Residual Effects of Cannabis on Young Drivers' Performance ...

Residual Effects of Cannabis on Young Drivers’

Performance of Driving-Related Skills:

An Interim Analysis

by

Jie Fei Pan

A thesis submitted in conformity with the requirements

for the degree of Master of Science in Pharmacology

Department of Pharmacology and Toxicology

University of Toronto

Copyright by Jie Fei Pan 2016

ii

Residual Effects of Cannabis on Young Driver’s Performance of

Driving-Related Skills

Jie Fei Pan

Master of Science

Department of Pharmacology and Toxicology

University of Toronto

2016

Abstract

The effects of cannabis may not be limited to the time period immediately after use. This current

study examines the residual effects of cannabis on driving-related skills in young drivers using a

high-fidelity driving simulator. The study is a randomized, double-blind, placebo-controlled mixed

design trial. Eligible participants are regular cannabis-using drivers, aged 19-25, who smoke

cannabis 1-4 days per week. Measures of simulated driving performance, cognitive and

psychomotor functions, and subjective drug effects are collected concurrently with levels of

cannabinoids in biological fluids before and after a one-time cannabis administration of active

(12.5% THC) or placebo (<0.01% THC) cannabis. Preliminary findings of the interim analysis

showed limited residual effects of cannabis on driving performance 24 and 48 hours after smoking.

Future analyses with the full sample size will provide a more clear understanding of the residual

effects of cannabis on driving behaviour and implications on traffic safety.

iii

Acknowledgements

Being part of this project has been a tremendous learning experience. I would like to express my

sincere gratitude to the people who have supported and guided me through this period of

academic and personal growth.

I would first like to thank my supervisor, Dr. Bernard Le Foll. The memory of our first interview

is still fresh in my mind, where he asked me “what is a PPAR?”. Although I barely answered the

question, Dr. Le Foll accepted me to his lab and I have had an amazing time here since. I

appreciate the freedom he has given me to explore on my own and the trust he has placed in me

to conduct this project.

I would also like to thank Dr. Bruna Brands, who has been a wonderful and caring mentor.

Whether I needed help with work or needed some life advice, she would always make time for

me until the problem was solved. Despite having tricked me into a cookie bake-off but never

actually eating my cookies, she has always brought excitement to my day and the project with

her energy and enthusiasm.

I am very grateful to have a colleague and friend like Gina Stoduto, with whom I probably spend

the most time at the lab. Her patience and thoughtfulness have helped greatly and made the study

much easier to run. Our lunch hangouts and long discussions about endless topics were always

very enjoyable.

Dr. Mann for his insightful comments, guidance, and encouragement throughout the study.

Jillian Burston for being there with me through all the testing sessions, for always arriving on

time to pack the cart, and for sharing the fun and frustration of participant recruitment and

scheduling.

Dr. Christine Wickens and Chloe Docherty for their help with the study and for all the fun

conversations.

Most importantly, I would like to thank my mom for her unconditional love and protection

through my years of study. I would also like to thank Alex for his continuous and unchanging

support, encouragement and care. They provided me with the strength to make this all possible.

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Table of Contents

1 Introduction ...........................................................................................................................................1

1.1 Statement of the Problem ..............................................................................................................1

1.2 Objective and Hypothesis ..............................................................................................................2

1.2.1 Objective................................................................................................................................2

1.2.2 Hypothesis .............................................................................................................................2

1.3 Cannabis Use and Prevalence ........................................................................................................2

1.4 Cannabis Pharmacology ................................................................................................................3

1.4.1 The Endocannabinoid System ...............................................................................................3

1.4.1.1 Endocannabinoids: Structure, Synthesis, and Degradation ...............................................4

1.4.1.2 Endocannabinoid Receptors and Signaling .......................................................................5

1.4.1.3 Other Endocannabinoid Targets ........................................................................................7

1.4.2 Cannabis Chemistry and Composition ..................................................................................7

1.4.3 Pharmacokinetics ...................................................................................................................9

1.4.3.1 Absorption .......................................................................................................................10

1.4.3.2 Distribution ......................................................................................................................10

1.4.3.3 Metabolism ......................................................................................................................12

1.4.3.4 Elimination ......................................................................................................................13

1.4.4 Pharmacodynamics ..............................................................................................................14

1.4.4.1 Euphoria, Mood, and Perception .....................................................................................14

1.4.4.2 Cognitive Performance and Psychomotor Control ..........................................................15

1.4.4.3 Other Biological Effects ..................................................................................................17

1.4.5 Pharmacokinetics and Pharmacodynamics Relationship .....................................................18

1.4.6 Toxicity, Tolerance, and Dependence .................................................................................19

1.5 Cannabis Use and Driving ...........................................................................................................20

1.5.1 Epidemiological Studies ......................................................................................................21

1.5.2 Laboratory Studies ...............................................................................................................23

1.5.2.1 Memory ...........................................................................................................................24

1.5.2.2 Attention and Concentration ............................................................................................25

1.5.2.3 Psychomotor control ........................................................................................................26

1.5.2.4 Decision making ..............................................................................................................27

1.5.2.5 Risk-taking and Impulsivity ............................................................................................27

1.5.2.6 Perception of Time and Distance .....................................................................................28

Summary .........................................................................................................................................28

1.5.3 Simulator Studies .................................................................................................................28

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1.5.3.1 Speed and Speed Variability............................................................................................29

1.5.3.2 Lane Control ....................................................................................................................30

1.5.3.3 Headway ..........................................................................................................................31

1.5.3.4 Reaction Time .................................................................................................................31

1.5.3.5 Collisions .........................................................................................................................31

1.5.3.6 Divided attention .............................................................................................................32

1.5.4 On-Road Studies ..................................................................................................................32

Summary .........................................................................................................................................34

1.6 Residual effects of Cannabis .......................................................................................................34

2 Methods ...............................................................................................................................................38

2.1 Overall Study Design ..................................................................................................................38

2.2 Participant Selection ....................................................................................................................40

2.3 Study Recruitment .......................................................................................................................41

2.4 Study Procedures .........................................................................................................................41

2.4.1 Telephone Screening (Pre-screen) .......................................................................................41

2.4.2 Eligibility Assessment (Session 1) ......................................................................................41

2.4.3 Practice Day (Session 2) ......................................................................................................42

2.4.4 Drug Administration Day (Session 3) .................................................................................43

2.4.5 24 and 48 hour Post Drug Administration (Session 4 and 5) ..............................................43

2.4.6 Follow-up ............................................................................................................................44

2.5 Outcome Measures ......................................................................................................................44

2.5.1 Simulated Driving Measures (Primary Outcomes)..............................................................44

2.5.2 Cognitive and Psychomotor Measures ................................................................................45

2.5.2.1 Digit Symbol Substitution Test (DSST) ..........................................................................45

2.5.2.2 Hopkin’s Verbal Learning Test-Revised Version (HVLT-R) .........................................45

2.5.2.3 Connor’s Continuous Performance Test II (CPT-X) .......................................................46

2.5.2.4 Grooved Pegboard Task (Lafayette Model 32025) .........................................................46

2.5.2.5 Shipley-2 IQ Test ............................................................................................................46

2.5.3 Subjective Drug Effects/Pharmacodynamics Measures ......................................................47

2.5.3.1 Visual Analogue Scales (VAS) .......................................................................................47

2.5.3.2 Addiction Center Research Inventory (ARCI) 49-Item Form .........................................47

2.5.3.3 Profile of Mood States (POMS) ......................................................................................48

2.5.4 Behavioural Measures .........................................................................................................48

2.5.4.1 Driving Behaviour Self-Report Questionnaire (SRQ) .....................................................48

2.5.5 Physiological Measures .......................................................................................................49

2.5.5.1 Breath Alcohol Concentration (BAC) .............................................................................49

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2.5.5.2 Urine Toxicology Screening and Pregnancy Testing ......................................................49

2.5.5.3 Vital Sign Measures ........................................................................................................50

2.5.6 Laboratory Assays ...............................................................................................................50

2.5.6.1 Whole Blood Concentrations of THC, 11-OH-THC, and THC-COOH..........................50

2.5.6.2 Urine Levels of THC, 11-OH-THC, and THC-COOH ...................................................50

2.5.7 Assessments of Eligibility ...................................................................................................51

2.5.7.1 Physical Examination and Laboratory Tests ...................................................................51

2.5.7.2 Structured Clinical Interview for DSM-IV Axis I Disorder (SCID-I).............................51

2.6 Investigational Products (IP) .......................................................................................................51

2.6.1 IP Suppliers .........................................................................................................................51

2.6.2 IP Preparation and Accountability .......................................................................................52

2.6.3 IP Administration ................................................................................................................52

2.7 Sample Size .................................................................................................................................53

2.8 Driving Simulator ........................................................................................................................53

2.9 Ethics ...........................................................................................................................................54

2.10 Statistical Analysis ......................................................................................................................55

3 Results .................................................................................................................................................57

3.1 Recruitment and Enrollment ........................................................................................................57

3.2 Demographics ..............................................................................................................................60

3.3 Driving Outcomes .......................................................................................................................61

3.3.1 Overall Mean Speed and Standard Deviation of Lateral Position .......................................61

3.3.2 Collisions .............................................................................................................................63

3.3.3 Straightaway Hazard: Mean Speed, Standard Deviation of Speed, and SDLP ...................65

3.3.4 Following Distance Behind a Slow Moving Vehicle ..........................................................69

3.3.5 Braking Distance to a Risk Taking Hazard .........................................................................70

3.4 Cognitive Performance and Psychomotor Outcomes ..................................................................72

3.4.1 Continuous Performance Test-X .........................................................................................72

3.4.2 Hopkin’s Verbal Learning Test-Revised .............................................................................75

3.4.3 Digit Symbol Substitution Test ...........................................................................................77

3.4.4 Grooved Pegboard ...............................................................................................................79

3.5 Pharmacodynamic Outcomes ......................................................................................................81

3.5.1 Visual Analog Scales ...........................................................................................................81

3.5.2 Addiction Research Centre Inventory .................................................................................82

3.5.3 Profile of Mood States .........................................................................................................85

3.6 Physiological Outcomes ..............................................................................................................88

3.6.1 Heart Rate ............................................................................................................................88

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3.6.2 Blood Pressure .....................................................................................................................89

3.6.3 Body Temperature and Respiration Rate .............................................................................90

3.7 Frequency of DUIC .....................................................................................................................91

3.8 Cannabis Strength ........................................................................................................................91

3.9 Adverse Events ............................................................................................................................92

4 Discussion ...........................................................................................................................................94

4.1 Driving Outcomes .......................................................................................................................96

4.2 Cognitive and Psychomotor Measures ......................................................................................100

4.3 Pharmacodynamic Measures .....................................................................................................101

4.4 Physiological Measures .............................................................................................................103

4.5 Challenges and Limitations .......................................................................................................103

4.6 Conclusion .................................................................................................................................105

4.7 Future Directions .......................................................................................................................105

Reference ...................................................................................................................................................107

Appendices ................................................................................................................................................126

Appendix A: Study Advertisements ......................................................................................................126

Appendix B: Telephone Screening Forms.............................................................................................134

Appendix C: Participant Information Sheet ..........................................................................................138

Appendix D: Informed Consent Form ...................................................................................................140

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List of Tables

Table 1. Reasons for loss of interest during the initial contact ....................................................................57

Table 2. Reasons for exclusion based on the telephone pre-screen .............................................................57

Table 3. Reasons for exclusion based on the eligibility assessment............................................................58

Table 4. Demographic characteristics .........................................................................................................60

Table 5. Repeated measures mixed MANOVA of overall mean speed and SDLP under the single-task

driving condition .................................................................................................................................61

Table 6. Repeated measures mixed MANOVA of overall mean speed and SDLP under the dual-task


Table 7. Repeated measures mixed ANOVA of the total number of collisions under the single-task


Table 8. Repeated measures mixed ANOVA of total number of collision under the dual-task driving

condition ..............................................................................................................................................64

Table 9. Repeated measures mixed MANOVA of mean speed, standard deviation of speed, and SDLP

during the straightaway hazard under the single-task driving condition .............................................65


during the straightaway hazard under the dual-task driving condition ...............................................66

Table 11. Repeated measures mixed ANOVA of the following distance behind a slow moving vehicle

hazard under the single-task driving condition ...................................................................................69


hazard under the dual-task driving condition ......................................................................................69

Table 13. Repeated measures mixed ANOVA of the braking distance to a risk taking hazard under the

single-task driving condition ...............................................................................................................70


dual-task driving condition ..................................................................................................................71

Table 15. Three-way repeated measures mixed ANOVA of omission and commission errors committed

during the CPT-X test..........................................................................................................................72

Table 16. Repeated measures mixed ANOVA of hit rate in the CPT-X test ..............................................73

Table 17. Repeated measures mixed MANOVA of variability and detectability scores in the CPT-X test

.............................................................................................................................................................74

Table 18. Repeated measures mixed MANOVA of performance on the Revised Hopkin's Verbal Learning

Test ......................................................................................................................................................75

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Table 19. Repeated measures mixed MANOVA of total completed trials and percent of correct trials in

the DSST test .......................................................................................................................................78

Table 20. Repeated measures mixed ANOVA of the mean reaction time during the DSST test ................79

Table 21. Three-way repeated measures mixed ANOVA of performance time on the grooved pegboard

task ......................................................................................................................................................80

Table 22. Three-way repeated measures mixed ANOVA of response on the Visual Analog Scales..........81

Table 23. Three-way repeated measures mixed ANOVA of response on the Addiction Research Centre

Inventory .............................................................................................................................................82

Table 24. Three-way repeated measures mixed ANOVA of response on the Profile of Mood States

questionnaire .......................................................................................................................................85

Table 25. Repeated measures mixed ANOVA of heart rate ........................................................................88

Table 26. Three-way repeated measures mixed ANOVA of blood pressures .............................................89

Table 27. Repeated measures mixed ANOVA of body temperature and respiration rate ...........................90

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List of Figures

Figure 1. Chemical structures of endocannabinoids and endocannabinoid-like compounds ........................4

Figure 2. Structure of 9-tetrahydrocannabinol, the main psychoactive constituent of cannabis .................8

Figure 3. Structure of main cannabinoids in cannabis ...................................................................................9

Figure 4. Phase plot of subjective high versus plasma THC concentration after an oral dose of cannabis

from 0-360 minutes, demonstrating a counter-clockwise hysteresis. ..................................................18

Figure 5. Study timeline ..............................................................................................................................39

Figure 7. Recruitment and enrollment flow chart ........................................................................................59

Figure 8. Overall mean speed (km/hr) and overall SDLP (m) pre-dose compared to 24hr and 48hr post-

dose......................................................................................................................................................63

Figure 9. Total number of collisions pre-dose compared to 24hr and 48hr post-dose ................................64

Figure 10. Comparison of mean speed (km/hr), standard deviation of speed, and SDLP (m) during the

straightaway hazard between active and placebo cannabis at baseline, and at 24hr and 48hr post-dose

.............................................................................................................................................................68

Figure 11. Following distance behind a slow moving vehicle pre-dose compared to 24hr and 48hr post-

dose......................................................................................................................................................70

Figure 12. Comparison of baking distance to a risk-taking hazard between pre-dose, and 24hr and 48hr

post-dose ..............................................................................................................................................71

Figure 13. Comparison of omission and commission errors in the CPT-X between pre-dose, and 24hr and

48hr post-dose .....................................................................................................................................73

Figure 14. Hit rate in the CPT-X at baseline compared to 24hr and 48hr post-dose ...................................74

Figure 15. Comparison of variability and detectability scores pre-dose, and 24hr and 48hr post-dose

between active and placebo cannabis ..................................................................................................75

Figure 16. Total recall, learning score, percent retained, and discrimination index in the HVLT-R

compared between active and placebo cannabis pre-dose, and at 24hr and 48hr post-dose ...............77

Figure 17. Comparison of the total number of trials completed and percent of trials correct in the DSST

pre-dose, and at 24hr and 48hr post-dose ............................................................................................78

Figure 18. Mean reaction time during the DSST pre-dose, and 24hr and 48hr post-dose ..........................79

Figure 19. Time taken to complete the Groove Pegboard Task ..................................................................80

Figure 20. Subjective drug effects measured by the Addiction Centre Research Inventory .......................84

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Figure 21. Mood states measured by the Profile of Mood State .................................................................87

Figure 22. Fluctuation in heart rate pre-dose, and 24hr and 48hr post-dose compared between active and

placebo cannabis .................................................................................................................................88

Figure 23. Changes in systolic and diastolic blood pressure .......................................................................89

Figure 24. Changes in body temperature and respiration rate .....................................................................91

Figure 25. Self-report of cannabis strength by participants who received active cannabis .........................92

Figure 26. Reported adverse events in relation to the investigational product or study protocol. ..............93

Figure 27. Adverse events related to the investigational product or study procedures ...............................93

xii

List of Appendices

Appendix A: Study Advertisements ..........................................................................................................126

Appendix B: Telephone Screening Forms.................................................................................................134

Appendix C: Participant Information Sheet ..............................................................................................138

Appendix D: Informed Consent Form .......................................................................................................140

1

1 Introduction

1.1 Statement of the Problem

Motor vehicle accidents (MVAs) have emerged as an important public health concern that is associated

with high social and economic costs. In 2013, there were 1923 cases of motor vehicle fatalities

nationwide and 165,360 cases of crash injuries, of which 10,315 were serious injuries that required

hospitalization1. These collisions translated to an estimated societal financial burden of $20 billion,

including cost to property damage and repair, traffic delays, hospital and treatment, police attendance and

response, fire and ambulatory rescue, legal dispute, out-of-pocket expense, and loss of productivity2,3. In

Ontario, one person is killed in a MVA every 15 hours, which resulted in a total of 476 deaths and 59,737

injuries in 20134.

