dissipated rapidly after the first test. On the average, the subjects' hand steadiness was

even superior at a time two hours after smoking to what it had been initially.

MANOVA revealed a significant Time effect (F4,18=6.38; p<.002). Yet separate

comparisons showed that hand steadiness was only significantly different from baseline in the

first test after smoking (F,,==16.89; p <.001; p,=.013).

Heart rate (bpm)

115 r

110

105

100

95

90

85

. .80

75

I I 70,

-90 0 90 60 90 120 150 180 210

Time after imitation of smoking (min)

Figure 3.5 Mean (+SE) heart rate by Time.

Heart Rate * 

The subjects' average heart rate, presented in Figure 3.5, varied between 75 and 100 beats per

minute (bpm) in close accordance with their subjective feelings. Thirty minutes after smoking,

the increase in heart rate varied from 2 to 77 bpm, with a mean elevation of 24 bprn. Heart rate

diminished over successive measurements approaching baseline values after 3'4 hours.

MANOVA revealed a significant Time effect (F4118=10.43; p<.001) and separate ANOVA

comparisons showed that these elevations were significantly different from baseline at each but

the last measurement (F1,22=35.64, 21.90, 12.67 & 2.37; p <.001, :001, .002 & .14; p,=.013,

.017, .025 & .05, respectively).

Intra-Subject Relations between Variables

Table 3.5 shows the average intra-subject correlations between [THC], log,0[THC], and

[THC-COON] with each of the other variables. The log transformation was again applied to

-26-
 *

achieve a more linear and hotpeoscadastic relationship between THC values and the other

variables. The constant of 1 was added to the raw [THC] values for avoiding negative log

transformations. It can be concluded from this table that, within subjects, higher plasma levels

of the drug were associated with, and probably produced, increased heart rate, increased feelings

of perceived "high", diminished hand steadiness, and diminished feelings of calmness,

contentedness and alertness. The correlation with clticalT tracking performance was not

significant, confirming the insensitivity of the test. The log transformation of [THC] did not

change the size of the correlations dramatically.

Table 3.5 Average intra-subject correlations (* p <.05 ** p <.01; 2-tailed).

[THC] Logio([THO] + 1) [THC-COON]

Heart `Rate * - .79•' .82** .68•'

Perceived "high" .88•• *

.950• .87••

Xc -.20 * -.22 -.27

Side Contacts .48• * .45• .39

Calmness -.510 * -.38 .02

Contentedness -.57•• * -.59•• -.46•

Alertness -.64•• -.72•• *

Perceived "high" *

100% r

x0.88

90% q

Om q *0

 *

80%

*0 0

70% ap q

60%

b 00

50% 0 IN 0 0 • p

407.

307. * Q A q t=30

20% t=90

• t=150

107. • A%&,& t=210

0 ^ • I L J

0.0 0.2 0.4 0.6 0.8 1.0 1.2 1.4 1.6 1.8 2.0

LoL([THC]+1)

Figure 3.6 Scatter diagram of log([THC] + 1) in plasma and perceived "high".

Regression line comprising all data is inserted.
Inter-Subject Relations between Variables 

Inter-subject correlations between plasma concentrations of the drug and measures of subjective 

feelings, heart rate and performance were typically low-(r<.50) at each sampling time. The 

correlations between log [THC].+1 and perceived "high", for example, were r=0.07 (ns), 0.19 

(ns), 0.43 (p<.05) and 0.35 (ns), at t=40, 100, 160 and 220 minutes after. initiation of 

smoking, respectively. These low correlations are -probably due to "restriction of range ", i.e. 

the variability in both measures is relatively small at each sampling time. If all available data 

(N=92, 4 measurements of 23 subjects) were included in the correlational computation the 

highest correlation found was that between log [THC] + 1 and perceived "high" (r=0.66; Figure 

3.6). In fact, this correlation is a combination of intra-subject and inter-subject correlations, and 

should therefore only be regarded as an indication of what the correlation might have been if all 

these data had been independent observations. 

DISCUSSION 

The pilot study's major purpose was to determine the amount of THC recreational users of 

cannabis smoke to reach a comfortable "high" and to establish from these results the maximum 

dose for subsequent driving studies. Median and mean amount of THC consumed were 308 and 

292 μg/kg respectively. From these results it was decided that the maximum dose for subsequent 

driving studies would be 300 gg/kg. This is considerably higher than doses that have usually 

been administered to subjects in experimental studies (typical, 100-200 μg/kg THC). This could 

mean either that previous studies' THC doses were lower than those usually consumed by 

current users, or that the present study's subjects were less efficient smokers and, consequently, 

smoked more to achieve the same effect. Yet one important point should be raised. Imposed 

smoking procedures differ considerably between studies on marijuana's effects and can be 

divided at first glance in two types, self-paced in which subjects may smoke in their customary 

fashion and machine-paced procedures. in which subjects smoke in a prescribed manner with 

regards to duration of inhalation of smoke and air, holding inhalation, etc. The former method 

is more realistic while the latter is more controlled. This study applied the former because of 

the disadvantage of the latter that it might induce unrealistic reactions in some subjects. 

One way to contemplate this study's results is to compare the mean [THC] with those found 

in other studies in which similar procedures were applied with respect to smoking (ad lib 

fashion) and plasma analysis (GCIMS using a deuterated internal standard) as we did. To the 

authors' knowledge only one such study has been reported, namely by Ohisson et al. (1980). 

Marijuana cigarettes containing 19 mg THC were administered to eleven male subjects who were 

instructed to smoke in their own fashion such as to obtain the maximum desired "high". 

Subsequent gravimetric estimation showed that a mean of 13.0 nig THC was consumed. [THC] 

values ranged between 5.4 and 18.0 (mean 12.4) ng/ml 30 minutes after termination of smoking. 

Only the males of the present study should be included in the comparison with Ohlsson's study, 

because of the significant difference found between [THC] values of both sexes in the current 

study. Eleven males in the present study smoked 22.3 mg THC, on average, and their plasma 

concentrations ranged between 6.7 and 45.9 (mean 17.7) ng/ml 40 minutes after initiation of 

smoking. Thus, our subjects smoked 70% more THC than Ohlsson's subjects did, resulting in 

a 43 % higher THC level in plasma, as measured 30 minutes after smoking. The average [THC] 

found in the present study was therefore in the expected direction. This observation may lead 

-28­
to the tentative conclusion that the preferred THC dose to reach a desired "high" in the present 

study was not due to inefficient smoking but to the fact that current marijuana (or hashish) users 

do smoke higher THC doses than previously administered in scientific studies. 

Other results from the present study showed that perceived "high" and heart rate are very 

sensitive (psychological and physiological) measures of marijuana intoxication which confirms 

prior research. Impairments in laboratory tests performance were measured at the time of peak 

subjective feelings but generally, objective impairment dissipated more rapidly than the feelings 

themselves. All objective signs of impaired functions were gone within 1.5 hours after smoking. 

The explanation may be that practice and habituation effects, or both, occurred during the 

session concealing marijuana's impairment, or, that procedural errors have been made in 

administering these tests. No definitive answer can be provided and no conclusions can be drawn 

from this study with respect to marijuana's effects upon performance because of the lack of a 

control group. The study was simply not designed to estimate these effects, only to indicate 

whether either of these measures should be considered for inclusion in later studies. If any 

measure appeared to be systematically related to the inferred changes in THC's pharmacological 

activity over time, this measure might assume a high degree of practical importance. 

Correlational analyses, however, -showed no strong relationships between [THC] or 

[THC-COOH] and performance in any test. 

An important issue relating to traffic safety is whether subjects would drive a car while under 

the influence of marijuana. Although all subjects had admitted driving a car while intoxicated 

at least once before, a majority (about 65 %) of the subjects was not willing to drive a car for 

relatively unimportant reasons shortly after smoking when experiencing the drug's peak 

subjective reaction. However, most said they would drive, for a very urgent reason. On one 

hand, this means that the majority of the subjects are aware of a potential marijuana related 

driving impairment; on the other, a sizable minority (35 %) would not refrain from driving a car 

for unimportant reasons when they are experiencing a "high". These subjects in particular are 

a source of concern with respect to traffic safety, if marijuana smoking indeed impairs driving 

performance. Two questions that arise -from these contemplations were addressed by the 

succeeding driving studies; namely, 1. does marijuana adversely affect driving performance, and 

2. is willingness to drive after marijuana smoking related to driving impairment? 
CHAPTER 4 - MARIJUANA AND DRIVING ON A RESTRICTED HIGHWAY 

INTRODUCTION 

As mentioned in Chapter 1, THC's effects on actual driving performance have been assessed in 

a relatively small number of studies and only once in the presence of other traffic. The effects 

of doses up to about 250 μg/kg were modest, if present at all. These findings provided some 

assurance that it would be safe for subjects to undertake carefully supervised driving tests on 

normal roads and in traffic, even after treatment with the somewhat higher average dose (i.e. 

300 ug/kg) that was preferred by regular marijuana users in the pilot study. Nonetheless normal 

prudence demanded a demonstration of the test's safety in an environment resembling reality but 

where neither the subjects nor other road users would be endangered if The optimistic forecast 

proved false. One objective of the present study was to provide that demonstration using a 

standard test on a 'highway closed to other traffic. 

The second objective was to define the dose-effect relationship between inhaled THC dose 

and that parameter of vehicular control which is measured in the standard test; i.e. standard 

deviation of lateral position (SDLP), an index of "weaving" amplitude the subject allows while 

attempting to maintain a constant speed and steady lateral position between traffic lane 

boundaries during uninterrupted highway driving. Alcohol's effects on SDLP were previously 

measured by Louwerens et al. (1985, 1987) in practically the same manner as THC's in this 

study. The earlier results showing a .nearly perfect (r=0.99) exponential relationship between 

mean blood alcohol concentration (0-0. 12 g%) and mean SDLP for 24 "social drinkers", serve 

admirably for evaluating THC's_ effects in the present case. 

Other objectives were to measure changes in SDLP from tests after placebo to those 

following separate THC doses of 100, 200 and 300 μg/kg; and, to relate these objective 

measures of driving impairment to subjective impressions of driving quality and expressed 

willingness to drive in the same states of intoxication under normal circumstances. 

METHODS 

Subjects 

The same twelve men and twelve women who participated in the pilot study served. again as the 

subjects. Plasma from the pilot study_ was still not analyzed at the time data collection 

commenced. The male that apparently did not inhale marijuana smoke was therefore not dropped 

from the study. As before, his plasma samples showed neither THC nor THC-COOH. Data from 

this subject had to be again excluded from further analyses. Characteristics of the remaining 23 

subjects are shown in the previous chapter (Table 3.1). 

Design, Doses and Administration 

Marijuana and placebo cigarettes were obtained from the same source as before. The subjects 

were treated on separate occasions with THC doses of 0, 100, 200, 300 μg/kg. Placebo 

-31­
cigarettes were prepared by ethanol extraction of THC from the plant stock. Marijuana cigarettes 

were prepared from batches containing 1.75 % THC for the two lowest, and 2.57 % THC for the 

highest. dose. Cigarettes were cut to different lengths to provide the doses appropriate for the 

individuals' body. weights. It was necessary to provide the five largest subjects with two 

cigarettes at a time since one would not contain the total dose. Cigarettes were smoked through 

a plastic holder in a fashion determined by the subject but with the constraint that smoking had 

to be finished within ten minutes. After cessation of smoking, cigarettes were retained for 

subsequent gravimetric estimation of THC consumed. These analyses revealed that the average 

(±SD) amount of consumed THC in the three marijuana conditions was 6.8 (±0.9), 13.6 

(± 1.9) and 20.4 (±2.8) mg, which equals 94 (±4), 186 (± 13) and 282 (±18) μg/kg, 

respectively, or about 6 % less than target doses. Order of treatments were counterbalanced. 

They were administered subject- and observer-blind (i.e. the investigator who prepared the 

treatments was not involved in their administration or with data collection). 

Testing Procedures 

Eight subjects were tested per night and all 24 within a week. Subjects were tested at the same 

times and on the same days of the week for four consecutive weeks. Breath and urine tests were 

executed upon the subjects' arrival to check for the presence of alcohol and illicit drugs. If 

cannabinoids were found 'in the urine, a blood sample was taken for later verification of the 

presence of THC. Two subjects commenced smoking at a time at t=0 (Table 4.1). Driving tests 

were performed twice, beginning at t=40 and 100 minutes and lasting 15-20 minutes. Blood 

samples were taken before the driving tests. The subjects' pulse was taken and their performance 

measured in two laboratory tests that began after the driving tests. Subjective assessments were 

made immediately after smoking, and before and after the driving tests. Before the start of the 

experiment, subjects were individually trained to operate the vehicle under generally the same 

conditions as the tests later occurred. 

Table 4.1 Schedule of activities on test-days. 

Relative Time (min) Activity 

0-10 Smoking 

30-35 Blood Sampling 

40-60 Standard Driving Test 

70-80 Tracking and Hand Steadiness Tests 

Heart rate and Blood Pressure 

90-95 Blood Sampling 

100-120 Standard Driving Test 

130-140 Tracking and Hand Steadiness Tests 

Heart rate and Blood Pressure 

Driving Test 

The driving test, developed and standardized by O'Hanlon et al. (1982, 1986) and applied in 

more than 40 open- and closed-road studies by three Dutch Institutes during the last decade, 

-32­
measures the ability to control an instrumented vehicle's speed and lateral -position. Subjects 

were instructed to maintain speed at 90 km/h (56 mph), or less if they felt incapable of driving 

safely at that speed, and a steady lateral position between the delineated boundaries of the traffic 

lane. 

Driving was performed over a 11 km (6.8 mi) section of a primary highway (A76) that 

connects the Dutch cities o€ Geleen and Heerlen. Two lanes in the same direction were closed 

to normal traffic between the hours of 19.00 and 24.00 on three consecutive week-nights over 

four consecutive weeks of testing. Driving began at one end of the section, involved turning at 

the other and ended witix a return to the origin. A licensed driving instructor accompanied each 

subject. He was charged with responsibility for ensuring safety at all times and was able to 

intervene, if necessary, using redundant vehicular controls. 

Two Volvo station wagons containing essentially the same instrumentation were employed 

in the study. The first-of a pair of subjects who received treatments together departed from the 

origin driving one vehicle and was followed by the second driving the other after 2' minutes. 

The first subject waited for the arrival of the second at the turning point before returning to the 

origin. The purpose was to avoid having the subjects, travelling in opposite directions, meet ­

en route. The major instrumentation comprised devices for acquiring-continuous analog signals 

representing steering wheel angle, vehicle-speed and lateral position relative to the midline stripe 

delineation, and a computer system for recording those signals continuously at a 4 Hz sampling 

rate. 

The primary dependent variable was the standard deviation of lateral position (SDLP), which 

has been shown to be both highly reliable (typical test-retest correlation of 0.7-0.9) and very 

sensitive to the influence of sedative drugs and alcohol. Other dependent variables were mean 

speed (SP) and standard deviation of speed (SDSP)-and steering wheel angle (SDST). 

Questionnaires

The same subjective questionnaires used in the pilot study were' administered to the subjects

immediately after cessation of smoking (t= 10) and again at the beginning of each driving test

(t=40 & 100). At the end of each driving test (t=60 & 120), the subjects were required to

retrospectively rate their effort made while performing the test (Zijlstra and Van Doom, 1985;

Meyman and Zijlstra, 1986) and subjective driving quality on respective visual-analog scales.

Scores on these scales will be expressed as percentage of total scale and percentage of "normal"

driving quality, respectively. Questionnaires are enclosed in Appendix A.

Laboratory Tests 

Two of the tests employed in the pilot study were also applied here, namely the critical tracking 

and hand steadiness tests. Exactly the same procedures were employed in their administration 

as* described in the previous chapter. 

Physiological Assessments 

Heart rate, systolic and diastolic blood pressure were measured by means of a digital blood 

pressure monitor prior to the hand steadiness test. 

-33­
Blood Sampling 

Blood samples were taken by venepuncture. The samples (2 aliquots containing 10 ml each) were 

heparinized and centrifuged. The plasma fractions were placed in frozen (-20°C) storage prior 

to analysis for [THC] and [THC-COOH]. 

Data Analysis 

All data measured on ratio or interval scales were taken in a mixed between-groups, withinsubjects MANOVA analysis. Sex was the between-groups factor. Dose (4 levels) and Time after 

dosing 12 or 3 levels) were factors tested within-subjects. If a significant (p < .05) Dose effect 

was found, repeated measures ANOVAs were conducted for testing differences between 

measures obtained after placebo and each THC dose, separately. Data in these cases were 

collapsed across Sex and Time unless the MANOVA analysis had revealed a significant 

interaction between either factor and Dose. In the figures, the mean of the variable is depicted 

by the height of the bar and its standard error (SE) by the height of the vertical line above the 

bar. 

Separate dose effects were tested using the "Sequential Bonferroni" procedure for adjusting 

the a-probability criterion (p(,) in accordance with the number of separate comparisons in a given 

set (Overall and Rhoades, 1987). This means that for the largest of three differences tested at 

once, p had to be less than .05/3=.017 to be judged significant. For the second, it had to be 

<.05/2=.025; and for the smallest difference, p<.05. The adjustment had the effect of holding 

the probability of making a type I error at p:5.05 over the entire. set of comparisons. 

The subjects' expressions of willingness to drive were made on the basis of a dichotomous 

decision and could not for that reason be analyzed in the same manner as other variables. These 

data were therefore analyzed using Cochran's Q-statistic test for assessing differences between 

dosing conditions at each time of testing, separately. 

Significant Sex effects were generally absent. Results pertaining to differences between the 

sexes are therefore only reported for the. exceptional cases where the differences were 

significant. 

Inter-subject and intra-subject correlations were computed and tested as described in the 

previous chapter. 

RESULTS 

Plasma Concentrations of the Drug 

Though consumed dose differed little between subjects, [THC] and [THC-000H] varied 

enormously. Thirty minutes after smoking 300 μg/kg, for example, [THC] ranged between 1.6 

and 59.6 ng/ml. Table 4.2 shows mean, median and range of [THC] and [THC-COON] by Dose 

and Time. Placebo values were not used in the statistical analyses since these were zero in most 

cases. 

As shown by Table 4.2 plasma concentrations of the drug were clearly related to the 

administered dose and time of blood sampling. MANOVA confirmed this observation yielding 

a significant Dose (F2.20= 14.65 &. 16.59 for [THC] and [THC-COOH], respectively; both 

p<.001) and Time (F,.2,=50.76 & 21.16; both p < .001) effect. There was a significant Dose 

by Time interaction for [THC] (F2.20=10.07; p < .001) and not [THC-COOH]. Though not shown 

-34­
 *

in the table, males had significantly higher [MC-COON] values, 9 ng/ml on average, than

females (F,,2,=4.49; p < .05); average [THC] values were virtually the same for both sexes.

Table 4.2 Mean, median and range of [THC] and [THC-COOH] in ng/ml (N=23).

100 μg/kg 200 μg/kg 300 μg/kg

t=30 t=90 t=30 t=90 t=30 t=90

mean 9.5 3.5 15.9 4.8 20.7 6.2

[THC] median 9.0 3.2 12.0 4.3 19.1 5.6

range 0.0-21.3 0.0-1 1.0 1.7-39.3 0.0-1 1.8 1.6-59.6 0.8-15.4

mean 10.9 9.4 14.2 12.1 17.5 15.2

[THC-OOOH] median 7.2 4.7 13.4 9.6 13.8 11.4

range 0.0-61.9 0.0-55.5 2.2-73.9 2.0-65.2 2.6-64.4 2.6-55.4

Perceived '%*h"

60%

CI pia ®TSC-loo *

TSC-800 = TSC-300 70%

60%

50%

40% * 

*

30% *

20%

10%

07.

t=10 t=40 t=100

Time after initiation of amoldng (min)

Figure 4.1 Mean (+SE) perceived "high" by Dose and Time.

Perceived "high"

Average subjective feelings of intoxication ("high") were dose-related and highest just before

the first driving test (Figure 4.1). Relative to maximum personal experience, peak levels of

intoxication were about 30%, 50% and 60% after 100, 200 and 300 μg/kg doses, respectively.

-35-
 *

Feelings of "high" after placebo were near zero in most cases. Therefore changes occurring after

marijuana smoking, relative to placebo, instead of the raw values, were analyzed by MANOVA.

Change scores were significantly different from zero (F1,21=125.22; p<.001), dose-related

(F2.20=21.76; p <.001) and time-related (1 2.20=36.68; p <.001). Females felt more intoxicated

than males ( 1.21=4.59; p<.05), but there was no significant Sex by Dose. interaction. Univariate_

analyses revealed that intoxication ratings were different from zero and followed a quadratic

trend in all marijuana conditions.

Driving Performance

No driving tests had to be stopped for safety reasons by the driving instructors: -Yet nn--two

instances, both after the highest THC dose; the instructor felt compelled to intervene. In one

case, the driving instructor twice warned the subject to avoid a screwdriver laying on the road

but when he failed to react the instructor did by steering away from the object (it was

immediately removed following this incident). The subject was queried about this situation after

termination of the ride. He recalled that the driving instructor had taken control but did not

recall why! In the other case, a subject failed to decelerate as he approached the turning point.

The instructor told him to do so whereupon the subject abruptly brought the vehicle -to. a stop

using the break.

 *

30 SUP (cm)

11 Pl. ® THC-loo THC-too = THC-300

 * * 

*

First Second

Driving Test

Figure 4.2 Mean (+SE) standard deviation of lateral position by Dose and

Time.

SDLP reliability was high in this study: the -correlation between measurements made on

successive trials after placebo was 0.92 (p <.001). Correlations between SDLP values on the

-36-
first and second trials after THC doses of 100, 200 and 300 μg/kg were 0.90, 0.91 and 0.91 (all 

p < .001), respectively. This means that subjects' SDLPs from the second ride were almost 

perfectly related to those of the first, and, consequently, that SDLP measurement error was very 

small. 

Mean values of SDLP are shown in Figure 4.2 as a function of Dose and Time. Higher 

values, indicating poorer road tracking performance, were found after marijuana smoking. 

MANOVA revealed that the Sex effect (F,.21=4.41; p<.05) was significant, females having 

higher SDLPs than males. The Sex by Dose interaction, however, was not significant 

(F3.19=2.54; p < .09), indicating that the effect of marijuana was grossly the same for both sexes. 

The analysis indicated a clear Dose effect (F3•19= 8.92; p < .001). Neither Time nor Dose by Time 

effects were statistically significant indicating that impairment after marijuana was the same in 

both trials. Separate dose comparisons revealed that performance after marijuana was always 

worse than after placebo (F,,22=7.45, 19.96 & 14.58 for the 100, 200 & 300 μg/kg conditions, 

respectively; p <.0127,- ..00l & .001;,p,;=.05, .017 & .025). 

Mean speed was very close to that established as the target by instructions and varied 

between conditions from 88.9 to 90.5 km/h (55.3 to 56.2 mph). Subjects drove 0.4 km/h 

(0.25 mph) faster after the 100 μg/kg dose, and 0.4 km/h slower after both of the higher doses, 

than after placebo. Yet these differences were small as percentages of the average, and pot 

significant. On average, speed was 0.6 km/h (0.37 mph) higher in the second than in the first 

ride resulting in a significant Time effect (F1121=5.24; p<.04). 

Differences in standard deviation of speed.were greater between sexes than between 

conditions. There was a significant Sex effect (F1121=6.99; p<.02), females having greater 

difficulty in maintaining a constant speed than males. SDSP was; after each THC dose, higher 

in the first, but lower in the second ride relative to placebo. Changes from placebo were, 

however, small and not significant. 

Changes in standard deviations of steering wheel angle were small and not significant. 

Perceived Driving Quality and Effort 

Figures 4.3 and 4.4 respectively show mean perceived driving quality, and effort to accomplish 

the test, by Dose and Time. Subjects rated their driving performance as better than "normal" 

after placebo. Ratings were around normal after the lowest THC dose but poorer than normal 

to about the same degrees after both of the higher doses. Differences attributable to Dose were 

significant (F3•19=3.76; p < .03). Separate dose comparisons showed that the effects of all three 

doses were significantly different from placebo (F1a2=4.80, 8.64 & 10.76 for the 100, 200 and 

300 μg/kg respectively; p <.04, .008 & .003; p,=.05, .025 & .017). Perceived driving quality 

was higher in the second driving test than in the first (F1.21= 8.06; p <.01), but the lack of a 

significant Dose by Time interaction indicated that this was independent of the administered dose. 

Effort to accomplish the driving test increased systematically with the administered dose. 

Although there were only small differences in either SDLP or perceived driving quality between 

the two highest dose conditions, effort was, especially in the first trial, greater after the 300 than 

after the 200 μg/kg dose. This suggests that subjects had to compensate more after the highest 

dose to achieve about the same objective and subjective driving performance. MANOVA 

revealed significant Dose (F3.19=13.41; p <.001), Time (F,.21=8.59; p <.W8) and Dose by Time 

(F3.19=10.27; p < .001) effects. Separate dose comparisons showed that perceived effort was 

higher in all three marijuana conditions (F1a2=7.57, 20.17 & 37.96 for the 100, 200 and 300 

-37­
 *

Perceived driving quality

150% r

140% O Pia ®THC-too K!X THC-200 = TUC-300

1307.

120%

70%

60%

 *

50%

First Second

Driving Teat

Figure 4.3 Mean (+SE) perceived driving quality, expressed as percentage of

"normal", by Dose and Time.

 * * 

*

Perceived effort

607.

Pta ® TUC-too gxx THC-200 = THC-300 I

50%

40%.

30%.-

20%

 *

10% *

07.

First Second

Driving Test

Figure 4.4 Mean (+SE) perceived effort to accomplish the test, expressed as

percentage of maximum of scale, by Dose and Time.

-38-
μg/kg, respectively; p<.012, .001 & .001; p, = .05, .025 & .017) than in the placebo condition. 

The Dose by Time interaction was significant after the two higher doses (F,==8.45 & 24.95 

for the 200 and 300 μg/kg, respectively; p<.008 & .001; p,=.025 & .017); i.e. the effort 

requirement diminished over the interval separating smoking and driving in these conditions. 

Willingness to Drive.

Table 4.3 presents the percentage of subjects willing to drive under specified conditions of

different urgencies (A. unimportant though gratifying; B. important but avoidable; and, C.

urgent).

Table 4.3 Percentage of subjects willing to drive under circumstances A, B & C (see text) by

Dose and Time. Rightmost columns display Cochran Q-statistic (df=3) with p values.