Driving is one of the most challenging activities that occur on a daily basis. It requires a high level of

information processing and psychomotor coordination to allow drivers to accurately perceive and

appropriately respond to traffic conditions. Therefore, given the complexity of this task, driving abilities

can be negatively affected by many factors, including psychoactive substances. Cannabis is one of the

most widely used illicit substances in the world5–7 and the psychoactive drug most frequently found in

serious and fatal collisions after alcohol8–11. While the risks associated with driving under the influence of

alcohol (DUIA) are well-defined, many perceive driving under the influence of cannabis (DUIC) to be

safe12–14. However, this may be a dangerous belief as cannabis may increase collision risks by impairing

cognitive and psychomotor skills necessary for safe driving15–21. Although the impairing effects of

cannabis on driving-related skills have been demonstrated immediately after use, little evidence exists on

how long these impairments last. Due to the high lipophilicity and unique pharmacokinetics of THC, the

main psychoactive ingredient of cannabis, THC level drops rapidly in the blood after consumption but

may persist in the brain for a longer period of time, resulting in residual effects of cannabis that could

impair driving abilities. Despite the clear relevance of these effects on collision risks, only a few studies

have examined the residual effects of cannabis on driving performances.

Given the high societal cost of motor vehicle accidents, understanding the impairing effects of cannabis

on driving abilities and the time frame in which it is safe to drive after consumption is a crucial step in

reducing collision risks. More specifically, since young adults have the highest risks of MVA1, the highest

2

prevalence of cannabis use5,7, and less driving experience, understanding the impact of cannabis on

driving behavior in this population is especially important.

1.2 Objective and Hypothesis

1.2.1 Objective

The present study aims to examine the residual effects of a moderate dose of smoked cannabis (12.5 2%

THC) on driving abilities in young drivers between the ages of 19-25. Performances on simulated driving

and tests of cognition, motor skills, and subjective drug effects are measured concurrently with levels of

cannabinoids in biological fluids at approximately 24 and 48 hours after drug administration.

1.2.2 Hypothesis

We hypothesize that impairments on simulated driving performance, cognitive functions, and

psychomotor skills will be detected 24 and 48 hours after smoking a single cannabis cigarette containing

12.5 2% THC. The impairing effects on simulated driving performance are expected to be more

significant when drivers are distracted. In addition, we hypothesize that subjects will not be aware of any

intoxication the following day; hence, it is expected that there will be no significant difference in mood

and subjective drug effects 24 and 48 hours after smoking. Moreover, no physiological effects of

expected to be observed 24 and 48 hours post-dose.

1.3 Cannabis Use and Prevalence

Cannabis, a generic term that refers to Cannabis sativa L., is an herbaceous plant that originated from

Central Asia as early as 4000 B.C..22 Historically, it has been used in folk medicine23 and as a source of

hemp fiber to make rope, fabric, and paper22,24. Following the growth of imperial colonies and the

expansion of international trade, cannabis cultivation and use spread across the globe5,25. Popular for its

psychoactive properties in recreational use, cannabis is now the most widely used illicit substance in the

world5.

In a 2015 drug report published by the United Nations, it is estimated that 2.7-4.9% of people aged 15-64

years have used cannabis at least once in the past year5. This corresponds to a population of 125-277

3

million world-wide. In Canada, 43% of Canadians have reported cannabis use at least once in their

lifetime and 10.6% of Canadians have used at least once in the past year6,7. According to the Canadian

Tobacco, Alcohol, and Drugs Survey (CTADS) conducted in 2013, cannabis use in the past year was

more prevalent in males (13.9%) than females (7.4%), and was most common amongst adolescents and

young adults7. In fact, Canadian adolescents exhibit the highest rate of cannabis use compared to their

counterparts in other developed countries6,7. People between the ages of 15-19 and 20-24 years reported a

past year use of 22.4% and 26.2%, respectively, both of which were almost 2.5 times higher than adults

above the age of 25 (8%)7. According to the 2012 Canadian Community Health Survey-Mental Health,

1.8% of the Canadian population above 15 years of age reported daily use in the previous year26. Daily

use was twice more likely in males than females (2.4% vs 1.2%), and more common in young adults

between the ages of 18-24 (4.9%) compared to other age groups26.

Similarly, in Ontario, population surveys revealed that 14% of adults and 23% of high school students

consumed cannabis in 201327. For comparison purposes, only 8.5% of the Ontario population have

reported smoking cigarette in the same year7. Of those who reported past-year cannabis use, 60% have

consumed cannabis at least once in the last month and about 27% use it daily7,28. Amongst students

between Grade 7 and 12, male students are more likely to report use than females (25% vs 21%) and 3%

of students exhibit habits of daily use29. In Toronto, students are less likely to use cannabis (20%)

compared to those in northern (33%) or western Ontario (29%)29. Due to the high prevalence and

continuous rise in cannabis use, understanding the impact of cannabis on neurological and behavioural

function is a public health priority.

1.4 Cannabis Pharmacology

1.4.1 The Endocannabinoid System

The endocannabinoid system (ECS) is an evolutionary-conserved, ubiquitous lipid signaling system that

has important regulatory functions throughout the body30. The ECS is involved in a broad range of

physiological processes including neurological development, psychomotor behaviour, memory, immune

function, inflammation and pain, appetite, energy balance and metabolism, cardiovascular functions, and

emotional state regulation31–35. The system consists of: (1) cannabinoid receptors 1 and 2 (CB1 and CB2);

(2) endogenous cannabinoid ligands, of which anandamide and 2-arachidonoylglycerol (2-AG) are

considered the primary mediators of cannabinoid signaling; and (3) enzymes involved in endocannabinoid

synthesis and degradation30.

4

1.4.1.1 Endocannabinoids: Structure, Synthesis, and Degradation

Anandamide was the first endocannabinoid discovered and was named from the Sanskrit word Ananda

for “supreme bliss”36. 2-AG, a monoglyceride, was identified shortly after37,38. Additional endogenous

ligands including virodhamine39, 2-arachidonolyglerol ether (noladin ether)40, N-arachidonoyl dopamine

(NADA)41,42, N-homo--linolenoylethanolamine (HEA)43,44, and docusate-traenylethanoalamide

(DEA)43,44 were subsequently identified. Chemical structures of these molecules are depicted in Figure 1.

Figure 1. Chemical structures of endocannabinoids and endocannabinoid-like compounds45,46.

Endocannabinoids are synthesized “on demand” from phospholipid precursors in the postsynaptic

terminals47. Anandamide is produced by cleaving a phospholipid precursor, N-arachidonoyl-

phosphatidylethanolamine (NAPE)48, which is formed by transferring arachidonic acid from the sn-1

position of phosphatidylcholine to the nitrogen atom of phosphatidylethanolamine49. The transfer is

carried out by N-acyltransferase (NAT), which is regulated by cAMP-dependent protein kinase A50,51.

The cleavage of NAPE into anandamide is catalyzed by a phospholipase D (PLD)52. The activity of PLD

is stimulated by activation of glutamate N-methyl-D-aspartate (NMDA) receptors51,53, nicotinic 7

neuronal receptors, dopamine receptors, and acetylcholine receptors54–56. Synthesis of 2-AG is mediated

through phosphatidylinositol phospholipase C (PLC), where phosphatidylinositol is hydrolyzed to

5

diacylglycerol (DAG) with arachidonic acid added on the sn-2 position57–59. DAG is then hydrolyzed to 2-

AG by diacylglycerol lipase (DAGL)60.

Endocannabinoid signaling is rapidly terminated by cellular uptake and enzyme hydrolysis.

Endocannabinoid membrane transporters are widely distributed in the brain and facilitate the uptake of

anandamide and 2-AG down their concentration gradient61. Degradation of endocannabinoids is

performed by hydrolytic enzymes, fatty acid amide hydrolyse (FAAH) and monoacylglycerol lipase

(MAGL)62,63. FAAH, a member of the serine-hydrolase family, is localized in the postsynaptic membrane

and is primarily responsible for the degradation of anandamide62. MAGL, also a serine-hydrolase, is

localized in the presynaptic membrane and preferentially degrades 2-AG62,64.

1.4.1.2 Endocannabinoid Receptors and Signaling

Endocannabinoids primarily bind and activate CB1 and CB2 receptors, both of which are G-protein

coupled receptors65. The CB1 receptor gene (CNR1) is located on chromosome 5q15 and encodes a

protein of 472 amino acids66. Remarkably, the amino acid sequence is 97-99% identical across all

vertebrate species, reflecting the crucial functions of the endocannabinoid system67. The CB1 receptor is

mainly expressed in the central nervous system (CNS)68. It is the most abundant G-protein coupled

receptor (GPCR) found in the brain, with a concentration 10-15 times higher than classic GPCRs such as

dopamine or opioid receptors67,68. However, when compared to other GPCRs, the CB1 receptor is 7 times

less efficient in coupling to its G-protein69–71. The CB1 receptor could also be found in many other places

including the peripheral nervous system, the reproductive system, some glandular system, and

microcirculation67,68,72–74. However, there is a low concentration of CB1 receptors in the brainstem

region75.

The CB2 receptor gene (CNR2) is located on chromosome1p3667. It encodes a protein of 360 amino acids

and shares a 48% amino acid sequence similarity with the CB1 receptor67. CB2 receptors are mainly

expressed in tissues and cells of the immune system76. Its concentration is highest in B lymphocytes,

moderate in monocytes and polymorphonuclear neutrophils, and lowest in T lymphocytes51,76,77. CB2

receptors could also be detected in the bone, liver, and some nerve cells such as astrocytes and microglial

cells78.

Both cannabinoid receptors are coupled to the Gi/Go- protein and signal through a similar transduction

pathway67,72. Activation of the receptors inhibits adenylyl cyclase, decreases cAMP formation and

6

corresponding PKA activities, and inhibits Ca2+ influx through N79, P/Q80, and L-type81 calcium channels.

It also increases K+ efflux through potassium channels, which activates the mitogen-activated protein

kinase (MAPK) signaling cascades82. Specifically, CB1 receptors activate the ERK/p38-MAPK

pathway83,84 while CB2 receptors activate the phosphatidylinositol 3-kinase (PI3K)/Akt pathway85. Recent

studies have shown that under certain conditions, CB1 receptors can couple to the Gs protein and

stimulate cAMP formation70. In addition, CB1 receptors are associated with “lipid rafts” (LR), which are

special membrane microdomains that modulate CB1 signaling86. The interaction between CB1 and LR is

altered by the cholesterol level in the membrane. A high cholesterol content decreases CB1 activation,

and reduces signaling through adenylyl cyclase and MAPK. In contrast, a low level of cholesterol disrupts

LRs, modifies anandamide-induced CB1 receptor endocytosis, and reduces CB1 receptor degradation by

lysosomes87,88.

Upon stimulation, endogenous cannabinoids are released from the postsynaptic terminal and diffuse

backwards across the synaptic cleft to activate CB1 receptors at the presynaptic terminal89. The overall

effect of CB1 receptor activation is presynaptic hyperpolarization and inhibition of neurotransmitter

release, including GABA, glutamate, acetylcholine, and noradrenaline65,90,91. In immune cells, CB2

receptor activation inhibits cytokine release and leukocyte migration, resulting in complex modulatory

effects on suppressing immune functions92.

Endogenous cannabinoids exhibit different binding affinity and efficacy at CB1 and CB2 receptors.

Anandamide is a partial agonist at both receptors, but has a higher affinity for the CB1 receptor67,93. Its

efficacy is 4-30 times higher at the CB1 receptor than at CB267. In contrast, 2-AG is a full agonist and

binds equally well to both cannabinoid receptors. It also has a higher potency and efficacy for the

receptors compared to anandamide59,67.

Moreover, the endocannabinoid system has been demonstrated to exhibit tonic activity. In several

bioassay experiments, cannabinoid receptor antagonists behave as inverse agonists when administered

alone, suggesting that there may be a constant release of endocannabinoids or a portion of cannabinoid

receptors that are constitutively active94,95. In a few studies using mice models, tonic activity of the

endocannabinoids systems has been observed in the pain circuits96–98, appetite control99, and emetic

circuits100.

7

1.4.1.3 Other Endocannabinoid Targets

In addition to CB1 and CB2 receptors, endocannabinoids have a number of other targets. Recent evidence

has suggested that GPR55, an orphan GPCR, could be the third cannabinoid receptor101–106. GPR55 has

little sequence homology to CB1 and CB2105,106. It is expressed in the brain and several peripheral organs.

Activation of GPR55 has been linked to an increase in Ca2+ influx106, stimulation of small GTPase

proteins RhoA, Rac, and Cdc42105,107, and ERK phosphorylation108. A non-cannabinoid receptor target for

anandamide is the transient receptor potential vanilloid type-1 (TRPV1) receptor, a member of the

transient receptor potential channel family. It is a non-selective transmembrane cation channel that is

activated by heat (>42°C), low pH (<6), and capsaicin109,110. Another endocannabinoid, NADA, is also a

potent ligand for the TRPV1 receptor while 2-AG appears to have lower affinity for the receptor42. Lastly,

some research has suggested that anandamide and 2-AG also bind to the peroxisome proliferator activated

receptors (PPAR)- and , which are nuclear receptors that regulate the expression of genes involved in

immune response, inflammation, and lipid metabolism. It has also been implicated in other physiological

processes including energy balance, neuroprotection, circadian rhythms, and cognitive functions111,112.

1.4.2 Cannabis Chemistry and Composition

Cannabis is a complex plant that contains over 450 chemical compounds113, of which Δ9-

tetrahydrocannabinol is the main psychoactive constituent114,115. Δ9-tetrahydrocannabinol is a highly

lipophllic aromatic terpenoid that belongs to the phytocannabinoid family, along with 66 other

cannabinoids in the plant113. It has two chiral carbon centers, C-6a and C-10a, generating 4 different

isomers (Figure 2). However, only (-)trans- Δ9-tetrahydrocannabionol is the natural occurring isomer that

has psychotropic properties115. The (-)trans-isomer will be referred to as Δ9-tetrahydrocannabinol (THC)

in this text.

8

Figure 2. Structure of 9-tetrahydrocannabinol, the main psychoactive constituent of cannabis

THC is present in the cannabis plant mainly as tetrahydrocannabinolic acid, a cannabinoid acid that has

no psychoactive effects. The ratio of Δ9-THC acid to THC is approximately 2:1 in leaves and >20:1 in

flowers. Only a small amount of cannabinoids are found in the stem and root, but none are present in the

seeds116. Therefore, smoked cannabis is often prepared from dried leaves and flowering tops of the plant.

Upon heating during smoking, cannabinoid acids are decarboxylated to phenols, producing the

psychoactive THC compounds117.

The main metabolites of THC are psychoactive 11-hydroxytetrahydrocannabinol (11-OH-THC) and non-

psychoactive 11-nor-9-carboxy-tetrahydrocannabinol (THC-COOH)118. These will be discussed in more

details in Section 1.4.3. Δ8-tetrahydrocannabinol (Δ8 THC) exhibits similar characteristics and activities as

THC, but is slightly less potent and is only present in a small amount119,120. Cannabinol (CBN) is an

oxidation production of THC that has 10% of the activity of THC, but its effects have not been well-

studied119,121. Lastly, cannabidiol (CBD) is an important cannabinoid in cannabis that does not have

detectable psychoactivity in the brain nor most other effects of THC. It does not bind to CB1 and CB2

receptors at physiological concentrations, but does regulate the activity of a significant number of

receptors, ion channels, and enzymes119,121. In several in vitro assays and animal models of epilepsy, CBD

has shown anticonvulsant effects122,123 by affecting neuronal hyperexcitability via mechanisms such as

antagonizing GPR55 and reducing glutamate release124,125, activating 5-HT1a receptors126, stimulating and

desensitizing TRPV1 and TRPV2 channels127,128, and inhibiting the uptake of some neurotransmitters129–

131. Preliminary data in human studies have also shown promising results. In a large multi-center

intervention study involving patients with severe, pharmacoresistant epilepsy, an oral daily dose of 2-

5mg/kg of CBD reduced the monthly occurrence of motor seizures by 36.5% with limited adverse

effects132. Moreover, CBD has been implicated as an intervention for drug abuse and addiction. In several

9

mice models, CBD was shown to reduce the reward-facilitating effects and cue-induced relapse of opioid

and psychostimulant addictions133–135. Preliminary findings in human studies have also demonstrated

some beneficial results of CBD towards tobacco136 and cannabis dependence137. However, despite these

preclinical and early clinical evidence of CBD as a possible treatment for epilepsy and drug addiction,

data from human studies are still limited and more randomized controlled trials are needed before any

conclusions can be drawn. Structures of the aforementioned cannabinoid compounds are shown in Figure

3.

Figure 3. Structure of main cannabinoids in cannabis138,139.

1.4.3 Pharmacokinetics

Cannabinoid pharmacokinetics is difficult to study due to cannabinoids’ low analyte concentration, rapid

metabolism, and physical-chemical characteristics preventing separation from biological fluids and each

other. Early pharmacokinetics data relied on radiolabeled cannabinoids, which are highly sensitive but

less specific. New extraction techniques and mass spectrometry allow more specific quantification of

cannabinoids in a variety of biological specimens and tissues to better characterize pharmacokinetic

parameters of cannabinoids, particularly THC140.

10

Routes of administration determine the pharmacokinetics of cannabinoids. The most common and

preferred route is smoking, which has a fast onset of action and efficient drug delivery from the lungs to

the brain140,141. Users are also able to self-titrate to achieve the desired effect. Since smoking is the

administration method used in this study, only pharmacokinetics data on smoked cannabis will be

discussed.

1.4.3.1 Absorption

THC can be detected in plasma only a few seconds after the first inhalation142. Huestis et al. measured the

plasma concentration of THC starting from the first puff and for a period of 7 days after smoking in

participants who are smoking for the first time. A single dose of placebo cigarette and cigarettes

containing 1.75% or 3.55% of THC were administered. Mean THC concentrations were 7.0 ± 8.1mg/mL

and 18.1 ± 12.0 ng/mL upon a single puff of the low and high dose, respectively. Peak plasma

concentration was reached 3-10 minutes after onset of administration. At low and high doses of THC, a

peak plasma concentration of 84.3ng/mL and 162.2ng/mL were obtained142. Similar results were reported

by other studies. Smoking cigarettes containing 1.64% and 1.8% of THC produced a peak plasma

concentration of 77ng/mL and 75ng/mL respectively143,144. In whole blood, smoking one cannabis

cigarette with 6.8% of THC resulted in a median peak concentration of 60ng/mL (ranging from 13-

63ng/mL)144.

Systemic bioavailability ranges from 2-56% due to intra- and inter-subject variabilities in smoking

habits145–147. Time of smoking, number of puffs, depth of inhalation, and breathhold time all alter the

degree of drug exposure and contribute to uncertainty in the dose delivered. The remaining amount is lost

through combustion and side-stream smoke148–150. Duration of smoking over lifetime also affects systemic

bioavailability, which is lower in infrequent or light users (2-24%) compared to heavy or chronic users (6-

56%)147,151. More interestingly, expectation of drug reward may influence smoking dynamics as well.

Cami et al. observed a change in the methods of smoking hashish cigarettes to obtain greater THC

concentrations when subjects anticipated to receive active cannabis compared to placebo cigarettes152.

1.4.3.2 Distribution

Distribution of THC occurs immediately after absorption, resulting in a rapid decrease of plasma THC

concentration after the end of smoking140. 90% of THC is found in the plasma153, of which 95-97% are

bound to low density lipoproteins153–155. The remaining 10% is found in red blood cells153. Despite high

11

levels of protein binding, THC has a large steady state volume of distribution (Vd) of approximately

10L/kg156–158. However, these early pharmacokinetics data have been questioned for the possible

inaccurate quantification methods used140. More recently, advanced gas chromatography-mass

spectrometry (GC-MS) was used and the average volume of distribution was calculated to be 3.4L/kg141.

Due to its high lipophilitcity, THC is taken up primarily by tissues that are highly perfused, such as the

brain, heart, lungs, the liver, and intestines159. Eventually, THC accumulates and retains in adipose

tissues160–162, which leads to a THC concentration ratio as high as 104:1 between fat and plasma163.

Subsequently, slow release from fat storage results in a prolonged period of elimination160–162.

On the other hand, distribution of THC is limited in the brain. At the time of peak psychoactivity, only

about 1% of THC administered intravenously is detected in the brain164–166. This is possibly due to the

high perfusion rate of THC entering and exiting the brain tissue167. The persistent and preferential

retention of THC in adipose tissue was first described by Kreuz and Axelrod. They administered

consecutive doses of radiolabeled THC in neutral fat and reported that the ratio of fat to brain THC

concentration was 21:1 after 7 days and 64:1 after 27 days of drug exposure. The extended retention of

THC in adipose tissue suggests that fatty acid conjugates of THC may be formed to increase its stability

in a lipophilic environment162.

In a more recent study conducted by Mura et al., postmortem blood and brain tissues in 12 cannabis users

were analyzed for THC and its metabolites using GC-MS. THC concentrations were always higher in the

brain than in the blood, ranging from 0.9 to 29.9ng/g versus <0.2 to 11.5ng/mL, respectively. In three

cases, THC and its metabolites were still quantifiable in the brain but were undetectable in the blood.

Moreover, substantial levels of THC and metabolites were found in seven brain areas highly populated

with CB1 receptors. These include the locus niger, hippocampus, occipital lobe, striatum-putamen-

palladium, frontal lobe, spinal cord, and corpus callosum. Although it is uncertain how long THC persists

in the brain in the long-term, based on these findings, the authors postulated that the residual

neurocognitive deficits in abstinent heavy cannabis users may, at least in the short term, be caused by

retention of THC in the brain168.

Distribution of the active metabolite 11-OH-THC is faster and higher than THC in the brain, suggesting

that 11-OH-THC contributes significantly to the overall CNS effects of cannabis164,169. Possible low

plasma protein binding or enhanced OH-metabolite transport at the blood brain barrier increases the

penetration of 11-OH-THC into the brain169.

12

1.4.3.3 Metabolism

THC is mainly metabolized by the liver, carried out by cytochrome P450s including CYP2C9, CYP2C19,

and CYP3A4. Phase I oxidation reactions of THC include allylic and aliphatic hydroxylation, oxidation

of alcohols to ketones and acids, epoxidation, and decarboxylation. Phase II involves conjugation with

glucuronic acid140.

The first oxidation step involves the hydroxylation of THC at the C9 position by CYP2C9, which

produces the primary and equipotent metabolite, 11-OH-THC170–172. On the other hand, CYP3A4 oxidizes

THC to produce other cannabinoids including 8b-OH-THC, epoxyhexahydrocanninol, and some minor

metabolites173. Peak plasma concentration of 11-OH-THC is approximately 5-10% of THC while area

under the curve (AUC) is approximately 10-20% of the parent compound140,174. Plasma concentration of

11-OH-THC peaks at 15 minutes after smoking, closely following the peak of THC concentration174.

Subsequently, 11-OH-THC is oxidized to the inactive metabolite THC-COOH. It is then glucuronidated

to increase its water solubility and excreted as the end product175,176. Peak plasma concentration of THC-

COOH occurs at 1.5-2.5 hours after smoking and is approximately a third of the concentration of THC174.

Other than the liver, tissues such as the brain, intestines, lungs, and the heart may also metabolize

THC177–179. CYP1-4s are also present in the small intestines and in the brain at low concentrations. In

studies with rats, guinea pigs, and rabbits, a psychoactive metabolite of THC is produced in the brain by

hydroxylation at the C4 position; however, its relative activity is unknown179. Moreover, hydroxylyzing

enzymes such as non-specific esterases, b-glucuronidases, and sulphatases in the GI tracts may also

contribute to THC metabolism178.

Genetic polymorphism in CYP enzymes affect THC metabolism. For example, individuals with

homozygous CYP2C9*3 allelic variant have reduced THC hydroxylation, resulting in a significantly

higher plasma concentration of THC and increased AUC compared individuals who are homozygous for

the CYP2C9*1 allele or are 1*/3* heterozygotes. Such genetic variability contributes to as high as a 5-

fold difference in THC metabolism180.

13

1.4.3.4 Elimination

Mean plasma THC concentration drops to approximately 60% of peak concentration 15 minutes after the

end of smoking and to 20% after 30 minutes174. About two hours later, plasma concentration is below 5

ng/mL181 and reaches a pseudoequilibrium of less than 2ng/mL between the plasma and other tissues

around 6 hours post administration181. After 5 days, 80-90% of THC in the body is excreted182,183.

The average plasma clearance rate is approximately 11.8L/hr for women and 14.9L/hr for men. This is

similar to the volume of hepatic blood flow, indicating that the rate limiting factor of plasma clearance is

hepatic blood flow147,157. In regular users, a higher plasma clearance rate of 60L/hr has been detected in

some studies157. More than 65% of the total THC dose is eliminated in feces predominately as 11-OH-

THC182,184, and 20% is eliminated in urine mainly as THC-COOH glucuronide conjugate acid156,182.

Slow elimination of THC is primarily a result of significant enterohepatic recirculation and slow re-

diffusion from the fat storage to the blood185. As such, and in combination with the need for highly

sensitive procedures to measure low cannabinoid levels at the terminal stage of excretion, the accurate

terminal plasma elimination half-life (t1/2) of cannabinoids is difficult to calculate. In addition, many

studies only examined blood cannabinoid concentrations within 24-72 hours, which is a short sampling

window that may underestimate the half-life140. Kelly and Jones reported a THC plasma t1/2 of 117

minutes and 93 minutes in frequent and infrequent users, respectively. On the other hand, the plasma

elimination half-lives for THC metabolites are longer than that of the parent compound. One study

examined the concentration of 11-OH-THC and reported a mean detection window of 4.5 hours and 11.2

hours corresponding to the consumption of a low (1.75% THC) and high (3.55% THC) dose174. A mean

plasma THC-COOH t1/2 was determined to be 5.20.8 and 6.26.7 days in frequent and infrequent users,

correspondingly186. When THC-COOH plasma concentration was examined over four weeks in chronic

users, the t1/2 was up to 12.6 days after a single cannabis dose187. When employing sensitive analytical

techniques, the terminal plasma half-life of THC-COOH was estimated to be on average 4 days.

Moreover, higher doses lead to a longer plasma elimination period. Following consumption of a low or

high dose cannabis cigarette with 16mg or 34mg of THC, the detection limit of 0.5 ng/mL of THC in

plasma was reached within an average of 7.2 hours and 12.5 hours, respectively. THC-COOH remained

detectable in blood for a longer period of time, on average 3.5 days and 6.3 days after smoking the two

doses188.

14

Renal clearance reaches a maximum of 1.2L/h 100 minutes after smoking and decreases to 0.06L/h 4 days

later147. The high lipophilicity of THC leads to high tubular reabsorption and low renal excretion of the

parent compound189. After smoking cannabis cigarettes containing 15.8mg and 33.8mg of THC, mean

peak concentrations of THC-COOH in urine were reported to be 89.831.9ng/mL and 153.449.2ng/mL,

respectively. These concentrations were reached at 7.70.8 hours and 13.93.5 hours for the two doses190.

Urine THC-COOH level decreases rapidly at first to 20-50ng/mL then gradually at a slow rate.

Consequently, following administration of a cannabis cigarette with 18mg or 34mg THC, an excretion

half-life in urine for THC-COOH was observed to be 30 hours over a monitoring period of 7 days and 44-

60 hours over 14 days191. Due to the unique pharmacokinetics of cannabinoids, particularly their

extensive retention in and slow release from adipose tissues, the first observation of a negative urine

immunoassay screening for THC (20g/L cut-off) was 8.5 day and 19.1 days for occasional and regular

users after a single dose of cannabis. Furthermore, urine immunoassays may also show fluctuations

between positive and negative results for several days after consumption. Therefore, the last observation

of a positive urine reading was 12.9 days and 31.5 days for occasional and regular users, respectively176.

1.4.4 Pharmacodynamics

1.4.4.1 Euphoria, Mood, and Perception

Much of the pharmacodynamic effects of cannabis is exerted by its main constituent THC, which behaves

as a partial agonist at the CB1 and CB2 receptors192. The primary effects of THC involve the central

nervous system, through its action at the CB1 receptor. It binds to the receptor at three locations: the C3

lipophillic alkyl chain, free phenolic hydroxyl group, and C9 substituent193,194.

After acute consumption, users generally experience an initial period of euphoria or ''high'' accompanied

by relaxation, distortion of time and space, heightened auditory and visual senses, and loss of inhibition

such as uncontrolled laughter114,119,195–199. Maximum euphoria is usually reached within 15 minutes after

smoking and is followed by a depressant period of drowsiness and disconnection with the real world199.

Some people may also experience negative effects including dysphoria, anxiety, and paranoia. These

reactions are often dose-related and more likely to occur in naive users and psychologically vulnerable

subjects119,200.

15

Like other recreational drugs, the underlying mechanism of the ''high'' is not well established. Huestis et

al. conducted an experiment where participants were administered either rimonabant, a selective CB1

antagonist, or placebo before smoking cannabis. Rimonabant blocked the psychotropic effects of

cannabis, clearly demonstrating that cannabis intoxication is mediated through CB1 receptors201. As

mentioned earlier in Section 1.4.1.2, endocannabinoids modulate the level of neurotransmitters through its

action on CB1 receptors90,91. In a microdialysis study, Tanda et al. showed that THC increases the release

of dopamine from the nucleus accumbens and prefrontal cortex, a common effect seen with heroin,

cocaine, amphetamine, and nicotine202. Electrophysiology experiments have also demonstrated that THC

activates and increases firing of dopamine neurons in the ventral tegmental area203. Collectively, these

effects may be responsible for the reinforcing properties and abuse potential of cannabis.

1.4.4.2 Cognitive Performance and Psychomotor Control

One of the most well documented effects of cannabis intoxication is short-term memory impairment204–

206. Animal studies have consistently shown that THC, anandamide, and other synthetic cannabinoids

impair performance in memory tests such as the radial arm maze207,208, spatial learning tasks206, delayed

match tests206,209, and fixed ratio food acquisition task210. The deficits were reversed using rimonabant,

illustrating that the disruptive effects are mediated through CB1 receptors208. In humans, CB1 receptors

are expressed abundantly in the hippocampus, particularly in presynaptic terminals of a subset of

GABAergic basket cells211,212. These interneurons synapse with large pyramidal neurons in the CA1-CA4

hippocampal regions and are thought to control the synchrony of pyramidal cell activity. Through

reducing GABA release and GABAergic inhibition, cannabinoids affect learning and information

acquisition213. Moreover, memory formation in the hippocampus requires long-term potentiation (LTP)

and long-term depression (LTD), both of which are mediated by glutamatergic pyramidal neurons. CB1

receptors are also expressed in the presynaptic terminals of these pyramidal neurons. Studies have shown

that cannabinoids reduce the release of glutamate below the concentration required to activate NMDA

receptors postsynpatically, which inhibits the induction of LTP and LTD required for memory

function214,215.

CB1 receptors are most heavily expressed in the basal ganglia and cerebellum, which reflect the

importance of the cannabinoid system on psychomotor functions216,217. Cannabis has been shown to

produce a tetrad of effects in various animal models, including spontaneous suppression of locomotor

activity, hypothermia, antinociception, and immobility/catalepsy218. One of the earliest experiments with

dogs reported an awkward swaying and rolling gait after administering cannabis. It is also accompanied

16

by a period of intensified response to auditory and tactile stimuli and a subsequent phase of catalepsy and

sleep219. Similarly, in rodents, mice treated with THC displayed a ''popcorn effect''. Although sedated and

exhibiting reduced locomotion, groups of mice would jump up (hyperreflexia) in response to auditory or

tactile stimuli. As they fall back onto other mice, those would in turn jump up, resembling corns

popping166. In rats, while low doses of THC decrease motor movements, higher doses trigger catalepsy220.

Cannabis also affects a wide range of simple motor skills and psychomotor behaviours in human subjects.

At a moderate dose of intoxication, cannabis smokers demonstrated impaired performance on tests that

require fine psychomotor control, such as tracking221 and balancing222. Users also prefer isolation and

remain immobile for periods of time after intoxication222. A number of studies have attempted to

determine the underlying mechanism of cannabinoid modulation on psychomotor activity. In the basal

ganglia, CB1 receptors are typically expressed in presynaptic terminals of striatal GABAergic medium-

spiny neurons that project to the globus pallidus and susbtantia nigra reticulata. High abundance of CB1

receptors is also found in presynaptic terminals of glutamatergic neurons that projects from the

subthalamic nucleus to the globus pallidus and substantia nigra reticulata68,223–227. Sanudo-Pena proposed

that one key role of the endocannabinoid system may be to inhibit tonic release of glutamate in the

substantia nigra, regulating basal level of motor activity. Similarly, THC is speculated to inhibit glutamate

release in the substantia nigra and reduce locomotion. THC also inhibits GABA release in the striatum,

globus pallidus, and substantia nigra, which could result in disinhibition of inhibitory projections to the

thalamocortical pathway and in turn, inhibit locomotor activity223. Interestingly, CB1 receptor density in

the cerebellum is substantially lower in humans compared to rats, which could explain the lack of gross

motor impairment in humans after cannabis consumption68.

Other impairments of cognitive functioning have also been observed after acute cannabis consumption.

Subjects experience fragmented thoughts, mental clouding, slowed reaction time, difficulty concentrating,

decreased attention, especially on long and boring tasks, and reduced ability to make decisions or inhibit

their own actions119,228–234. Impairments are more prominent on tasks of higher complexity or those that

require divided attention119,235. The combination of these effects may significantly impair performance on

demanding tasks such as driving a car or flying an aircraft233,236. Laboratory studies and driving

experiments that examine the effects of cannabis on driving abilities are discussed in more detail in

Sections 1.5.2 and 1.5.3.

17

1.4.4.3 Other Biological Effects

Acute intoxication of cannabis is correlated with an increase in appetite, particularly for sweet foods. In

rats, THC and anandamide stimulate food intake in diets high in fat or sweets but not in standard chow237.

The effect was then reversed by CB1 receptor antagonist rimonabant238. When taken alone, rimonabant

suppressed food intake and reduced body weight in adult rats239. Similarly, rimonabant abolished milk

ingestion in new-born mice, which led to detrimental effects on growth and death within 4-8 days. The

phenomenon was almost completely reversed when THC was co-administered240. These findings suggest

that the endocannabinoid system plays a role in regulating food intake, and cannabis increases appetite

through its action on CB1 receptors. Furthermore, CB1 agonists have been shown to inhibit gastric acid

secretion, motility, and emptying in rats, mediated through the CB1 receptors by reducing vagal

stimulation to the stomach241,242. Several animal studies have also demonstrated that rimonabant induces

emesis, while THC and other CB1 receptor agonists block the effect, possibly through inhibition of

serotonin release243,244. Consistent in humans, clinical trials have shown that THC counteracts the loss of

appetite and body weight in patients suffering from eating disorders and AIDS wasting syndrome118,245.

THC has also been shown to suppress nausea and vomiting, particularly in patients undergoing cancer

chemotherapy246. Moreover, in one study, THC has been demonstrated to delay gastric emptying in

human subjects247.