0 μg/kg 100 μg/kg 200 μg/kg 300 μg/kg Cochran's Q p< 

t=10_ 96 87 48 - 48 23.54 .001 

A t=40 96 65 48 43 23.22 .001 

t=100 96 83 65 61 16.40 .001 

1=10' 91 83 65 57 12.00 .008 

B t=40 91 70 48 61 15.14 '.002 

t=100 91 87 74 57 17.22 .001 

t=10 100 96 91 74 13.11 .005 

C t=40 100 96 87 74 11.45 .01 

t=100 100 96 96 87 6.33- NS 

Subjects' responses were similar to those in the pilot study. The lower the administered THC 

dose and the more urgent the reason for driving, the more subjects declared that they would be 

willing to drive. According to the subjects' declarations, 40-60% would have driven for 

unimportant reasons shortly after the two highest doses. However, more than 75 % would have 

driven for an urgent reason. Nearly all would have driven 1' hours after smoking for an urgent 

reason when objectively measured driving performance was still impaired. Differences between 

treatments were significant in all cases, except one: the percentages of subjects who said they 

would have driven for an urgent reason 100 minutes after initiation of smoking were not 

different between treatment conditions. 

Perceived Alertness, Contentedness and Calmness 

Subjective feelings of alertness, contentedness and calmness were all affected by Dose 

(F3.19=11.18, 4.86 & 5.14, respectively; p <.001, .011 & .009). After marijuana smoking, 

subjects felt less alert, content and calm. Significant Time effects were found for alertness and 

calmness (F2020=7.89 & 8.10, respectively; bothp <.003): subjects felt more alert and calm later 

-39­
 *

in the session. A significant Sex by Time effect was found for feelings of contentedness, females

feeling less and males more content later in the session. Separate comparisons showed that all

three THC doses produced significantly reduced feelings of alertness (F,,==12.46, 28.94 &

24.80 for the 100, 200 and 300 μg/kg, respectively; p<.002, .001 & .001; p,=.05, .025 &

.017). Only the two higher doses produced significantly reduced feelings of contentedness

(F,==8.70 & 15.05 for the 200 and 300 μg/kg, respectively; p <.007 & .001; p,=.025 & .017)

and calmness (F,,==14.29 & 11.70 for the 200 and 300 ug/kg, respectively; p <.001 & .002;

PC=.017 & .025).

Critical. Tracking Test

Subjects' tracking performance, i.e. X, was not affected by THC. Males performed significantly

better than females (F,aa,=12.61; p<.002) and performance of all subjects was worse at the

second than at the first assessment (F,,21 =10.89; p < .003), but these observations are not of

great concern.

1.

Square root of total aide contacts 7.0 r

6.5 E1 Pia THC-loo K^x TSC-too = TSC-Soo * 

6.0

5.5

5.0

4.5

4.0

3.5

3.0

2.5

2.0

t=70 t=130

Time after initiation of smoking (min)

Figure 4.5 Mean (+SE) square root of total number of side contacts in the

hand steadiness test by Dose and Time.

Hand Steadiness Test

Figure 4.5 demonstrates that hand steadiness diminished after all THC doses. MANOVA

revealed a significant Dose (F3_19=5.04; p <.O1) and Time (F,.2, = 8.61; p <.008), but no Dose

by Time effect. This means that marijuana's impairment was still persistent two hours after

-40-
 *

smoking. Separate comparisons showed that both.higher THC doses, but not the lowest,

diminished hand steadiness (F,.m=7.67 & 11.76 for the 200 and 300 pg/kg, respectively;

p<.011 & .002; p,=.025 & .017).

Heart Rate and Blood Pressure

Heart rate and blood pressure were measured 70 and 130 minutes after the initiation of smoking.

Yet as Figure 4.6 demonstrates, heart rate was still . levated in a dose related manner at both

assessments. MANOVA confirmed this observation revealing a significant Dose effect

(F3.19 =7.71; p<.001). Heart rate was always lower at the second assessment resulting in a

significant Time effect (F1121=24.34; p<.001). Dose by Time interaction was not significant.

Separate comparisons revealed that all three THC doses produced significant heart rate elevations

relative to placebo (Fi2z=9.00, 13.62 & 20.61 for the 100, 200 and 300,ug/kg, respectively;

p < :007, .001 & .001; p,=.05, .025,& .017).

Heart rate (bpm) 95

=1 P1& ® THC-100 THC-too = THC-300

90 I

65

 *

60

75

70

 * 

65 *

 *

 *

60

t=70 t=130

Time after initiation of smoking (min)

Figure 4.6 Mean (+SE) heart rate by Dose and Time.

Systolic and diastolic blood pressure measurements were simultaneously analyzed in one

'doubly" repeated measures design. This means that both measures are analyzed in one

multivariate design. Univariate effects of THC on systolic and diastolic pressures were only

tested for significance, separately, if the multivariate Dose effect was significant. The lowest

THC dose produced slightly lower blood pressure relative to placebo, whereas the highest dose

had the opposite effect. Changes in blood pressures varied between -2.0 to +5.8 mmhg.

MANOVA failed, however, to reveal either a significant Dose or Dose by Time effect. The only

-41-
significant factor was Time (F1 21=6.92; p<.005), indicating that blood pressure decreased 

significantly from the first to the second assessment: this occurred in both the systolic 

(F1.21 = 12.92; p < .002) and diastolic blood pressure (F1,21=4.77; p < .05). 

Intea-Subject Relations between Variables 

Table 4.4 shows the average intra-subject correlations of [THC], [THC-COOH], and SDLP with 

each of the other variables. The averages were computed from 23 intra-subject correlations, 

calculated from data obtained at eight sampling times (twice in each condition). The table shows 

that higher plasma levels of the drug were associated with increased feelings of perceived 

"high", higher levels of effort to accomplish the driving test, decreased ratings of subjective 

driving quality, and increased heart rate. There was no strong relationship, within subjects, 

between plasma levels of the drug and SDLP. This was because drug concentrations declined 

between the first and second sampling time, whereas SDLP scores hardly changed. When 

average intra-subject correlations were computed for the first and second sampling times 

separately, the correlations between [THC] and SDLP were 0.59 (p <.Ol) and 0.42 (p <.05), 

respectively. 

Table 4.4 Average intra-subject correlations (*p<.05 **p< .01; 2-tailed). 

[THC] [THC-COON] SDLP 

Perceived "high" .83" .80" .41 

Perceived Effort .53" .58" .30 

Perceived Driving Quality -.43' =.44' -.29 

SDLP .23 .35 1.00 

SP -.35 -.34 .05 

SDSP -.02 .05 .16 

.11 .07 -.22 

Side Contacts .26 .20 .14 

Heart Rate .49' .39 .27 

Inter-Subject Relations between Variables 

Relationship between Drug Levels and Performance; Inter-subject correlations between plasma 

concentrations of the drug and performance were calculated to determine whether subjects with 

higher plasma levels of the drug performed poorer than those that had lower plasma levels. 

Correlations between driving performance and performance' in -the laboratory were also 

calculated. The results are presented in Table 4.5. It appeared that. correlations involving plasma 

concentrations were greater when logarithmic values of THC values were used in the 

computation (1 ng/ml was added to all THC values before the transformation in order to avoid 

negative log values). Correlations with THC-COOH were generally smaller than those with log 

THC values; therefore only correlations with log THC values are shown in the table. 

-42­
Table 4.5 Inter-subject correlations between drug concentrations in plasma and raw performance 

scores in marijuana conditions (* p <.05, ** p < _O1; 2-tailed). 

100 μg/kg 200 μg/kg 300 μg/kg 1:' 2°d 1:t 2°w 1:' 2' 

r(Log([THC] +1),SDLP) -.23 -.32 -.26 .01 .13 .07 

r(Log([THC]+1),SP) -.68" -.72" _ -.45': -.39 -.52 -.58" 

r(Log([THC] + 1),SDSP) -.37 -.57" -.52' -.38 -.27 -.22 

r(Log([THC] + 1), X) -.33 .51' .24 .35 .08 .33 

r(Log([THC]+1),Side Contacts) .16 .24 .04 -.19 .31 .47' 

r(SDLP,X) . -.47' -.50' -.42' -.56" -.47' ' -.27 

r(SDLP,Side Contacts) .41 .38 .10 .41 .27 .38 

Table 4.5 shows that SDLP was not related :to prevailing plasma levels of THC. Another driving 

performance measure, mean speed, was only moderately, yet consistently, related to THC; 

subjects having high [THC] values drove slower than those having low [THC] values. Driving 

performance was moderately related to critical tracking; poorer tracking performance on the road 

(higher SDLPs) concurred with poorer tracking performance in the laboratory (lower )'s). 

Five percent of the driving tests undertaken in this experiment yielded SDLP scores above 

the normal limit of 35 cm (Table 4.6). This limit was established by several hundred young and 

middle-aged volunteers and psychiatric patients who uniformly failed to achieve higher scores 

in the same test after being treated with placebo in all of the Institute's studies since 1986. It is 

illuminating to examine the present drivers who drove over the limit with respect to their prior 

treatments and the plasma concentrations of THC and its metabolite they exhibited at these 

times. ­

Table 4;6 Drug levels and SDLPs from those subjects whose SDLPs exceeded 36.0 cm. 

[THC] [THC-COON] SDLP 

Subject Condition Trial ((ng/ml) (ng/ml) (cm) 

1523 100 ug/kg 2 2.5 3.2 38.7 

1503 200 μg/kg 2 1.7 5.1 36.3 

1523 200 μg/kg - 1 8.8 6.7 39.2 

1523 200 μg/kg 2 4.3 4.3 37.0 

1527 200 ug/kg 2 10.0 16.2- 39.4 

1506 300 μg/kg 2 9.8 3.8 '36.6 

1523 300 μg/kg 1 18.0 11.5 36.9 

1523 300 μg/kg 2 5.2 9.2 39.3 

1526 300 μg/kg 2 6.7 16.2 36.6 

These data are important in two respects. Aberrant driving performance never occurred after 

placebo smoking, only once after the lowest THC dose and with equal frequency (4x) after both 

-43­
of the higher doses. Moreover, aberrant driving generally occurred during the second and not 

the first ride in direct opposition to the trend in plasma THC concentrations. From this, it's easy 

to infer the futility of predicting changes in SDLP, and presumably other aspects of driving 

performance, from a single [THC] estimation. 

Correlations were also computed between drug plasma concentrations and changes in driving 

performance from placebo to marijuana conditions. These correlations were generally smaller 

than those involving the raw scores. Thus, [THC] does not predict changes in that performance. 

Relationship between Driving Performance and Frequency of Current Use. Subjects were 

classified into two categories according to the frequency of reported cannabis consumption. 

Twelve subjects were infrequent users; i.e., between once weekly to once monthly; eleven 

subjects were classified as frequent users; i.e. at least once weekly but less than daily. SDLP 

values then entered a repeated measures MANOVA with Frequency of use as a between-groups 

factor, and Dose and Time as within-subjects factors. MANOVA failed to show a main effect 

of Frequency; interactions of Frequency and the other factors were also not significant. 

Relation between Driving Performance and Driving under the Influence Experience. 

Subjects were classified into two categories according to the frequency of reported driving within 

one hour of cannabis consumption (see Table 3.1). SDLP values then entered a repeated 

measures MANOVA with Experience as a between-groups factor, and Dose and Time as within 

subjects factors. Neither Experience nor any interaction was significant. 

Relation of Willingness to Drive to Perceived "high" and Driving Performance. The 

relationship between willingness to drive and changes in SDLP and perceived "high" was 

determined as follows. Groups were defined by their willingness to drive; i.e., two groups were 

defined comprising those subjects who would not have driven and those who would, for each 

combination of condition (4x), sampling time (2x) and urgency of circumstance (3x), separately. 

Student's 2-tailed t-test for independent means was employed to determine whether the groups 

had significantly different change scores (drug minus placebo) of SDLP and perceived "high". 

Thus, 18 different t-lest were performed for each variable, SDLP and perceived "high". 

Criterion for statistical significance was set at .01 because.of the large number of tests. No 

significant differences in SDLP change were found between subjects willing and those reluctant 

to drive. With respect to changes in perceived "high", only two significant effects were found. 

Subjects willing to drive under the imagined circumstance B ("important but avoidable") at both 

sampling times in the 200 μg/kg condition felt less "high" than those who would not drive. 

However, this observation is not of major concern, since it was not supported in the other 

conditions and circumstances. From these results, it can therefore be concluded that subjects' 

willingness to drive was not related to either perceived "high" or driving performance. 

DISCUSSION 

This study demonstrated that marijuana impairs driving performance as measured by an increase 

in SDLP; all three THC doses significantly affected SDLP relative to placebo. It is remarkable 

that driving impairment was about the same after the two higher doses. This cannot be due to 

a ceiling effect, since greater deterioration in road tracking performance has been found after 
 *

many prescription drugs (e.g. Robbe et al., 1989) and also high doses of alcohol (Louwerens

et al., 1987). One possible explanation for the lack of a clear dose related impairment may be

that subjects were able to mitigate the effects of the highest dose by "trying harder". Indeed,

subjects reported putting more effort in performing the test after smoking the highest THC dose.

In other words, subjects tried to overcome the perceived disparity between their actual state and

the one required to drive the car efficiently; the higher the THC dose, the greater the disparity

between the actual and required states, and the harder they tried to compensate for it.

Though marijuana's adverse effects on SDLP were somewhat smaller in the second test than

in the first, no significant interaction was found between the treatments and repetition of the test.

This means that the driving performance decrement after smoking marijuana persisted almost

undiminished for two hours after smoking.

What is the practical relevance of the size of. the effects of marijuana upon lateral position

variability? This can be inferred by comparing marijuana's effects to those of alcohol in the*

same test. As cited above, Louwerens et al. (1985, 1987) conducted a study to establish the

dose-effect relationship of alcohol. Their study resembled the present one in many aspects: they

applied exactly the same driving test, the study was performed on a closed road, and involved

the participation of 12 male and 12 female volunteers. They were able to derive an empirical

equation for predicting the change in SDLP from placebo levels with increasing blood alcohol * 

concentrations. Mean SDLP began to change significantly at blood alcohol concentration of

0.03 g% and increases exponentially to the point where the-vehicle's lateral motion can no

longer be restricted to within lane boundaries (at about BAC = 0. 12-0.15 g%, on the average).

Equivalent BAC effect (g) 0.10 r

® TRC-loo K^x THC-200 M THC-300

0.08

0.06

0.04

0.02

0.00

First Second

Driving Test

Figure 4.7 Comparison of mean SDLP changes after marijuana smoking to

those associated with BAC.

Elevations of the group's mean SDLP in the first and second test after smoking 100, 200

and 300 μgfkg are presented in Figure 4.7, but now as their respective BAC equivalent

-
producing the same driving impairment. Two tentative conclusions can be drawn from these 

data: first, small doses of THC are capable of impairing driving performance; secondly, 

performance deterioration is only little worse, yet equivalent to BACs over the Dutch legal limit 

of 0.05 g%, when much higher doses are smoked. 

As mentioned above, mean SDLP values did not change greatly over time. The same can be 

said of mean subjective driving quality ratings. Yet other parameters did change over time; THC 

in plasma, perceived "high", heart rate elevation and perceived effort to accomplish the driving 

test were all less in the second test than in the first. Another important observation was made 

when the 5% highest SDLPs were examined in greater detail. Nearly all of these scores were 

recorded in the second rather than the first driving test after smoking higher THC doses. It may 

be that subjects did not try to compensate as much during the second ride because they felt less 

intoxicated. Whatever the reason, these results clearly indicate that the behaviorally toxic effect 

of THC had not yet dissipated. This means- that "behavioral intoxication" may outlast 

physiological and subjective marijuana intoxication, a phenomenon already reported by other 

investigators (e.g. Reeve et al., 1983; Yesavage et al., 1985). On the other hand, • subjects' 

perceived driving performance, measured retrospectively, did not change from the first to the 

second test when compared to placebo. Thus, while they felt less intoxicated in the second test 

they realized that their driving impairment was still the same as in the first test. Subjective 

feelings of "high" should therefore not be equated with subjective feelings of impairment, as is 

often done. 

Some investigators (Klonoff, 1974; Hansteen et al., 1976) found that marijuana impairs 

lateral position control as measured by number of cones hit in slalom tests. Others (Casswell, 

1979; Attwood et al., 1981) did not find any effect of marijuana upon lateral position control 

as measured in a similar way as in the present study,. presumably due to the low THC dose (6.25 

mg in Casswell's study) or the small number of subjects (eight in Attwood's study). Peck et al. 

(1986) found that the number of cones hit decreased after smoking marijuana, probably due to 

a reduction in speed. Most of these studies also measured alcohol's effects (BACs between 0.04 

and 0.10 g%) on lateral position control. It was generally-concluded that marijuana's effects 

were less than alcohol's, especially at BACs of 0.08 g%. Marijuana's effects on lateral position 

variability were significant, yet not dramatic, in the present study and always less than or equal 

to the equivalent BAC effect of 0.07 g%. The reduction in mean speed, though small, fits also 

well with previous findings. It can therefore be concluded that this study's results are in close 

accordance with previous closed-course driving studies of THC effects on vehicle handling 

parameters. This implies that simple psychomotor functions involved in driving are impaired by 

normally consumed THC doses, though not to such an extent that traffic safety is seriously 

compromised. _ 

Yet disturbing observations of two individuals' attentional deficits were observed; a sudden 

loss of the ability to shift attention from the prescribed task to an unexpected event (screwdriver 

on the road) and the lack of anticipation for a normal event (end of circuit). Since perception 

and attention are important aspects of actual driving, these instances may indicate an unusually 

hazardous property of THC when the drug is consumed shortly before operating a vehicle. 

Therefore, the revised conclusion must be: what was measured was only moderately affected by 

THC, but another major deficit may have existed after the highest dose which bears further 

examination. One can not conclude whether the standard driving test applied in this study 

measures the most important deficits. 

-46­
Important practical implications of the study are whether driving performance decrements can 

be predicted by prevailing plasma concentrations of the drug. Though average [MC] and 

[THC-COON] values were clearly dose-related, driving impairment reached a ceiling before the 

highest concentrations were achieved. Inter-subject correlations between plasma concentrations 

of the drug and driving performance after every dose were essentially nil, partly due to the 

peculiar kinetics of THC. It enters the brain relatively rapidly, although with a perceptible delay 

relative to plasma concentrations. Once there, it remains even at a time when plasma 

concentrations approach or reach zero. The conclusion is that driving impairment cannot be 

predicted by prevailing plasma concentrations of THC or THC-COOH. 

Another way of predicting driving impairment was explored; namely, by performance in 

laboratory tests that might be potential "roadside" tests. Hand steadiness was impaired by 

marijuana after high doses but not after 100 ug/kg. Performance in this test was not related to 

driving performance: Previous studies employing the same test (Clark et al., 1970; Milstein et 

al., 1975) showed greater sensitivity to marijuana-induced impairment of hand steadiness. In 

-those studies subjects were not allowed to rest their hands on the table, which is probably the 

major reason for the observed difference. In fact, the present' and the preceding study merely 

measured finger rather than hand steadiness. The conclusion must be that hand steadiness was 

not properly tested, but the results suggest that it is not possible to predict driving impairment 

by means of hand steadiness performance. 

Critical tracking performance was another candidate for being a good "roadside" test. Yet 

this test failed to show any effect of marijuana which is in conflict with prior research conducted 

by . Sharma and Moskowitz (1975) and more recently Moskowitz 'et al. (1981).. They 

demonstrated that a THC dose. of 200 μg/kg impairs critical tracking performance for at least 

up to 4 hours post-smoking. Peck et al. (1986), however, also reported a failure of marijuana 

alone (1.0 g cigarette containing 1.9% THC) to affect X scores. They hypothesized that their 

conflicting results could be explained by their subjects' greater cannabis experience and 

tolerance. Although the same argument could be applied in the present study, it is suspected that 

the failure,to detect significant changes in k after marijuana smoking is due to the particular 

version employed in this and the pilot study (this group's mean values after placebo were also 

considerably lower than those commonly found in healthy volunteers). The device used was a 

commercial PC/AT version of CTT which was originally programmed on a Commodore-64 

computer. The latter has been successfully applied in psychopharmacological research by the 

authors and their colleagues and hitherto appeared as a very sensitive test for drug-related 

impairment (e.g. Robbe et al., 1989; Ramaekers et al., 1992a). This study was the first in which 

the commercial PC/AT version was employed, so the conclusion that the software or hardware 

was not well designed seems inevitable. 

All subjects were willing to undertake the driving tests. But test conditions were artificial and 

the same individuals may or may not have been willing to drive under normal circumstances. 

Therefore, one questionnaire inquired into the subject's willingness to drive an automobile when. 

experiencing the same drug effect under "normal" conditions. Subjects' willingness to drive was 

related both to consumed THC dose and urgency: After smoking a low THC dose, nearly all 

were willing to drive, especially for urgent reasons. After higher doses, fewer were willing to 

drive under all circumstances. According to what subjects said, they did not become less 

cautious after inhaling increasingly large doses (unlike what is often reported about alcohol). On 

the contrary, their caution increased with intoxication. Still, 50% of the subjects reported that 

they would have driven for an unimportant reason shortly after smoking the two highest THC 

-47­
doses. Since willingness to drive was not related to objective driving impairment, it may be 

concluded that at least some of the subjects either were.not, able to appraise their driving 

performance before they had actually driven or did not consider their impairment as critical. 

It is interesting to compare plasma concentrations of THC found after smoking the highest 

THC dose in this study with those found in the pilot study. The highest dose administered in the 

present study was comparable to the average dose the same subjects consumed in the pilot study. 

Mean plasma concentrations of THC after the highest dose in the present study, determined 30 

and 90' minutes after initiation of smoking, were 50 and 40% higher than those measured in the 

pilot study after 40 and 100 minutes. This large difference can only be partially explained by 

the 10 minutes delay between the two stadies' -blood .sampling schedule. Apparently, subjects 

smoked more efficiently in this than the previous study. Since most volunteers were used to 

smoking hashish instead of marijuana, the increased efficiency compared to that in the pilot 

study may be explained by familiarization with the particular formulation of the drug. 

One of the objectives of this study was to determine whether or not the same experimental 

conditions could be implemented in a study on marijuana's effects on driving on a primary 

highway public for other traffic. All subjects were willing and able to finish the driving tests 

without great difficulty. Incases of the exceptional. events, the driving instructor was able to 

control the situation, safely. The effects of marijuana on SDLP were never so large as after 

many other drugs that had been safely studied in the presence of other traffic. Furthermore, it 

can be inferred from what subjects said and did that they would not be expected to seek 

dangerous situations and would be' responsive to the instructor's advice. Normal safeguards were 

deemed sufficient to ensure safety. Hence, the final conclusion was that it would be safe' to 

repeat this study on a normal highway in the presence of other traffic. 
CHAPTER 5 - MARIJUANA AND DRIVING ON A NORMAL HIGHWAY

IN TRAFFIC

INTRODUCTION 

The preceding study showed that the average driving impairment on a closed highway segment 

was never particularly great after doses of 100, 200 and 300 μg/kg THC (equivalent to 

impairment at 0.05 to 0.07 g% BAC) making it ethically acceptable to test the same doses' 

effects on performance in a more natural environment. It seemed essential to do so because the 

extent to which one can generalize from closed-course testing to the real world is presently 

unknown. Therefore, the same approach was applied for testing THC's effects on driving 

performance in a more realistic situation.. In particular, the same THC doses were administered 

to a new group of subjects undertaking similar driving tests, though now on a highway in the 

presence of other traffic. 

The present study was only the second wherein subjects drove in real traffic after receiving 

THC treatments. It was the first in which subjects inhaled higher "street doses" of THC before 

driving. Though the preceding study on a closed highway failed to show dramatic effects of.high 

THC doses on high-speed driving,, a conservative approach was chosen in designing the present 

study in order to satisfy the strictest safety requirements. This approach is unique in traffic 

science but closely follows the procedure used to determine the tolerability of medicinal drugs 

in human pharmacological research. It is to test THC's effects on actual driving performance 

in an ascending dose series (below). If any subject would have reacted in an unacceptable 

manner to a lower dose, he/she would not have been permitted to receive a higher dose. 

The major objective of this study was to confirm the relationship between inhaled THC dose 

and lateral position variability in the context of a standard road tracking test. A secondary 

objective was to measure performance in another actual driving test (i.e. car following) to 

determine whether degrees of impairment would correlate between the two tests in a manner 

indicating a general influence of THC on driving behavior. The third objective was to continue 

efforts to correlate plasma concentrations of THC and THC-COOH with driving performance 

impairment as measured in both tests. 

METHODS 

Subjects 

Sixteen new subjects, equally comprised of men and women, were selected according to the 

same inclusion/exclusion criteria as before. They were individually trained to perform the 

driving tests in a preliminary "dress rehearsal". Training at laboratory tests continued until each 

subject achieved satisfactory, asymptotical performance levels. 

Plasma analyses after conclusion of the study showed that one female's plasma contained 

neither THC nor THC-COOH in any sample. It was concluded that this subject had not inhaled 

smoke, so her data were excluded from further analyses. Characteristics of the remaining 15 

subjects are given in Table 5.1. T-tests for independent samples showed that males were heavier 

smokes than females (p < .007). There were no other significant differences between the sexes. 

-49­
Table 5.1 Mean±SD (range) of subjects' characteristics. 

Males Females 

(N=8) (N=7) 

Age (yrs) 28.3±7.4 (22-42), 25.0±4.6 (21-34)

Weight (kg) 70.8±7.0 (61.0-83-.5)* 66.7±7.9 (55.5-79.0)

Weight (lb) 156±15 (134-184) 147±17 (122-174)

Smoking Experience (yrs) 8.3±6.5 (2-21) 6.3±5.9 (1-16)

# Joints/Month 8.3±5.0 (1-16) 2.0±1.4 (1-4)

Driving Experience (yrs) 6.8±5.7 (2-20) 4.9±4.6 (1-15)

Driving Experience (km x 1000) 78±101 (10-320) 38±66 (5-188)

Driving Experience (mi x 1000) 48±63 (6-199) 24±41 (3-117)

# of Subjects Having Driven within

1 Hour following Cannabis Consumption:

less than 5 times 4 7

5 times or more 4 0

Design, Doses and Administration

The study was conducted according to an ascending dose series design where both active drug

and placebo conditions were administered, double-blind, at each of three THC dose levels. THC

doses were the same as those used in the previous study, namely 100, 200 and 300 μg/kg.

The lowest dose and placebo were administered in separate First Level treatment conditions 

spaced a week apart. Half the group received these treatments in the same order, the others in 

reverse order. Subjects proceeded to the next dose only if, in the driving instructor's opinion, 

no severe and potentially unsafe drug effects had occurred; and, if the subject was willing to go 

on to the next level. The intermediate dose and placebo were administered the same way in the 

Second Level conditions and the decision to proceed was made on the same grounds. The highest 

dose and placebo were administered the same way in the Third Level conditions to conclude the 

study. 