Besides effects on the central nervous system, cannabis is also known to produce a series of peripheral

responses. In the heart, THC increases cardiac output and triggers a dose-dependent tachycardia, which

may be due to an inhibition of acetylcholine release from the vagus nerve and a suppression of vagal tone

on cardiac contraction. On the other hand, regular use of cannabis can lead to bradycardia. Individuals

with pre-existing cardiovascular diseases may be at risk of experiencing aggravated disease symptoms

after acute consumption. Cannabis could also cause a widespread systemic vasodilation, leading to

orthostatic hypotension and conjunctivae reddening114,248,249. Animal studies have shown that THC and

anandamide both induce hypotension in rats by activating CB1 receptors located on peripheral

sympathetic neuron terminals, which inhibits noradrenaline release and induces vasodilation. The

hypotensive response was reversed by a selective CB1 receptor antagonist, confirming the involvement of

CB1 receptors250.

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1.4.5 Pharmacokinetics and Pharmacodynamics Relationship

The relationship between plasma concentration of THC and its psychoactive, cognitive, and motor

responses is ill-defined. Interpretation of THC's pharmacokinetics-pharmacodynamics relationship is

further complicated by the formation of psychoactive metabolite, 11-hydroxy-THC, and the re-

distribution of THC from fat tissues140.

Peak THC effects often fall behind the rise of THC concentration in the blood, representing a

counterclockwise hysteresis (Figure 4)141. Following inhalation, maximal heart rate and conjunctival

reddening were reported within 1-5 minutes after smoking151. Peak "high" was achieved after 30-45

minutes, by which time THC plasma concentration had already fallen significantly while brain

concentrations remained high141,143,251. In a study using monkeys, an intravenous dose of radiolabelled

THC produced maximal radioactivity in the brain 15-60 minutes after administration, which corresponds

to the time of peak psychotropic effects in human after smoking252.

Figure 4. Phase plot of subjective high versus plasma THC concentration after an oral dose of cannabis

from 0-360 minutes, demonstrating a counter-clockwise hysteresis. Every solid point represents a 30

minute time point. While a maximum THC plasma concentration of 5.7ug/L was reached after 60

minutes, a maximum subjective high was reported 2-4 hours after consumption141.

It has been proposed that the distribution of THC occurs in the first hour of smoking141, after which THC

concentrations in the plasma compartment reach an equilibrium with the effect compartments253.

Therefore, there is a good correlation between THC concentration in the plasma and its effects beyond

19

one hour after administration253,254. Studies have also found that peak effects of THC occur when THC

and THC-COOH have reached equal concentrations, which takes place 30-45 minutes after smoking142.

Beyond 45 minutes, the plasma THC/THC-COOH concentration ratio was generally found to be <1142,186.

Various pharmacological models have been proposed to calculate THC plasma concentration based

on report of subjective ''high''. It is estimated that a THC plasma concentration of 7-29ng/mL is required

to achieve 50% of the maximal subjective ''high'' response (EC50)255. In contrast, other studies suggested

that the EC50 of subjective high ranges from 2-250ng/mL of plasma THC256. The duration of maximal

response is dose-dependent, and was reported to be 45 minutes after smoking 9mg of THC257 and longer

than 60 minutes with larger doses258. The psychotropic effects generally returned to baseline

approximately 3-4 hours after smoking258.

1.4.6 Toxicity, Tolerance, and Dependence

The lethal dose (LD50) of orally administered THC in rats is approximately 1000mg/kg, ranging from

800-1900mg/kg depending on the sex and strain. No cases of death were reported in dogs and monkeys

after a maximum oral dose of up to 3000mg/kg and 9000mg/kg, respectively259. In humans, the lethal

dose of intravenous dronabinol (synthetic THC) is estimated to be 30mg/kg260, although there have been

no reports of death exclusively related to cannabis overdose. This may partially be attributed to the low

density of CB1 receptors in regions that control cardiovascular and respiratory activities261. However, in

young children, accidental overdose of cannabis have resulted in a case of stupor and ataxia262 and two

cases of coma263. Moreover, in people with pre-existing cardiovascular diseases, cannabis-induced

myocardial infarction may be triggered by the effects of THC on the heart and vasculatures114. Adverse

effects experienced after acute intoxication typically include dizziness, sedation, tachycardia,

hypotension, dry mouth, distorted perception, and clumsiness, all of which are generally tolerable. In

some rarer cases, users may experience symptoms of panic attacks, psychosis, or convulsions. Serious

adverse events related to the CNS have been observed with an oral dronabinol dose of 0.4mg/kg260.

Tolerance to the effects of cannabis has been demonstrated in animals and humans, and can develop after

just a few doses264. There is strong evidence that tolerance to cannabis is predominately a result of

pharmacodynamic origin, through CB1 receptor desensitization or receptor downregulation265,266. A

positron emission tomography (PET) imaging experiment in chronic cannabis users showed a down

regulation of CB1 receptors in the brain and only within selective areas, suggesting that the mechanism of

controlling receptor desensitization or downregulation differs between different brain regions.

20

Consequently, the degree of tolerance and the speed at which tolerance develops are different between

various cannabis effects267. As seen in other studies, after administering a daily oral cannabis dose of

120mg/day268 or smoking a cannabis cigarette with 3.1% THC daily269, subjects reported tolerance to the

euphoria/''high'' but not for appetite. Additionally, tolerance to cardiovascular effects develops quickly,

but the tolerance to other effects develops more slowly and is more likely to appear with higher doses and

more frequent use.

Withdrawal symptoms can occur after abrupt cessation of use or rapid reduction in dose. An oral dose of

180mg of THC taken daily for 11-21 days is enough to produce some well-characterized withdrawal

symptoms such as anger and irritability, anxiety and restlessness, craving, insomnia and strange dreams,

headache, shakiness, sweating, depressed mood, and decreased appetite231,270,271. These symptoms

normally start within 1-2 days after cessation, peak between 2 to 6 days, and generally resolve after a

week or two of abstinence272.

The development of tolerance provokes cannabis users to increase their dose while the occurrence of

withdrawal symptoms drives continuous use. Despite the general perception that cannabis is not an

addictive drug or is less addictive than other substances of abuse, it has significant addictive potential.

Approximately 5-9% of cannabis users develop cannabis dependence, and early exposure of cannabis

during adolescents increases this rate to about 17%28,273,274. The risk of developing cannabis dependence is

modulated by both biological and environmental factors including genetics, age of first use, gender, and

socioeconomic status28,275–277. Verweji et al. conducted a meta-analysis of twin studies and concluded that

nearly half of the predisposition in early and problematic cannabis use are genetically driven. The

prevalence of developing cannabis dependence is highest between the ages of 15-24 and declines strongly

with age277. As high as 1 in 10 high school students who have used cannabis at least once in the past year

exhibit symptoms of dependence28,277. The lifetime risk of developing cannabis addiction is higher among

males (12%) than females (5.5%)278, but adolescent girls between the ages of 12-17 are especially

vulnerable with early use279. Other factors such as regular and chronic use, low socioeconomic status,

persistent anti-social behaviour, and chronic cigarette smoking have also been identified as contributors of

cannabis dependence28,275–277.

1.5 Cannabis Use and Driving

It is well established that alcohol impairs driving performance and exponentially increases the risk of

collisions280,281. With an increase prevalence of driving under the influence of cannabis (DUIC),

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especially among young adults, attempts have been made to investigate the effects of cannabis on driving

abilities and provide a scientific basis for improvement of traffic safety policies17,18,282. Three types of

studies are useful in evaluating the risk of cannabis on increasing traffic accidents: 1.) Epidemiological

studies that examine the association between cannabis use and motor vehicle accidents 2.) Laboratory

studies that examine the effects of cannabis on neurocognitive and psychomotor functions that are

considered essential to safe driving 3.) Experimental simulator and on-road studies that directly assess

driving performance under the influence of cannabis. These studies are reviewed in this section.

1.5.1 Epidemiological Studies

In Canada, the rates of DUIC have increased over the recent years. A national survey reported a rise from

1.5% to 2.3% of Canadians who admitted to have driven within two hours following cannabis use from

2002 to 201327,283. This represents over half a million of Canadians who have committed DUIC. In

Ontario, 2.9% of drivers have driven within one hour after using cannabis in the past year prior to their

participation in the survey284. Similarly in other jurisdictions, the European Monitoring Centre for Drugs

and Drug Addiction (EMCDDA) found that between 0.5% and 7.6% of injured or killed drivers were

tested positive for cannabis in Belgium, Denmark, Finland, Italy, Lithuania, Sweden, and the

Netherlands285. The percentage of drivers suspected of driving under the influence of cannabis were at a

shockingly high rate of 27-50% in countries including Australia, Austria, Denmark, Hungary, and

Switzerland286–289.

The rates of DUIC is disproportionally higher among young drivers, which is also the group with the

highest risk for MVAs27,285. Almost a quarter (23%) of young drivers aged 18 to 19 have driven under the

influence of cannabis in the 12 months prior to their participation in the survey290. Likewise, another

national survey reported that 39.8% of drivers between the ages of 15 to 24 admitted to have driven after

using cannabis within the past 12 months, compared to 20.9% for DUIA291. The average number of times

of driving under the influence was approximately 10 for cannabis and only 1.6 for alcohol282. In a recent

study by Bergeron and Paquette, 72 cannabis users between the ages of 18 and 25 were asked to self-

report DUIC over the past year. Of these participants, 49% reported to have always or often driven, 39%

admitted to have occasionally driven, and 12% claimed to have never driven immediately after

consumption292. Similarly in other countries, a self-report study conducted in the United Kingdom found

that 40% of university students and 59% of young clubbers have engaged in DUIC293. Moreover, in a

survey of Scotland drivers who drove within 12 hours of using cannabis, 15% of individuals were aged

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17-39 years while only 3% were above 40 years old. The study also showed that people who reported

DUIC drove an average of 8.1 times per year while intoxicated294.

At present, cannabis is the psychoactive drug most commonly detected in drivers involved in MVAs8–11.

Early epidemiological data have been inconclusive regarding whether cannabis increases collision risks.

This discrepancy is largely attributed to methodological challenges and weak study design. Firstly, many

studies only measured inactive THCCOOH in urine, which can be detected long after acute effects have

dissipate and has limited relations to driving abilities19,295. Secondly, some studies have not included a

control group of drivers who were not involved in accidents or have included control groups that were

inappropriately matched in case-control studies, both of which alter estimation of relative collision

risks20,296. Lastly, many studies did not adjust for confounding factors such as alcohol consumption and

demographic characteristics296,297.

More recently, well-designed observational studies and meta-analyses provided stronger evidence

towards an increase in collision risks following acute cannabis consumption. In a large retrospective study

of 64657 male drivers, Gerberich and colleagues found an odds ratio (OR) of 2.3 in car injuries between

cannabis users and nonusers298. Similarly, among 900 injured drivers admitted at the emergency

department, an OR was calculated to be 2.5 for individuals who used cannabis versus 900 sober

controls299. Moreover, a large prospective study examining fatal car collisions in Quebec found an OR of

2.2 for fatalities as a result of DUIC297. Comparable results were reported in two recent meta-analyses that

reviewed 9 studies each. After adjusting for confounders, both analyses documented that acute

consumption increases the risk of MVAs by approximately 2 fold [pooled OR = 2.66300 and OR=1.96301].

Some studies also investigated DUIC in relation to the culpability of the accident, whether the driver was

at fault in the collision. From 10 years of Fatality Analysis Reporting System (FARS) data, drivers who

were positive for cannabinoids were significantly more likely to have at least one driver-related factor

(OR=1.29), which is considered as unsafe behaviour contributing to collisions302. The low OR, which

remained statistically significant after adjusting for confounders, may be attributed to the long detection

window of THC metabolites in urine samples. Drummer et al. reported a significant increase of crash

responsibility with an adjusted OR of 2.7 while DUIC. The OR increased to 6.6 when blood THC

concentration was above 5ng/mL303. Similarly, in a sample of 544 fatal vehicle accidents, 23 out the 24

individuals who were only positive for THC were deemed responsible for their accidents. Swan

concluded that the risk of having a fatal collision is 6 times more likely while DUIC304.

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Furthermore, blood THC concentration, time of exposure prior to driving, and frequency of use appear to

affect the risk of cannabis on car crashes19,295. Driving within 1 hour after smoking doubled the risk of

MVAs than driving within 2 hours [OR=5.8 vs OR=2.2]305. Increasing blood THC concentration from <1,

1-2, 3-4, to >5 ng/mL corresponded to an increase culpability risk of 2.18, 2.54, 3.78, and 4.72 crude OR,

respectively9. In a study of 456 drivers who had an average blood THC level of 2.2ng/mL, clinical test for

impairment (CTI) determined that 54% of the individuals were impaired. After grouping drivers by

concentration and adjusting for confounders, the ORs for impaired driving increased correspondingly by

2.4, 2.5, and 3.2 with blood THC concentrations of 3-4.8, 4.9-10.1, and >10.2ng/mL. Moreover, with

similar levels of blood THC, self-reported regular cannabis drivers were significantly less likely to be

judged as impaired by the CTI compared to occasional users (32% vs 55%, OR=1.8)306.

In summary, epidemiological studies have highlighted the risk of acute cannabis consumption on

increasing MVAs and at-fault collisions, particularly with increased blood THC concentrations. While

they are useful in assessing driving behaviours in the general population, epidemiological studies may

involve selection bias and cannot establish a direct causal relationship. Therefore, laboratory studies

conducted in a controlled setting are required to clarify the link between cannabis consumption and its

associated increase in collision risks.

1.5.2 Laboratory Studies

A plethora of experimental studies have been conducted to evaluate the effects of cannabis on cognitive

functions and psychomotor skills related to driving abilities. Evidence of impairment in learning,

memory, attention, reaction time, motor control, and perception has been reported15,258,307–310. Other

researchers have also observed adverse effects on decision-making and impulsivity19,20,310–312. Some of

these deficits can manifest at a dose as low as 2.5mg of THC and occurs in a dose-dependent

manner19,20,312. Across these studies, memory deficits after acute consumption is one of the most

uniformly reported impairments. However, findings for other neurocognitive effects have been less

consistent310–312. Studies in the past were often inconclusive because they lack outcome measures that are

tailored and sensitive to the effects of cannabis. With an improvement in experimental methodology and

the use of placebo-controlled double-blind designs, evidence on the effects of cannabis on driving has

been strengthening and is becoming more clear312,313. The following literature review on cognitive and

psychomotor effects of acute cannabis intoxication is presented in the order of evidential strength from

most to least consistently impaired.

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1.5.2.1 Memory

For over 40 years, researchers have homogenously shown that acute cannabis consumption impairs

memory function, particularly in verbal learning and episodic memory19,309–312. Miller et al. found that

cannabis, at varying doses of THC, decreased immediate free recall of words compared to placebo in a

dose-dependent manner314. In a follow-up study where moderate to heavy cannabis users were

administered 14mg of THC or placebo, a similar decrease in immediate recall as well as a decrease in

delayed recall were observed315. Normally, recall tasks that involve more meaningful processes such as

semantic or syntactic processes allow subjects to better integrate the information and improve their ability

to recall. However, while under the influence of cannabis, subjects were especially impaired in delayed

recall involving words that are more meaningfully processed316. Moreover, Curran et al. examined the

effects of cannabis containing 7.5 and 15mg of THC on memory performance using the Buschke's

Selective Reminding Task in infrequent cannabis users. Subjects were asked to recall a list of 16 words

three times and each time was followed by a repetition of the words forgotten. Learning of new

information over the three trials were dose-dependently inhibited, where the number of words recalled on

the third trial was less than the first317. Similar results have also been reported in other studies318,319.

While most studies have shown that cannabis produces significant impairments in verbal learning and

recall memory, a few studies failed to obtain such findings320–324. In these studies, a battery of tests

examining a variety of cognitive functions was administered before and after smoking cannabis. No

effects were detected for most of the cognitive domains examined, including learning and memory.

Interestingly, pre-administration of CBD or administration of cannabis containing a higher CBD content

may protect against some THC-induced deficit in verbal learning and memory325,326. Moreover, poor

performance is associated with regular cannabis use and is directly correlated with frequency of use,

duration, and age of first use327–329.

Working memory is the ability to temporarily store and manipulate information within a short period of

time. It differs from short-term, episodic memory in that working memory emphasizes on the

manipulation of newly stored information. A variety of tests have been used to examine working memory,

including Delayed Match to Sample Task (DMST), Steinberg test, N-Back Task, Digit Recall, and Digit

Span Task317,330–335. Possibly because of the wide range of tests used across studies, whether cannabis

impairs working memory remains unclear. In a randomized, placebo-controlled study, working memory

was assessed using digit recall tasks in infrequent cannabis users who received an oral THC dose of 20,

40, and 60mg. Both forward and backward digit recall significantly decreased at all doses but not dose-

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dependently. While impairment of forward recall returned to baseline at 3.5 hours after use, backward

recall remained impaired beyond 3.5 hours330. Similarly, cannabis decreased accuracy on the N-Back

task333 and disrupted performance on the DMST334 in a dose-dependent manner. In contrast, Darley et

al.336 and Heishman et al. failed to observe an effect on the Steinberg test331,336 while Curran et al. found

no impairment in working memory through the serial sevens task317.

Furthermore, cannabis is associated with an increase in intrusion errors in recall tasks and false positive

responses in recognition tasks232,314. In a study conducted by D'Souza et al., learning, free recall, and

delayed recognition were assessed by the Hopkin's Verbal Learning Task in healthy individuals who

rarely used cannabis. Outcomes were measured 30 minutes after administering an intravenous dose of 2.5

and 5mg of THC. In addition to a significantly impaired immediate and delayed recall, THC also dose-

dependently increased the number of false positives and intrusions in the delayed recognition task. This

effect appears to be unique to cannabinoids, as other studies using different forms of recall task also

reported similar results232.

1.5.2.2 Attention and Concentration

Impairments in focused, divided, and sustained attention following acute exposure is another commonly

observed deficit of cannabis intoxication. In a study with light cannabis users who received either active

(2.5% THC) or placebo cannabis, a significant decrease in attention 30 minutes after administration was

seen in the THC group compared to the placebo group335. In another double-blind, placebo-controlled

study conducted by Hunault et al., 24 non-daily cannabis users smoked cannabis cigarettes containing 0,

29.3, 49.1, and 69.4mg of THC over four drug administration days. Cannabis impaired multiple forms of

attention, including selective, sustained attention, and divided attention. The degree of impairment

linearly correlated with the amount of THC administered, suggesting a dose-dependent relationship337.

Similar results have been reported in other studies232,318,320,338–340. In particular, impairment was most

frequently reported when 2 or more tasks were conducted simultaneously, suggesting a greater sensitivity

of divided attention to the effects of cannabis.

In contrast, a few studies observed no deficits or even improvements in attention after cannabis

consumption. Hart et al. compared the effects of placebo, light-dose (1.8% THC), and high-dose (3.9%

THC) cigarettes in chronic, daily cannabis users and reported no significant difference in response

accuracy of attention tasks322. Moreover, individuals who received a high dose of THC performed

significantly better on a tracking task that required sustained attention. Similarly, improved performance

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in a divided attention task was also observed after acute cannabis intoxication in daily users269. This

discrepancy may be attributed to the difference in the degree of cannabis use and the degree of tolerance

developed over time among the subjects studied. In two experiments that compared the effects of

cannabis on divided attention between occasional and heavy cannabis users, THC significantly affected

performance on divided attention tasks in occasional but not heavy users338,341. Interestingly, Kelleher et

al. found that information processing speed, which is a fundamental component of attention and

concentration340, was significantly reduced in heavy chronic cannabis users after abstinence but returned

to normal after smoking342. This suggest that heavy, long-term cannabis use may cause neuroadaptive

changes in attention and concentration, which may be disrupted more by acute abstinence than acute

intoxication342.

1.5.2.3 Psychomotor control

Motor coordination and response reaction time are components of psychomotor functions that have been

implicated with cannabis intoxication. Reduction in motor performance, including physical strength,

balance, coordination, and steadiness, have been reported following cannabis consumption16,119,343,344. In a

study conducted by Liguori et al., subjects smoked a cannabis cigarette containing 0, 1.77, or 3.75% of

THC and were then asked to stand on a dynamic platform while staring at a simulated landscape. In

response to the moving platform and landscape, the body would naturally sway to maintain balance and

steadiness. The high dose of THC significantly increased body sway, illustrating a decreased ability to

coordinate motor movements345. Similarly, Manno et al. reported impaired motor performance measured

in a pursuit meter test after smoking a high dose cannabis cigarette containing 5mg of THC346. In these

studies, a low dose of THC (1.77% and 2.5mg of THC, respectively) did not produce any effect345,346.

Virtual Maze and Critical Tracking Task are more integrated tests used to examine perceptual motor

control and fine motor coordination. Such complex tasks are particularly sensitive to the impairing effects

of cannabis. Regular cannabis users who smoked 13mg and 17mg of THC increased the number of wall

collisions in a virtual maze347. Several other studies have reported a significant decrement in critical

tracking performance among light cannabis users after smoking or vaporizing338,341,343,348,349.

Increased reaction time is another cannabis-associated impairment commonly reported, although studies

on chronic users have been mixed. Kuzthalzer et al. conducted a study with 60 healthy individuals who

smoked either active (2.9mg/kg THC) or placebo cannabis and performed several psychomotor tests 15

minutes post-dose. The authors observed a decrease of speed and accuracy in the Efficiency Test System

after smoking the active cannabis compared to the placebo350. Increased stop reaction time and decreased

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response accuracy were observed during a Stop Signal Task after cannabis consumption in occasional

users, and also in heavy users at a higher dose338,341,348,349. On the other hand, several other studies have

failed to report any effect319,340,351. Hunault et al. even reported, in heavy cannabis users, a significant

decrease in response time on a motor control task after consuming varying doses of THC. This decrease,

however, was accompanied by a dose-dependent increase in response error337.

1.5.2.4 Decision making

The ability to anticipate and reflect on the consequences of decisions are portrayed through one’s

performance on decision making tasks. In a study with occasional smokers, acute administration of

cannabis containing 17.5mg THC significantly reduced the number of correct decisions in the Tower of

London Tests 45 minutes and 5.75 hours after consumption. Moreover, those who received the active

cannabis required a longer time to plan (response latency) compared to the placebo group349. Similarly,

Vadhan et al. found that chronic daily cannabis users who received light (1.8%) and heavy (3.9%) doses

of THC were significantly slower in making decisions than the placebo controls352. In contrast, 13mg and

17mg of THC did not affect decision-making speed in a gambling task an hour after cannabis

consumption, although the chance of choosing a less likely outcome was significantly higher with 17mg

of THC compared to the placebo group347. Likewise, in both occasional and frequent cannabis users,

response time in the Tower of London test was not affected after smoking cigarettes containing 25mg and

35mg of THC338,340.

1.5.2.5 Risk-taking and Impulsivity

Drugs of abuse are often associated with impulsive and risky behaviour that may lead to uncontrolled and

poorly planned actions while driving under the influence. In a study with 37 occasional cannabis users,

acute consumption of a high dose of THC (15mg) significantly increased impulsivity353. Likewise, in

another group of 10 occasional users, increasing levels of cannabis intoxication is correlated with more

risky responses between two choices354. In contrary, a more recent study indicated that cannabis may alter

some motivational and reinforcement processes during risky choices, which may actually reduce risk-

taking behaviours in young adults355.

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1.5.2.6 Perception of Time and Distance

While subjective effects of perceptual distortion following cannabis intoxication is well documented,

experimental evidence in this area is limited. In one study, individuals who are occasional cannabis users

were asked to smoke 2 cannabis cigarettes (3.6% THC) 2 hours apart at 4 puffs each. They found that

cannabis lead to an underestimation of 60s and 120s time intervals after smoking320. In contrast, a recent

study reported that varying intravenous doses between 0.015 to 0.05mg/kg of THC increased internal

clock speed, leading to time overestimation and underproduction. The alteration was not dose-dependent

and was blunted in frequent cannabis users356. Similarly, in chronic daily users, 13mg and 17mg of THC

did not alter time and distance perception, possibly due to drug tolerance and neuroadaptation from heavy

cannabis use340.

Summary

Laboratory studies have shown evidence of impairment in verbal learning and memory, working memory,

attention, and motor coordination after acute consumption. These deficits generally occur in a dose-

dependent manner and impairments may be blunted in chronic cannabis users as a result of tolerance. The

effect of cannabis on reaction time, decision-making speed and accuracy, risk-taking and impulsive

behaviours, and perceptual distortions have been mixed. Overall, there is reasonable evidence that

cannabis disrupts some essential cognitive and psychomotor functions necessary for safe driving

immediately after use. While laboratory studies provide a better understanding to the nature of cannabis

impairment, whether they serve as a good model to assess driving ability as a whole remains unknown.

Many tests are short and simple, and may not necessarily reflect the complexity of driving and

performance in real traffic. Therefore, driving simulator and on-road studies, which offer greater face

validity, are essential to establish the causal relationship between cannabis intoxication and impaired

driving performance.

1.5.3 Simulator Studies

Simulation technology was introduced in the early 20th century. The first simulators developed were flight

simulators, used to train pilots in preparation for wars at a lower operational cost357,358. In the late 1950s, it

became apparent that simulation technology could be used for a wide-range of applications, including

manufacture, education, and research357–359. In particular, there has been a strong increase in the use of

driving simulators to study driving behaviours. Simulated-driving provides a safe and controlled

29

environment, allowing researchers to study many aspects of driving behaviour under fixed conditions

while avoiding ethical challenges of exposing participants to traffic danger357,358,360.

The earliest driving simulator study examining cannabis effects was conducted by Crancer et al. in

1969361. Participants were divided into three treatment conditions: smoking a cannabis cigarette

containing 22mg of THC, drinking an alcoholic beverage that produced 0.1% BAC, and no treatment.

While viewing a 23-minute film in a mock car, they were asked to maneuver the steering wheel,

accelerator, brake, and turn signals in response to the film. Unlike alcohol, cannabis did not affect any of

the above measures. The lack of effects observed may be a result of poor experimental design and

possibly a dose of cannabis that was less than intended. In another study conducted by Rafaelson et al.,

participants were asked to manipulate the simulator in response to a moving landscape projected onto the

windshield of a car mockup after ingesting a dose of cannabis. Those who received 12 and 16mg of THC

increased response latency to the appearance of red and green lights. However, a lower dose of 8mg did

not produce any effect. There was no change in mean speed and tracking performance across all doses313.

In contrast, using a more interactive computer-controlled simulator, Smiley et al. reported significant

impairment in a series of responses. Cannabis increased speed variability and lane deviation during curves

or windy roads. Increased following distance behind others cars and increased reaction time to peripheral

light stimuli were also observed362. Moreover, drivers under the influence of cannabis were less likely to

attempt risky maneuvers, refusing to pass obstacles at times when participants under the placebo

condition would have313,362.

Over the last decade, technological advancements have led to the development of high-fidelity driving

simulators. Digital computer programming offers more flexibility in designing research specific

scenarios, while automated measurements of driving data reduce experimenter bias. These state-of-the-art

machines also incorporate better visual displays and improved sensory feedback, creating an experience

that is more realistic and transferrable to real-life driving363.

1.5.3.1 Speed and Speed Variability

Drivers under the influence of cannabis appear to be aware of their impairment and are suspected to

compensate by driving more cautiously21. Consistent with this theory, more than half of the studies that

investigated driving speed reported a decrease in mean speed after acute intoxication.

In a study conducted by Sexton et al., 13 occasional cannabis users smoked a cannabis cigarette

containing 0, 1.7% or 2.7% of THC and drove on a 16.7km motorway. Both doses of cannabis

30

significantly decreased average speed compared to placebo364. In a follow-up study under the same

conditions, a similar decrease in speed was observed365. Lenne et al. conducted another study using 22

young novice drivers aged 18-21 with less than 2 years of driving experience and 25 experienced drivers

aged 25-40 with more than 7 years of driving experience. Participants were instructed to smoke two

cannabis cigarette containing 0 or 19mg of THC, with a total of 8 puffs per cigarette. Only the high dose

of THC (38mg) decreased mean speed and standard deviation of speed compared to the placebo group366.

Moreover, Ronen et al. reported a marginal decrease in average speed with no effect on speed

variability367. Although several studies failed to observe a change in speed339,345,368, no studies do date

have found an increase in mean speed while driving under the influence of cannabis.

1.5.3.2 Lane Control

The ability to control a vehicle within fixed boundaries is a crucial aspect of safe driving. Standard

deviation of lateral position (SDLP) is one the most sensitive measures used to examine lane control and

driving impairment348,369,370. Lane departure, deviation of steering position, and line straddling are some

other examples of lane control measures. Across almost all studies, cannabis has consistently impaired

vehicle control364–368,371–373. A recently published study by Hartman et al. investigated the effect of

vaporized cannabis on driving skills in 19 occasional users. Driving tasks were completed roughly 1 hour

after consumption. Cannabis containing 2.9% and 6.7% of THC significantly increased SDLP in a 45-

minute drive containing urban, interstate, and rural segments. This increase linearly correlated with an

increase in blood THC concentration. The authors also concluded that driving under a blood THC

concentration greater than 8.2ug/L produced a similar impairment in lane control as a BAC of 0.05%, a

legal alcohol limit in many jurisdictions372. In a mixed group of novice and experienced drivers, a low

(19mg) and high (38mg) dose of THC increased SDLP by 4 and 7 cm, respectively, along with an

increased deviation in steering wheel angles366. In another study with 12 young, recreational cannabis

users between the ages of 24-29, 13mg of THC significantly increased steering wheel variability and lane

position variability after smoking367. Furthermore, THC-induced impairment on road tracking tasks was

observed 60-330minutes371 and 80 minutes373 after smoking 14-52mg of THC. However, at an earlier time

point of 30 minutes post-dose, results did not attain significance373. Likewise, in two other studies with

occasional cannabis users, 1.7-3.95% of THC did not increase the number of cones knocked over345 and

lane deviation 2-30minutes after intoxication339,345.

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1.5.3.3 Headway

Headway refers the distance between the driver’s car and the vehicle in front. Even though only a few

studies have examined the effects of cannabis on headway maintenance, findings have been

consistent362,365,366. In a study conducted by Sexton et al., 13 male subjects were administered active

(1.7%THC) or placebo cannabis. Cannabis was found to increase the minimum distance maintained

behind the car ahead. In another study with a car following task, participants were instructed to maintain a

fixed distance of 40 meters behind a lead vehicle that travels at varying speed365. Lenne et al. reported a

dose-dependent increase in mean headway after smoking 19mg and 38mg of THC. Moreover, this

increase was also accompanied by an increase in the standard deviation of headway, further supporting an

impairment in vehicle control while under the influence of cannabis366.

1.5.3.4 Reaction Time

Findings on driving reaction time have been mixed. While some studies reported an increase in reaction

speed, others were unable to find any effect. In a study by Liguori et al., 10 cannabis users smoked a

cannabis cigarette containing 0, 1.77, and 3.95% of THC and drove on a simulator 2 minutes later.

Participants were asked to brake as quickly as possible to stop the vehicle before hitting a yellow barrier

fence. The high dose of cannabis marginally increased brake latency by a mean time of 55ms. In a car that

is travelling at 95km/hr, this latency is comparable to an increase braking distance of nearly 1.5 meters

closer to the barrier. Moreover, the degree of increase in brake latency is equivalent to that of subjects

with a BAC of 0.05%345. In a more recent study, performance on a sign detection task while driving on a

straight arterial road was measured. Similar to the previous study, only participants in the high dose

condition (38mg of THC) demonstrated increased reaction time. Interestingly, inexperienced drivers and

female drivers were slightly faster at detecting road signs than experienced and male drivers366.

Conversely, reaction time in response to an emergency vehicle and a braking hazard was not affected by

1.7-2.9% of THC364,365. When Downey et al. measured reaction time to emergencies after smoking a low

(1.8%) and high (3.3%) dose of cannabis, non-regular users actually responded significantly faster

compared to regular users and placebo368.

1.5.3.5 Collisions

Although epidemiological studies have demonstrated that cannabis use is associated with an increase in

collision risks, only a few stimulator studies have examined collision events as an outcome variable. In a

32

study conducted by Ronen et al., 3 out of 12 subjects had a collision under the influence of cannabis while

none of the subjects collided under the placebo condition. This result is comparable to subjects under the

influence of alcohol, where 2 out of 12 subjects with a BAC of 0.05% had a collision367. Moreover, there

appears to be a dose-related pattern in collision events. In another study by the same group of authors, 6

subjects collided after smoking 17mg of THC compared to 3 subjects who had a collision after smoking

13mg of THC373. However, these numbers are too low for statistical analyses and interpretation.

Moreover, using a collision avoidance scenario, Anderson et al. did not find any difference in collisions

between active cannabis (22.9mg THC) and placebo groups374.

1.5.3.6 Divided attention

Complex tasks requiring divided attention are particularly sensitive to the impairing effects of cannabis.

In one study, participants were asked to complete the Paced Auditory Serial-Addition Test (PASAT)

during an uneventful segment of a simulated drive. The test measured auditory processing speed and

cognitive flexibility. Under this dual-task condition, cannabis containing 2.9% of THC decreased mean

driving speed more so than the placebo group. Such phenomenon was not observed without the secondary

task. Moreover, those who smoked active cannabis failed to demonstrate practice effects on the PASAT,

suggesting that cannabis may hinder the use of information and experience previously acquired374. In

another study, Ronen et al. also incorporated a distraction task into a driving assessment. An array of

lights with corresponding buttons was placed on the dashboard. During the drive, lights were randomly lit

and participants were required to press the corresponding buttons as fast as they can. Those who received

a low (13mg) and high (17mg) dose of THC responded significantly slower compared to the control

group367.

1.5.4 On-Road Studies

On-road testing is another method used to study driving behaviour. It examines actual driving

performance using an instrumented vehicle on closed-course tracks or in real traffic. Due to safety and

ethical concerns, only a handful of on-road studies exploring the effects of cannabis on driving behaviour

have been conducted.

The first on-road study was conducted by Klonoff on the streets of Vancouver in 1974. A total of 38

subjects were divided into three groups and received either 4.9mg THC, 8.4mg THC, or placebo cannabis

cigarettes. After smoking, participants drove an approximate distance of 26km on the city streets and

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driving performances were evaluated by a professional examiner. Out of the 11 driving behavioural

subscales used to assess driving skills in the study, three subscales (concentration, care while driving, and

judgements) were significantly affected by the high dose of cannabis. However, the authors reported large

variabilities in the data observed, which may have been due to subjective judgements of the driving

examiner375.

In another study, Hansteen et al. examined the effects of cannabis cigarettes containing 1.4mg or 5.9mg of

THC on driving performance in a close-course test. A significant increase in the number of cones hit and

the time required to complete the driving trial was observed after smoking a high dose of cannabis

compared to placebo. There was no difference between driving performances in the low-dose and placebo

groups376.

A more comprehensive series of on-road driving studies were conducted by a group of researchers in the

Netherlands. Robbe examined the effects of smoked cannabis containing 0, 100, 200, and 300 ug/kg of

THC on driving performance in a 22km road tracking, restricted highway test. Cannabis produced a dose-

dependent increase in SDLP with no significant effect on mean speed and standard deviation of speed.

The degree of increase was the same at 40 minutes and 100 minutes after smoking377. In a separate

experiment with the same escalating dose regimen, 16 participants drove on a 64km road tracking test and

16km car following test. Cannabis increased SDLP in a dose-dependent manner on the road tracking test,

with the lowest dose producing a small but non-significant increase, and the medium and high dose

producing significantly greater impairments. In the car following test, mean headway increased by 8, 6,

and 2m for the three doses, respectively. The inverse headway to dose relationship may be a result of

practice effects, where participants became more comfortable and less cautious with increasing driving

experience. No differences in reaction time, headway variability, and overall driving quality were

observed relative to placebo377.