Marijuana cigarettes were prepared from batches supplied by NIDA, containing 1.77 % THC 

for the lowest, 2.64 % - THC for the intermediate, and 3.58 % THC for the highest dose. Doses 

were administered by smoking and cigarettes appeared identical at each level of treatment 

conditions. Cigarettes were smoked through a plastic holder in a fashion determined by the 

subject but with the constraint that smoking had to be finished within ten minutes. After 

cessation of smoking, cigarettes were retained for subsequent gravimetric estimation of THC 

consumed. These analyses revealed that the average (±SD) amount of consumed THC in the 

three marijuana conditions was 6.9 (±0.7), 13.8 (±1.4) and 20.7 (±2.2) mg, or 100 (±4), 204 

(±7) and 299 (±7) μg/kg, respectively. 

Testing Procedures 

Upon arrival at the laboratory, subjects' breath and urine were tested for the presence of alcohol 

and cannabinoids. If cannabinoids were found in the urine, a blood sample was taken for later 

verification of the presence of THC. Two subjects at a time commenced smoking at t=0 (Table 

-50­
5.2). Thirty minutes after onset of smoking the subjects performed a battery of laboratory tests 

(tracking, hand steadiness and body sway) and yielded a blood sample. They were then 

transported to a primary highway (A76, different than in the previous study) between the Dutch 

cities of Maastricht and Heerlen where the driving tests were performed. Two instrumented 

vehicles, the same as those in "the previous study, were employed in this study. One subject 

started the car following test (below) in the eastward direction whilst the other subject was sitting 

in the passenger's seat of the preceding car involved in the same test. The test was conducted 

on a 16 km (9.9 mi) circuit of the highway and lasted about twelve minutes. At the end of the 

circuit the car turned at a signalized intersection and parked at a service station, whereupon the 

subjects reversed roles to repeat the test running in the opposite direction. The new driver 

reentered the highway and began his/her car following test. After conclusion of the car following 

test, the subject left the highway at an exit ramp and reentered in the opposite direction on the 

associated entrance ramp. Thereupon both vehicles parked on the paved shoulder. 

Table 5.2 Schedule of activities on test-days. 

Relative Time (min) Activity 

0-10 Smoking 

30-40 Tracking, Hand Steadiness and Body Sway Tests 

40-45 Blood Sampling 

55-70 Car Following Test (1st Subject) 

70-85 Car Following Test (2nd Subject) 

85-135 Standard Driving Test (Both Subjects) 

140-155 Car Following Test (1st Subject) 

155-170 Car Following Test (2nd Subject) 

190-195 Blood Sampling 

195-205 Tracking, Hand Steadiness and Body Sway Tests 

Both subjects -then commenced the standard driving test (below) in separate instrumented vehicles 

at t = 85 and t =88, respectively. The test circuit was the same as for the car following test. 

Subjects drove twice around the circuit (in total, 64 km or 40 mi) without stopping in about 50 

minutes. At the conclusion of this test, both subjects participated again in the car following test 

in the same order as before. Subjects were then transported back to the laboratory where they 

yielded a blood sample and repeated the test battery. 

Two pairs of subjects were tested per test night. One pair performed the driving test in 

daylight, i.e. between 19.30 and 21.30 hours; the other pair commenced driving at 21.30 hours 

and finished at 23.30 hours in darkness. 

Driving Tests 

The standard test was-the same as described in the previous study (Chapter 4) except for its 

duration and the presence of other traffic. Subjects were instructed to maintain a constant speed 

of 95 km/h (59 mph) and a steady lateral position between lane boundaries in "the right traffic 

-51­
lane. They were allowed to deviate from this only if it would become necessary to pass a slower 

vehicle in the same lane. Data from the standard test were analyzed to yield the same 

performance measures as in the previous study; namely, standard deviation of lateral position 

(SDLP), mean and standard deviation of speed (SP and SDSP), and standard deviation of 

steering wheel angle (SDST). 

The car following test measures drivers' ability to perceive changes in a preceding vehicle's 

speed and to react in a manner maintaining a constant headway. It began as the preceding and 

the following vehicle, respectively driven by one of the driving instructors and the subject, 

operated in tandem on the slower traffic lane while travelling at a speed of 100 km/h (62 mph). 

The subject was instructed to maintain a 50 m (164 ft) headway however the preceding vehicle's 

speed might vary. After driving in this manner for about one minute, the operator of the 

preceding vehicle released the accelerator pedal allowing its speed to fall to 80 km/h (50 mph). 

Immediately thereafter, the operator of the preceding vehicle accelerated to 100 km/h (62 mph). 

The.duration of one deceleration and acceleration maneuver was approximately 50 seconds and 

six to eight, depending upon traffic density, were executed during one test. 

The velocity of the leading vehicle was transmitted via telemetry to a receiver in the 

following vehicle. This signal, along with the following vehicle's own velocity were recorded 

in parallel, time-coded files on computer files. These data entered a power spectral analysis for. 

yielding phase-delay, modulus or gain and coherence between the vehicle's velocities at the 

maneuver cycle frequency (i.e. 1/50 s = 0.02 Hz). The average phase-delay between 

frequencies of 0.01 and 0.03 Hz., encompassing the frequency of the deceleration and 

acceleration maneuvers, was then calculated and transformed to the time domain to yield a 

measure of the subject's average reaction time to the movements of the leading vehicle (RT; in 

seconds). This was taken as the primary dependent variable from the car following test. Gain 

and coherence were recorded -for control. purposes. If the test was performed according to 

instructions, gain should have a value of about 1.0, and coherence, >.90. 

During the trials, 3 to 6 direct measurements of separation distance between the following 

and leading vehicle were made by means of a S-VHS video recording system which was 

mounted between the following vehicle's front seats facing forward through the windshield. 

Images of the rear of the preceding vehicle were acquired prior to each decelerationlacceleration 

maneuver. The camera's internal clock signal was recorded . with the video imagery and also 

converted in an electronic pulse code for simultaneously computer recording along with the two 

vehicles' speed. 

Video imagery recorded throughout the trials were analyzed off-line using an interactive 

software routine implemented on a IBM-AT computer. A single frame would show the 

appearance of the preceding vehicle at the moment it begins to decelerate. Next the coordinates 

of two target markers, spaced 119 cm apart on the rear of the leading vehicle were identified 

on the display. From this information the distance separating the two vehicles or "headway" was 

calculated according to the equation, 

d (in m) = k (1 m / tan (612)) 

where k is a proportionally constant and 6 the horizontal angle subtended by the camera lens. 

Once the starting distance was determined from a single measurement, headway changes during 

the maneuver were calculated using differential speed according to the equation, 

H (r) _ VP dt - S Vf dt + Ho 

-52­
where headway varies as a function of time (t) according to the difference between integrals of 

velocities of preceding and following vehicles (VV,Vf) plus the headway .(HO) that existed at the 

beginning of the maneuver. Headway and coefficient of variation of headway (CV-Headway) 

during maneuvers were taken as secondary dependent variables. The coefficient of variation of 

headway, and not standard deviation, is preferable because of the latter's confounding by mean 

headway. -. 

Questionnaires

The same subjective questionnaires used in the previous study were administered to the subjects

in the present study. Subjective feelings of "high", present cognitive and emotional state, and

subjects' willingness to drive were assessed before the onset and after the conclusion of the

driving tests (t=50 and 175). Subjects-were also asked about their perception of the administered

treatment, whether it was THC or placebo. At the end of each driving test, subjects were

required to retrospectively rate the effort given in performing the test and perceived driving

quality. Questionnaires are enclosed in Appendix A.

Laboratory Tests

Three tests were administered to the subjects: critical tracking, hand steadiness and body sway.

These were also administered in the preceding studies, but the equipment or procedures were

changed in this study.

I .­ Equipment, not procedures, changed in case of the critical tracking test (CTT). The test had 

shown no sensitivity to treatments administered in the preceding studies, in spite of the fact 

that other investigators had used the same test for showing significant effects of much lower 

THC doses. The validity of the particular MS-DOS version used in the preceding studies was 

doubtful. Therefore an older Commodore-64 version was employed in the present study. This 

version of the CTT " had proven its sensitivity to drug-induced sedation in several previous 

studies conducted by the authors and their colleagues (e.g. Robbe.et al., 1989; Ramaekers 

et al., 1992a). Test duration was approximately 5 minutes and mean X. was the dependent 

variable. 

2.­ As discussed in the previous chapter, the hand steadiness test examined finger rather than 

hand steadiness because subjects were allowed to rest their hands on the table. Subjects were 

not allowed to do this in the present study. The modification was expected to induce greater 

instability. Therefore, the diameters of holes were increased to avoid ceiling effects of the 

number of contacts between their sides and the hand-held stylus. The diminishing diameters 

of the five circular holes-were now set to 6.30, 4.70, 3.90, 3.05 and 2.70 mm (0.25., 0.19, 

0.15, 0.12 and 0.11 in) respectively. The dependent variable was again the square root of 

the total number of contacts of the stylus with any side. The test lasted about 3 minutes. 

3.­ Postural instability, or body sway, was measured using the stabilometry method (Kapteyn 

et al., 1983). It involved the use of a balance platform that measures the location of the 

vector of force which extends vertically downward from the body's center of gravity and its 

movement over time. Analog output of force transducers within the platform were digitized 

-53­
and analyzed to yield simultaneous measures of lateral and sagittal motion around the vertical 

axis. Subjects were instructed to maintain a static posture while standing over the center of 

the balance platform with their feet together. Two, 30-second recordings followed. The first 

with the subject's eyes open, the second with eyes closed. While standing with the eyes 

open, the subject was required to fixate on a target mounted on the wall from a distance of 

2.0 in (6.6 ft). The mean area circumscribed by the vertical vector of force (i.e. curve 

surface, in mm2) was taken as the dependent variable (CS-O and CS-C for eyes open and 

closed, respectively). t 

Physiological Assessments 

The electrocardiogram (ECG) was measured from precordial leads (RC5), and the interbeat 

interval (IBI) times were registered continuously during the driving tests. Cardiac interval times 

were analyzed to yield three different parameters, mean IBI, the coefficient of variation 

(CV-IBI), and relative amplitude in the power density spectrum between the frequencies of .07 

and .14 Hz (PWR-HR). 

CV-IBI, is defined as standard deviation of IBI divided by the mean. It is the best measure 

of IBI variability in the time domain. The coefficient of variation, and not the standard 

deviation, of IBI is preferable because of the latter's confounding by mean IBI. 

PWR-HR is a variability measure within a restricted region of the frequency domain and 

calculated from the time series of instantaneous heart rates, which are computed at each 

successive heart beat. It is defined as the integrated amplitude in the power density spectrum 

between 0.07 and 0.14 Hz. 

Mean interbeat interval, and more frequently its reciprocal, mean heart rate, is frequently 

used for measuring THC's chronotropic cardiac effect. As shown in the previous study, the 

measure is valuable for assessing the course of the drug's activity over time. However the other 

measures, , CV-IBI and PWR-HR, possess greater psychological significance. They are 

alternatively used for estimating relative changes in an individual's mental workload, or more 

correctly the amount of mental effort he must exert for handling a particular workload. In 

general, both measures vary inversely with the imposed mental workload or the increase in 

mental effort which is required to cope with a constant workload while maintaining the same 

level of performance efficiency under the influence of drugs or fatigue (Mulder, 1980; Mulder 

and Mulder, 1981). 

Blood-Sampling 

Blood samples were obtained from the subjects by venepuncture immediately before they were 

transported to the' test site and immediately after their return, or approximately 35 and 190 

minutes after initiation of marijuana smoking. Two aliquots containing 10 ml each were 

heparinized and centrifuged, and the plasma fractions were placed in frozen storage for later 

assays to determine [THC] and [THC-COOH]. The analytical procedures were the same as those 

employed in the preceding studies. 
Data Analysis 

The first step executed was determining the reliability and consistency of performance and 

subjective parameters measured in the successive placebo treatment conditions. Test-retest 

reliability coefficients were determined and mean differences between data collected in 

successive conditions were tested for significance using repeated measures MANOVA. Previous 

studies wherein unmedicated subjects performance was repeatedly measured in the standard test 

have failed to show any significant changes over time intervals as long as one week; and, testretest reliability coefficients for the SDLP measure have always been higher than r=.80. 

However, intervals separating successive placebo tests were longer in the present study and the 

reliabilities of measures obtained in the car following test had yet to be determined. For these 

reasons it appeared necessary to check the consistency of the subjects' performance in the 

present study. 

Subsequently, data from drug and placebo conditions on the first, second and third levels 

were analyzed separately. Performance variables recorded on ratio or interval scales were 

subjected to repeated measures MANOVA with Sex as a between-groups and Drug (placebo 

versus marijuana) as a within-subjects factor. The effect of Time of testing (2 levels) was, if 

pertinent, simultaneously tested as a within-subjects factor in the same analyses. 

It appeared that marijuana's effects on reaction time in the car following test were 

confounded by mean headway. Reaction times were therefore also analyzed by means of 

covariance analysis, using headway as the covariate. Covariance analysis estimates what the 

scores on one variable (in this case, reaction time) would have been if the same "average" score 

on another variable (in this case, mean headway) would have occurred in all conditions. It 

allows one to estimate the effects of THC on reaction time independently of those on headway. 

Willingness to drive data were analyzed in the same manner as the parametric data. That is, 

data from drug and placebo conditions on the first, second and third levels were analyzed 

separately. Thus, data from both sampling times in a drug condition and its respective placebo 

condition were simultaneously tested for assessing differences in the proportion of subjects 

willing to drive for a particular reason. 

Separate dose effects were tested using the "Sequential Bonferroni" procedure for adjusting 

the a-probability criterion (p,) in accordance with the number of separate comparisons in a given 

set (Overall and Rhoades, 1987). For the largest of three differences tested at once, p had to be 

less than .05/3 =. 0 17 to be judged significant. For the second, it had to be < .05/2 =..025; and 

for the smallest difference, p < .05. The adjustment had the effect of holding the probability of 

making a type .I error at p:5.05 over the entire set of comparisons. 

Though data from both the marijuana and respective placebo condition entered MANOVA, 

figures illustrating the results display mean difference scores (drug - placebo) and standard errors 

of the difference (SED). The former are depicted by the height of the bars, the latter by the 

vertical lines above or below the bars. Difference scores were used in order to keep the figures 

as simple as possible. As a consequence, main effects of Time could not be depicted in the 

figures: a parallel rise or fall in the mean levels of a variable over time would not affect their 

difference. This is, however, not a major problem, since it is not very interesting to know 

whether subjects' performance changed in both conditions in the same manner. More interesting 

is a Time by Drug effect, which means that the difference- between effects of marijuana and 

placebo changed over-time. This effect would be obvious in the figures. 

Significant Sex effects were generally absent. Results pertaining to differences between the 

sexes are therefore mentioned only in the exceptional cases where these were significant. 

-55­
RESULTS

No subject dropped out during the experiment, neither on their own initiative nor on the driving 

instructor's. Therefore, the results presented below include data from fifteen subjects at each 

level of treatment. It was impossible to obtain every blood sample from one woman, even after 

repeated attempts. Her data were therefore excluded from all analyses involving drug and 

metabolite plasma concentrations. However, assays of what samples were obtained indicated that 

she did inhale THC. Consequently, her data were not excluded from other analyses. 

Test-Retest Correlations and Consistency of Performance 

Correlations between measurements obtained from the successive placebo treatment conditions 

are shown in Table 5.3.', Correlations between repeated SDLP's were somewhat lower.than those. 

obtained in earlier studies for "normal" subjects, but were still both highly significant and 

consistent. Mean and standard deviation of speed were also quite reliable. 'Steering wheel 

variability, however, was not 'a reliable measure. 

Table 5.3 Correlations between parameters measured at the same time in the successive placebo 

treatment conditions (*p<.05 ** p < .Ol; one-tailed). 

1S' and 2nd placebo 2nd and 3' d placebo * 1S` and 3"d placebo 

1S' test 2nd test 1S' test 2nd test 1 5L test 2"d test 

Standard Driving Test: 

SDLP 

SP 

.75" 

.61" 

.76" 

84" 1 

.72" 

.77" 

SDSP .66" .69" .55' 

SDST -.21 .17 -.62 

Subj. Driv. Quality .24 .24 .30 

Perceived Effort .72" .50' .56' 

Car Following Test: 

Headway .73" .31 .60" .90" .67" -.0-1 

CV-Headway .48 _ .19 .36 .40 ..55' .07 

RT .61 .45' .81" .68" .64" .09 

Subj. Driv. Quality .51' .06 .64" .28 .61" -.06 

Perceived Effort .72" .80" .67" .69" .33 .71" 

Laboratory Tests: 

k .68" .70" .73" .87" .67" .78" 

Side Contacts .75" .80" . .84" .66" .63" .63" 

CS-O .43 .49' .20 .62" .04 .31 

CS-C .25 .56'. .71 .18 .37 .41 

Other Subjective Feelines: 

Alertness .44' .92" .88" .78" .59' .75 

Contentedness .52' .79" .76" .77" .46' .59 

Calmness .71" .34 .87" .41 .51' .22 

56
Subjective driving quality ratings were also unreliable, probably due to restriction of range; i.e. 

most subjects naturally rated their driving performance as ' about normal (100%) following 

placebo treatment. Perceived effort ratings were somewhat more reliable, indicating that driving 

under the conditions of this study was consistently a more effortful occupation for some subjects 

than others. 

Car following parameters were not as reliable as those measured in the standard driving test. 

Performance in the second ride in the first placebo condition.. was not related to that in the 

second ride of the second and third placebo conditions. This means that the test still needs 

further standardization to reduce the error variance of the measures tested. Ratings of perceived 

effort in the car following test were only slightly more reliable than those obtained in the 

standard test. Remarkably, ratings of subjective driving quality were highly reliable in the first 

car following test, but not in the second. 

Hand steadiness and k, but not body sway measures, were highly reliable. Ratings of 

alertness, contentedness and calmness were moderately reliable. Surprisingly, alertness and 

contentedness ratings were generally more reliable when measured after driving, in contrast to 

calmness ratings which were more reliable before the driving tests commenced. Correlations 

between perceived ratings of "high" were not computed since they were generally very low or 

zero following placebo. 

Mean differences between data collected in successive placebo treatment conditions were 

tested for significance using repeated measures MANOVA. Only k changed nearly significantly 

over successive placebo treatment conditions (F2,12=3.81; p < .052); subjects' performance in 

this test improved during the study (14=4.6, 4.8 & 5.0, for the respective placebo conditions, 

averaged across both sampling times). Obviously performance had not reached an asymptotic 

level during practice trials which preceded the beginning of experimental sessions. 

Plasma Concentrations of the Drug

Table 5.4 shows mean, median and range of [THC] and [THC-COON] by Dose and Time.

Placebo values were not used in the statistical analyses since these were zero in most cases.

Therefore, data from all THC conditions were analyzed in one MANOVA. The tabular data

indicate that [THC] was related to inhaled THC dose, and fell to about the same level three

hours after smoking.

Table 5.4 Mean, median and range of [THC] and [THC-COOH] in ng/ml (N=14).

100 μg/kg 200 pg/kg .300 μg/kg 

t=35 t=190 t=35 t=190 . t=35 t=190 

mean 7.9 0.7 12.0 1.1 16.1 1:5 

[THC] median 6.5 0.9 10.0 1.0 15.8 1.5 

range 0.8-17.2 0.0-1.3 1.5-27.1 0.0-2.7 4.7-30.9 0.4-3.2 

mean 8.2 4.1 12.2 7.61 15.3 10.0 

[THC-COON] median 7.4 4.1 11.2 6.4 13.0 8.2 

range 1.4-19.4 0.0-12.0 2.0-37.2 0.0-32.2 4.2-39.6 1.5-36.3 

-57­
 *

MANOVA confirmed this impression with significant Dose (F2111=20.75; p<.001) and Time

(F,.12=54.81; p < .001) effects, and Dose by Time interaction (F2.11=17.80;p< .001). Males had

somewhat higher [THC] than females and the Sex effect approached significance (F1112=4.60;

p < .053); Sex by Dose interaction was not significant.

Plasma levels of the metabolite, THC-COOH, were about the same as those of THC 35

minutes after initiation of smoking, but did not decline as rapidly. Table 5.4 shows that

[THC-COON].was also dose-related at both sampling times. Significant Dose (F2,11=14.49;

p <.001) and Time (F1,12=62.50; p <.001) effects, but no Dose by Time interaction, were shown

by MANOVA.

T_

Perceived "high"

Ratings of "high" after placebo were near zero in most cases. Therefore changes occurring after

marijuana smoking, relative to placebo, instead of the raw values, were analyzed by MANOVA.

Average subjective feelings of "high" were dose-related and greatest just before the first driving

test (Figure 5.1). Relative to maximum personal experience, peak levels of intoxication were

Perceived "high" 100% r

90% - t=50 ® t=175

80% * 

70%

60%

50%

40%

30%

207

109:

0%

100 200 300

THC Done

Figure 5.1 Mean (+SED) changes in perceived "high" by Dose and Time,

relative to placebo.

about 30%, 50% and 75% after 100, 200 and 300 ,ug/kg doses. The approximately linear

correspondence between the administered dose and average subjective response was impressive.

Change scores were significantly dose-related (F2.12=35.07; p < .001) and time-related

(F1.13=40.25; p<.001). The decline in feelings of "high" over time was also dose-related,

resulting in a significant Dose by Time interaction (F2,12=7.87; p < .007).

-58-
Driving Performance in the Standard Driving Test 

All subjects undertook and completed each test in a safe manner; the driving instructors neither 

terminated any ride prematurely nor intervened while subjects were driving. In other words, the 

subjects' safety was never compromised. 

Figure 5.2 shows the mean changes in SDLP from placebo to marijuana conditions. 

Performance after consuming THC was worse than after the respective placebo treatment; mean 

changes in SDLP were 1.1, 1.8 and 2.9 cm for the. 100, 200 and 300 μg/kg conditions, 

respectively. MANOVA showed that SDLP was significantly elevated after inhaling both the 

higher, but not the lowest, THC doses relative to placebo (F1.13=2.66, 6.63 & 10.16 for the 

100, 200 and 300 μg/kg conditions, respectively; p<.13, .023 & .007; p"=.05, .025 & .017). 

No significant differences between males and females were discovered. 

SDLP (cm)

5.0 r 

3.0 

2.5 

2.0 

1.5 

1.0­

0.5 

0.0 

100 200 S00 

TSC Dose 

Figure 5.2 Mean (+SED) changes in standard deviation of lateral position in 

the standard driving ..test by Drug, relative to placebo. 

Mean speed was very close to that established as the target by instructions' and varied between 

conditions from 94.5 to 96.1 km/h (58.7 to 59.7 mph). Subjects drove slower following 

marijuana than following placebo, but the mean differences were quite small: 0.3, 1.1 and 

0.5 km/h (0.2, 0.7 and 0.3 mph) for 100, 200 and 300 μg/kg conditions, respectively. 

MANOVA showed that only the change after the intermediate dose was significant (F1.13=8.05; 

p<.014; p,=.017). 

Standard deviation of speed was very small in each condition, on average 2.5% of mean 

speed. Though speed variability increased after smoking THC, the effects were minor and not 

-59­
significant. Standard deviations of steering wheel movements were also not affected by THC; 

mean changes after smoking THC were essentially nil. 

Subjects rated their driving performance in the standard test as about "normal" after smoking 

placebo and after the lowest dose of THC. Ratings were 90% and 77% of "normal" driving 

performance following the 200 and 300 jig/kg conditions, respectively. Changes relative to 

placebo are shown in Figure 5.3. MANOVA demonstrated that changes in perceived driving 

quality approached the levels of significance required by the "Bonferroni" adjustment after the 

two higher THC doses (+ 1.13=5.29 & 5.42 for the 200 and 300 μg/kg conditions, respectively; 

p<.039 & .037; p,=.025 & .017), but were not significantly different from placebo after the 

lowest THC dose. 

Perceived driving quality

10% r

0% 

-10% 

-20% 

-30% 

-40% 

-50% 

100 200 900 

TEC Dose 

Figure 5.3 Mean (+SED) changes in perceived driving quality in the standard 

driving test by Drug, relative to placebo. Raw scores were expressed as 

percentage of "normal". 

Changes in perceived effort ratings were trivial after the two lower THC doses. Effort did 

increase from 29 % after placebo to 39 % following the highest dose. MANOVA failed, however, 

to reveal any significant effects of THC on perceived effort. 

Half of the subjects performed the driving tests in darkness, the other half under daylight 

conditions. Therefore, repeated measures analysis was again applied. to the data, but now with 

LightlDarkness as a between-groups factor. No significant differences were found between the 

groups for any variable. 

60
 *

Driving Performance in the Car Following Test

All subjects were capable of performing the car following test in each treatment condition. There

was no need for the driving instructors to ever intervene or prematurely terminate the test. In

one instance, a subject needed the driving instructor's help after smoking the highest THC dose.

The subject appeared confused when he took his seat in the car prior to the first car following

test. The driving instructor noticed the subject's uncertainty as to what he should do and advised

him to turn the engine on. Thereafter, the subject had no problems following the instructions and

completing the ride.

Mean headway varied between conditions from 44.5 to 54.9 in (146 to 180 ft); changes

relative to placebo are shown in Figure 5.4. It is interesting to note the inverse relationship

between THC dose and headway: the lower the dose the greater the headway, especially in the

first test after smoking. MANOVA showed that mean headway was significantly increased. after

smoking the 'lowest THC dose, relative to placebo (F1113=7.57; p <.016; p,=.017); the two

higher doses had no significant effect on headway. No significant Time or Drug by Time effects

were found in either THC condition.

20 Headway (m)

16

= lot ride ® tad ride 16

14-

12-

10

a

6

4

2

0

2

-6

-10

too 200

TEC Done

300

Figure 5.4 Mean (+SED) changes in headway in the car following test by

Drug and Time, relative to placebo.

Coefficients of variation of headway, expressed as a percentage, were high and varied between

conditions from 18.8% to 23.7%. Figure 5.5 shows an inverse relationship between

CV-Headway and administered dose, with the exception of the first ride after the highest dose.

MANOVA revealed a significant effect following the lowest dose (F1113=16.62; p<.001;

-61-

 *

 * * 

*
 *

pC=.017)., but not the higher doses. Drug by Time interaction approached significance following

the highest dose (F1.13=4.85, p<.046; p,= .017); 300 μg/kg THC produced an increased

headway variability in the first test after smoking, but not in the second.

CV Headway 10%r

let aide 2nd side

6%

4l

2%-

0%

-2%-

. -4%-

-870

100 200 300

TSC Done

Figure 5.5 Mean (+ SED) changes in coefficient of variation of headway in the

car following test.by Drug and Time, relative to placebo.

Mean. reaction time to perceived changes in the preceding car's speed varied from 1.56 to

2.30 s, between conditions. The changes, shown in Figure. 5.6, followed a similar pattern as

those of headway; the greatest increase of reaction time occurred after the lowest THC dose, and

the smallest after the highest dose. Reaction times were significantly increased after smoking

both 100 μg/kg and 200 μg/kg THC, but not 300 μg/kg (F1,13 =10.78, 6.26 & 1.88, respectively;

p < .006, .027 & .193; p,, =.017, .025 & .05). Reaction times were, however, strongly related * 

to mean distance (r=0.76, across all conditions). This is understandable: the further apart two

cars are, the more difficult it becomes for the subject to perceive changes in the preceding

vehicle's velocity.