In a subsequent study with 18 occasional cannabis users, driving performance on a 40km road tracking

test and car following test were measured after smoking 0, 100, or 200ug/kg of THC. Similar to the

previous studies, SDLP increased significantly by 2.7 and 3.5cm, respectively, 30 mins after smoking the

two doses. A significant impairment in headway variability was also observed, with an increase of 2.9 and

3.8m after smoking 100 and 200 ug/kg of THC. However, cannabis did not affect mean headway, reaction

time, and time spent out of traffic lane378.

34

Lastly, Lamers et al. conducted a 15km driving test through 2-lane undivided streets in business and

residential areas. Driving performance was rated by the Driving Proficiency Test, which included

subscores for vehicle checks, vehicle handling, traffic manoeuvers, observations and understanding of

traffic, and turning. In addition, visual search frequency was measured using a head-mounted eye

movement tracking system. After smoking cannabis containing 2.2% of THC, there was no significant

difference in driving quality and visual search frequency compared to placebo379.

Summary

In general, simulated and on-road driving studies thus far have shown that drivers exhibit more cautious

behaviour while under the influence of cannabis by reducing their speed and increasing headway

maintenance. However, despite an apparent effort to compensate their impairment, drivers have reduced

lane control immediately after use. The impairing effects of cannabis become more prominent while

driving under a distracted condition, supporting the hypothesis that complex tasks are more sensitive to

cannabis-induced impairment. However, findings on driving reaction time and collision events have been

mixed. Since high-fidelity driving simulator is a relatively new and expensive technology while on-road

testing imposes ethical concerns, only a handful of studies have been published, most of which have a

small sample size. Therefore, more research is required to clarify the impairing effects of cannabis on

driving performance.

1.6 Residual effects of Cannabis

Most available studies on the effects of cannabis focused on the acute or short-term impact of the drug.

While acute intoxication clearly produces impairment in some driving skills, it is less clear how long

these deficits last. After absorption, THC, a highly lipophilic compound, is rapidly redistributed from the

plasma to other compartments159. It accumulates in fat tissues and is then slowly released over time. As a

result of these unique pharmacokinetics, THC may persist in the brain, a highly fatty organ, for a longer

time frame than that reflected by the plasma concentration and may produce clinically significant residual

effects on cognitive and psychomotor functions beyond short-term impairments160–162. Moreover, the

primary metabolite of THC, 11-OH-THC, exhibits psychoactive properties and a longer elimination half-

life than THC, which may further lengthen the residual effects of cannabis174.

Before reviewing the literature, it is important to first define “residual effects” in the context of this study.

The term “residual effects” has been used by various researchers to imply one of three conditions: (1)

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drug effect attributed exclusively to a residue of the drug in the body, also known as “drug residue” or

“hang-over” effects; (2) effects caused by persisting alterations of the central nervous system that are

present even after the drug has been completely eliminated from the body; (3) a combination of both236. In

this study, we are interested in the first condition. Specifically, we are interested in whether a residual

amount of THC and its active metabolite impair driving-related performance after a single dose of

cannabis.

Majority of studies on the residual effects of cannabis assess heavy cannabis users after a period of

abstinence312,380–382. However, it is difficult to interpret the results of these studies because any impairing

effects observed could be attributed partially to a “drug residue” effect and/or lasting CNS alterations as a

result of heavy cannabis use. In addition, heavy users may be more impaired after acute abstinence than

acute intoxication due to withdrawal symptoms, which makes the results even more challenging to

decipher. Furthermore, the dose of cannabis and the duration of abstinence across these studies differ

significantly, adding another layer of variation and complexity. Therefore, in the following review, only

studies that exclusively examined residual drug effects of cannabis after controlled administration of a

known cannabis dose will be discussed.

In one of the first laboratory studies exploring the residual drug effects of cannabis, Chait and colleagues

examined whether smoking cannabis in the evening could produce measurable behavioural effects the

next morning. In the study, 13 regular cannabis users smoked either an active (2.9% THC) or placebo (0%

THC) cannabis cigarette in the evening and were assessed 9 hours later the following morning. Cannabis

produced a significant impairment in time estimation, where subjects overestimated the time in a 10s- and

30s- time production task. Subjective drug effects were also observed the next morning, where more

participants reported feeling “dopey and hung over” after smoking the active cannabis. However, this

effect was subtle383. In a separate study conducted by Chait, 16 light cannabis users aged 18-26 years

were administered a cannabis cigarette containing either 0% or 2.1% THC in the evening and were

assessed 12 hours later the following morning. Cannabis significantly impaired performance on the

backward digit span task and the time production task. Contrary to the previous study, participants who

smoked the active cannabis produced shorter time intervals compared to the placebo condition. There was

no evidence of residual subjective drug effects and mood changes384. Since these studies were only

conducted up to 12 hours after smoking, it is uncertain whether the observed effects lasted beyond this

time frame. In a more in depth study conducted by Heishman et al., three light cannabis users smoked two

cannabis cigarettes containing either 0 or 2.57% THC and were assessed on a battery of cognitive and

psychomotor tests immediately after smoking and on the following day. Cannabis significantly increased

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response time to a serial addition/subtraction task immediately and 24 hours after smoking. Response

accuracy on the digit recall task also remained impaired until 31 hours after smoking either one or two

cannabis cigarettes. There were no cardiovascular and subjective effects observed the following day331.

Although some studies have found evidence of residual effects up to 24 hours after smoking a single dose

of cannabis, others have shown conflicting results. Barnett et al. investigated the effects of cannabis on

performance in a visual search task, divided attention task, and critical tracking task, all three of which

assessed skills related to driving. In the study, eight occasional cannabis users smoke one cannabis

cigarette containing 100, 200, or 250ug/kg of THC and were tested 13 times over the following 24 hours.

A significant decrease in reaction time and increase in tracking error were observed only until 7 hours

after smoking. No impairment was found at 24 hours post-dose385. In another study conducted by Fant et

al., 10 male participants aged 21-31 years smoked a cannabis cigarette containing 0, 15.6, and 25.1mg

THC over three separate experimental sessions. Participants smoked according to a paced-puffing

procedure, with eight puffs per cigarette, 20 seconds retention per puff, and 40 seconds rest interval

between puffs. Significant subjective drug effects and physiological responses (e.g. increased heart rate,

reduced pupillary light response) were observed immediately after smoking but did not persist more than

1.75 and 3.5h after the low and high dose of cannabis, respectively. Performance on the tracking, digit

recall, logical reasoning, and spatial perception tasks did not change 23-25hr after smoking either doses of

cannabis321. Similarly, in a larger study with 60 participants, there was no difference in psychomotor

speed and accuracy 24 hours after smoking a cannabis cigarette containing 290ug/kg of THC compared to

placebo350. No effects on subjective drug effects and mood were observed at 24 hours pose-dose320.

To our knowledge, only one study has attempted to examine the residual effects of cannabis on simulated

driving performance. In this study, eight male subjects aged 21-29 years ate a small cannabis cake

containing 0, 8, 12, or 16mg of THC and were tested on simulated driving performance up to 16 hours

after ingestion. While cannabis significantly increased brake time and start time immediately after

consumption, no difference in any driving measures were observed at 16 hours. Similarly, no effects on

cognitive and subjective tests were reported313. In the late 1980s and early 1990s, Yesavage and

colleagues were concerned with potential residual effects of cannabis on flying skills, and conducted a

series of flight simulation studies that produced mixed results. In the first study, ten experienced pilots

performed a flight simulator landing task before and 24 hours after smoking a cannabis cigarette

containing 19mg of THC. The authors found that cannabis significantly increased the number and size of

aileron changes, size of elevator changes, degree of lateral and vertical deviation, and off-center distance

on approach to landing. Despite these impairments, subjects reported no awareness of diminished flying

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abilities386. Likewise, a later study also found evidence for 24-hour carry-over effects with 20mg of THC

compared to placebo on a flight-simulator piloting task. While most pilots demonstrated some degree of

deficit, only one noted any awareness of impaired performance. However, no difference in flight

simulator performance was observed 48 hours after smoking compared to placebo387. In contrast, the

same group of authors assessed flight simulator performance on a calm and a turbulent flight and reported

conflicting results. Subjects smoked a cannabis cigarette containing 0, 10, or 20mg of THC and flew on

the simulator 1, 4, 8, 24, and 48 hours following consumption. While cannabis impaired performance on

the turbulent flight 1 and 4 hours after smoking, it did not affect flying abilities at 24 and 48 hours post-

exposure. Based on their findings, the authors concluded that recreational cannabis use does not

necessarily impact performance on operating a complex machine such as an airplane. However, if other

negative factors such as bad weather or flight-related difficulties are added, then performance may

become significantly impaired388.

The inconsistent findings across these studies could be attributed to methodological deficiencies, such as

small sample size, lack of blindness, failure to control for wash-out period or use of alcohol and other

drugs, varying cannabis dose administered, and lack of sensitive data collecting tools (e.g. high-fidelity

driving simulator)236. Despite these mixed results, they were considered sufficiently strong to urge

recommendations for restrictions on pilots389. Conversely, the implication of these effects on driving and

roadway safety have received little attention. The present study will serve to clarify the residual impact of

cannabis use on driving behaviour and collision risks, and contribute significantly to the current body of

literature on DUIC research.

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2 Methods

2.1 Overall Study Design

The current study aims to examine acute and residual effects of smoked cannabis on the performance of

driving-related skills in young drivers. It is a double-blind, placebo-controlled, mixed design trial. The

study consisted of 5 sessions, which include an eligibility assessment (Session 1), a practice day (Session

2), and three testing days (Session 3-5). Session 1 could be conducted at any time but the remaining four

sessions must be completed on consecutive days. A single active or placebo cannabis cigarette containing

12.5 2% or 0.010 0.006% THC was administered in Session 3.

The study consisted of a single-blinded pilot phase and a double-blinded randomization phase. During the

initial pilot phase, the first five participants enrolled would be assigned to smoke active cannabis. The

pilot phase was helpful to determine if any study procedures would need to be amended or improved for

practical or logistical considerations. Following the pilot phase, participants subsequently enrolled were

randomized according to a 2-to-1 active to placebo randomization ratio.

During the study, participants were asked to operate a high fidelity driving simulator, from which driving

measures were recorded. Measures of cognitive ability, psychomotor functioning, and subjective drug

effects are assessed using a battery of computer-based tests. Biological samples and vital signs were

collected to establish a pharmacokinetic and pharmacodynamic relationship following cannabis

administration and to confirm ongoing eligibility criteria. Figure 5 illustrates the study timeline. Study

procedures and outcome measures are described in greater details under sections 2.4 and 2.5. Although

the larger study explores both the acute and residual effects of cannabis on driving-related performance,

the current analysis will only focus on the residual effects.

39

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40

2.2 Participant Selection

Participants were selected based on the following inclusion and exclusion criteria. Participants were

withdrawn from the study if any ongoing exclusion criteria were met.

Inclusion criteria:

19 to 25 years of age

Self-reported regular use of cannabis, between 1 to 4 days per week. Recent use was confirmed

by a positive urine immunoassay result for cannabinoids

Held a valid class G2, for at least 12 months, or class G driver’s license (or equivalents from

other provinces or country)

Willing to abstain from cannabis use 48 hours prior to Session 2 and during the remaining

sessions until study completion

Able to provide a written and informed consent

Used an approved form of birth control for the duration of the study (abstinence, hormonal

contraceptives, barrier devices, or surgical interventions) – women only

Exclusion criteria:

Self-reported regular use of psychoactive medications (e.g. antidepressants, benzodiazepines,

stimulants)

Diagnosed with a severe medical or psychiatric condition during Session 1

Met criteria for any current or lifetime DSM-IV Substance Use Disorders, except nicotine.

Has a first-degree relative diagnosed with schizophrenia

Is pregnant, trying to become pregnant, or breastfeeding upon study entry – women only

Ongoing exclusion criteria:

A positive alcohol breathalyzer result on any study day

A positive urine toxicology result indicating use of a psychoactive substance other than cannabis

during Sessions 2 to 5

Additional use of cannabis during Sessions 2-5

Alcohol breathalyzer test, urine point-of-care toxicology drug screen, urine point-of-care pregnancy test,

and urine immunoassay were used to monitor participant compliance. Abstinence from additional

41

cannabis use was assessed secondarily by quantifying blood cannabinoid concentration after study

completion. Data from participants whose results indicated additional use of cannabis are excluded from

analyses.

2.3 Study Recruitment

The study was advertised through several sources on the Internet and in print. Online advertisements were

placed and updated twice per week on Kijiji, Craigslist, and Toronto’s Backpage. Information on the

study were also available publicly on the CAMH recruitment website and the Clinicaltrial.gov registry.

Print advertisements were posted in the NOW Magazine and across the University of Toronto St. George

campus. To further increase recruitment, additional posters were placed on the Toronto Transit

Commission (TTC) subway trains (see Appendix A). Potential participants interested in the study were

directed to call the study telephone line found on the advertisements for a brief telephone screen (see

Section 2.4.1).

2.4 Study Procedures

2.4.1 Telephone Screening (Pre-screen)

Potential participants were contacted initially via telephone. Study personnel provided a brief description

of the study and any additional information requested. Once participants confirmed their interest to

participate, study personnel conducted a preliminary telephone screen to assess their eligibility (see

Appendix B). If participants were eligible based on the telephone screen, they were invited to attend an

in-person eligibility assessment. In addition, study personnel emailed participants an information sheet,

which includes a more detailed description of the study and any instructions provided over the telephone

(see Appendix C).

2.4.2 Eligibility Assessment (Session 1)

Participants were asked to sign an informed consent and had to demonstrate comprehension of study

procedures, risks, and requirements. A signed informed consent must be obtained before conducting any

study activities (see Appendix D). Abstinence from alcohol consumption was tested using an alcohol

42

breathalyzer. An urine sample was collected and a point-of-care toxicology drug screen was performed to

verify recent cannabis use. The urine sample was also sent to the CAMH Clinical Laboratory to confirm

toxicology drug screen results by urine immunoassay. For female participants, pregnancy was tested

based on the urine hcG level using a point-of-care pregnancy strip. Blood samples were collected for

biochemistry and haematology analyses by the CAMH Clinical Laboratory. A blood sample for genetic

testing was collected under a separate consent. Subsequently, participants underwent a physical

examination, in which a medical doctor obtained their vital signs, physiological measurements, and

information on their current and past drug use, medical conditions, and psychiatric symptoms. Lastly, the

Structured Clinical Interview for DSM-IV Axis Disorders (SCID) was administered by qualified

personnel to diagnose any psychiatric conditions and Substance Use Disorders. (Participants are paid up

to $25 in compensation at the end of Session 1 and up to $175 at the end of the study upon completion of

all study sessions. All screening results were reviewed by the qualified investigator and participants were

notified of their eligibility.

2.4.3 Practice Day (Session 2)

Once participants were scheduled to attend Sessions 2-5, they were asked to abstain from using cannabis

and any drug not for medical purposes 48 hours before Session 2 and for the duration of the study. If

participants were prescribed medications that are contraindicated with the study (e.g. Tylenol 3®) for

treatment of an illness, they were rescheduled. Breath and urine samples were collected to verify ongoing

eligibility using the alcohol breathalyzer and point-of-care urine toxicology screen, respectively. The

urine sample was then sent to the CAMH Clinical Laboratory for toxicology immunoassay confirmation.

For female participants, pregnancy was checked using the point-of-care pregnancy strip. Participants with

a positive result in alcohol breath test, urine toxicology screen, or pregnancy test were excluded or

rescheduled. Subsequently, participants performed a series of computer-based tests. These included tests

that measure cognitive and psychomotor functions: HVLT-R, DSST, CPT, and grooved pegboard as well

as tests that measure subjective drug effects: ARCI, POMS, and VAS. Next, participants completed the

driving behaviour self-report questionnaire followed by the Shipley-2 test. Lastly, participants practiced

on the driving simulator by performing two 10-minute simulation scenarios with no cars or obstacles on

the road. The first trial was driving under full attention. The second trial involved driving under a dual-

task condition, where participants were asked to drive and count simultaneously. Session 2 provides an

opportunity for participants to familiarize with the study procedures, driving simulator, and computer

tests, which is necessary to achieve stabilization of performance before drug administration.

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2.4.4 Drug Administration Day (Session 3)

Breath and urine samples were collected to validate ongoing eligibility. Participants with a positive result

in the alcohol breathalyzer test or urine toxicology screen were terminated from the study. Baseline

measures of cognitive functioning (HVLT-R, DSST, CPT, and grooved pegboard) and subjective drug

effects (ARCI, POMS, VAS) were collected 30 minutes before drug administration. Participants then

performed two additional practice scenarios followed by two 10-minute driving trials. Simulator trials

alternate from driving under the full attention and under the dual-task condition. Following the simulation

driving at baseline, participants rated their driving ability on a self-report questionnaire for this particular

driving session. Subsequently, participants were asked to smoke a single cannabis cigarette in the

Biobehavioural Addictions and Concurrent Disorders Research Laboratory (BACDRL). The cigarette

contained either 12.5% or <0.1% THC. Participants were instructed to smoke ad lib, for a maximum of 10

minutes or at any time if they were feeling ill. 30 minutes after smoking, simulated driving skills were

measured through two 10-minute trials (full attention and dual task conditions) followed by a self-report

questionnaire on their driving performance. Cognitive and subjective drug effects were assessed 1 hour

after smoking. Sequential blood samples were collected using an intravenous catheter at baseline and 9

times following drug administration (5, 15, 30 minutes, 1 hour and hourly thereafter until 6 hours after

smoking). Vital signs and VAS were measured concurrently with each blood draw. At the end of Session

3, to ensure their safety, participants were sent home in a taxi and were asked refrain from driving a motor

vehicle until the end of the study.