One may question what the effect of THC on reaction time would have been if subjects had

driven at the same mean headway in all conditions? Covariance analysis of reaction time with

headway as covariate was applied to answer this question. Figure 5.7 shows the mean changes

in adjusted reaction times, from placebo levels. The figure makes clear that the differences in

the adjusted reaction times were much less than those in the original ones. Though each THC

dose increased reaction. time, none did significantly. This means that the elevation in the raw

reaction times following the lowest THC dose were simply due to a longer headway.

-62-
 *

Reaction time (s)

1.2 r

= lit ride ® 2nd ride

1.0

0.8

0.6

0.4

Vt

0.2

 * 

0.0

100 200 300

THC Dose

Figure 5.6 Mean (+SED) changes in reaction time in the car following test

by Drug and Time, relative to placebo.

Adjusted reaction time (s) 1.2

= lot ride ® 2nd ride

1.0

0.8

0.8

*

0.4 *

02

0.0 *

100 200 300

THC Does

Figure 5.7 Mean (+SED) changes in reaction time, adjusted for changes in

headway, in the car following test by Drug and Time, relative to placebo.

- 63 -
 *

Subjects rated their driving quality in the car following test as somewhat better than.normal

following each placebo, and worse following each THC dose. Changes from placebo to drug are

displayed in Figure 5.8. As for headway and reaction time, there was no clear dose-response

Perceived driving quality 10% r

M lot ride ® tad ride

o7

-10%

20%

:: z..

-50%

100 200 300

THC Dose

Figure 5.8 Mean (+SED) changes. in perceived driving quality in the car

-following test by Drug and Time, relative to placebo. Raw scores were

expressed as percentage of "normal".

relationship that determined how subjects rated their driving quality. Though they rated it the

worst after the highest dose overall their judgement after the lowest dose was nearly as critical.

MANOVA demonstrated that driving quality ratings after the highest dose were significantly

different from placebo, but those after the lower doses were not (F1.13=6.04, 3.19 & 13.84, for

the 100, 200 and 300 μg/kg conditions, respectively; p<.029, .097 & .003; p,=.025, .05 &

.017). Neither Time nor Drug by Time effects were significant. * 

Though perceived effort ratings were generally higher following THC than placebo,

MANOVA failed to show any significant drug effect.

Willingness to Drive

Table 5.5 presents the percentage of subjects willing to drive under specified conditions of

different urgencies (A. unimportant though gratifying; B. important but avoidable; and C.

urgent). Subjects' responses were similar to those in the previous study. The lower the

administered THC dose and the more urgent the reason for driving, the more subjects declared

that they would be willing to drive.

-64
Table 5.5 Percentage of subjects willing to drive under circumstances A, B & C (see text) by 

treatment condition and sampling time. 

0 μg/kg 100 μg/kg 0 μglkg 200 μg/kg 0 μg/kg 300 μg/kg 

A -t=50 93 53 93 47 93 27

t=175 93 80 80 87 93 53

B­ t=50 100 73 100 60 100 40

t=175 100 80.. 100 100 100 67

C­ t=50 100 93 100 93 100 73

t=175 100 93 100 93 100 87

Cochran's test showed that the numbers of subjects who would have driven for an unimportant 

reason following every THC dose were significantly less than after placebo (Qdf.3 = 12.0, 13.4 

& 21.6 for the 100, 200 and 00 4ug/kg conditions, respectively; p <.008, .004 & .0001; 

PC= .05, .025 & .017). The "e held true for the somewhat more important reason 

(Qdf-3 =10.2, 18.0 & 21.4 for the 100, 200 and 300 μg/kg conditions, respectively; p<:02, 

.0004 & .0001; pc=.05, .025 & .017). In contrast, the numbers of subjects who would have 

driven for an urgent reason after every THC dose were not significantly different from placebo 

(Qa1_3 =3.0, 3.0 & 9.4 for the 100, 200 and 300 gg/kg conditions, respectively; p <.40, .40 & 

.024; pr=.05, .025 & .017).. 

Perceived Alertness, Contentedness and Calmness 

Table 5.6 shows the mean subjective ratings of alertness, contentedness and calmness, presented 

as the percentage of maximum scale. Mean subjective ratings generally declined after smoking 

marijuana, relative to placebo, indicating that subjects then felt less alert, content and calm. 

MANOVA showed that subjects felt significantly less alert after smoking THC (F1.13=12.57, 

6.48 & 21.24 for the 100, 200 and 300 μg/kg conditions, respectively; p <.004, .024 & .001; 

PC= .025, .05 & .017). Furthermore, a significant Drug by Time interaction was found for the 

100 μg/kg condition (F1113=13.78; p<.003; p,=.017), due to the recovery in feelings of 

alertness from the first to the second time of testing. 

Contentedness ratings were only significantly reduced after smoking the highest THC dose 

(F1113=10.20; p <.007; pc=.017). Drug by Time interaction was significant in the 100 μg/kg 

condition (F1.13=7.71; p <.016; pp=.017). Calmness ratings also declined after the higher THC 

doses (F1.13=6.05 & 14.65 for the 200 and 300 μg/kg conditions, respectively; p <.029 & .002; 

PC=.025 & .017), and Drug by Time interaction approached significance in all conditions 

(F1.13 =4.33, 6.62 & 5.10 for the 100, 200 and 300 μg/kg conditions, respectively; p<.058, 

.023 & .042; pt=.05, .017 & .025). 

In summary, subjects felt less alert, content and calm after smoking each THC dose, relative 

to placebo. The effects were strongest and persisted throughout the testing session after smoking 

the highest dose. 

-65­
 *

Table 5.6 Mean (SE) ratings of alertness, contentedness, and calmness by treatment condition

and sampling time.

0 μg/kg 100 μg1kg 0 μg/kg 200 μg/kg 0 μg/kg 300 μg/kg

Alert t=50 78.3 (3.7) 59.0 (4.3) 76.0(4-4) 63.9 (4.1)., 80.0 (3.4) 57.7 (4.6)

t=175 69.6 (5.0) 64.7 (4.9) 72.4 (5.5)' 66.1 (3.6) 70.6 (4.3) 56.9 (6.2)

Content t=50 . 79.3 (2.7) 66.2 (5.1) 77.6 (3.3). 73.6 (3.6) 78.3 (3.4) 67.2 (4.4)

t=175 72.4 (3.4) 70.3 (4.3) 74.9 (4.4) 73.1 (3.5) 76.7 (3.2) 65.7 (4.9)

Calm t=50 78.2 (4.2) 64.2 (5.2) 79.5 (4.4) 61.7 (6.8) 79.5 (3.6) 59:6 (5.8)

t=175 72.5 (5.0) 72.4 (3.8) 75.9 (4.1) 71.3 (4.0) 77.5 (3.5) 70.5 (4.8)

 * 

Critical Tracking Test

As shown in Figure 5.9, mean k measured 30 minutes after initiation of smoking diminished

in a dose-related manner. Measured 3'k hours after initiation of smoking, k remained low after

Critical lambda (rad/s)

0.6 r *

- t=30 EM t--195 0.4

0.2

0.0

-0.2

-0.4

-0.6

-0.8

-1.0

100 200 300

THC Dose

Figure 5.9 Mean (+SED) changes in X in the critical tracking test by Drug

and Time, relative to placebo.

the highest, but not the two lower doses. The lowest THC dose did not affect k significantly.

A nearly significant Drug by Time interaction was found in the 200 μg/kg condition (F1113=4.69;

p<.05; p,=.017); i.e. that dose diminished X shortly after smoking, but the effect dissipated

-66-
 *

after three hours. The highest dose had a significant effect on k (+ 1.13=9.03; p <.01; p,=.017),

both shortly after smoking and three hours later.

Hand Steadiness Test

Hand steadiness diminished in relation toithe dose after marijuana smoking (Figure 5.10). All

doses produced significantly greater instability (F1113 =6.72, 13.05 & 45.33 for the 100, 200 and

300 μg/kg conditions, respectively; p <.022, .003 & .001; pc= .05, .025 & .017).

Square root of total side contacts 5.0 r

4.5 -t-.9o ® io5

4:0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0 * 

100 200 900

TEC Dose

Figure 5.10 Mean (+SED) changes in the square .root of total number of side

contacts in the hand steadiness test by Drug and Time, relative to placebo.

Instability diminished after three hours, irrespective of the dose, resulting in significant Time

effects in each drug-placebo comparison. Drug by Time interaction was- not significant after the

lowest dose, but approached significance after the higher doses (F1.13 =4.51 & 6.28 for the 200

and 300 μg/kg conditions, respectively; p<.053 & .026; p,=.025 & .017).

Body Sway

Mean values for the area circumscribed by the vertical vector of force (i.e. curve surface) are

displayed in Table 5.7. Curve surface for subjects standing with eyes open (CS-O) increased

after THC, relative to placebo. These effects approached significance (F1.13=4.67, 5.20 & 4.95

for the 100, 200 and 300 μg/kg conditions, respectively; p < .050, .040 & .044; p,=.050, .017

& .025). The greatest change from placebo to marijuana smoking was observed in the 200 μg/kg

-67-
condition, but only in the first test after smoking, resulting in a significant Drug by Time 

interaction (F,.,3=9.23; p <.015; p,=.017). 

Table 5.7 Mean (SE) curve surface (mm2) in the body sway test, both with eyes open (CS-O) 

and closed (CS-C), by treatment condition and sampling time. 

0 μg/kg 100 μg/kg 0 μg/kg 200 μg/kg 0 μg/kg 300 μg/kg 

CS-O­ t=50 29.2 (4.5) '38.7 (4.8) 26.7 (3.2) 42.3 (4.4) 32.9 (4.0) 39.1 (4.3) 

t=175 32.1 (3.8) 43.3 (5.4) 35.5 (5.7) 37.3 (4.8) 31.7 (4.1) 38.5 (3.5) 

CS-C­ t=50 27.9 (3.9) 53.0 (8.6) 33.7 (6.8) 55.2 (8.8) 36.1 (6.2) 57.7 (11.2) 

t=175 43.3 (6.5) 43.9 (8.3) 40.1 (7.7) 35.2 (5.4) 32. .0 (5.5) 36.3 (5.6) 

Mean curve surface for the subjects standing with eyes closed (CS-C), increased markedly in 

the first but not in the second test. The main effect of Drug approached significance (p < .10) 

in all three conditions, but Drug by Time interactions were significant for the two lower THC 

doses (F1.13=8.86, 7.82 & 3.55 for the 100, 200 and 300'Ug/kg conditions, respectively; 

p < .011, .015 & .082; p,=.017, .025 & ..05). Analysis of variance of only the first 

measurements after smoking revealed that curve surface increased significantly after all THC 

doses, relative to placebo (F1.14 = 8.66, 10.45 & 4.96 for the 100, 200 and 300 μg/kg conditions, 

respectively; p <.01 1, .006 & .043; p,=.025, .017 & .05). 

In summary, body sway was affected by all three THC doses, but this effect had dissipated 

three hours after smoking. Body sway parameters did not discriminate between different THC 

doses. 

Heart Rate 

ECG data could not be obtained from every subject in all conditions due to recurrent equipment 

failures. Though the problem was solved in time to obtain complete data from all 15 subjects 

in the highest dose conditions, analyses could only be conducted using data from 14 and 9 

subjects in the middle- and low-dose conditions. The results of those analyses are summarized 

in Tables 5.8 and 5.9 for the standard and car following tests, respectively. 

Both tables show that driving under the influence of THC is accompanied by shorter interbeat 

intervals (i.e. increased heart rates) and decreased variation both in the time domain (CV-IBI) 

and frequency domain between 0.07 and 0.14 Hz (PWR-HR). No clear dose-response 

relationship was found, except in mean IBI in the car following test. 

With respect to the standard driving test, MANOVA showed that all THC doses produced 

significantly shorter IBIs relative to placebo (F177=9.07, F1.12=7.63 & F1113=21.61 for the 100, 

200 and 300 μg/kg conditions, respectively; p<.02, .017 & .001; p,=.05, .025 & .017). 

CV-IBI was significantly diminished after the two higher doses (F1.12=11.52 & F1.13=28.90 for 

the 200 and 300 μg/kg conditions, respectively; p <.005 & .001; p,=.025 & .017), but not the 

lowest. PWR-HR, on the other hand, was significantly diminished by all THC doses (F1.7=18.62 

F1.12 =12.20 & F1.13 = 28.47 for the 100, 200 and 300 μg/kg conditions, respectively; p < .004, 

-68­
.004& .001; p,=.025, .05 &.017). Thus, the more specific measure, PWR-HR, which includes 

only one source of heart rate variability, is more sensitive to THC's effects than CV-IBI, a 

measure of total variability. In conclusion, both mean 1131 and heart rate variability were 

significantly reduced by all THC doses. Since the latter measure is interpreted as a parameter 

of mental effort,.it can be concluded that subjects needed to invest more effort in driving after 

smoking marijuana than after placebo. 

Table 5.8 Mean interbeat interval time (IBI), coefficient of variation of IBI (CV-IBI), and power 

density of heart rate (PWR-HR) in the frequency band between 0.07 and 0.14 Hz during the 

standard driving test. 

N=9 N=14 N=15 

0 μg/kg 100 pg/kg 0 pg/kg 200 pg/kg 0 pg/kg 300 jig/kg 

IBI (ms) 792 721 805 743 797 709 

CV-IBI (%) 5.97 4.91 5.40 4.48 5.41 . 4.15 

PWR-HR 1114 666 877 570 862 499 , 

12. 

With respect to the car following tests, MANOVA showed that mean IBI decreased significantly 

after the two.higher doses (F1.9=9.66 & F1.7=26.24 for the 200 and 300 μg/kg conditions, 

respectively; p <.013 & .001; pp=.025 & .017), but not after the lowest. Mean IBI was always 

larger during the second ride relative to the first resulting in a significant Time effect in all 

conditions (F1,9=52.92, F199=57.02 & F177=79.07 for the 100, 200 and 300 μg/kg conditions, 

respectively; p <.001, -.001 & .001; p,=.05, .025 & .017). Drug by Time interaction was not 

significant. This means that subjects were more relaxed when they performed the second than 

the first car following test, whether they had inhaled THC or placebo. 

Table 5.9 Mean interbeat interval time (IBIj, coefficient of variation of IBI (CV-IBI), and power 

density of heart rate (PWR-HR) in the frequency band between 0.07 and 0.14 Hz during the car 

following tests. Data from the first and second tests are separated by a slash. 

N=9 N=14 N=.15 

0 μg/kg 100 μg/kg 0 μg/kg 200 pg/kg 0 μg/kg 300 μg/kg 

IBI (ms) 739/821 697/801 778/859 697/790 750/841 646/755 

CV-IBI (%) 5.48/6.31 4.69/4.86 5.18/5.83 3.85/5.25 4.67/5.41 4.05/4.57 

PWR-HR 983/1347 608/807 . 909/1094 438/967 726/993 405/633 11 
CV-IBI was diminished after smoking THC in each condition relative to placebo and these 

effects were only nearly significant (F1,9=7.09, F199=8.40 & F177=6.21 for the 100, 200 and 

300 μg/kg conditions, respectively; p<.026, .018 & .041; p,=.025, .017 & .05). As in the 

standard test, PWR-HR was more sensitive to drug induced variability reduction; MANOVA 

showed that PWR-HR was significantly affected by all doses (F1.9=10.46, F19 9=6.04 & 

F,.7=9-01 for the 100, 200 and 300 μg/kg conditions, respectively; p<.010, .036 & .020; 

PC=.017, .05 & .025). Though PWR-HR was generally higher in the second than in the first 

test, a significant Time effect was only found in the 200 μg/kg condition (F199 = 8.58; p < .0168; 

A.=.017). Though subjects felt more relaxed in the second car following test than the first, as 

measured by MI, both rides required much the same mental effort, as measured by heart rate 

variability. 

Intra-Subject Relations between Variables 

The average intra-subject correlation between [THC] and perceived "high" was, as in the 

previous study, very high (R=0.90; p<.01). The correlation between measured SDLP and 

[THC] measured before driving was 0.63 (p<.05), individual correlations ranging from -.14 

to .96; between SDLP and [THC] measured after driving 0.57 (p < .05), individual correlations 

ranging from -.10 to .92. These correlations closely resemble those found in the previous study 

where SDLP correlated 0.59 and 0.42 in the first and second tests, respectively. This means that 

the change in driving performance, as measured by SDLP in the standard driving test, is, within 

individuals, moderately related to the existing [THC]. Performance in the car following test was 

not significantly correlated with [THC]. 

The square root of the number of side contacts in the hand steadiness test was significantly 

correlated. to [THC] and perceived "high" (both r=.66; p <.01). SDLP scores were significantly 

related to hand instability measured before driving (r=.52; p <.05), but not with scores obtained 

after driving (r=.35; ns). None of the other laboratory performance measures were either related 

to plasma concentrations of the drug or to driving performance. 

In summary, as [THC] varied within a given individual so did that individual's perceived 

"high", hand steadiness and SDLP or road tracking error in the standard test. 

Inter-Subject Relations between Variables 

Relationship between Drug Levels and Performance. Inter-subject correlational analysis 

between [THC] and [THC-000H] on one hand and performance parameters on the other failed 

to reveal any consistent relationship. The most consistent, yet still not strong, relationships found 

were those involving [THC] on one hand and mean speed in the standard driving test and CTT 

performance in the laboratory on the other (Table 5.10). Correlations with Log [THC] were 

generally the same as with [MC]; those with [THC-COOH] were, except a few, generally 

lower than those with [THC]. _ 

The correlations presented in Table 5.10 were derived from raw scores. Another question 

is whether changes in performance from corresponding placebo levels were related to prevailing 

[THC]. Correlational analyses showed, however, that these correlations were even smaller than 

those with the raw scores. Thus, neither [THC] nor [THC-COOH] predicted performance or 

performance impairment. 

-70­
Table 5.10 Correlations between [THC] and raw performance scores in the marijuana 

conditions. If performance was measured only once (like SDLP), then the same scores were 

correlated with [THC] values as measured before and after the driving tests. 

100 μg/kg 200 μg/kg 300 pg/kg 

1s` 2nd In . 2"d 1s` 2nd 

Standard Driving Test: 

SDLP -.33 .02 -.13 .09 -.25 -.18 

SP -.26 -.18 -.50 -.20 -.55" -.61 

SDSP -.22 -.14 -.34 -.32 -.20 -.15 

Car Following Test: 

Adjusted RT -.18 .20 .41 .24 :04 .05 

Headway .32 .15 .39 -.02 .18 .05 

CV-Headway -.21 .40 .27 .43 - -.29 -.09 

Laboratory Tests: . ­

.63* .31 .48 .. 27 .45 .18 

Side Contacts .45" -.38 .54` .32 .44 .50 

OC-O -.25 -.13 • .43 .02 -.38 .06 

OC-C -.05 -.02 .36 -.25 -.26 -.37 

Relationship between Driving Impairment and Willingness to Drive. In general, the average 

road tracking impairment in the standard test of those subjects, who indicated before the driving 

tests commenced that they would normally not have driven under the imagined circumstances, 

was greater than of those who would have driven. Statistically; these effects were neither 

significant when willingness to drive for "unimportant though gratifying" reasons was used as 

the grouping factor, nor when willingness to drive for "urgent" reasons was used. This was 

probably due to the small number of subjects who would not have driven under the former 

condition, and would have driven under the latter condition. When willingness to drive for 

"important, but avoidable" reasons was used as the grouping factor, no significant difference in 

road tracking impairment was found between the groups after the highest THC dose; but, 

following the two lower doses, subjects who would not have driven were significantly more 

impaired than those who would have driven (F113=10.38& -6.93 for the 100 and 200. pg/kg 

conditions, respectively; p <.007 & .021; p,=.017 & .025). 

Relationship between Driving Performance and Other Measures. In the previous study, 

SDLP was moderately correlated with k from the CTT. The present study showed the same 

pattern of correlations i.e. -.41 and -.50 in the 100 μg/kg condition, -.49 and -.37 in the 

200 μg/kg condition, and -.58 (p <.05) and -.54 (p <.05) in the 300 μg/kg condition. Despite 

the interesting theoretical aspects of these consistent results, correlations of such magnitude are 

generally considered too low for predictive purposes. Performance in the car following test was 

not significantly correlated with Xc. Neither hand steadiness nor body sway were related to 

performance in the standard driving test or the car following test. _ . 

w, 

-71­
As in the previous study, repeated measures analysis of SDLP in the standard test was 

repeated with reported Frequency of cannabis smoking as a between-subjects factor. MANOVA 

failed to reveal any significant effect. 

The relationship between test performance and previous experience of driving under the 

influence could not be determined: too few indicated having driven in that condition more than 

a few times (Table 5.1).. 

DISCUSSION 

The conservative approach of administering THC according to an ascending, placebo controlled, 

dose series achieved its purpose of ensuring the subjects' safety. All"were able-to complete the 

series without suffering any untoward reaction while driving. However it is fair to ask whether 

this approach could have conceivably biased the results toward minimization of the drug's 

effects. We have three reasons for believing that this was not the case. Driving performance 

during successive repetitions of the standard highway driving test after placebo smoking was 

relatively constant; so that the reference for judging effects of every dose's effects was 

essentially the same. The measured mean changes in SDLP after the lowest and highest TBC 

doses in the present study were about what they had been in the previous study where dose 

orders were counterbalanced. Finally, there was apparently one dose sequence effect on car 

following performance but it was the opposite of any which could bias the results toward 

minimizing THC's effects. Such a bias would have existed if the subjects choose to operate more 

cautiously as doses ascended. Yet as described below, -they appeared to operate most cautiously 

in the car following test after the lowest dose. If any bias existed in this test it was toward 

maximizing, rather than minimizing THC effects. 

Road tracking performance in the standard test was impaired in a dose-related manner by 

THC. The 100 μg/kg dose produced a slight elevation in mean SDLP (1.1 cm), albeit nearly 

significant. The 200 pcg/kg dose produced a significant elevation (1.8 cm), of dubious practical 

relevance. The 300 pg/kg dose produced a highly significant elevation (2.9 cm) which may be 

viewed as practically relevant but unexceptional in comparison with similarly measured effects 

of many medicinal. drugs. 

For example, diazepam given for one week in its lowest therapeutic dose (5 mg, thrice daily) 

caused anxious patients to drive with a mean SDLP about 7 cm higher than their premedication 

baseline (Van Laar et al., 1992). Furthermore, THC's effects on SDLP were, after the 100, 200 

and 300 μg/kg doses in this study, about the same as those of BACs = 0.02, 0.04 and 0.06 g% 

according to the empirical equation described by Louwerens et al. (1985, 1987). The comparison 

reinforces our impression of the relevance of SDLP changes after THC. The two lower doses 

produced elevations less than the lowest BAC associated with intoxication and an elevated risk 

of causing a traffic accident (i.e. 0.05 g%; Borkenstein et al., 1964; Council on Scientific 

Affairs, 1985), whereas the highest dose, and one preferred by the drug's users, produced a 

marginally greater elevation. But even this change in SDLP can not, by itself, be taken to 

indicate exceptional impairment. 

It is often reported that subjects compensate for THC's adverse effects on driving abilities 

by operating at slower than normal speeds, especially through curves or slaloms. Our subjects 

were instructed to maintain a speed of 95 km/h (58 mph) unless compelled to slow down for 

safety reasons. Following marijuana smoking they drove with an average speed that was only 

-72­
slightly lower (maximum, 1 km/h or 0.6 mph) than after placebo and very close to the 

prescribed level. They apparently felt that it was within their capability to safely perform this 

relatively simple task while operating at the normal highway speed. 

The objective of confirming results obtained in the previous closed highway study was 

achieved in this one. It should be recalled that subjects' SDLPs were measured twice on the 

former occasion; i.e. in 22 km (13.7 mi) trials beginning 40 and 100 minutes after the initiation 

of smoking. The timing of the second trial most closely corresponded to that in the present study 

so their respective results will serve as the basis for comparison. Mean SDLP elevations after 

the lowest and highest doses differed little between the two studies: 100 ug/kg, 1.4 and 1.1 cm; 

and 300 μg/kg, 2.4 and 2.9 cm, respectively. Mean SDLP elevations after the 200 μg/kg dose 

differed somewhat between studies, being 3.3 cm in the first case and 1.8 in the second. Yet the 

results of the first study were anomalous in two respects. Not only did the former group's 

reaction in the 2nd trial exceed that in the I` trial following the 200 μg/kg dose, it was also 

greater than their 2nd trial reaction after the 300 μg/kg dose. Both results were in contradiction 

to plasma THC concentrations measured at these times. Thus the peculiar elevation in mean 

SDLP during the 2nd trial after the intermediate dose was probably a consequence of sampling 

error. That it was not replicated in the present study should dispel any notions to the contrary. 

The car following test was implemented for the. first time in the present study. In it, subjects 

maintained a headway of 45-50 m (148-164 ft) while driving in the successive placebo 

conditions. They lengthened mean headway by 8, 6 and 2 m (26.2, 19.7 and 6.6 ft) in the 

corresponding THC conditions after 100, 200 and 300 μg/kg, respectively. The initially large 

drug-placebo difference and its subsequent decline is a surprising result in need of an 

explanation. If one considers that changes in headway after THC results from impaired distance 

perception, the inverse relationship between administered dose and mean headway defies 

explanation. But if one considers these differences as the results of the subjects' caution in 

approaching the task under the influence of THC on successive occasions, another explanation 

seems plausible. 

Performing the car following test in the company of investigators while under the influence 

of THC was a novel experience for all subjects. Neither the investigators nor the subjects could 

predict - how the latter would be able to operate the vehicle. The former were somewhat 

apprehensive and it would not be surprising if the latter were also, particularly, on the first 

occasion the test was performed after THC inhalation. Subjects were required to match their 

vehicle's speed with that of the preceding vehicle's and so were unable to reduce velocity as a 

compensatory action. They could however maintain a longer headway and thereby slightly 

increase their margin of safety which might be needed if THC retarded their reactions. We 

believe they did so after receiving the lowest THC dose. When nothing untoward happened and 

the subjects' confidence in their ability to control the vehicle grew, they apparently tended to 

diminish headway after each of the succeeding doses so that it came progressively closer to the 

distance measured after all of the placebo treatments. Thus our explanation for. the initial 

difference between headways maintained after THC and placebo, and why it diminished in 

subsequent pairs of these conditions, is that the subjects' caution was greatest the first time they 

undertook the test under the influence of THC and progressively less thereafter. 

The only other plausible explanation is that lower THC doses induce a greater sense of 

caution than higher doses. There is of course no way to determine which of the two explanations 

is valid from the results of this study. But the fact that the subjects reported feeling, less calm 

and content as the doses increased seems to contradict the notion that they simultaneously 

-73­
became less cautious. Whatever explanation is favored, it is clear that large doses of THC have 

little effect on mean headway during car following. 

Reaction time to changes in the preceding vehicle's speed increased following THC 

treatment, relative to placebo. The administered THC dose was inversely related to the change 

in reaction time, as it was to headway. Mean increases in reaction time were 0.55, 0.41, and 

0.19 s following the 100, 200 and 300 μg/kg dose, respectively. However, reaction time data 

were confounded with headway. That is, increased reaction times were partly due to longer 

headway. Statistical adjustment for this confounding resulted in smaller and non-significant 

increases in reaction time following marijuana treatment, the greatest impairment (0.32 s) being 

observed in the first test following the lowest THC dose. Headway variability followed a similar 

pattern as mean headway and reaction time; the greatest impairment was found following the 

lowest dose. 

A secondary objective of the study was to determine whether degrees of impairment would 

correlate between the two tests in a manner indicating a general influence of THC on driving 

behavior. The results obtained in this study showed that this was not the case; a significant doserelated impairment was found with road tracking, but not with car following. Test duration can 

not have been the critical point, since the standard test in the previous study was of the same 

duration as the present car following test. 

The car following test was both less sensitive and reliable than it could. ,be following the 

removal of certain procedural flaws. Intervals between successive maneuvers' were practically 

constant and the preceding vehicle's deceleration was both abrupt an stereotyped. Thus the 

occurrence and nature of the maneuvers were highly predictable for the subjects. 

Greater irregularity in both the timing of maneuvers and the profile of velocity changes 

would probably increase the sensitivity of the test. After the fact we recognized that the indirect 

and discontinuous method used for measuring headway produced a degree of error variance 

which appreciably reduced the reliability of these data. Equipment has become available since 

the initiation of this study which now makes it possible to measure headway directly and 

continuously (i.e. an inexpensive pulsed laser reflection recording system). Use of this 

equipment should increase the reliability of headway measurement in future applications of this 

test. Finally, the greatest source of error variance was the procedure of allowing the subject to 

assume, within limits, whatever headway he/she chooses. Whether this is a flaw or not depends 

upon one's desire to measure or control headway at the beginning of maneuvers. However the 

subject's choice of headway is certainly a factor which inflates reaction time error variance. 

Adjusting the data statistically to overcome the confounding effect of headway on reaction time 

is only a partial solution to the problem. We would probably have been wiser to strictly enforce 

headway control in order to increase the reliability of reaction time measurements and their 

sensitivity to drug effects. 

Without trying to minimize the impact of procedural errors on the data, it is doubtful whether 

any flaw or all in combination seriously obscured a practically important THC effect. SDLP 

recorded in the standard highway driving test was about as sensitive to low-dose THC effects 

as any of the traditional laboratory performance measures taken in the study. Moreover the 

average intra-subject correlation between [THC] and SDLP was as high or higher than any 

measured between the drug's plasma concentration and another performance variable. This 

relationship could not -have been measured if SDLP were not one of the most sensitive 

parameters known for measuring the effects of THC. The fact that car following performance 

-74­
was less sensitive does not mean that it would have failed to reveal effects of practical 

importance if these truly existed. SDLP showed no such effects even after the highest dose. 

The reasons why SDLP and not car following performance showed the modest impairing 

effects of THC may have less to do with the inadequacy of the latter test than to the difference. 

between what the two tests measure. SDLP is controlled by a very fast and high capacity human 

information processing system which operates in a wholly "automatic" manner. That is, outside 

of conscious control. The process is relatively impervious to environmental changes as shown 

again by the high reliability of SDLP under repeated placebo conditions in the present study. It 

is, however, highly vulnerable to internal factors that retard the flow of information through the 

system. THC and other drugs are among these factors. When they interfere with the process to 

elevate SDLP there is very little the afflicted individual can do in way of compensation. Car 

following performance on the other hand depends upon more discrete perception of events 

leading to a'conscious decision, a response selection and its execution. Performing the test 

involves far more sustained attention and conscious effort than does road tracking in the standard 

test. Because car following performance is under conscious control and well within the speed 

limitations of "cognitive" compensatory mechanisms it is possible for individuals to recognize 

their deficiencies and correct them by effort that increases attention. In short, any deficiencies 

that THC might have otherwise produced may have been overcome by the subjects' compensatory effort. The cost of effort focused on accomplishing a task is however accompanied by less 

capacity left for performing another in parallel. The subjects indeed related that their investment 

of effort in the first car following test increased with the administered dose, and relative to 

corresponding placebo levels, more so than in the standard driving test. Though these differences 

were not statistically significant in either case, they were in line with the significant reduction 

in heart rate variability, that occurred independently of mean rate changes after every THC dose, 

including. the lowest. Together the findings support the premise that THC increases the 

requirement for compensatory effort during car following which maintains constant performance, 

but possibly reduces the capacity for undertaking any. activity in parallel. Coupled with THC's 

reputably adverse effect on the ability to divide attention between tasks performed simultaneously 

(Smiley, 1986), the net effect might constitute a more serious impediment to safe driving than 

any observed in this study. It will be interesting to explore this possibility in further research. 

Subjects' report of their willingness to drive under specified conditions of different urgencies 

were similar to those in the previous study. The lower the administered THC dose, and the more 

urgent the reason for driving, the more subjects declared that they would be willing to drive. 

Furthermore, there was a tendency for subjects who would normally not have driven to be more 

impaired in road tracking than those who would. Apparently these subjects recognized their 

respective degrees of impairment while under the influence of every THC dose. This is 

supported by the subjects' judgments of their own driving quality which changed in a realistic 

dose related manner after marijuana smoking. 

Critical tracking and hand steadiness tests were more sensitive to THC induced impairment 

than in the previous study. This confirms our impression that the earlier CTT version was poorly 

conceived. It also indicates that applying the correct procedures for measuring hand steadiness 

is very important; i.e. subjects should not be allowed to rest their hand on the table while 

performing the test. Both tests showed dose-related impairment shortly after cessation of 

smoking. When the tests were repeated three hours later, hand instability was still present though 

to a lesser degree. The effect of the highest but not this two lower doses on CTT performance 

persisted undiminished from the first to the second test, or over a 3-hour period after smoking. 

-75.­
These results partially confirm results obtained by Sharma and Moskowitz (1975). They found 

that THC 200 μg/kg had a virtually undiminished effect on tracking performance for up to four 

hours. The time course of postural instability after marijuana smoking followed a different 

profile. All THC doses increased body sway to the same extent shortly after cessation of 

smoking but none did three hours later. 

An important practical objective of this study was to determine whether degrees of driving 

impairment can be accurately predicted from either measured concentrations of THC in plasma 

or performance measured in potential roadside "sobriety" tests of tracking ability or hand and 

posture stability. These results, like many reported before, indicate that none of these measures 

accurately predicts changes in actual driving performance under the influence of THC. CTT 

performance. came closest but even its correlation with driving was only r=.50. However, that' 

test might well be included in a battery of similarly predictive tests, measuring different abilities, 

to collectively yield a single more predictive index of impairment. 
CHAPTER 6 - MARIJUANA, ALCOHOL AND URBAN CITY DRIVING 

INTRODUCTION 

In the previous study, THC doses of 200 μg/kg, and higher, produced significant impairment 

of road tracking, but not car following, performance. The lowest dose, 100 1&g/kg, failed to 

produce significant effects on road tracking, but increased headway during car following. The 

latter observation was interpreted as the result of increased caution, since mean headway did not 

change following subsequent higher THC doses. It therefore seems that low doses of THC do 

not, or only slightly, impair driving performance. Yet normal driving is far more complex and 

varied than simply maintaining a safe lateral position and headway during uninterrupted travel 

on a highway. A THC dose having no effect on these parameters might still impair driving 

performance in more complex urban driving situations. 

There were logical and safety reasons for restricting the THC dose in the third driving study 

to that which had failed to produce significant impairment in the second. Both the 200 and 

300 pg/kg doses impaired performance on the highway and could be expected to do so again in 

the urban driving environment. There the consequences of high dose THC effects are more 

difficult to predict and therefore safely control. The 100 pg/kg dose had some significant effects 

on the.highway but none that could rightfully be called dangerous. This dose might still cause 

impairment in more complex city driving, but the risk was judged to lie within the realm of the 

acceptable. For that reason it was given to a group of regular cannabis users, along with placebo 

in the present study. 

For comparative purposes another group of regular alcohol users were treated with a modest 

dose of their preferred recreational drug, and again placebo, before undertaking the same test. 

It was hoped that this addition would not only verify the sensitivity of the test but also allow a 

comparison between effects of recreational drugs that Dutch society' considers as illicit and licit 

when both are given iri relatively low doses. The comparison was not designed to show that one 

drug is "'safer" for use by drivers than the other. Surely neither are safe when consumed before 

driving in high doses. However if respective low dose effects are comparable then one would 

be justified to conclude that THC may be considered as posing a traffic safety hazard which is 

in some respects similar to alcohol's. 

The only study that has been conducted in actual traffic before this program started was also 

a city driving study. Klonoff (1974) assessed the effects of two THC doses, 4.9 and 8.4 mg 

THC which are equivalent to 70 and 120 gg/kg for a 70 kg (154 lb) person. Aspects of subjects' 

driving performance were scored by a professional examiner using an abbreviated version of the 

British Columbia Department of Motor Vehicles' standard driver's licencing test. The results 

showed that subjects performed less competently when under the influence of the highest, but 

not the lowest, dose. In particular, they scored lower on judgment and concentration scales. 

Moskowitz (1985) and Smiley (1986) criticized the method of measuring driving performance 

on the grounds that the examiners' reliability was never determined - and that the scoring 

instrument had never been shown to. provide measures related to driving safety. Smiley 

questioned, for example, whether ratings of posture and irritability are relevant for good driving 

performance. These are sound criticisms but one has to assume that Klonoffs approach -should 
have been sensitive to serious driving performance impairment, related to safety, if it had in fact 

occurred. 

Two scoring methods were employed in the present study. The first was in fact a method 

similar to that applied by Klonoff; i.e. the driving instructor acting as the safety controller 

during the tests retrospectively rated the driver's performance using -a standard scale. This 

method has been applied previously to show the impairing effects of alcohol (De Gier, 1979) 

and diazepam (De Gier et al., 1981) in similar situations. Jones (1978) criticized this use of 

driver licensing assessment procedures. She opposed the lack of precise definitions for many of 

the behaviors rated by examiners and the requirement for rating all of them at once. In contrast 

to this "molar" approach, she developed a more "molecular" one for evaluating driving 

proficiency. Her method was also applied in the present study. It involves the employment of 

specially trained observers who apply simple and strict criteria for recording when the driver 

makes or fails to make each in a series of observable responses at predetermined points along 

a chosen route. 

The professional observer's global ratings are inherently less reliable than the scores obtained 

by the molecular rating scheme. Still the molar approach has some advantages. The professional's experience with many drivers operating in all traffic situations provides him with the 

ability to integrate far more information than is possible to obtain from limited performance 

sampling. He has internalized a broad concept of acceptable driving performance and applies 

more flexible criteria for judging when it is unsafe within a particular test situation. Of course 

the danger that a professional's biases may influence his judgments needs to be overcome by 

training and his adherence to structured rules which are specific for the investigation. But when 

this is done, he may provide a more valid estimation of the overall safety of a subject's driving 

performance. If this were not the case it would be difficult to explain how every developed 

society relies upon the professional's and not a traffic scientist's opinion of whether a particular 

individual should be licensed to drive. 

The objective of this study would be satisfied in one way if neither observer rating method 

yielded a significant difference between driving performance after 100 μg/kg THC and placebo. 

These results would confirm those obtained in the previous study by indicating that the selected 

dose lies below that capable of impairing driving performance. This.conclusion would only be 

warranted, however, if it could be shown that the tests were sensitive enough to measure 

significant driving performance impairment after alcohol relative to placebo. If that were not the 

case, test insensitivity could be judged as the factor responsible for negative results, rather than 

the lack of a THC effect. 

The objective would be satisfied in another way if either or both rating methods showed 

significant impairment after THC. Such results would indicate that any dose likely to be 

consumed before driving should be considered hazardous, regardless of whether alcohol's effects 

were the same, more or less. In the event that significant impairment occurred after THC, we 

were prepared to determine its relationship with plasma concentrations of THC and THC-COOH 

measured at about the same time. 
METHODS

Subjects 

Two groups of sixteen new subjects apiece, equally comprised of men and women, participated 

in the study. The groups will be referred to by the alcohol and marijuana group. Subjects in both 

groups were recruited according to the same inclusion/exclusion criteria as before with one 

exception. Subjects in the alcohol group were regular users of alcohol but not marijuana (see 

below). All subjects were individually trained to perform the city driving test in a preliminary 

"dress rehearsal" and were familiarized with the other tests and questionnaires. 

Plasma analyses after conclusion of the study showed that two males' plasma contained 

neither THC nor THC-COOH in any sample. It was concluded that these subjects had not 

inhaled smoke so their data were excluded from further analyses. 

Characteristics of the remaining subjects are given in Table 6.1. Except for the reported 

incidence of marijuana use, there were no significant differences between any of the groups' 

characteristics. 

Table 6.1 Mean±SD (range) of subjects' characteristics. 

Alcohol Group Marijuana Group 

N 16 14 

Age (yrs) 23.7±2.7 (20-28) 22.4±3.5 (20-34) 

Weight (kg) 68.1±7.9 (60.0-86.1) 67.9±8.9 (54.0-90.5) 

Weight -(lb) 150.1±17.4 (132.2-189.8) 149.7±19.6 (119.0-199.5) 

# Alcoholic Drinks/Week 8.3±6.2 (1-21) 10.6±8.4 (1-30) 

Smoking Experience (yrs) 0 3.1±2.1 (1-10) 

# Joints/Month 0 2.3±2.5 (1-8) 

Driving Experience (yrs) 4.8±2.6 (2-10) 4.1 ±3.3 (2-15) 

Driving Experience (km x 1000) 35.3±28.3 (5-90) 28.6±45.7 (6-180) 

Driving Experience (ini x 1000) 21.9± 17.6 (3-56) 17.8±28.4 (4-112) 

Design, Doses and Administration 

The study was conducted according to a mixed between-groups within-subjects design, one group 

drinking alcohol and placebo alcohol and the other smoking marijuana and placebo marijuana. 

Alcohol was administered as 99.8% ethanol mixed with orange juice and Grand Marnier 

essence to a volume of 250 ml. The dose . was 0.43 g/kg lean body mass (On average, this 

resulted in a dose of 0.36 g/kg body weight in males, and 0.31 g/kg in females). Lean body 

mass was calculated by subtracting the percentage of fat, determined by skinfold thickness 

(Durnin and Womersley (1974),. from total body weight. The dose was chosen to yield a Blood 

Alcohol Concentration (BAC) approaching 0.05 g% when the driving test commenced 45 

minutes after onset of drinking. Subjects were instructed to fast 21 hours before drinking and 

to ingest the dose within 5 minutes. Alcohol in the subjects' expired air was monitored using aLion S-D3Breath-Alcohol Analyzer to ensure that subjects would not drive with BACs that were 

higher than 0.05 g%, which is the legal limit in.The Netherlands. 

-79- T 4 
Marijuana and placebo cigarettes were obtained from the-same source as before. The subjects 

were treated on separate occasions with THC doses of 0 and 100 ugfkg. Placebo cigarettes were 

prepared by ethanol extraction of THC from the plant stock. Marijuana cigarettes were prepared 

from batches containing 1.77% THC. Cigarettes were cut to different lengths to provide the 

doses appropriate for the individuals' body weights. Cigarettes appeared identical in both 

treatment conditions and were smoked through a plastic holder in a fashion determined by the 

subject but with the constraint that smoking had to be finished within five minutes. After 

cessation of smoking, cigarettes were retained for subsequent gravimetric estimation of THC 

consumed. These analyses revealed that the average (±SD) amount of consumed THC in the 

marijuana condition was 6.9 (± 1.0) mg or 101 (±6) μg/kg. 

Half of both groups received the treatments in the same order, the others, in reverse order. 

The driving instructor and observer who rated subjects' driving performance were blind 

regarding both the administered drug (active or placebo) and the subject's group membership. 

Testing Procedures 

Upon arrival at the laboratory, subjects were tested for the presence of alcohol in breath. 

Subjects in the marijuana group were further tested for the presence of cannabinoids and other 

drugs in urine (as described in Chapter 2). If cannabinoids were found, a blood sample was 

taken for later verification of the presence of THC. The schedule of further activities on-testdays is shown in Table 6.2. 

Table 6.2 Schedule of activities on test-days. 

Alcohol Group Marijuana Group 

Relative Time (min) Activity Relative Time (min) 

0-5 Drinking / Smoking 0-5 

30-35 Hand Steadiness and 15-20 

Time Perception Tests 

35-40' Blood Sampling and 20-25 

Questionnaires 

45-95 City Driving Test 30-80 

95-100 Blood Sampling and 80-85 

Questionnaires 

105-110 Hand Steadiness and 90-95 

Time Perception Tests 
Driving Test and Scoring Methods 

Driving tests were conducted in daylight over a constant 17.5 km (10.9 mi) route within the city 

limits of Maastricht (population ca. 115,000). The route was constructed through business and 

residential areas on 2-lane undivided streets and included a 6 km (3.7 mi) 4-lane divided segment 

on a major cross-city thoroughfare (Figure 6.1). Subjects drove their placebo and active drug. 

rides through heavy, medium and low density traffic on the same day of the week, and at the 

same time of day. Maneuvers included left and right turns at some intersections and driving 

through others, left and right lane changes, and responding to traffic control devices (i.e. stop 

signs and signals). There was one special maneuver, repeated twice; i.e. executing a Y-turn on 

a residential street. A schematic representation of the standard route is shown in Figure 6.1 and 

the symbols used for maneuvers and road densities are shown in Table 6.3 (the performance 

variables will be discussed below). 

Driving tests were conducted in a dual control 2-door sedan (Volkswagen Golf) normally 

used for driving instruction/examination. Two persons accompanied the subject: a licensed 

driving instructor sitting in the front passenger's seat and an trained observer sitting in the center 

of the rear seat. The former had access to redundant controls and his primary responsibility were 

controlling safety and giving the route instructions; and, to rate the driver's performance. 

retrospectively (below) after the ride. The observer in the rear seat scored the driver's 

performance "on-line" and timed the duration of the ride. 

As described above, two different procedures were employed for determining a driver's 

proficiency from observer ratings; i.e. the molecular and the molar methods. The major 

difference between both methods is that performance variables are repeatedly measured on-line 

at different points along the route using the molecular approach; and, only once, retrospectively, 

in the molar approach. 

The molecular approach was adopted from Jones (1978) who simplified the scoring of driving 

behaviox* so that the trained observer, sitting in the rear seat, attends to only one event at a time. 

The events observed at specific points along the route.are only few aspects of total driving 

behavior. Thus, the observer is enabled to attend completely to the occurrence of each event in 

sequence while ignoring all other behavior which would in any case vary between tests. All 

aspects of a maneuver, such as a left turn, will be scored a number of times over the course of 

the whole route, but never more than a single aspect at a given moment. 

Jones defined twelve aspects, called performance variables (Table 6.3), which were 

repeatedly scored, 156 times in total, at specific points along the route. The route was designed 

to fulfill Jones' requirements concerning maneuvers and road densities. The scoring sheet 

consisted of the schematic route map with symbols indicating the driver behavior to be scored 

at each point (reproduced in Figure 6.1.with symbology defined in Table 6.3). The observer 

moved his finger along the route and attended. only to the behavior indicated, comparing it with 

a predefined standard of performance, and circled (if correct), crossed (if wrong) or underlined 

(if not observed) the symbol. If, for example, the observer were to score Path (P) at a lane 

change (1') the correct response was defined as: 1. maintains straight path while scanning, 2. 

signals before the lane change, 3. steers smoothly with gradual angular movement, 4. straightens 

vehicle in new lane, and 5. cancels signal. If the driver failed to make one or more of these 

responses Path was scored as fail, otherwise pass. A complete description of all maneuvers is 

included in Appendix B. 

-81­
 *

OPS PSG MOPS

MPS SHO PSOM :

'PJ

Iabotatory PI=-OP

SO

OG. ovS J

 * 

..........."l .DS.......41

ON

P5G PSO OPS 0 JI OPS

HOG

S- +. 7

PSG

OPS

S..

OLL

ovs 0

S..

S.. S..

OPS

OPS

MOPS •vsM

PSG

Figure 6.1 Scoring sheet for molecular approach, consisting of the schematic route map with

symbols indicating the driver behavior to. . be scored at each point (for explanation of the

symbols, see Table 6.3).

-82-
Table 6.3 Maneuvers, road densities, performance variables and their symbols. 

Maneuvers: Road Density: 

Right Turn r--P, Heavy Density Traffic 

Left Turn a-i Medium Density Traffic 

Driving Through - - - - - Low Density Traffic 

Right Lane Change 

Left Lane Change Halt-Line: '• 

Y-Turn Y 

Performance Variables: # of times scored: 

0 Observation 38 

G ' • Gap Acceptance 14 

M Mirror Check 16 

P Path 30 

S Speed 39 

A Approach at Intersection 5 

F Following Distance 4 

LL Limit Line (stopping at halt-line) 4 

L Location at Y-Turn 2 

B Backing at Y-Turn 2 

Pre-op Pre-operations I 

SD Shut-Down 1 

At the end of the test, the Total Score was calculated by summing all passing items and dividing 

by the total number of observed items. Subscores were also calculated for Observing, Car 

Control, Judgment and Other.(Table 6.4). Three additional scores were obtained from the 

driving instructor; 1. Instructor Control, the number of times the instructor took control, either 

orally or physically, 2. Hazard Score, the number of times the driver responded correctly to 

hazards divided by the total number of hazards encountered, and 3. Instructions, the number of 

times the driving instructor had to repeat a route instruction. All scores, except Instructor 

Control and Instructions, were expressed as per cent correct. 

The molar approach required the driving instructor to retrospectively rate the driver's 

performance using a shortened version of the Royal Dutch Tourist Association's (ANWB) 

Driving Proficiency Test (Appendix B). This instrument is normally applied for practical 

purposes; e.g. remedial training, driver's licensing, qualifying for a reduction In insurance 

premiums, etc. Items that did not apply to the driving test, e.g. those regarding railway crossing 

and special maneuvers like driving backwards and parking, were dropped from the normal list. 

In total, 108 items were dichotomously scored, as either pass or fail. Total test performance was 

measured by the percentage items scored as "paps". Subscores were calculated for Vehicle 

Checks, Handling of Vehicle, Action in Traffic, Observation. and Understanding of Traffic, and 

Turning (Table 6.5). 

-83­
Table 6.4 Dependent variables, and their operationalization, measured by the molecular 

approach. 

Dependent Variable Operationalization 

Total Score % correct of all 156 items 

Observing % correct of 68 items comprising Observation, Gap Acceptance, 

and Mirror Check 

Car Control % correct of 69 items comprising Path and Speed 

Judgment % correct of 13 ,items comprising Approach, Following Distance 

and Limit Line 

Other % correct of 6 items comprising Y-turn Location and Backing, 

Pre-Operations and Shut-Down 

Hazard Score - % of correct responses to hazards encountered along the route 

Instructor Control # of times instructor took control, either orally or physically 

Instructions # of times the driving instructor had to repeat a route instruction 

Table 6.5 Dependent variables, and their operationalization, measured by the molar 

approach. I 

Dependent Variable

Operationalization 

Total Score

% correct of all 108 items 

Vehicle Checks

% correct of 13 items regarding preparations for driving and 

driving away 

Handling of Vehicle

% correct of 23 items regarding posture and steering, controls 

handling, speed adjustment and stopping, and driving .through 

curves 

Action in Traffic

% correct of 60 items regarding straight driving, behavior near 

and at intersections, right turns, left turns, overtaking, driving in 

lanes and lane changing, driving through traffic circles, and on 

highways 

Observation and Under- % correct of 8 items regarding perception and traffic insight 

standing of Traffic 

Turning % correct of 4 items regarding Y-turns 

Driving Time

time duration (s) of ride 

Questionnaires 

Questionnaires used in the previous studies were administered to the subjects in the present 

study. Subjective feelings of intoxication ("high" or "drunkness"), present cognitive and 

84
emotional state, and subjects' willingness to drive were assessed before the onset and after the 

conclusion of the driving tests. Subjects were also asked about their perception of the 

administered treatment, whether it was an active or placebo. At the end of each driving test, 

subjects were required to retrospectively rate the'-effort given in performing the test and 

perceived driving quality. Questionnaires are enclosed in Appendix A. 

Laboratory Tests 

Subjects performed two laboratory tests before and after driving. The hand steadiness test was 

used since it had shown a significant effect of the 100 jig/kg THC dose in the previous study 

and confirmation of this result would indicate the equivalent sensitivities of the present and 

previous groups to the drug. In addition a time perception test (method of interval production; 

Fraisse, 1963) was used to satisfy the investigators' curiosity about an oft-reported effect of 

THC. The former followed the same procedures as described in Chapter 5. The latter required 

the subjects to stand with eyes closed and indicate when he/she thought that 30 seconds had 

elapsed since a starting signal. The verbal response was timed to the nearest second by stopwatch. 

Blood Sampling 

Blood samples were obtained by venepuncture immediately prior to and following all placebo 

and drug driving tests. Two aliquots containing 10 ml each were heparinized and centrifuged, 

and the plasma fractions were placed in frozen storage for later assays to determine [THCJ and­

[THC-COOH], in the marijuana group; and, [EtOH], in the alcohol group. The analytical 

procedures regarding THC and THC-COOH assays were the same as in previous studies. As 

before, samples obtained in conjunction with placebo marijuana tests were only analyzed if the 

urine test had been positive. Plasma samples obtained from subjects in the alcohol condition 

were analyzed using gas-chromatography. 

Data Analysis 

For each variable measured on interval or ratio level, except plasma concentrations, change 

scores were computed by subtracting raw scores obtained in the placebo condition from those 

in the drug condition. In the figures, the mean change of the variable is depicted by the height 

of the bar and its standard error (SED) by the height of the vertical line above or below the bar. 

Change scores were expressed in absolute and not relative units. This means that if a 

performance measure fell from 80%. after placebo to 70% after active drug; the change score 

would be 10 % and not 12.5 %. Mean drug-placebo changes were tested for significant departure 

from zero by 2-tailed t-tests, for each group separately. Differences between the groups' mean 

changes were tested by 2-tailed t-tests for independent samples. Willingness to drive data were 

again analyzed for assessing differences between drug and placebo conditions using Cochran's 

Q-test. Differences between the respective groups' willingness to drive after drug treatments 

were analyzed by Mann-Whitney's U-test. Correlations were computed by Pearson's r and tested 

for significant departure from zero by 2-tailed t-tests. 