2.4.5 24 and 48 hour Post Drug Administration (Session 4 and 5)

The procedures were identical for sessions 24 and 48 hours post-dose. Breath and urine samples were

collected to verify ongoing eligibility. Participants with a positive result in the alcohol breathalyzer test or

urine toxicology screen were terminated from the study. Vital signs were taken concurrently with blood

samples, which were used to quantify cannabinoid levels. A series of computer tests measuring cognitive

functions (HVLT-R, DSST, CPT, and grooved pegboard) and subjective drug effects (ARCI, POMS, and

VAS) were administered. Lastly, participants completed two 10-miunte simulated driving trials, the first

under full attention and the second under the dual-task condition.

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2.4.6 Follow-up

Ongoing adverse events were followed-up until the end date of the event or until follow-up was no longer

deemed necessary by the qualified investigator. From study recruitment to follow-up, study personnel was

responsible for assessing the participants, ensuring their safety and welfare, collecting trial data, and

monitoring the study progress.

2.5 Outcome Measures

2.5.1 Simulated Driving Measures (Primary Outcomes)

Driving performance was assessed by pre-programmed driving scenarios in the Virage VS500M Driving

Simulator. Driving trials were conducted at baseline (30 minutes before smoking), and at 30 minutes, 24

hours, and 48 hours after smoking. Each driving trial consisted of two driving scenarios, which were

approximately 7 minutes in length. In the first scenario, known as the single-task condition, participants

were instructed to drive as they would normally under full attention. In the second scenario, also known

as the dual-task condition, participants were asked to complete a distraction task where they had to count

backwards by threes from a randomly selected number between 700 and 999. The number was provided

to participants by a study personnel before the scenarios began and participants were allowed to count at

their own pace as long as they counted continuously throughout the scenario. Audio recordings were

obtained during the dual-task driving condition.

Driving scenarios were situated in a rural setting on a one-lane highway with a speed limit of 80km/hr. In

each scenario, four categories of driving measures were collected:

1. Overall driving performance across the entire scenario including the overall mean speed, overall

standard deviation of lateral position (SDLP), and total number of collisions

2. Straightaway hazard: a section of road with no traffic. The mean speed, standard deviation of

mean speed, and SDLP during this section were assessed.

3. Slow-moving vehicle hazard: a vehicle moving at half the speed limit. The following distance

behind the slow vehicle was measured

4. Risk-taking hazard: a stationary obstacle blocking half of the lane while an oncoming car

approaches on the opposite lane, leaving just enough space in between to pass. The braking

distance to the risky stimulus was measured.

45

Hazards appeared in a slightly different form and order within each scenario to mitigate practice effects

over repeated testing.

In addition, practice driving trials were conducted on Practice Day (Session 2) and prior to baseline

driving trials on Drug Administration Day (Session 3). They allowed the participants to become

accustomed to the driving simulator and to reduce potential confounds from poor driving performance

due to lack of familiarity with the simulator or participant variability in driving improvements over time.

Practice trials also occurred in a rural setting on a one-lane highway and consisted of two scenarios, the

first being a single task condition and the second as a dual-task condition. However, practice scenarios did

not contain other vehicles or obstacles.

2.5.2 Cognitive and Psychomotor Measures

2.5.2.1 Digit Symbol Substitution Test (DSST)

The computer-automated Digit Symbol Substitution Test is used to assess associative ability, information

processing speed, and overall cognitive functioning. On the test screen, participants are presented with a

digit code panel containing numbers one to nine, each associated with a different block pattern. Below the

panel, a larger number would appear and participants were asked to reproduce the pattern in an empty 3 x

3 grid by referring to the panel. The test is 90 seconds in length and participants were instructed to

complete as many correct pattern as possible. The number of total trials completed, correct trials, and

mean reaction time were recorded.

2.5.2.2 Hopkin’s Verbal Learning Test-Revised Version (HVLT-R)

The Revised Hopkin’s Verbal Learning Test measures verbal learning and memory. Participants were

read, at two second intervals, a list of 12 words that are categorized into three semantic groups. After

reading the last word, participants were asked to immediately recall as many words as possible in any

order. This is repeated two more times with the same list of words. Subsequently, following a 23 minutes

delay, participants were asked to recall as many words as possible without having them read again.

Following this final trial, participants were read another list of 24 words, which included the 12 target

words on the original list and 12 non-target words (6 of which were semantically related to the target

word categories and 6 were unrelated). For each word in this recognition task, participants were asked to

respond yes or no to distinguish between words on the original list and words not previously presented.

46

The HVLT-R is approximately 30 minutes in length and 5 alternate forms were used the study, each

containing a different set of words. Measures collected include total recall (total number of words recalled

in the first 3 trials), percent retained (amount of words recalled in the final trial), and discrimination index

(a recognition score calculated based on the number of true-positives minus true-negatives in the

recognition task).

2.5.2.3 Connor’s Continuous Performance Test II (CPT-X)

The Connor’s Continuous Performance Test II is an assessment of vigilance, sustained attention, and

impulsivity. During the test, white letters flashed up at varying speeds in the middle of a black screen and

participants were asked to press the space bar as fast as possible after every letter except if the letter was

an X. Measures including percentage of omission errors and commission errors, hit rate, hit rate

variability, and detectability were analyzed. Errors of omission occurs when the participant failed to

respond to a target stimulus (any letter but X) while errors of commission occurs when the participant

responded to a non-target stimulus (letter X). Detectability is the ability to distinguish between a target

and non-target stimulus, where a higher detectability represents better target discrimination.

2.5.2.4 Grooved Pegboard Task (Lafayette Model 32025)

The Grooved Pegboard Task is a dexterity test used to measure complex hand-eye coordination and motor

control. The instrument contained a board with 25 randomly oriented grooves and pegs with protrusions

along one side. When placing a peg into a groove, it must be rotated to match the orientation of the

groove. Participants were asked to start the task with their dominant hand and insert the pegs one at a time

as fast as possible until all grooves have been filled. The same is repeated with the non-dominant hand.

Time used to complete the task for both hands was recorded.

2.5.2.5 Shipley-2 IQ Test

The Shipley-2 is a short and robust test that evaluates overall cognitive functioning and impairment. It

consists of a Vocabulary scale that measures crystalized ability obtained from education and experience

and an Abstraction scale that examines cognitive fluidity or the capacity to apply logic and adapt to new

information. The Vocabulary scale contains 40 questions, each with a given word and a list of four

answer choices. Participants were required to select one word from the list that has the closest meaning to

the given word. The Abstraction scale contains 25 sequence questions and the participants are asked to

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deduce the pattern and complete the missing value in each sequence. These tests were only administered

once on Practice Day (Session 2) and must be completed in 10 minutes and 12 minutes, respectively.

When scoring the tests, 1 point was given to each correct answer and 0 to each incorrect or missing

answer. The raw score was then translated into a standardized score that reflected overall cognitive ability

and impairment.

2.5.3 Subjective Drug Effects/Pharmacodynamics Measures

2.5.3.1 Visual Analogue Scales (VAS)

The Visual Analogue Scales are self-report questionnaires used to measure subjective drug effects,

specifically cannabis effects in this study. Participants were provided seven statements on the computer,

each associated with a horizontal scale ranging from 0 to 100 and were asked to rate their subjective

feelings towards each statement at the time of the test. These statements include 1.) “I feel a drug effect”;

2.) “I feel this high”; 3.) “I feel the drug’s good effects”; 4.) “I feel the drug’s bad effects”; 5.) “I like the

drug”; 6.) “I feel a rush”; and 7.) “It feels like cannabis”. They correspond to measures of drug effect,

high, good effects, bad effects, drug liking, rush, and feels like cannabis, respectively. Through assessing

subjective experiences over a continuous spectrum, the VAS can pick-up smaller changes and produce

more sensitive measurements of subjective drug effects compared to tests that use categorical ratings.

2.5.3.2 Addiction Center Research Inventory (ARCI) 49-Item Form

The Addiction Center Research Inventory is a self-report questionnaire designed to evaluate subjective

effects of psychoactive substances and to differentiate the effects between different classes of drugs. In

the test, participants were presented with a list of statements describing effects commonly experienced by

individuals under the influence of a psychoactive drug and were asked to answer true or false to each

statement based on how they were feeling at the time of the test. The responses were then coded under

seven subscales that reflect different drug categories or drug effects. The full version of the ARCI that

was first developed in the 1960s contained 550 statements/items. In this study, the short and modified

version of the ARCI that contains 49-items and additional subscales was used. The five original subscales

include 1.) Pentobarbital-Chloropromazine-Alcohol Group (PCAG); 2.) Morphine-Benzedrine Group

(MBG); 3.) Benzedrine Group (BG); 4.) Amphetamine (AMPH); and 5.) Lysergic Acid Diethylamide

(LSD). The modification of the ARCI implemented by John Hopkins School of Medicine incorporated

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two additional subscales: 6.) Euphoria and 7.) Sedation. The test required approximately five minutes to

complete.

2.5.3.3 Profile of Mood States (POMS)

The Profile of Mood States is another self-report questionnaire and it is used to determine fluctuations in

mood. The test contains a list of 72 adjectives associated with various moods and participants were asked

to rate how each adjective best describes their mood at the time of the test. The rating is based on a 5-

point Likert scale, where 0 is “Not at all”, 1 is “A little”, 2 is “Moderately”, 3 is “ quite a lot” and 4 is

“extremely”. The responses were then coded under 10 subscales that reflect different mood states,

including 1.) Tension and Anxiety; 2.) Anger and Hostility; 3.) Depression/Dejection; 4.) Friendliness; 5.)

Fatigue; 6.) Confusion; 7.) Vigor; 8.) Elation; 9.) Arousal, 10.) Positive Mood. Of these, scores for

subscales Arousal and Positive Mood are derived measures. They are calculated from the sum of

Confusion and Fatigue subtracted by the sum of Tension/Anxiety and Vigor and from the difference of

Depression/Dejection and Elation scores, respectively.

2.5.4 Behavioural Measures

2.5.4.1 Driving Behaviour Self-Report Questionnaire (SRQ)

The Driving Behaviour Self-Report Questionnaire is a computer-based questionnaire package designed to

assess demographic information, driver behaviour, and individual difference constructs that may be used

as covariates in additional analyses. The package is composed of several small questionnaires, including

1.) the Driver Behaviour Questionnaire that examines driving errors, lapses, and violations, 2.) the

Driving Vengeance Questionnaire and the Road Rage Victimization and Perpetration Questionnaire that

assess driver aggression and retaliation towards several common driving scenarios, 3.) the Risk Taking

Behaviour in Traffic Questionnaire that measures risky driving behaviours, 4.) the General Health

Questionnaire (GHQ-12) that assesses overall health status, particularly psychiatric distress such as

depression, anxiety, or social functioning issues, 5.) the Brief Sensation Seeking Scale and the

Impulsivity Questionnaire, and the Delayed Discounting Task that examine impulsive and reward-seeking

behaviour. The SRQ was only administered once on Practice Day and required approximately 20 minutes

to complete.

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2.5.5 Physiological Measures

2.5.5.1 Breath Alcohol Concentration (BAC)

At the start of each session, a breath test for alcohol was conducted to verify the absence of alcohol,

which is known to have impairing effects on driving and cognitive functioning. Participants were asked to

provide a 5 second moderate and continuous breath sample into the breathalyzer. Those with a BAC

above zero percent, suggesting that they were under influence of alcohol, were terminated from the study

or rescheduled. The AlertTM J4X and the AlertTM J5 Portable Breath Alcohol Tester, produced by Alcohol

Countermeasures System Inc., Toronto, were used in the study. The breathalyzers were calibrated by the

CAMH Clinical Laboratory on an annual basis.

2.5.5.2 Urine Toxicology Screening and Pregnancy Testing

An urine sample was collected at each session for toxicology screening to determine ongoing eligibility.

The initial screening was conducted by study personnel using a point-of-care drug cup. The point-of-care

testing screened for 12 categories of drugs including: THC, amphetamine, cocaine, LSD, PCP, opioid,

methamphetamine, barbiturates, benzodiazepines, ecstasy, methadone and oxycodone. Subsequently,

results were confirmed through an urine immunoassay conducted by the CAMH Clinical Laboratory. The

confirmatory results from the Clinical Laboratory were used to make the final decision on continuing

eligibility.

For the eligibility assessment, a positive urine screening for THC indicated recent cannabis use and

fulfilled an inclusion criterion. Participants with a negative THC result were asked to return on a different

day to provide a second, or possibly a third, urine sample. If participants were negative for THC

following three separate urine toxicology screenings, they were excluded from the study. During Sessions

2 to 5, participants who were tested positive for any drug other than THC were terminated from the study.

In addition, pregnancy tests were conducted for female participants during the eligibility assessment and

Session 2 using the point-of-care pregnancy strip. Those with a positive pregnancy test were disqualified.

50

2.5.5.3 Vital Sign Measures

Vital signs were recorded to monitor the status of the body’s vital functions and their fluctuations

following cannabis administration. Measures collected include heart rate, systolic and diastolic blood

pressure, respiratory rate, and tympanic temperature. Vital signs were obtained as part of the medical

assessment during the eligibility screening, once in Session 2, ten times in Session 3 (at 30 minutes before

smoking, 5, 15, 30 minutes and hourly thereafter for 6 hours after smoking), and once in Sessions 4 and 5.

2.5.6 Laboratory Assays

2.5.6.1 Whole Blood Concentrations of THC, 11-OH-THC, and THC-COOH

Quantification analyses of THC, 11-OH-THC, and THC-COOH were performed in whole blood to

evaluate their pharmacokinetic profiles and to predict a PK/PD model. Blood samples were collected by a

nurse at baseline (30 minutes before smoking), at 5, 15, 30 minutes and hourly thereafter until 6 hours

after smoking, and at 24 hours and 48 hours post-dose. Samples collected were immediately frozen on

dry-ice, then stored in plastic cyrotubes at -20°C, and sent to the CAMH Clinical Laboratory for analyses

every month. Samples were purified via solid-phase extraction and analyzed by gas-chromatography

mass-spectrometry (GC-MS).

2.5.6.2 Urine Levels of THC, 11-OH-THC, and THC-COOH

In addition to the urine toxicology screening and pregnancy testing, the urine samples collected from

Session 3 to Session 5 were further analyzed by the CAMH Clinical Laboratory for secondary exclusion.

Levels of THC, its metabolites, and creatinine were quantified and the THC-COOH-to-creatinine ratios

were used to determine any additional cannabis use during the study.

It is expected that only participants who received active cannabis will have an increase in the THC-

COOH/creatinine ratio 6 hours after drug administration and the ratio should decrease over the next two

sessions. Participants who received the placebo cannabis should have a continuous decrease in the THC-

COOH/creatinine ratio over the study sessions. Data from participants that revealed additional cannabis

use during the study were secondarily excluded from the analysis.

51

2.5.7 Assessments of Eligibility

2.5.7.1 Physical Examination and Laboratory Tests

A physical examination was conducted, as part of the eligibility assessment, by a qualified physician to

evaluate the participant’s general physical health. Information on medical and drug use history, vital

signs, and other measures such as weight and height were collected and only used to determine eligibility

status.

In conjunction, blood samples were collected for biochemistry and haematology analyses, including

Complete Blood Count (CBC), Basic Metabolic Panel (glucose, sodium, potassium, blood urea nitrogen,

creatinine), and Liver Function Tests (alanine aminotransferase, aspartate transaminase, and gamma

glutamyl transpeptidase). Samples were collected and analyzed by the CAMH Clinical Laboratory.

Participants with any serious medical conditions or medical issues that may predispose them to risks in

the study were excluded.

2.5.7.2 Structured Clinical Interview for DSM-IV Axis I Disorder (SCID-I)

The Structured Clinical Interview for DSM-IV was conducted, as part of the eligibility assessment, to

evaluate the participant’s psychiatric conditions and drug use history. Results from the interview were

solely used to determine inclusion or exclusion status. Participants diagnosed with any current DSM-IV

Axis I Disorder, current or past drug dependence, or psychiatric conditions that may predispose them to

risks in the study were excluded.

2.6 Investigational Products (IP)

2.6.1 IP Suppliers

Active cannabis, comprised of mature flowering heads of female Cannabis sativa L. ssp. Indica, was

cultivated and supplied by Prairie Plant Systems Incorporated in Saskatoon, Saskatchewan. Under strict

standards and controls of Health Canada, the active cannabis contained a THC level of 12.5 2% and a

moisture content around 14%.

52

Placebo cannabis, comprised of Mississippi-grown Mexican cannabis, was prepared and supplied by the

National Institute on Drug Abuse (NIDA) in Bethesda, Maryland, USA. After processing by ethanol

extraction, the placebo cannabis contained a THC content of 0.010 0.006% and a moisture level of 12.2

0.11%.

2.6.2 IP Preparation and Accountability

According to the World Health Organization, a typical cannabis joint contains 0.5-1.0 g (average 750mg)

of plant material and varying THC concentrations of 7.5-225 mg (1-30%). In this study, an average size

cigarette containing 750mg of cannabis plant material was used. Therefore, at 12.5% 2%, the active

cannabis contained approximately 79-109 mg of THC, representing a moderate dose. The placebo

cannabis produced a dosage less than 0.75mg of THC.

All cannabis plant materials were prepared and dispensed by designated personnel at the CAMH

Pharmacy. Active cannabis was received as loose leaf plants while placebo cannabis was received as pre-

packaged cigarettes that had to be dissembled and repackaged. Rolled cigarettes containing 750 mg of

active or placebo cannabis were made to be visually indistinguishable from each other and were stored at

-20°C in a secure freezer. The cigarettes were re-humidified for at least 12 hours to raise the moisture

content prior to use.