Preliminary analyses were executed to determine whether change scores were significantly 

different between subjects who received placebo in the first, and active drug in the second 

-85­
condition and those who received treatments in reversed 'order. Significant differences were 

generally absent and are therefore mentioned only in the exceptional cases where these were 

significant. 

RESULTS 

Plasma Concentrations of the Drugs 

Table 6.6 shows mean, median and range of [THC] and [THC-COOH] in the marijuana group 

and [EtOH] in the alcohol group. In the marijuana group, [THC] and [THC-COOH] were in the 

expected range. In the alcohol group, mean [EtOH] at t=35 was somewhat lower than expected. 

Furthermore,, the fall in [EtOH] to t=95 was less than expected from alcohol's pharmacokinetics; a fall of .02 % per hour is commonly seen during the elimination phase in subjects who 

fast prior to alcohol intake. This probably means that peak [EtOH] generally occurred during 

the driving test and was not much higher than measurements taken before and after. This 

situation contrasts to that for the subjects in the marijuana group whose [THC] reached its peak 

before the test and fell much more rapidly during it. Average plasma concentrations were 

significantly different from zero in all cases (p<.001). 

Table 6.6 Mean, -median and- range of [THC] and [THC-COON] in ng/ml (N =14), and of 

[EtOH] in g % (N =16). 

[THC] . [THC-000H] [EtOH] 

t=20 t=80 t=20 t=80 t=35 t=95 

mean 10.5 2.3 7.5 5.6 .034 .028 

median 7.8 1.9 6.1 4.3 .034 .028 

range 4.3-31.2 1.1-4.9 2.9-18.9 1.7-15.1 .013-.050 .018-.036 

Perceived "high" and "drunkness" ­

Mean levels of intoxication reported by both groups varied from placebo to drug conditions in 

a remarkable manner. Few subjects in either group reported feeling intoxicated after placebo and 

their average levels were about 5% of maximum personal experience. After both -THC and 

alcohol these levels rose to about 35 % when the respective groups were about to begin driving, 

then declined to 25% at the end of driving. Means and standard errors of differences (SED) in 

reported intoxication are shown in Figure 6.2. 

T-tests showed that ratings of intoxication after active drugs were significantly different from 

zero in the marijuana and alcohol groups, both before (T13=4.36 & T15=5.20, respectively; 

p<.001) and after driving (T13=3.44 & T15=5.23, respectively; p<.001). 

Subjects' responses to the question of whether they thought the administered drug was active 

or placebo showed that they were well aware of what they smoked or drunk. In the marijuana 

group, 93 % of the subjects correctly identified the placebo cigarette when it was administered, 

and 79%, the active drug. In the alcohol group, 94% of the subjects correctly identified the 

placebo alcohol when it was administered, and 87%, the active drug. 

-86­
Perceived intoxication

60% r

= t=35 ®t 95 

50% 

40% 

30% 

20% 

10% 

0% 

• Alcohol 

Drug Treatment 

Figure 6.2 Mean (+SED) changes in perceived intoxication by Drug and 

Time, relative to placebo. Raw scores were expressed as percentage of 

maximum personal experience. ­

Driving Performance Measured by the Molecular Approach 

Though some of the changes were positive, indicating better performance after drug and some 

were negative, showing the opposite, no mean change was significant (Table 6.7). Differences 

between the two ' groups' changes were also not significant, although one came close: the 

difference between improvement shown by the marijuana group and impairment shown by the 

alcohol group in Car Control approached significance (p < .059). In general, the effects of both 

drugs on driving performance, as measured by the molecular approach were very small or 

absent. 

Driving Performance Measured by the Molar Approach 

Mean Total Score obtained using the molar approach varied between 82.8 % and 89.5 % over the 

conditions of the study. Groups' mean change scores on all dependent variables are given in 

Table 6.8. It is apparent that THC did not significantly affect Total Score or any of the 

component scores. On the other hand, alcohol significantly diminished the Total Score as well 

as two components, Handling of Vehicle and Action in Traffic. Mean Driving Time was, within 

two seconds, the same for both groups following placebo, namely about 41' minutes. Subjects 

drove 46 s slower after THC and 42 s faster after alcohol, but neither change was statistically 

significant. 

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Table 6.7 Mean (±SED) changes in driving performance scores measured by the molecular 

approach for the marijuana (N =14) and alcohol group (N =16); and, the significance of each 

change and difference between changes. 

Dependent Variable Marijuana Group Alcohol Group Marijuana vs Alcohol 

P< 11 p< P< 

Total Score 1.6(±1.7) as -1.5 (±1.7). as - as 

Observing 2.4 (±3.1) as -0.3 (±2.8) as as 

Car Control 2.7 (±2.1) as -2.6 (±1.8) as 059 

Judgment -8.3 (±4.8) as -2.2 (±4.0) as as 

Other -3.6 (±4.3) as 1.3 (±4.4) as as 

Hazard Score 6.3 (±17.6) as 14.6 (±9.4) as as 

Instructor Control 0.5 (±0.4) as 0.4 (±0.5) as as 

Instructions 0.1 (±0.6) as 0.8 (±0.6) as 

Table 6.8 Mean (±SED) changes in driving performance scores measured by the molar 

approach for the marijuana (N =14) and alcohol group (N =16); and, the significance of each 

change and difference between changes. 

Dependent Variable Marijuana Group Alcohol Group Marijuana vs Alcohol 

A . P< A p< p< 

Total Score -0.7 (±2.7) as -6.8 (±1.8).002 .065 

Vehicle Checks -0.6 (±1.5) as 0.5 (±1.3) as as 

Handling of Vehicle 3.7 (±2.8) as -8.4 (±2.2).002 .002 

Action in Traffic -2.7 (±3.1) as -8.4 (±2.3).003 as 

Observation and Under- 1.8 (±8.7) as -6.3 (±7.0) as as 

standing of Traffic 

Turning -1.8 (±4.9) as 3.1 (±7.5) as as 

Driving Time 45.6 (±51.8) as -42.0 (±32.4) as . as 

Differences between the groups' mean change scores were also significant or nearly so. The 

greater drop in Total Score caused by alcohol was almost significantly different from that caused 

by THC (p <. 065). The difference between groups' changes in Handling of Vehicle, a component score, was significant (p<.002): whereas the marijuana group's performance improved 

slightly, that of the alcohol group deteriorated under the influence of their respective drugs. In 

particular, 6 items checked under the category of Handling of Vehicle discriminated between the 

groups' reactions to the drugs. These all pertained to how well the driver handled the vehicle 

through curves. Whereas THC had little effect on this ability, alcohol seemed to affect it 

-88­
strongly:. This more than any other factor was responsible for the, difference between the 

instructor's ratings of bow the two groups were affected by the respective drugs. 

Perceived Driving -Quality and Effort to Accomplish the Test 

Both groups rated their driving performance following placebo as somewhat better than 

"normal". Following the active drug, ratings were about 35 % lower in the marijuana group, but 

only 5% lower in the alcohol group (Figure 6.3). This striking mean difference was substantiated 

by the statistical analysis. Mean change of driving quality ratings was significantly lower in the 

marijuana (T13 =-3.05; p<.009), but not in the alcohol group. The difference between the 

_.groups' mean changes approached significance (T2s=-1.97; p-< .058). 

Perceived driving quality 

10% r: 

0% 

-10% 

-20% 

-30% 

-40% 

-50% 

20%

Marijuana Alcohol

Drug Treatment 

Figure 6.3 Mean (+SED) changes in perceived driving quality by Drug, 

relative to placebo. Raw scores were expressed as percentage of "normal". 

Perceived effort to accomplish the driving test was about the same in both groups following 

placebo. Following the active drug; a greater increase in perceived effort was reported. by the 

marijuana group than the alcohol group (Figure 6.4). Statistical analysis showed that increased 

effort ratings following the drug were only significant in the marijuana group (T13=2.39; 

p < .033). No significant difference between the groups' mean changes was found. 

-89­
Perceived effort

40%r

35% 

30% 

25% 

20% 

15% 

10% 

5% L 

0% 

Marijuana Alcohol 

Drug Treatment 

Figure 6.4 Mean (+SED) changes in perceived effort to accomplish the 

driving test by Drug, relative to placebo.. Raw scores were expressed as 

percentage of maximum of scale. 

Willingness to Drive 

Table 6.9 presents the percentage of subjects willing to drive' under specified conditions of 

different urgencies (A. unimportant though gratifying; B. important but avoidable; and C. 

urgent). The more'urgent the reason for driving, the more subjects declared that they would be 

willing to drive. 

Table 6.9 Percentages of subjects willing to drive under circumstances A, B & C.(see text) by 

treatment condition and sampling time; and, the significance of each difference between placebo 

and active drug condition, tested by Cochran's Q-test. 

Alcohol Group Marijuana Group 

placebo alcohol P< placebo marijuana P< 

A t=50 100 38 .006 86 50 .044 

t= 175 100 50 .012 93 57 .044 

B t=50 100 44 .008 93 57 .044 

t=175 100 . 75 .07 100 57 .03 

C t=50 100 94. ns 100 93 ns 

r= 175 100 94 ns 100 100 ns 

-90­
Cochran's Q-test showed that the numbers of subjects who would have driven for an unimportant 

reason following the active drug were significantly less than after placebo, in both groups. The 

same held true for the somewhat more important reason. In-contrast, nearly all subjects indicated 

that they would have driven for an urgent reason, irrespective of the administered drug. MannWhitney's U-test failed to reveal any significant difference between the groups' percentages 

following the active drug. 

Perceived Alertness, Contentedness and Calmness 

Changes in subjective feelings of alertness, contentedness aiid calmness are shown in Table 6.10. 

Feelings of alertness were significantly diminished in both groups and at both time points 

following the active drug relative to placebo. Subjects felt also less content and calm following 

the active drugs, but the effects were smaller. Statistical tests revealed only one significant 

effect: alcohol producing significantly diminished feelings of contentedness measured after 

termination of the driving test. ;r. 

Table 6.10 Mean (±SED) changes in subjective feelings of alertness, contentedness and 

calmness (raw scores being expressed as percentages of maximum) for the marijuana (N =14) 

and alcohol group (N =16); and, the significance of each change and difference between 

changes. 

Dependent Variable Marijuana Group Alcohol Group Marijuana w Ak obd 

p< A p< p< 

Alertness­ t=35 -15.4 (±4.2).003 -18.9 (±3.6).001 ns 

t=95 -15.1 (±5.3).014 -20.1 (±3.0).001 ns 

Contentedness t=35 -6.2 (±4.0) ns -5.8 (±4.3) ns ns 

t=95 -5.7 (±3.6) ns -8.9 (±2.3).002 ns 

Calmness­ t=35 -7.5 (±4.4) ns -1.2 (±4.2) ns ns 

t=95 -10.0 (±5.2).077 -7.3 (±5.3) ns as 

Hand Steadiness Test 

Mean square root of total number of side contacts were about the same in the placebo conditions 

for both groups. The active drugs, however, affected hand steadiness differently; the number of 

side contacts increased after THC whereas the opposite occurred after alcohol (Figure 6.5). 

Statistical analysis showed that the impairment following THC was highly significant, both 

shortly after smoking and more than one hour later (T13=3.96 & 3.40; p<.002 & .005, 

respectively), whereas the improvement following alcohol was only significant shortly after 

drinking (T,5 =-2.29; p<.037). The differences between the groups' mean changes were 

significant both before and after the driving test (T2,=4.71 & 3.35; p<.001 & .002, 

respectively). 

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 *

Square root of total aide contacts 3.0 r

2.5 - t-30 ®t-io5

0.0

4.5

-1.0

-1.5 * 

-2.0

MarMuana Alcohol

Drug Treatment

Figure 6.5 Mean (+SED) changes in the square root of total number of side

contacts in the hand steadiness test by Drug, relative to placebo.

Interval Production (s)

lr

- t-30 EM t=105

I F\

*

Marijuana Alcohol

Drug Treatment

Figure 6.6 Mean (+SED) changes in attempted production of a 30-second

interval by Drug, relative to placebo.

-92-
lime Perception Test

Mean attempted production of a 30-second interval was close to the target for the alcohol group,

both after placebo and active drug yielding very small, and non-significant, changes (Figure

6.6). Subjects in the marijuana group produced a foreshortened interval in both conditions, but

foreshortening was greater following THC. The change in interval production was, however,

only significant after, and not before, the driving test (T13 =-2.36; p < .045).

Inter-Subject Relations between Variables

Relationship between Plasma Concentrations- and Driving Performance. Correlational

analyses were performed to determine whether driving performance was related to plasma

concentrations of the drugs, measured both before and after the driving tests. The first step

involved correlational analysis between raw variables; the second step, between changes in

driving performance and plasma concentrations. Neither analysis yielded 'significant results.

Relationship between the Molecular and Molar Approach. Correlations were also computed

between the raw Total Scores obtained by both the molecular and molar approach: These

correlations were computed in each condition separately. For the marijuana group, the

correlation between the Total Scores were 0.71 (p<.005; 2-tailed) and 0.54 (p<.044) in the

placebo and active drug condition, respectively. For the alcohol group, the corresponding

correlations were 0.71 (p<.002) and 0.79 (p<.001), respectively. Differences between these

correlations were not significant. The second step involved -correlational analysis of change

scores. This analysis revealed that changes- in Total Scores of both methods were not

significantly correlated, neither in the marijuana (r=0.O5) nor in the alcohol group (r=0.08).

Relationship between Driving Performance and Driving Experience. Correlations were also

computed between driving experience on one hand, and driving performance and changes in

driving performance following the active drug on the other. Neither analysis revealed significant

correlations. This means that driving experience of the subjects in the present study could neither

predict driving performance per se nor changes following the active drug.

Relationship between Plasma Concentrations and Perceived Intoxication. Correlations of

perceived "high" following THC with [THC] were 0.65 (p<.013) shortly after smoking and

0.47 (p < .093) following termination of the driving test. Correlations with [THC-COON] were 

0.74 (p<.002) and 0.62 (p<.018), respectively. Correlations of perceived intoxication 

following alcohol and [EtOH] were not significant (r=0.27 & 0.39, respectively). Correlations 

of plasma concentrations with changes in perceived intoxication were nearly the same as those 

with the raw scores, because intoxication ratings were generally zero following placebo. 

DISCUSSION 

The present study showed that alcohol, administered in a dose of 0.43 g ethanol per kg of lean 

body mass yielding an average plasma alcohol concentration of about 0.04 g%, produced a 

significant impairment in city driving as measured by the molar approach, relative to placebo. 

Significant impairment was shown by changes in Total Score, and subscores describing Handling 

of Vehicle and Action in Traffic. Marijuana, administered in a dose of 100 μg THC per kg of 

whole body weight, on the other hand, did not significantly change mean driving performance 

-93­
as measured by this approach. Neither alcohol nor marijuana significantly affected driving 

performance measures obtained by the molecular approach. 

The first conclusion one might draw is that the methods applied for measuring driving 

performance did not yield exactly the same results. Yet both methods similarly measured 

individual differences in driving proficiency. Correlations between the total scores in all four 

conditions were between 0.54 and 0.79, and as such, highly significant. Obviously both methods 

were able to discriminate the relatively large pre-existing differences in the subjects' respective 

abilities to operate the vehicle in urban traffic. Change scores were, however, not correlated; 

i.e. r=0.05 & 0.08 in the marijuana and alcohol group, respectively. Since the molar, and not 

the molecular, approach was sensitive to alcohol's adverse effects, it is tempting to conclude that 

the latter may fail to measure some important driving deficits. That is, the molecular approach 

seems relatively insensitive to drug-induced changes. 

The second conclusion one might draw is that the molar method, having proven its sensitivity 

by detecting impairment associated with a low BAC, should be sensitive to any similar 

impairment occurring after a correspondingly low THC dose. That it failed to show any 

significant change in the marijuana group's driving performance leads to the third and most 

important conclusion: 

The 100 μg/kg THC dose these subjects received shortly before 

the test did not impair their city driving performance. 

The different effects of alcohol and marijuana on driving performance can not be explained 

by the subjects' reported driving experience. Although subjects in the alcohol group were 

somewhat more experienced drivers than those in the marijuana group, the difference was not 

significant. Furthermore, correlational analysis showed that neither driving performance nor 

driving impairment was significantly related to previous driving experience. The different effects 

of alcohol and marijuana on driving performance can also not be explained by differences in the 

groups' subjective feelings. There was a remarkable correspondence between the two groups' 

feelings of intoxication, i.e. "high" or "drunkness". Prior to the driving test, both groups 

reported intoxication levels of about 35 % of the highest ever experienced, and 25 %, after its 

termination. THC's significant impairing effect on hand steadiness also showed that the subjects 

in the marijuana group. were sensitive to THC's effects. 

The difference between the drugs' effects on driving may be explained, however, by 

compensational mechanisms, such as increased effort. Both groups reported about the same 

amount of effort in accomplishing the driving test following placebo. Yet only subjects in the 

marijuana group reported significantly higher levels of invested effort following the active drug. 

Previous on-road driving studies indicate that subjects may compensate for THC's -adverse 

effects by slowing down (Hansteen et al., 1976; Casswell, 1979; Peck et al., 1986). Results of 

the present study were in the same direction: it took the marijuana group an average- of 46 s 

longer to complete the circuit after THC than following placebo. That this difference was not 

significant was probably due to the real-life character of the test: unforseen obstructions and 

variable traffic density probably increased the error variance of this measure over what it would 

have been on a closed course. Thus, there was evidence that subjects in the marijuana group 

were not only aware of their intoxicated condition but were also attempting to compensate for 

it. 

-94 
There were other striking differences between the groups' reactions to their respective drugs. 

As stated, subjects in the marijuana group invested more effort in the test while driving under 

the influence of THC. The alcohol group apparently made no greater effort after the drug than 

placebo. Yet for all of their effort, the marijuana group rated their driving performance as being 

significantly worse after THC than placebo. The alcohol group who invested no special effort 

after the drug, not surprisingly, thought they had driven as well as following placebo. They were 

nonetheless driving in a deficient manner according to the instructor's ratings. These seem to 

-be important findings. They support both the common belief that drivers become overconfident 

after drinking alcohol and investigators' suspicions that they become -more cautious and selfcritical after consuming low THC doses by smoking marijuana. 

These impressions were seemingly contradicted by the similarity in the groups' responses 

indicating their willingness to drive after the respective drugs. About 50% of both groups .said 

they would have been unwilling to drive for less than very urgent reasons. This profession of 

caution seems a bit odd for the alcohol group who knew that they could not be given a dose 

which would produce BACs over the legal limit during the test. The "contradiction" in this case 

seems to be a reflection of the group's desire to give "socially desirable" answers 'to_ the 

questionnaire, whether the same was true for the marijuana group in the present and preceding 

studies is a moot point. 

The laboratory performance tests also discriminated between the drugs' effects. Hand 

steadiness was impaired following THC and improved following alcohol, relative to placebo. 

The difference between the drugs' effects was significant, both before and after the driving test. 

Impairment after THC was about as much as that produced by the same dose in the previous 

study, indicating equivalent sensitivities of the present and previous groups. Production of time 

intervals was not affected by alcohol, but THC significantly shortened interval production, 

relative to placebo. This confirms the common finding that THC affects time estimation 

(Hollister and Gillespie, 1970; Bech et al., 1973). As usual, THC accelerated the subjects' 

perception of time passing. They arrived at a foreshortened production of 30 -s and would have 

estimated the duration of the actual interval as longer that it actually was. Changes in driving 

performance were not correlated with changes in performance in either laboratory test. 

Nevertheless, both tests should be seriously considered for inclusion in any test battery for 

measuring these drugs' effects, mainly because of the different pattern of results they produced. 

Plasma concentrations of THC and THC-COOH were comparable to those obtained in the 

previous studies. Plasma concentrations of ethanol were somewhat lower than predicted, and the 

fall in plasma concentration during the driving test was less than expected. This probably means 

that peak plasma concentrations generally occurred during the driving test. If so, it probably was 

about 0.04 g%. Ratings of "high" were significantly related to plasma concentrations of THC 

and THC-COOH but those of "drunkness" were not significantly related to plasma concentrations of ethanol. Drug plasma concentrations were neither related to absolute driving 

performance scores nor to the changes that occurred from placebo to drug conditions. With 

respect to THC, these results confirm the findings in previous studies. They are somewhat 

surprising for alcohol but may be due to the restricted range of ethanol concentrations in the 

plasma of different subjects. 

How do the present results relate to those reported by Klonoff (1974)? He also assessed the 

effects of relatively low THC doses on aspects of subjects' driving performance in a city driving 

test using a similar molar approach. His subjects commenced driving immediately after cessation 

of smoking. They scored lower on judgment and concentration scales when under the influence 

-95­
of the highest, but not the lowest, dose. Behaviors that were more directly related to driving 

performance, e.g. lane changing, compliance with traffic signals and posted speed advisories, 

were not affected by the drug. -Subjects in the present study commenced driving 30 minutes after 

initiation of smoking. The molar method applied in the present study did not include ratings of 

judgment or concentration. With the exception of these two items, neither study indicated 

significant effects of THC on driving performance and are, therefore, in complete agreement. 
CHAPTER 7 - GENERAL DISCUSSION, CONCLUSIONS AND

RECOMMENDATIONS

INTRODUCTION 

It is commonly assumed that marijuana smoking in real-life social situations delivers THC doses 

that seriously degrade the ability to safely operate motor vehicles; and, that the drug's users 

frequently drive shortly after smoking. If these premises are correct, it would follow that 

marijuana users are, while intoxicated, at increased risk of traffic accident involvement and 

constitute a safety hazard for other road users. However, the. foremost impression one gains 

from reviewing the literature is that no clear relationship has ever been demonstrated between 

marijuana smoking and either seriously impaired driving performance or traffic safety. The 

epidemiological evidence, as limited as it is, shows that the combination of THC and alcohol 

is over-represented in injured and dead drivers and more so in those who actually caused the 

accidents. Yet there is little if any evidence to indicate that drivers who have used marijuana 

alone are any more likely to cause serious accidents than drug free drivers. To a large extent, 

the results from driving simulator and closed-course tests corroborate the epidemiological 

findings by indicating that THC in single inhaled doses up .to about 250 μg/kg has relatively 

minor effects on driving performance, certainly less than BACs in the range 0.08-0.10 g%. 

But how well do these findings relate to the actual driving performance of regular marijuana 

users? If previous experience is any guide, little of crucial importance will emerge from 

experimental research until it is conducted in a more realistic manner. Therefore, a series of 

studies were conducted to determine the dose-response relationship between THC and objectively 

and subjectively measured aspects of real world driving. A variety of driving tasks were 

employed, including maintenance of a constant speed and steady lateral-. position during 

uninterrupted highway travel, adjusting velocity to the movements of a leading car on a 

highway, and city driving. The purpose of applying different tests was to determine whether 

similar changes in performance under the influence of THC occurs in all thereby indicating a 

general drug effect on driving safety. 

However real these tests might appear, the circumstances in which the subjects smoked the 

drug and drove the car were still somewhat artificial. First, the subjects consumed the drug in 

a neutral setting, alone or in the presence of a stranger. This was of course different from the 

situation wherein they normally smoke marijuana, i.e. in the company- of friends who might 

reinforce a certain type of behavior not normally considered as conservative or prudent. Marks 

and Pow (1989) found that marijuana smokers derived slightly greater pleasure from THC in the 

company of friends than strangers from which one might infer a social amplification of the 

pharmacological effect. However, neither they nor any other investigators ever indicated that 

social amplification outlasts the situation which gives rise to it. In the absence of such evidence, 

we tend to discount the possibility that the unusual setting for drug administration had any effect 

upon subsequent driving performance. Social amplification of THC's adverse effects on driving 

performance might well occur if the driver were accompanied by similarly intoxicated 

passengers. We must therefore restrict generalizations from the studies' results to those situations 

97
where the intoxicated. driver is doing his best to perform efficiently and is uninfluenced by 

friends or any other factor which might amplify the drug's adverse effects. 

Secondly, subjects were aware of the fact that their driving behavior was being observed and 

that the accompanying driving instructor would intervene if necessary. The former is hardly 

avoidable in experimental studies but possibly provoked the subjects to do their utmost; the latter 

is a prerequisite for ensuring safety in actual driving studies and may or may not have produced 

nonchalance on the subjects' part resulting in poorer than normal performance. Yet according 

to what the subjects declared, they drove normally after placebo indicating that the experimental 

situation had not seriously altered their performance. Whether they drove in the test as they 

normally would after smoking marijuana remains open to question. The correspondence between 

experimental and epidemiological studies regarding THC's effects on driving performance 

suggests that this artificiality is also of minor concern. 

The present series of studies are about the best simulation of real world driving one can 

reasonably achieve and have gone further toward defining the effects of marijuana smoking on 

actual driving performance than any of its predecessors.- The results found in the successive 

studies were discussed at full length in the respective chapters. In this chapter, results of the 

separate studies will be. integrated to provide answers to some important questions concerning 

marijuana's influence on driving performance. First however, the implications of the pilot 

study's major result will be discussed, i.e. the THC dose that marijuana users prefer to achieve 

their desired "high". In the following section, the driving tests will be discussed in terms of the. 

kinds of mental operations they require. Some further remarks provided, in that section concern 

the relevance of the driving tests for traffic safety. The major part of this chapter will be 

addressed to the most important issue, i.e. what the results indicate as the real effects of 

marijuana smoking on driving performance. Finally, attention will focus on the relationship 

between plasma drug concentrations and drug-induced driving impairments. This chapter will 

end with a list of conclusions and recommendations. 

THC DOSES 

To avoid arbitrarily selecting an unrealistic maximum THC dose for the driving studies, it was 

necessary to establish the dose which marijuana users actually prefer for achieving their desired 

"high". A pilot study met this requirement. The study showed that marijuana users prefer higher 

THC doses than those previously administered in experimental studies. Previous THC doses 

were generally between 100 and 200 μg/kg, including the remaining butt, whereas the subjects 

in the pilot study preferred an average dose of 300 μg/kg, excluding the butt. This either means 

that today's marijuana users prefer higher doses than in the past or that investigators failed to 

administer realistic doses in previous studies, or both. 

Ohisson et al. (1980) compared THC's effects after three different routes of drug 

administration. In the smoking condition, subjects were allowed to smoke a marijuana cigarette 

containing 19 mg THC in their own manner such as to obtain the maximum desired "high". 

Comparing the weight of the remaining butt with the unlit cigarette revealed that the eleven 

males participating in the study had smoked 13.0 mg THC on the average. Ohlsson et at. failed 

to report the subjects' mean weight but, assuming that it was 70 kg (154 lb) on average, this 

would equal to a THC dose of nearly 200 hg/kg. Perez-Reyes et al. (1982) compared THC's 

effects after smoking marijuana cigarettes of three different potencies. Three males and three 

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females participated in that study and the same procedures were applied to determine the amount 

of THC consumed as in Ohlsson's study. It appeared that the amount of THC consumed was 

proportional to the THC content, or potency, of the cigarette. The subjects consumed 9.7, 12.8 

and 16.9 mg THC when smoking cigarettes containing 1.32%, 1.97% and 2.54% THC, 

respectively. Perez-Reyes et al. also failed to report the subjects' mean weight but, for a 70 kg 

(154 lb) person, the weight calibrated amount of THC consumed would have been 140, 180 and 

240 μg/kg, respectively. These results indicate that the potency of the marijuana cigarette is a 

major contributor to the preferred dose. Ohlsson failed to mention the potency of the marijuana 

cigarettes they used which makes a comparison with the data of Perez-Reyes impossible. The 

potency of the cigarettes used in the present pilot study was 2.57%, nearly the `same as the 

highest in Perez-Reyes' study, and our subjects smoked on the average a THC dose of 20.8 mg, 

or 308 μg/kg. This might be an indication that users presently prefer higher doses than in the 

early eighties. However, there is one important distinction between these earlier studies and the 

present one.that may account for the increase. Our subjects were allowed to smoke a second, 

and even a third, cigarette to achieve their desired "high". Subjects in previous studies were 

given only one cigarette, maybe out of ignorance but probably because it was not the 

investigators' primary objective to determine the subjects' preferred dose. Consequently, the 

preferred dose of subjects who smoked one cigarette completely but not yet achieved their 

desired "high" was under-estimated. Thus, whether current users indeed prefer higher doses than 

ten years ago is hard to say. What is clear from the pilot study's results, is that higher THC 

doses than those usually administered in previous studies should be included in future ones. 

The relation between preferred dose and the potency of the drug found by Perez-Reyes et al. 

(1982) raises two questions that might have implications for interpreting the present studies' 

results. The first question is, how-do people regulate their THC consumption? Apparently they 

do not titrate brain THC concentrations to within a narrow range as tobacco smokers reliably, 

do with nicotine (Jaffe, 1990). It's also doubtful that marijuana smokers integrate their THC 

concentrations over time to cease consumption when the cumulative effect approaches a certain 

threshold. In the earlier study the subjects may have simply ceased smoking after consuming the 

same volume of cigarettes, regardless of the delivered dose. But this could not have occurred 

in the. pilot study for the present series since our subjects smoked ad lib. The probable 

explanation is that our subjects were somewhat aware of both the momentary brain concentration 

and its rate of increase and ceased smoking before the expected rise would shortly exceed the 

preferred effect. This procedure was accurate enough to limit the drug's effects to below what 

they had previously experienced as an unpleasant maximum. It was not accurate enough to attain 

homogeneity in the subjects' achievement of the preferred "high" in relation to the maximum 

(coefficient of variation: 25%). In real life, marijuana users are usually more aware of the 

potency. of the material they smoke, from prior experience, upon the advice of other users or 

even from its "street" price. The material presented to the subjects in.the pilot study was 

definitely unfamiliar and they may have suddenly become prudent smokers. Confirmation of this 

supposition came from the same subjects' consumption of THC in the subsequent driving study. 

Though treated with the same average dose they had preferred in the pilot study, their plasma 

drug concentrations were now higher. This difference was interpreted as the result of increased 

smoking efficiency due to familiarization with the potency.of the material containing the drug. 

If familiarization plays a major role in smoking efficiency and, consequently THC plasma 

concentrations, THC's adverse effects on performance may also be dependent on this factor. 

That being the case, the second and third driving studies' results would under-estimate THC's 

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adverse effects on driving performance since new ' groups of subjects were recruited in both. 

However, the remarkable resemblance between effects of every THC dose on SDLP in the first 

and second driving studies indicates that familiarization is not a very, important factor. 

Nevertheless, we recommend that subjects in future studies be familiarized with the potency of 

the drug before the beginning of performance testing. 

The second question raised by the apparent relationship between the drug's potency and the 

preferred dose is, what the latter would have been if marijuana of much higher potency were 

smoked. This is an important question since potencies of marijuana are increasing rapidly. At 

present, potencies of marijuana cultivated in The Netherlands may contain 5-20% THC, and, 

in exceptional cases, 30%. It is hard to imagine that subjects would consume as much of a 

cigarette containing a very high THC concentration as one containing a very low one. Future 

research determining marijuana users' preferred dose should also include marijuana with much 

higher potencies. It may then appear that Perez-Reyes et al.'s findings were attributable to their 

subjects' inability to discriminate among potencies spanning a narrow range. A broader range 

of cigarette potencies would probably allow regular marijuana users to discriminate well enough 

to alter their consumption and thereby come closer to administering the same preferred dose 

after every one. 

On the basis of the pilot study's results, the highest dose of THC administered in subsequent 

driving studies was defined as 300 μg/kg; other doses were 100 and 200 μg/kg, and placebo. 

Marijuana cigarettes were prepared from batches obtained from NIDA with potencies varying 

from 1.75% to 3.58%, the highest that were then available. If future research shows that current 

users of marijuana prefer much higher THC doses when they smoke very potent marijuana, the 

results of the current program can only serve as an indication of the minimal effects the drug 

may have on actual driving performance. If, on the other hand, it shows that users prefer a THC 

dose of about 300 μg/kg to reach their desired "high" irrespective of the potency of the drug, 

the results presented in this report are truly valid estimates of what may happen in daily life after 

smoking THC doses that induce a preferred "high". 

THE DRIVING TESTS 

Three different tests were applied in the experiments that progressively increased in the number 

of skills employed by the driver: road tracking, car following and city driving. The first is now 

a standardized test which, in more than 40 studies, has proven to be very sensitive to sedation 

produced by a variety of medicinal and social drugs, including alcohol. The car following and 

city driving test were developed following the recognition that parameters measured in the 

standard test fail to represent all abilities considered important for safe driving. This section will 

describe the differences between the driving tests and the relevance of each to traffic safety. 

The difference between the three driving tests can be characterized in many ways. The one 

described here is that in terms of the type of information processing each requires. Two distinct 

types of human information processing can be distinguished (Shiffrin and Schneider, 1977): 

"automatic" and "controlled". The former is capable of accepting an enormous volume of 

perceptual information at a relatively high rate to mediate coordinated multi-effector responding 

in a normally stable input-output relationship. This process is not generally under voluntary 

control, proceeds in parallel with the stream of consciousness and involves no decision making. 

Controlled information processing is much slower but highly adaptive. It begins with the 

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conscious perception of a discrete event or situation. Identification of the meaning of that 

perception is made by comparing it with information stored in memory. A decision involving 

the selection and execution of a particular series of motor responses and/or the suppression of 

a motor routine in progress occurs next. This process can proceed in parallel with an automatic 

process and the integrity of both are essential for safe driving. 

Aspects of both types of information processing are present in most well practiced tasks. 

Most would agree that skilled performance is the integrated sum of automatic and controlled 

information processing and that their respective weights vary constantly with the task 

requirements. The more controlled information processing a task requires, the more it is 

experienced as demanding effort. According to this concept, lateral position control in the road 

tracking test depends principally upon automatic information processing. The car following test 

requires somewhat more controlled information processing and driving in urban traffic, even 

more. The concept can be illustrated by the ease of having a.conversation with other occupants 

of a vehicle while driving. It is easy to converse with them while driving on a highway in light 

traffic. It becomes somewhat more difficult when driving in heavy traffic and maintaining a safe 

headway behind cars travelling in a platoon. Conversing while driving in urban traffic is even 

more difficult and, at times, even impossible for, most drivers. Thus, the more controlled 

processing involved in a particular situation, the more effort the driving task demands and the 

less "spare capacity" is left for having a conversation with other occupants. This concept of 

effort relates to task or computational demands, and often, to the allocation of attention. There 

exists, however, also another concept of effort which relates to brain arousal mechanisms 

(Kahneman, 1973; Pribram and McGuinness, 1975) or the required psychological state (Hockey, 

1986). If one perceives a discrepancy between his actual state of arousal and that required to 

efficiently accomplish the task, he will first attempt to resolve the difference by compensatory 

effort, e.g. focussing attention. Failing that, he will try to reduce task demands to what can be 

efficiently accomplished in the deficient arousal state. The latter can be accomplished during 

driving by reducing speed or assuming a greater headway to compensate for slower reaction 

times. 

It is sensible to. keep the relevance of the separate driving tests for driving and traffic safety 

in mind. while discussing THC's effects on driving performance. It is obvious that the road 

tracking test measures only a few aspects of driving behavior. Yet proper road tracking is a 

general prerequisite for safe driving. Consequently, drugs that substantially impair a driver's 

fundamental road tracking ability possess a real potential for adversely affecting driving safety. 

Whether this means that drivers under the influence of such drugs have also a greater probability 

of becoming involved in a traffic accident seems plausible but has yet to be determined. The 

same kind of reasoning applies to the car following test. It measures only a few additional 

aspects of driving behavior, but their impairment is also incompatible with safe driving. The city 

driving test measures most aspects of driving behavior and therefore comes closest to reality. 

Driving in urban traffic is so common in daily life that any drug-induced impairment found with 

this test should be considered as the most important, though not necessarily the earliest, sign that 

the drug possesses properties that adversely affect traffic safety. 
EFFECTS OF THC ON DRIVING PERFORMANCE

One of the issues addressed by the first driving study was whether it would be safe to continue 

using the same approach for subsequent on-road studies in traffic. The first group complied with 

all instructions, even after high doses of THC. Changes in mood were often reported but 

changes in personality were never observed. Most importantly, the subjects were always able 

to complete every ride without major interventions by the driving instructors and their safety was 

never compromised. The same occurred in the subsequent studies showing that it is possible to 

safely study. marijuana's effects on actual driving performance in the presence of other traffic. 

In this respect, the drug is no different from many others studied by the same investigators and 

their colleagues. 

The standard test measured the subjects' ability to maintain a constant speed and a steady 

lateral position between the lane boundaries. Standard deviation of lateral position, SDLP, 

increased after marijuana smoking in a dose-related manner. The lowest dose, i.e. 100 μg/kg 

THC, produced a slight elevation in mean SDLP, albeit significant. in the first driving study. The 

intermediate dose, i.e. 200,ug/kg THC, increased SDLP moderately; and, the highest, i.e. 

300 μg/kg THC, substantially. It is remarkable how well the changes in SDLP following THC 

in the first driving study were replicated in the second, in spite of the many differences in the 

ways they were designed. The replication of THC's effects on SDLP substantiates the generality 

of these results. Other objective measures obtained by this test were much less affected by THC. 

Mean speed was somewhat reduced following the higher THC doses, but the effects were 

relatively small (max. 1.1 km/h or 0.7 mph). Standard deviations of speed and steering wheel 

movements were unaffected by the drug. Subjective ratings of perceived driving quality followed 

a similar pattern as SDLP indicating that the subjects were well aware of their diminished ability 

to control the vehicle after -marijuana smoking. 

The car following test measured the subjects' ability to follow a leading car with varying 

speed at a constant distance. All THC doses increased mean headway, but according to an 

inverse dose-response relationship- This type of relationship was unexpected and probably due 

to the particular design of the second driving study, i.e. the ascending dose series. It means that 

subjects were very cautious the first time they undertook the test under the influence of THC 

(i.e. after the lowest dose) and progressively less thereafter. As a consequence of this 

phenomenon, mean reaction time to changes in the preceding car's speed also followed an 

inverse dose-response relationship. Statistical adjustment for this confounding by analysis of 

covariance indicated that reaction times would not have increased significantly if the mean 

headway were constant. Coefficient of headway variation increased slightly following THC. 

Together, these data indicate that there is no more than a slight tendency towards impairment 

in car following performance after marijuana smoking. They also show that subjects try to 

compensate for anticipated adverse effects of the drug by increasing headway; especially when 

they are uncertain of what these might be. As in the standard test, subjects' ratings of driving 

quality corresponded to the objective changes in their performance. 

The city driving study measured the subjects' ability to operate a vehicle in urban traffic. For 

reasons mentioned in the respective chapter the THC dose in that study was restricted to 

100 μg/kg. For comparative purposes another group of subjects was treated with a modest dose 

of alcohol, producing a mean BAC of about 0.04 g%. Results of the study showed that the 

modest dose of alcohol, but not THC, produced a significant impairment in driving performance, 

relative to placebo. Alcohol impaired driving performance but subjects did not perceive it. THC 

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did not impair driving performance yet the subjects thought it had. After alcohol, there was a 

tendency towards faster driving and after THC, slower. 

. The results of these studies corroborate those of previous driving simulator and closed-course 

tests by indicating that THC in single inhaled doses up to 300, jig/kg has significant, yet not 

dramatic, dose-related impairing effects on driving performance. They contrast with results from 

many laboratory tests, reviewed by Moskowitz (1985), which show that even low doses of THC 

impair skills deemed important for driving, such as perception, coordination, tracking and 

vigilance. The present studies also demonstrated that marijuana can have greater effects in 

laboratory than driving tests. The last study, for example, showed a highly significant effect of 

THC on hand unsteadiness but not on driving in t ban traffic. 

It is a natural question why the effects of marijuana on actual driving performance appear 

to be so small. As in many previous investigations, subjects attempted to compensate for 

anticipated adverse effects of marijuana smoking. Our subjects were aware of the impairing 

effects of THC as shown by lower ratings of perceived driving quality. Consequently, they 

invested more effort to accomplish the driving tests following THC than placebo. Furthermore, 

in the car following test, they drove at a greater headway after marijuana smoking; and, in both 

road tracking and city driving tests, they slightly reduced their driving speed. Yet despite their 

effort, subjects were unable to fully compensate for THC's adverse effects on lateral position 

variability. This is because SDLP is primarily controlled by an automatic information processing 

system which operates outside of conscious control. The process is relatively impervious to 

environmental changes, as shown by the high reliability of SDLP under repeated placebo 

conditions, but highly vulnerable to internal factors that retard the flow of information through 

the system. THC 'and many other drugs are among these factors. When they interfere with the 

process that restricts SDLP, there is little the afflicted individual can do by way of compensation 

to restore the situation. Car following and, to a greater extent, city driving performance depend 

more on controlled information processing and are therefore more accessible for compensatory 

mechanisms that reduce the decrements or abolish them entirely. 

This still leaves the question open why performance appears to.be more affected by THC in 

laboratory than actual driving tests. Many researchers defend the primacy of laboratory 

performance tests for measuring drug effects on skills. related to driving on the basis of superior 

experimental control. Certainly some control is always necessary to reduce the confounding 

influence of extraneous factors that would otherwise so increase measurement error as to totally 

obscure the drug's effects. However, only some extraneous factors are truly sources of 

measurement error and others either attenuate or amplify drug effects in real driving and must 

be considered as relevant to a test's predictive validity. Simply eliminating all of them, first, 

removes their normal mediating influence on the drug effect, and secondly, affects the subject's 

motivation to perform the test by making it appear "unreal". Controlling the test usually involves 

drastic simplification and restriction of response options. The desire in doing this is to isolate 

a particular driving skill and determine how it changes under the influence of drugs. However, 

drivers always apply numerous skills in parallel and series. Should one become deficient, they 

are often able to compensate in a number of ways to achieve a satisfactory level of proficiency. 

Thus the demonstration of some particular 'skill decrement in the laboratory in no way indicates 

that this would ultimately reduce driving safety in reality, Finally there are some skills that 

simply can not be measured in laboratory tests, at least not easily enough to make it a routine 

matter. The acquisition of any skill which depends upon automatic information processing 

requires practice over weeks or months. After learning to drive, subjects possess such skills in 

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abundance and one can only demonstrate how they vary with drug effects in the real task or a 

very close approximation thereof. 

Profound drug impairment constituting an obvious traffic safety hazard could as easily be 

demonstrated in a laboratory performance test as anywhere else. But THC is not a profoundly 

impairing drug. It does affect automatic information processing, even after low doses, but not 

to any great extent after high doses. It apparently affects controlled information processing in 

a variety of laboratory tests, but not to the extent which is. beyond the individual's ability to 

control when he is motivated and permitted to do so in real driving. in short, it would appear 

as if over-control in laboratory performance tests has resulted in a misimpression of THC's 

effect, incomplete in some respects and exaggerated in others. The actual driving tests may 

provide a more realistic impression of the drug's effects, albeit still incomplete and perhaps 

tending to minimize them with respect to more complex driving situations that come closer to 

"worst case 

The degree of experimental control also varied between driving tests in this series in ways 

affecting the, subjects' motivation. This is illustrated by a comparison between the- first and 

second driving study. The standard road tracking test was applied in both, first in the absence 

and then in the presence of other traffic. It was only during the former that disturbing 

observations of two individuals' attentional deficits caused the driving instructor to intervene. 

Driving in the presence of other traffic, subjects were always able to complete the rides without 

intervention. Lateral position control, an automatic process, did not change as a consequence of 

the absence or presence of other traffic. What did change was the subjects' motivation to focus 

attention, a controlled process. Motivation in the second study was very probably affected by 

recognition of the increased risk of the untoward consequences of wandering attention. This 

means that the intrinsic motivation produced by the reality of the test situation is an important 

mediator of THC's effects on performance. 

Compensatory mechanisms help the driver under the influence of marijuana to maintain an 

effective level of performance but with an associated cost. If drivers compensate for THC's 

adverse effects. by diminishing driving demands (e.g. by reducing speed and/or increasing 

headway), this will occur without a reduction in spare capacity. But if they increase effort as 

well (e.g, by focusing attention), it will occur at the expense of spare capacity. Less capacity 

would be left for simultaneously performing another task, such as conversing with passengers, 

using a car telephone, or handling emergency situations. The information processing capacity 

these situations demand may well go beyond the driver's spare capacity with the result of 

impaired and perhaps dangerous driving. Results of the present program show that THC 

increases the mental load of driving, as shown by increased effort ratings and reduced heart rate 

variability, and consequently reduces spare capacity. This corroborates results from previous 

simulator and closed-course studies that with reasonable consistency show an adverse THC effect 

on subsidiary task performance (Smiley, 1986). Further research. is required to determine 

marijuana's effects on actual driving performance when the driver is simultaneously performing 

another task or suddenly confronted with a situation that requires a rapid adaptive response. The 

latter was occasionally encountered during the city driving test, but only after a low THC dose. 

The city driving test should therefore be repeated with subjects consuming higher THC doses. 

Hazardous driving can also occur in situations that demand very little of the driver's 

information processing capacity. If the driving task is very monotonous and the demand is low, 

wandering attention may result in negligent monitoring with disastrous results. This is in fact 

what happened twice during the driving study on the closed road. After the highest THC dose, 

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one subject failed to shift attention from the prescribed task to an unexpected event (screwdriver 

on the road); another failed to anticipate a normal event (end of circuit). Though even sober 

experienced drivers may experience similar deficits, the fact that it happened twice after the 

highest THC dose, and never after a lower dose or placebo, strongly suggests that drivers under 

the influence of THC would be unusually susceptible to attentional deficits during prolonged and 

monotonous driving. 

How do marijuana's effects on driving performance compare to those of alcohol? There are 

two sources from which one can draw to answer the question. Information can be directly 

obtained from studies comparing THC and alcohol effects in the same experiment; and, 

indirectly, from studies wherein alcohol's effects were assessed using the same methods as 

applied in the present THC studies. As mentioned in Chapter 1, most closed-course studies on 

THC also measured alcohol's effects (BACs between 0.04 and 0.10 g%). It was generally 

concluded that THC's effects were less than alcohol's, especially at BACs above 0.08 g %. The 

-city driving study in the present program also compared the effects of modest doses of alcohol 

and THC. For doses administered in that study, alcohol'produced the greater effects. Indirect 

evidence concerning the relative effects of THC and alcohol can be obtained from three studies. 

First, the alcohol calibration study by Louwerens et al. (1985, 1987) which resembled our first 

driving study in many respects. According to their empirical equation, THC's effects on SDLP 

were equal to or less than that of BAC = 0.07 g %. More recently, studies by Riedel et al. (1989) 

and Ramaekers et at. (1992a) measured the effects of low doses of alcohol (BACs of 0.05 and 

0.03 g % respectively) on SDLP. Both groups applied the,.standard test in the presence of other 

traffic, as in our second driving study, but on another highway. Mean SDLPs were respectively 

about 5.0 and 2.5 cm higher while driving after alcohol than placebo. The former elevation is 

greater than that produced by the highest THC dose in our study. The latter lies between the 

effects of 200 and 300 μg/kg doses, which were 1.8 and 2.9 cm respectively. There was some 

discrepancy between alcohol's effects on SDLP in the more recent studies and those predicted 

by the empirical equation: the former were higher than predicted. The discrepancy appears to 

be related to the difference between alcohol's effects on the ascending and descending phases 

of its pharmacokinetic profile. Louwerens measured alcohol's effects at the time when BAC was 

at the ascending but Riedel and Ramaekers measured them during the descending phase. 

Notwithstanding methodological differences among studies, both direct and indirect evidence 

converge on the conclusion that THC's effects after doses up to 300 μg/kg never exceed 

alcohol's at BACs of 0.08 g%. 

How do marijuana's effects on driving performance compare to those of drugs other than 

alcohol? No direct comparisons have ever been made, but many studies employing the standard 

road tracking test were conducted for measuring other drugs' effects on SDLP during the last 

decade. The results from a few will be mentioned. Diazepam (Valium) given for one week in 

a low therapeutic dose (5 mg, thrice daily) caused anxious patients to drive with a mean SDLP 

about 7 cm higher than their premedication baseline (Van Laar et al., 1992). The same drug and 

dose given over the same period caused healthy volunteers to drive with a mean SDLP about 

6 cm higher than placebo (Van Veggel and O'Hanlon, 1993). Lorazepam (Ativan'), another 

anxiolytic, given twice daily for one week in a 1.5 mg dose to healthy volunteers (Volkerts et 

al., 1988) and a 2 mg dose to patients (Vermeeren et al., 1993), produced an elevation of SDLP 

of about 10 cm in both cases. Amitriptyline (Elavil'), a widely prescribed antidepressant, given 

in a dose of 50 mg at night and 25 mg in the morning caused healthy volunteers to drive with 

a mean SDLP about 6 cm higher than placebo (Robbe et al., 1989). Flurazepam (Dalmane'), 

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a hypnotic, was administered to insomniacs and its "hang-over" effects on SDLP were measured 

10-11 hours after ingestion. A 15 mg dose of flurazepam elevated mean SDLP by about 4 cm; 

a 30 mg dose, 7 cm. Antihistamines also cause sedation and, consequently, impair road tracking 

performance. Triprolidine (Actifed) increased SDLP by 3.5 cm after a single 5 mg dose (Riedel 

et al., 1990); and, diphenhydramine 50 mg (Benadryl Kapseals) increased SDLP by 4.5 cm 

(Ramaekers et al., 1992b). This is not to say that all psychotropic drugs produce greater 

elevations of SDLP than THC. Many in the same and other experiments had less effect than 

THC did in our studies. These examples are merely cited to indicate that THC's effects as 

measured in the standard test were in no way unusual. In so far as its effects on SDLP are 

concerned, THC was just another moderately impairing drug. 

The foregoing comparisons might be misleading. THC's effects differ qualitatively from 

many other drugs, especially alcohol. For example, subjects drive faster after drinking alcohol 

and slower after smoking marijuana (Hansteen et al., 1976; Casswell, 1979; Peck et al., 1986; 

Smiley et -al., 1987). Moreover, the simulator study by Ellingstad et dl. (1973) showed that 

subjects under the influence of marijuana were less likely to engage in overtaking maneuvers, 

whereas those under the influence of alcohol showed the opposite tendency. Very importantly, 

our city driving study showed that drivers who drank alcohol over-estimated their performance 

quality whereas those who smoked marijuana under-estimated it. Perhaps as a consequence, the 

former invested no special. effort for accomplishing the task whereas the latter did, and 

successfully. This evidence strongly suggests that alcohol encourages risky driving whereas THC 

encourages greater caution, at least in experiments. Another way THC seems to differ 

qualitatively from many other drugs is that the former's users seem better able to compensate 

for its adverse effects while driving under the influence. Weil et al. (1968) were among the 

earliest authors who mentioned the possibility that marijuana users can actively suppress the 

drug's adverse effects. They presumed that THC's effects were confined to higher cortical 

functions'without any general stimulatory or depressive effect on lower brain centers. According 

to them, the relative absence of neurological, as opposed to psychiatric, symptoms in marijuana 

intoxication suggests this possibility. More recently, Moskowitz (1985) concluded that the 

variety of impairments found after marijuana smoking could not be explained by decrements in 

sensory or motor functions which led him to hypothesize that some important central cognitive 

process is impaired by THC, without saying what it is. Identification of THC's site of action 

would greatly enhance our understanding of the drug's psychopharmacological effects. 

Epidemiological research has shown that THC is infrequently detected in the blood of fatally 

injured drivers as the only drug present. In most cases alcohol is also detected. The effects of 

the combination of THC and alcohol on actual driving performance have never been studied in 

the presence of other traffic. Closed-course studies have shown that the effects of both drugs, 

when taken in combination, are generally additive (Attwood et al.,. 1981; Peck et al., 1986). 

This may only be so for those behaviors that are similarly affected by both drugs given 

separately. Closer examination of the combined use is warranted in those driving situations 

where both drugs produce qualitatively different effects. It may well be so that alcohol reduces 

drivers' insight or motivation to the point where they would no longer attempt to compensate 

for the THC effect. As a result, the combined effects on drivers' performance could well be 

greater than the sum of either drug acting separately. There is therefore a great need for further 

research on marijuana and actual driving research, but now extended to the combination of 

marijuana and alcohol. 

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In summary, this program of research has shown that marijuana, when taken alone, produces 

a moderate degree of driving impairment which is -related to the consumed THC dose. The 

impairment manifests itself mainly in the ability to-maintain a steady lateral position on the road, 

but its magnitude is not exceptional in comparison with changes produced by many medicinal 

drugs and alcohol. Drivers under the influence of marijuana retain insight in their performance 

and will compensate where they can, for example, by slowing down or increasing effort. As a 

consequence, THC's adverse effects on driving performance appear relatively small. Still we can 

easily imagine situations where the influence of marijuana smoking might have an exceedingly 

dangerous effect; i.e., emergency situations which put high demands on the driver's information 

processing capacity, prolonged monotonous driving, and after THC has been taken with other 

drugs, especially alcohol. We therefore agree with Moskowitz' conclusion that "any situation 

in which safety both for self and others depends upon alertness and capability of control of manmachine interaction precludes the use of marihuana". However, the magnitude of marijuana's, 

relative to many other drugs', effects also justify Gieringer's (1988) .conclusion that "marijuana 

impairment presents a real, but secondary, safety risk; and that alcohol is the leading drugrelated accident risk factor". Of the many psychotropic drugs, licit and illicit, that are available 

and used by people who subsequently drive, marijuana may well be among the least harmful. 

Campaigns to discourage the use of marijuana by drivers are certainly warranted. But 

concentrating a campaign on marijuana alone may not be in proportion to the safety problem it 

causes. 

DRUG PLASMA CONCENTRATIONS AND DRIVING PERFORMANCE 

One of the program's objectives was to determine whether it. is possible to predict driving 

impairment by plasma concentrations of THC and/or its metabolite, THC-COOH, in single 

samples. The answer is very clear: it is not. Plasma of drivers showing substantial impairment 

in these studies contained both high and low THC concentrations; and, drivers with high plasma 

concentrations showed substantial, but also no impairment, or even some improvement. The first 

driving study showed that impairment in the road tracking test was nearly the same in the first 

and second test, executed between 40-60 and 100-120 minutes after initiation of smoking, 

respectively. Plasma concentrations of THC and THC-COOH, however, were not the same 

during the tests: both were lower during the second than the first. The same pattern was found 

for ratings of perceived "high". It has been said that behavioral signs of intoxication, though 

small, outlast physiological and subjective reactions to THC (Reeve et al., 1983; Yesavage et 

al., 1985). To examine this hypothesis, future research should extend actual driving performance 

measurements to 4, 8, 16 and 24 hours after smoking. If driving impairment still occurs after 

THC disappears from plasma, it could mean that previous epidemiological research has underestimated the proportion of drivers who were driving under the influence of marijuana at the 

times their accidents occurred. 

Mean speed was the only measure of driving performance that was even moderately .related 

to plasma concentrations of the drug. Subjects with higher THC concentrations in plasma drove 

slower in the standard road tracking test (correlations varying from r=-.18 to r=-.72 between 

conditions). This effect might have been even more pronounced if the subjects had not been 

instructed to drive at a particular speed, and if they had had no feedback from the speedometer. 

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CONCLUSIONS 

The major conclusions from the present program are summarized as follows: 

• Current users of marijuana prefer THC doses of about 300 μg/kg to achieve their desired 

"high". 

• It is possible to safely study the effects of marijuana on driving on highways or city streets 

in the presence of other traffic. 

•

Marijuana smoking impairs fundamental road tracking ability with the degree of impairment 

increasing as a function of the consumed THC dose. 

•

Marijuana smoking which delivers THC up to a 300 pg/kg dose slightly impairs the ability 

to maintain a constant headway while following another car. 

• A low THC dose (100 μg/kg) does not impair driving ability in urban traffic to the same 

extent as a blood alcohol concentration (BAC) of 0.04 g%. 

• Drivers under the influence of marijuana tend to over-estimate the adverse effects of the drug 

on their driving quality and compensate when they can; e.g. by increasing effort to 

accomplish the task, increasing headway or slowing down, or a combination of these. 

• Drivers under the influence of alcohol tend to under-estimate the adverse effects of the drug 

on their driving quality and do not invest compensatory effort. 

• The maximum road tracking impairment after the highest THC dose (300 μg/kg) was within 

a range of effects produced by many commonly used medicinal drugs and less than that 

associated with a blood alcohol concentration (BAC) of 0.08 g% in previous studies 

employing the same test. 

• It is not possible to conclude anything about a driver's impairment on the basis of his/her 

plasma concentrations of THC and THC-COOH determined in-a single sample. 
RECOMMENDATIONS FOR FUTURE RESEARCH

The recommendations for future research are summarized as follows:

• Future studies on marijuana's effects on driving performance should include the THC dose 

that currents users of marijuana prefer to achieve their desired "high", i.e. 300 ug/kg. 

• Subjects in future studies should be familiarized with the potency of the material providing 

THC before the beginning of tests designed to measure its effects on performance. 

• Future research determining marijuana users' preferred dose should involve administering 

THC in different marijuana preparations that encompass a wide range of potencies. 

_ • Further research is required for determining marijuana's effects on actual driving 

performance in the presence of other traffic when the driver is simultaneously performing 

another task or suddenly confronted with a situation that requires a rapid adaptive response. 

• The city driving test should be repeated with subjects consuming THC doses over 100 μg/kg. 

• Further research on marijuana and actual driving research should be extended to include 

combinations of marijuana and alcohol. 

• Future research should extend actual driving performance measurements to 4, 8, 16 and 24 

hours after smoking. 
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APPENDIX A

Questionnaires
Subjective Intoxication and Willingness to Drive Questionnaires 

Please rate your feeling of "high" (or "drunkness" after drinking alcohol) as a percentage of the maximum ever 

experienced. 

100 The maxm,m ever experienced 

90 

80 

I- 70 

50 

40 

30 

L 20 

F- 10 

0 No effect 

Would you attempt to drive for a set distance if the reasons were: 

A. unimportant though gratifying, such as for transporting a friend to another-party Y / N 

B. important but avoidable, such as for transporting a mildly sick friend home 

when he would otherwise have to call a taxi Y / N 

C. urgent, such as transporting a severely sick infant to the hospital . Y / N 
Mood Rating Scale (Bond and Lader, 1974) 

This form is a mood rating scale and the intention is to measure your feelings as they are at this moment. The 

instructions are given below. Please read them carefully and proceed. Have you any questions? 

1. Please rate the way you feel in terms of the dimensions given below. 

2. Regard the line as presenting the full range of each dimension. 

3. Rate your feelings as they are at the moment. 

4. Mark clearly and perpendicularly across each line. 

Alert Drowsy (1) 

f 

Calm Excited (2) 

Strong Feeble (3) 

Muzzy Clear headed (4) 

Well-coordinated Clumsy (5) 

Lethargic -Energetic (6) 

Contented Discontented (7) 

Troubled Tranquil (8) 

Mentally slow Quick witted (9) 

Tense Relaxed (10) 

Attentive Dreamy (11) 

Incompetent Proficient (12) 

Happy Sad (13) 

Antagonistic Amicable (14) 

Interested Bored (15) 

Withdrawn Sociable (16) 

Do you think you received placebo or active drug ? Placebo / Active 

Scores on these scales were grouped to form 3 cluster scores for measuring the corresponding factors: alertness 

(1,3.4,5,6,9,11,12,15), contentedness (7,8,13,14,16) and calmness (2,10). 

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Perceived Effort Scale (ZijLctra and Van Doorn, 1985) 

Please rate the effort made while performing the driving test. 

extreme effort 

very great effort 

great effort 

considerable effort 

rather much effort 

some effort 

a little effort 

almost no effort 

absolutely no effort 
Perceived Driving Quality Scale (translated from Dutch) 

Please rate the quality of your driving in the test you just finished. 

r I drove exceptionally well

I drove normally 

I drove exceptionally poorly 

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APPENDIX B

Driving Proficiency Tests
Maneuvers in Molecular Approach (from Jones, 1978). 

Left Turn The driver will follow a standard path. A standard path runs from the center of the 

Path (P) left-most lane of the original street to the center of the left-most lane of the 

High, medium or low intersecting street'. The turn must commence at a point one-third to one-half of the 

traffic density. way into the intersection. The path passes just to the left of the center of the 

intersection. If the light is red, the driver must stop clearly behind the crosswalk 

line. 

Correct Response I.­ Enters intersection in the center of the left-most lane of a 4 (or more) lane 

street, or center of lane if single lane in each direction, and remains in the 

center until turning begins. 

2.­ Begins turning when one-third to one-half of the way into the intersection. 

3.­ If the car must stop for oncoming traffic in the intersection, the wheels must 

remain straight until the turn is started. (After stop, if vision is blocked by a 

left-turning truck, the driver may move forward into the turn but if he enters 

the oncoming'travel lane and forces vehicles to compensate, examiner will 

score Hazard or Instructor Control and coder should underline P.) 

4.­ Passes just to left of center of the intersection. 

5.­ Completes turn in center of the left-most lane of intersecting street'. (If that 

lane is blocked or otherwise inaccessible, for example, a roadwork crew or a 

disabled vehicle, and the driver selects another lane, the examiner will code as 

Hazard or Instructor Control (see Examiner's Manual) and coder should 

underline P.) 

6.­ Stops well behind nearest crosswalk line if light is red. 

Left Turn The driver will decelerate smoothly before the turn and accelerate smoothly when 

Speed (S) clearing the intersection. Failure to accelerate promptly is a frequent error of novice 

High and Medium drivers. 

Density Traffic 

Correct Response 1. Decelerates smoothly, coming to a stop or near stop if there is traffic. At no 

time should the tires squeal or the passengers be thrown. 

2.­ Accelerates smoothly, soon after he passes the one-third mark in the turn, 

steadily increasing to traffic speed. 

3.­ Adjusts speed so that vehicle does not interfere with oncoming traffic. 

4.­ Accelerates promptly; if driver hesitates or starts and stops without cause, speed 

is coded X. 

Left Turn The driver will control his speed before the turn by braking to 10-12 mph one car 

Speed (S) length from the corner. He will accelerate smoothly two-thirds of the way through 

Low Density Traffic the turn. (Driver must approach between 20 and 25 mph).­

Correct Response I. Before the turn, brakes to 10-12 mph. 

2.­ Two-thirds of the way through the turn, accelerates smoothly out of the turn. 

3.­ Accelerates promptly; if driver hesitates or starts and stops without cause, speed 

is coded X. 

For experienced drivers, it is acceptable to end in any open lane if it is safe to do 

so. This is not acceptable for novice drivers. 

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Left Turn The driver will scan the intersection for potential conflicts with vehicles and 

Observing pedestrians. 

Traffic (0) 

High and Medium 

Density Traffic 

Correct Response 1.­ Observes left and right, checks for a gap (looks forward), checks right again 

and rechecks turn path as he turns. 

2.­ Must not look at any spot longer than 2 seconds (count of 1001, 1002) unless 

he must stop. If so, rechecks. 

Left Turn Scans the intersection for potential conflicts with vehicles and pedestrians. 

Observing Traffic (0) 

Low Density 

Correct Response 1.­ Before entering the intersection, looks left, right, and left, in that order: Turns 

his head far enough to detect pedestrians on the near left and right comers 

(about 75°). (Note: forward scan in light traffic will not be noticeable.) 

2.­ Does not look at any spot longer than 2 seconds (1001, 1002 count) unless 

there is traffic and the driver's vehicle is stopped. . 

Right Turn The driver will steer to the right side of the right-most lane when making a speed 

Approach (A) reduction for the right turn. This lane is defined as the approach lane. The lateral 

High or Medium position of the vehicle in the approach lane is 2 to 3 feet from the curb. If the car 

Density Traffic must move laterally at least one car width to enter the approach lane, the driver will 

signal before changing lanes. 

(If the local ordinance requires that cars not invade the bike lane, driver may move 

over to within 3 feet of the curb only when he is one car length from the corner.) 

When entering the approach lane, the driver must make a timing judgment. By 

moving or signaling too early he may mislead other drivers to believe that he intends 

to turn at an earlier location and by moving too late he may risk a hazardous lane 

change by executing a hurried signal and blind spot check. Driver must stop clearly 

behind crosswalk when the light is red. 

Correct Response 1. If the car must move laterally one car width to enter approach lane: 

A. Signals before moving over. 

B. If there is a bike lane, driver may stay outside it or move to within 3 feet 

of curb no more than one car length from comer. 

C. Enters the approach lane before vehicle is 4 car lengths from the

intersection but not before 10 car lengths.

2. If there is no approach lane, or after approach: 

A. Moves to the right to within 3 feet of the curb, to permit following traffic 

to continue without slowing for the driver's vehicle. 

B.­ Stops well behind nearest crosswalk line if light is red. 

C. Signals 100 feet from intersection unless driveway intervenes (when he 

waits until beyond driveway.) 

Right Turn After the approach, the driver will follow a standard path when turning right. 

Path (P) 

High and Medium 

Density Traffic 

Correct Response 1.­ Begins turning - the driver will begin turning the steering wheel when his front 

wheels are lined up with the beginning of the bend in the curb. 

2.­ Completes rum - the driver must enter the middle of the right-most lane of 

traffic in a smooth turn. There should be no sudden correction of course. (If 

that lane is blocked and the driver selects another lane, the examiner will code 

as Hazard or Instructor Control and coder should underline P.) 

- 126 ­
Right Turn The driver must select a path that will allow him to start his turn two to three feet 

Path (P) from the curb and finish his turn in the middle of the right half of the street. 

Low Density 

Traffic 

Correct Response 1. Begins turning when vehicle is two to three feet from the curb and front wheels 

are even with the beginning of the bend of the curb. 

2.­ Turns steering wheel smoothly and follows a smooth curve to the center of the 

right lane on the new street. 

Right Turn­ The driver will decelerate smoothly before the turn and accelerate smoothly when 

•­ Speed Control (S) clearing the intersection. 

High and Medium 

Density Traffic • . 

Correct Response 1. Decelerates smoothly before the mm to 8-10 mph, or less if traffic warrants. 

2.­ Accelerates smoothly two-thirds of the way through the turn, increasing speed 

quickly enough so that following traffic in new path would not have to slow 

down or change lanes for-driver's vehicle. (The coder must turn around and 

observe traffic.) 

3.­ Adjusts speed to flow of traffic. 

4.­ Accelerates promptly; if driver hesitates or starts and stops without cause, smed 

is coded X. 

Right Turn Driver must control his speed by braking before the turn and resuming normal speed 

Speed Control (S) after completing his turn. 

Low Density 

Traffic 

Correct Response 1. Before one car length from the corner, brakes to a speed of 8 to 10 mph. 

2.­ Accelerates smoothly as soon as driver is two-thirds of the way through the 

turn. 

3.­ Accelerates promptly; if driver hesitates or starts and stops without cause, speed 

is coded X. 

Right Turn Driver will scan the intersection for potential conflicts with vehicles and pedestrians

Observing (0) prior to initiating turn.

High. Medium &

Low Density Traffic

Correct Response 1.­ Turns head to the right and looks for pedestrians or vehicles that could block 

intended path. If a pedestrian is on right near comer, head movement must 

indicate check of the spot (750 head movement). 

2.­ Turns head to the left and looks for approaching cross traffic. 

3.­ Turns head to the right again and looks at turn path just prior to the execution 

of the turn. 

Order of checks is important. (Note: forward scan will usually not be 

noticeable.) ­

4.­ Completes these checks quickly and does not look for more than 2 seconds 

(count of 1001,1002) at any spot unless there is traffic and the driver's vehicle 

is stopped. 
Lane Change The driver must maintain a straight lane position during scanning procedures 

Path (P) (mirrors and blind spot). He must signal before he moves and cancel after the move 

High or Medium is completed. The driver then steers smoothly with a gradual angular movement into 

Density Traffic the middle of the new lane without swerving to either side of the lane. 

Correct Response 1. Maintains straight path while scanning. 

2.­ Signals before the lane change. 

3. ' Steers smoothly with gradual angular movement. 

4.­ Straightens vehicle in new lane. 

5.­ Cancels a signal. 

Lane Change Driver will decrease, increase, or maintain speed according to traffic conditions.

Speed (S)

High or Medium

Density Traffic

Correct Response 1. If flow of traffic of new lane is faster, increases speed when entering new lane.

2.­ If flow of traffic of new lane is slower, decreases speed when entering new 

lane. 

3.­ If flow of traffic of new lane is of equal speed, maintains speed when entering 

new lane. 

Lane Change The driver will scan one or both mirrors, as appropriate, and check blind spot 

Observing Traffic (0) before changing lanes. He will observe traffic ahead in both present and intended 

High •or Medium lanes for possible slowing. Lane change (right or left)) is necessarily indicated on 

Density Traffic the scoring sheet at specific locations but refers to the entire segment of the route 

between two turns. If two lane change arrows occur within a segment (between 

turns), both of them should be coded whenever they occur. Ignore aborted lane 

changes. (If they are dangerous, the examiner will code hazard, and mark it wrong.) 

Correct. Response 1. Checks traffic ahead in present and intended lanes. 

2.­ Checks rear view mirror. 

3.­ Checks outside mirror for left hand change. 

4.­ Checks blind-spot by turning the head briefly (appr. I second: if the coder 

counts 1002, it is too long) in the direction of the lane change and then before 

steering into the new lane, again checks forward traffic. Driver must not look 

through back window when checking blind snot. If he does, check is wrong 

M. 

Proceeding Through The driver will scan the intersection before entering.

Intersection

Observing Traffic (0)

Correct Response 1. The driver will look left and right before entering a four-way controlled

intersection. 

2.­ At a four-way uncontrolled blind intersection, the driver will look left and right 

before entering the intersection. If blind at that point for less than 200 yards, 

checks left again. 

3.­ At a blind tee intersection, the driver will look briefly in the direction of the 

adjoining street. 

4.­ For all checks at intersections, the driver will not look in any direction for 

more than 2 seconds (count of 1001, 1002) at any spot unless there is traffic 

and the driver's vehicle is stopped. 

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Proceeding Through The driver will reduce speed before entering a four-way blind uncontrolled 

Intersection intersection. 

Speed (S) 

Low Traffic Density 

Correct Response 1.­ Brakes gently, to 10 to 15 mph, one car length before the corner and continues 

to cover brake pedal until the traffic checks have been completed. 

2.­ Does not stop or go slowly once into the intersection. 

3.­ Accelerates through the intersection. 

Normal Transit The driver will select the appropriate speed for conditions, being guided by speed 

Between Intersections limit signs, laws, and traffic conditions. 

Speed Control (S) 

High-medium or Low 

- Traffic Density 

Correct Response 1.­ Does not- exceed the legal speed limit at any time between the. beginning of the 

(S) coding and the start of coding the next maneuver. 

2.­ Does not exceed the speed of the traffic flow by more than 4 mph. 

3.­ Does not fall below the speed limit by more than 4 mph unless traffic or 

potential hazards require it. 

Following Distance The driver must maintain at least a 2-second interval from traffic ahead at all times. 

(F) 

High Traffic Density 

Correct Response Unless there is a significant amount of traffic, there is no opportunity to observe 

this. If the situation is favorable, there is ample opportunity to observe following 

distance in normal transit on high density streets. Following distance can also be 

coded if the driver comes up on slow traffic or traffic stopped at an intersection. 

Interrupt assessment of following distance to observe mirror check before driver 

slows down, but then return to following distance as he comes up on traffic. The 

driver must anticipate slowing of traffic ahead. He must brake gradually enough that 

he does not throw passengers forward. He must maintain a 2-second distance at all 

times. Following distance (F) is necessarily indicated on the scoring sheet at specific 

locations but refers to the entire segment of the route between two turns. If two F's 

occur, attempt to code it twice in that segment. Do not code following distances of 

more than four seconds. If it cannot be coded, underline the F's. 

Stop Sign

Stop sign for the driver's vehicle, but none for cross traffic. The driver must stop 

Limit Line (LL)

behind the limit line (and then continue when traffic permits). If there is no physical 

limit line, the stop should be made behind a line connecting the two near corners of 

the street the vehicle is on. The vehicle must not enter the intersecting street. 

Correct Response 1.­ Stops behind limit line. 

Mirror Check The driver will check rear view mirror before any speed reduction or lateral 

(M) movement and when approaching a traffic light. The coder must attend to the mirror 

check as soon as the previous coding has been completed, since driver may check 

early and, if there is no traffic, may not need to repeat. 

-129­

I 
Gap Acceptance Gap acceptance is coded on some turns where path and speed on the turn are also 

(G) called for. The novice should decline the smallest gaps that an experienced driver 

might accept but should not wait when there is ample time. 

Correct Response­ 1. Accepts a 10-second gap; does not accept a gap smaller than 9 seconds'. The

coder should check his judgment by counting seconds (1001, 1002, etc.). If

driver accepts too small a gap, code it as X. (Examiner may also code Hazard,

X, or Instructor Control, 1.)

2.­ Gap is also wrong if there is no traffic and driver does not move ro p mptly.

3.­ If there is no traffic and the driver moves promptly, underline G (i.e., a 

judgment cannot be made). 

Pre-operation The driver will perform these pre-operation checks before starting the engine: 

(Pre-op) 

Correct Response 1. Adjusts seat. 

2.­ Fastens seat belt and shoulder harness. 

3.­ Checks and insures that all passengers are also buckled up. 

4.­ Adjusts both mirrors correctly. If driver must make head adjustments, or 

adjusts mirrors later, then go back and mark Pre-op wrong. 

Shut Down The driver will perform these shut-down checks: 

. (S.D.) 

Correct Response 1. Puts gear selector lever in Park (or gear shift in neutral). 

2.­ Turns ignition off. 

3.­ Sets parking brake. 

Y Turnabout Driver will chose a safe location for the Y turnabout (three-point turnabout).

Low Density Traffic

(residential)

Location (L)

Correct Response 1. Chooses a point at least 200 feet from any intersection.

2.­ Does not start a Y turnabout when pedestrians or vehicles are nearby. 

3.­ If there is no safe place to turn and the driver traverses the whole block without 

attempting to turn, underline Location (L) and Backing (B). (The instructor will 

tell the driver how to get back on the route.) " 

Backing (B) Driver will look left, right, and back before moving the car in reverse. 

Correct Response 1. Looks left and right before backing. 

2.­ Turns head around and looks straight back over right shoulder when moving the 

car in reverse. Failure to be looking straight back at all times that the car is 

moving backwards is disqualifying, except for brief checks left, right, and 

forward. 

Experience drivers may accept smaller gaps, but must not throw passengers off 

balance nor clear on-coming car by less than 4 seconds. 

- 130 ­
Translation of the Royal Dutch Tourist Association's original "Verslag Rijvaardigheidsrft". 

The following categories did not apply to the driving test and were dropped from the scoring sheet: 'Condition 

of the Car' (Category 1.01), "Railway Level Crossing" (Category 111.16), and several Special Maneuvers 

(Categories V.19 to V.26. V.28 to V.30). 

I VEHICLE CHECKS 06 Speed control, deceleration and stopping 

Y 06-1 Choice of speed in view of circumstances 

02 Preparing to drive off 06-2 Use of accelerator and brake 

06-3 Use of mirrors before and during 

02-1 Passing in front of car and observing traffic deceleration 

02-2 Clear view and clean windows 06-4 Indication of deceleration in good time by 

02-3 Position of driver's seat use of stop-lights 

02-4 Instrument check 06-5 Correct sequence of maneuvers for 

02-5 Starting the engine deceleration 

02-6 Use of safety belt(s) 06-6 Declutch at the correct stage and put gear02-7 Checking mirrors lever in neutral 

02-8 Proper use of lights 06-7 Come to a stop smoothly 

06-8 Clutch not depressed whilst waiting 

03 Driving off 

07 Taking corners 

03-1 Checking position of hand-brake 

03-2 Looking ahead, to the side and to the rear 07-1 Safe starting speed 

before driving off 07-2 Selecting correct gear before entering corner 

03-3 Selecting correct position in traffic lane 07-3 Without slipping clutch or foot on the clutch03-4 Adapting speed immediately to traffic flow P 

03-5 Re-checking mirrors 07-4 No braking in corner 

07-5 No free-wheeling 

07-6 Correct driving line 

n HANDLING OF VEHICLE 

III ACTION IN TRAFFIC 

04 Manner of sitting behind the wheel, and 

steering 

08 Driving straight 

04-1 Manner of sitting behind the wheel when 

driving 08-1 Keeping to the right 

04-2 Position of hands on the wheel 08-2 Adapting speed to that of other similar traffic 

04-3 Steering through curves 08-3 Looking into side streets 

04-4 Position of head whilst talking to passengers 08-4 Taking into account blind spots caused by 

car design and passengers 

05 Handling of controls 08-5 Taking into account limitation of mirrors. 

08-6 Keeping.distance from traffic in front 

05-1 Accelerator 08-7 Driving in offset position with regard to 

05-2 Foot-brake preceding vehicle c 05-3 Hand-brake 08-8 Pedestrian crossings 

05-4 Clutch-pedal 08-9 Watching ' for pedestrians crossing the road 

05-5 Gear-lever (at other places than at zebra crossings) 

- 131 ­
09 Behavior at or near crossroads 13 Traffic lane technique 

09-1 Judging the situation beforehand 13-1 Keeping well within lane 

09-2 Behavior at the approach to traffic lights 13-2 Checking traffic before leaving lane 

09-3 Driving in traffic lanes marked with arrows, 13-3 Changing traffic lanes one at a time 

and according to other indications on road 13-4 Driving straight, avoiding minor deviations 

surface 13-5 Driving in lines abreast 

09-4 Taking position in traffic lanes marked with 13-6 Overhead traffic lane control 

arrows 

09-5 Bicycle and bus lanes 14 Driving on roundabouts 

09-6 Consideration of other drivers 

09-7 Complying with priority rules 14-1 Observation (dividing attention) 

14-2 Using direction indicators during the entire 

10 Right-hand turn maneuver 

14-3 Correct positioning for turning in good tune. 

10-1 Taking position in good time when filtering 14-4 Selecting and driving in the correct traffic 

(selection' of correct lane) lane 

10-2 Looking behind and to the right 14-5 Weaving out of the traffic flow correctly and 

10-3 Switching on direction indicators in good time 

10-4 Positive filtering and in good time, adapting 

. speed 15 Driving on highways 

10-5 Looking over right shoulder 

10-6 Not impeding traffic that continues straight 15-1 Using acceleration lane, observing traffic on 

ahead highway 

10-7 Final check 15-2 Choice of speed and lane 

10-8 Taking comer as closely as possible 15-3 Correct distance to vehicle in front 

15-4 Stopping and parking in emergency stopping 

11 Left-hand turn lane (if permitted) 

15-5 Leaving emergency stopping lane 

11-1 Taking position in good time when filtering 15-6 Use of lay-bys 

(selection of correct lane) 15-7 Behavior at approach to intersections 

11-2 Looking to the rear, rear left and left 15-8 Use of deceleration lane 

1 1-3 Switching on direction indicators 

11-4 Positive filtering and in good time, adapting 

speed IV OBSERVATION AND UNDER11-5 Not impeding traffic that continues straight STANDING OF TRAFFIC 

ahead 

11-6 Correct timing of wheel turning and, position 

on wide crossings 17 Observation 

11-7 Final check 

11-8 Taking a sufficiently wide corner 17-1 Observation technique 

17-2 Observation of overall picture of traffic, road 

12 Overtaking and surroundings 

17-3 Conscious observation of -traffic signs 

12-1 Judging traffic flow correctly and in time 17-4 Use of direction signs 

(oncoming, behind and to the left) 

12-2 Switching on direction indicators 18 Understanding of traffic 

12-3 Moving out smoothly and in good time 

12-4 Canceling direction indicators 18-1 Anticipation 

12-5 Observing vehicle that will be overtaken 18-2 Making allowance for any traffic situations 

12-6 Overtaking quickly and safely that may occur 

12-7 Keeping well clear of overtaken cyclists 18-3 Reactions to observations made 

12-8 Reverting to the right 18-4 Strategy 

12-9 Overtaking on the right when permitted 

-132­
•

V . SPECIAL MANEUVERS 

27

Turning 

27-1Stopping at the correct place 

27-2Driving slowly, while turning steering wheel 

rapidly; no use of steering wheel while 

stopped 

27-3 Looking alongside the car when approaching 

the kerb 

27-4 Observing traffic during the entire maneuver