2.6.3 IP Administration

During the study, a single cigarette of active or placebo cannabis was administered in Session 3. Smoking

occurred in the CAMH Bio-behavioural Addictions and Concurrent Disorder Research Laboratory

(BACDRL), a specialized smoking room with reverse airflow and external ventilation. Participants were

instructed to smoke as they usually would (ad libitum) for a maximum of 10 minutes and were told to

stop smoking if they have reached a high equivalent to the level that they normally experience or if they

were feeling ill. Any cigarette remnants were returned to the CAMH Pharmacy. The cigarette was

weighed before and after smoking to estimate the amount of THC consumed. The start and end time of

smoking were also recorded to calculate the duration of drug administration.

53

2.7 Sample Size

Due to relatively limited research available, the effect size for residual effects of cannabis on simulated

driving performance is difficult to estimate. In addition, the unique between-and within-subject design of

this study differs from most previous studies, which examined drug effects on driving abilities using

primarily within-subjects designs. Based on a medium effect size of 0.5 (Cohen’s terminology, d=0.5),

the sample size required to achieve a power of 0.8 in detecting a residual effect of cannabis was estimated

to be 114. Moreover, a 2:1 allocation ratio of active to placebo cannabis was used in this study in order to

maximize scientific yield and fulfill auxiliary aims such as future genetic testing. As a result, 76

participants would receive active cannabis and 38 would receive placebo. Anticipating an estimated

attrition rate of 25%, due to incomplete or secondarily excluded data, the study aims to recruit a total of

142 participants. This sample size is the largest among studies that examine the residual effects of

cannabis and their impact on simulated driving performance.

2.8 Driving Simulator

The Virage Simulation VS500M Car Driving Simulator System, manufactured by Virage Simulation Inc.,

replicates a General Motors compact car with automatic transmission. It consists of an open cabin with a

driver’s seat and center control console. The console includes a steering wheel, horn, acceleration pedal,

brake pedal, ignition key, left and right signals, gear shifter, hand brake, instrument panel cluster, warning

light cluster, and seatbelt.

The simulator is programmed with dynamic feedback to create an immersive and realistic driving

experience. The simulator cabin is installed on a compact three-axis motion platform with electric motors,

electronic controller, and amplifier. The platform provides motion and vibration feedbacks as a function

of the speed and acceleration, engine vibrations, and road surface textures. The steering wheel is

connected to an electrical DC motor with an amplifier and a control board. This generates force feedback

such as resistance when making a turn or special vibration effects from different road surfaces like gravel

shoulder, pot holes, or sidewalks. Moreover, the acceleration and brake pedals are spring-loaded to

simulate a more realistic sensation.

The visual display is comprised of three 52-inch LCD screens and provides a high definition 180°

forward visual view. Two smaller 19-inch side monitors are placed behind the driver’s seat as the left and

54

right blind spots. The rear view and side view mirrors are incorporated into the three front screens for

additional visual feedback.

The sound system produces 5.1 surround sound to generate auditory cues corresponding to engine noise,

acceleration, deceleration, road conditions. Sounds of passing vehicles, including simulation of the

Doppler Effect, provide additional realism to the driving scenarios.

Furthermore, the instrument panel and warning light clusters display realistic values and respond

accordingly to the virtual driving environment (e.g. speed, revolutions per minute, engine temperature,

etc.).

Preventive maintenance and system update on the driving simulator is conducted once a year by Virage

Simulation technicians.

2.9 Ethics

The study was approved by the CAMH and Health Canada Research Ethics Boards (REB). A Clinical

Trial Application was submitted to Health Canada and a No Objection Letter was obtained in 2012. An

exemption under section 56 of the Controlled Drugs and Substances Act for scientific purposes was also

granted. Moreover, the study was registered on clinicaltrials.gov under the NCT number 01592409.

Ethical implications on conducting cannabis research in young drivers have been comprehensively

reviewed and safety measures were designed to minimize risks to participants. Participant’s identity and

personal information (e.g. cannabis use and medical history) were kept confidential. In order to avoid

drug exposure to cannabis-naive subjects, a positive THC urine toxicology screen had to be obtained prior

to enrollment. Research suggests that cannabis use is linked to precipitation of psychotic episodes in

predisposed individuals; hence, anyone with a family history of schizophrenia was excluded. Those with a

history of substance dependence, except nicotine dependence, were also excluded. Moreover, compared

to on-road testing, studying driving behaviour using a simulator reduces the risk of real dangers in traffic.

Participants were also instructed to refrain from driving a motor vehicle until participation is complete.

Taxi chits and public transit tokens were provided by the study as alternate modes of transportation.

Lastly, participants were monitored for any adverse effects during the study and necessary medical

follow-up was provided. Adverse events and serious adverse events were reported to the CAMH and

Health Canada REB where appropriate.

55

Furthermore, to minimize experimenter bias, the study adopted a double-blind design. During the pilot

phase, study personnel were un-blinded to the condition but participants were still informed that there

would be a 2-to-1 chance of receiving active or placebo cannabis. The CAMH Research Pharmacy

maintained the randomization codes, which are enclosed in secure envelopes. In the instance of a medical

emergency, the Qualified Investigator would decide whether un-blinding would be necessary to ensure

the appropriate medical care. For the purpose of this interim analysis, approval to unblind was obtained

from the Health Canada REB and CAMH REB after 55 participants completed the study. .

2.10 Interim analysis

Interim analyses is an effective tool used in monitoring the accumulated data in a clinical trial and in

protecting the welfare of study participants. Results of the analysis can be used to assess whether early

closure of the study would be warranted. If a statistically significant difference is observed between the

control and treatment groups with a sample size smaller than the target sample, enrollment of new

participants should be stopped to minimize exposure of the treatment and any risks of the study to

additional subjects. On the other hand, if the results of the interim analysis indicate a negligible chance of

demonstrating a treatment effect even when the target sample is achieved, premature closure may also

occur for both safety and economic considerations. In addition, interim analyses provide valuable

information on the power and effect size of the current sample, which could be useful in sample size

estimations of future studies.

2.11 Statistical Analysis

The present interim analysis is based on 51 participants who have completed all study sessions.. Data

collected 30 minutes before smoking on Session 3 are referred to as baseline. Changes in driving ability at

24 hours and 48 hours after smoking was compared to baseline between the active and placebo groups.

Demographic characteristics between the active and placebo groups were analyzed using chi-square test

of independence for categorical variables and independent samples t-test for continuous variables.

Driving measures collected under the single-task and dual-task conditions were compared using the same

statistical analyses. Overall mean speed and overall SDLP were analyzed together using repeated

measures mixed MANOVA. Similarly, mean speed, standard deviation of speed, and SDLP during the

straightaway hazard were analyzed in combination. Following distance behind a slow moving vehicle and

56

braking distance to a risk-taking hazard were compared using repeated measures mixed ANOVAs. Time

(3 levels: baseline, 24hrs, and 48hrs) was the within-subject variable and drug condition (2 levels: active

and placebo) was the between-subject variable.

Cognitive and psychomotor measures were collected from the CPT-X, HVLT-R, DSST, and the grooved

pegboard task. For the CPT-X, percent of omission and commission errors were analyzed using a 3x2x2

repeated measures mixed ANOVA. Time (3 levels: baseline, 24hrs, and 48hrs) and error type (2 levels:

omission and commission error) were within-subject variables while drug condition (2 levels: active and

placebo) was the between-subject variable. Hit rate was analyzed using repeated measures mixed

ANOVA. Variability and detectability scores were analyzed together using repeated measures mixed

MANOVA. Time (3 levels) was the within-subject factor and drug condition (2 levels) was the between-

subject factor. For the DSST, changes in completed trials and percent of correct trials between the active

and placebo group were compared using repeated measures mixed MANOVA. Mean reaction time was

analyzed using repeated measures mixed ANOVA. Similar to previous analyses, time and drug condition

were the within- and between-subject variables, respectively. Grooved pegboard performance by the

dominant and non-dominant hand were analyzed using 3x2x2 repeated measures mixed ANOVA with

time (3 levels) and hand (2 levels: dominant and non-dominant) as within-subject factors, and with drug

condition (2 levels) as the between-subject factor.

Subjective drug effects and moods measured by the VAS, ARCI, and POMS were analyzed using three-

way repeated measures ANOVA. Time (3 levels) and subscales were within-subject factors, and drug

condition (2 levels) was the between-subjects factor. There are 7 subscale levels in VAS and ARCI, and

10 subscale levels in POMS.

Changes in heart rate, body temperature, and respiration rate were analyzed using repeated measures

ANOVA. Systolic and diastolic blood pressure were analyzed together with a 3x2x2 repeated measures

mixed ANOVA. Lastly, adverse events in the active and placebo groups were compared using chi-square

test for independence.

Greenhouse-Geisser adjustments of within-subject factors were used to protect against violation of

sphericity. Post-hoc analysis were performed where ANOVA and MANOVA results were significant. A

p-value smaller than 0.05 was considered statistically significant. Since the current analysis is an

exploratory analysis, results were not adjusted for multiple comparisons.

57

3 Results

3.1 Recruitment and Enrollment

Between July 2012 and April 2015, 852 number of people have contacted to inquire about the study, of

which 590 (69.2%) were interested in participating and were pre-screened on the telephone for inclusion.

The remaining 262 were either not interested after hearing about the study details (n=113) or were

deemed lost to follow-up after multiple unsuccessful attempts to reach them (n=149). Reasons to loss of

interest are listed in Table 1. Of the 590 people who were pre-screened, 134 (22.7%) met initial eligibility

criteria and were scheduled for the eligibility assessment (Session 1). Reasons of exclusion based on the

pre-screen are listed in Table 2, with smoking cannabis too frequently as the top reason. No individuals

were excluded due to pregnancy or breastfeeding. The telephone pre-screen form can be found in

Appendix B.

Table 1. Reasons for loss of interest during the initial contact

Reasons for loss of interest Number of callers

Time commitment or work schedule conflict 42

Inadequate compensation 2

Discomfort with blood draws 1

Others (e.g. express concern or wrong study) 2

Did not specify 66

Table 2. Reasons for exclusion based on the telephone pre-screen

Exclusion criteria Number of callers

Smokes more than 4 days/week 266

Smokes less than 1 day/week 2

Does not smoke cannabis currently 11

Over the age of 25 73

Below the age of 19 1

Does not meet driver’s licensing criteria 14

Regularly uses psychoactive medication 2

Diagnosed with a psychiatric disorder 2

Has a family history of schizophrenia 3

Resides outside of geographical limits 10

Excluded for 2 or more reasons 72

Of the 134 people who passed the telephone pre-screen, 99 attended the eligibility session. Of these, 55

met all inclusion criteria and were enrolled to complete the study. In the remaining 44 participants who

were not enrolled, 26 were excluded, 8 declined to participate, and 10 were lost to follow-up. Reasons for

58

exclusion are outlined in Table 3. No participants were ineligible due to a positive alcohol test, a family

history of schizophrenia, current use of psychoactive medications, or pregnancy and breastfeeding.

Table 3. Reasons for exclusion based on the eligibility assessment.

Exclusion criteria Number of participants

Met DSM-IV criteria for lifetime substance use disorders or cannabis

dependence

12

Diagnosed with a severe medical or psychiatric condition 5

Did not demonstrate recent cannabis use (negative urine toxicology screen

for THC)

6

Disclosed more frequent use of cannabis than on the telephone screen 1

Excluded for 2 or more reasons 2

Of the 55 participants enrolled, the first five were run as pilot subjects and all received active cannabis.

Following the pilot phase, participants subsequently enrolled were randomized according to the 2-to-1

randomization ratio. Complete residual data were not collected from two participants. One participant

withdrew during Session 3 because of an emotional distress adverse event that occurred shortly after

smoking cannabis. Another participant did not complete Session 5 due to personal plans. Furthermore,

data from two participants were secondarily excluded from the analysis. One participant drank large

amounts of alcohol during the evening between Sessions 3 and 4 and reported hang-over effects the next

day. Another participant claimed to be a cannabis advocate who wanted to prove that cannabis does not

impair driving abilities. After smoking and thinking they had received the placebo cannabis, the

participant demonstrated obvious attempts to skew the data by driving dangerously on the simulator.

Therefore, the current analysis is based on 51 participants with complete residual data. A summary of the

recruitment and enrollment status presented in Figure 6.

59

Figure 6. Recruitment and enrollment flow chart

Telephone screened for eligibility

(n=590)

Assessed for eligibility

(n=134)

Competed study (n=55)

▪ Pilot (n=5)

▪ Randomized (n=50)

Interim analysis -unblinded

(n=51)

Pre-screening

Enrollment

Allocation

Analysis

Meeting inclusion criteria (n=162)

Not meeting inclusion criteria (n=444)

Lost interest, lost to follow-up (n=78)

Not enrolled (n=44)

Not meeting inclusion criteria (n=26)

Declined to participate (n=8)

Lost to follow-up (n=10)

Withdrew (n=1)

Incomplete (n=1)

Excluded from analysis (n=2)

60

3.2 Demographics

Demographics characteristics are presented in Table 4. Participants in the active and placebo groups were

similar in age, gender, body mass index (BMI), frequency of smoking, license class, IQ, and level of

education.

Table 4. Demographic characteristics

Characteristics Active

(n=37) Placebo

(n=14) p-value

Sex

Male 26 (68.4%) 8 (57.1%) 0.45

Female 12 (31.6%) 6 (42.9%)

Age 22.08 2.10 22.71 2.20 0.34

BMI (kg/m2) 24.37 4.83 24.43 4.63 0.97

Frequency of smoking,

days per week 2.55 0.94 2.61 1.10 0.86

License class

G2 or equivalent 12 (31.6%) 4 (28.6%) 0.83

G or equivalent 26 (68.4%) 10 (71.4%)

IQ 114.0 12.29 114.07 9.31 0.98

Education

Some university/college 18 (47.4%) 7 (50.0%) 0.45

Completed

university/college

16 (42.1%) 7 (50.0%)

Completed graduate

studies or higher

2 (5.3%) 0

Completed high school 2 (5.3%) 0

61

3.3 Driving Outcomes

3.3.1 Overall Mean Speed and Standard Deviation of Lateral Position

Overall mean speed and overall SDLP were measured across the driving scenarios under both the single-

task and dual-task conditions, and were analyzed using repeated measures mixed MANOVA (Table 5-6).

In the single task condition, there was a significant multivariate effect of time (V=0.35, F(4, 46)=6.22,

p<0.001). There were no significant effect of drug condition (V=0.01, F(2, 48)=0.26, p=0.77) and no

significant interaction between time and drug condition (V=0.06, F(4, 46)=0.71, p=0.59). Within-group

univariate tests indicated a significant main effect of time for overall SDLP (F(1.53, 75.12)=4.69, p=0.02)

but not for overall mean speed (F(1.66, 81.36)=1.09, p=0.33). Post hoc analysis demonstrated that SDLP

at 48 hours after smoking was significantly higher than 24 hours post-dose, irrespective of drug condition

(p<0.001) (Figure 7A-B).

Similarly, in the dual-task condition, a significant multivariate effect was observed for time (V=0.25, F(4,

46)=3.85, p=0.01) but not for drug condition (V=0.03, F(2, 48)=0.77, p=0.47) and the interaction

(V=0.03, F(4, 46)=0.35, p=0.85). Univariate analyses revealed a significant main effect of time for overall

SDLP (F(1.71, 83.90)=10.25, p<0.001) but not for overall mean speed (F(1.47, 71.81)=0.081, p=0.87).

Post hoc test showed a significant increase in SDLP 48 hours after smoking compared to baseline

(p=0.001) and to 24 hours after smoking (p<0.001), irrespective of drug condition (Figure 7C-D).

Table 5. Repeated measures mixed MANOVA of overall mean speed and SDLP under the single-task

driving condition

Descriptive statistics (Mean ± SEM)

Cannabis Placebo

Time (n=37) (n=14)

Overall mean speed Baseline 82.28 ± 1.41 81.12 ± 2.38

+24 hr 81.38 ± 1.28 80.00 ± 2.92

+48 hr 82.16 ± 1.56 79.54 ± 3.04

SDLP Baseline 0.26 ± 0.01 0.27 ± 0.01

+24 hr 0.27 ± 0.01 0.26 ± 0.01

+48 hr 0.29 ± 0.01 0.27 ± 0.01

Multivariate effects

df Error F p-value

Drug condition 2 48 0.26 0.77

Time 4 46 6.22 <0.001*

Time x Drug

condition

4 46 0.71 0.59

62

Univariate effects

df Error F p-value

Overall mean speed Drug condition 1 49 0.39 0.54

Time 1.66 81.36 1.09 0.33

Time x drug

condition

1.66 81.36 0.57 0.53

SDLP Drug condition 1 49 0.26 0.61

Time 1.53 75.12 4.69 0.02*

Time x drug

condition

1.53 75.12 1.95 0.16

Table 6. Repeated measures mixed MANOVA of overall mean speed and SDLP under the dual-task

driving condition

Descriptive statistics

Cannabis Placebo

Time (n=37) (n=14)

Overall mean speed Baseline 79.71 ± 1.23 77.79 ± 3.01

+24 hr 79.75 ± 1.50 77.49 ± 3.90

+48 hr 80.41 ± 1.54 77.21 ± 3.52

SDLP Baseline 0.28 ± 0.01 0.28 ± 0.01

+24 hr 0.27 ± 0.01 0.28 ± 0.01

+48 hr 0.30 ± 0.01 0.30 ± 0.01


df Error F p-value


Time 4 46 3.85 0.01*

Time x Drug

condition

4 46 0.35 0.85

Univariate effects

df Error F p-value

Overall mean speed Drug condition 1 49 0.80 0.38

Time 1.47 71.81 0.08 0.87

Time x drug

condition

1.47 71.81 0.15 0.80


Time 1.71 83.90 10.25 <0.001*

Time x drug

condition

1.71 83.90 0.24 0.75

63

Figure 7. Overall mean speed (km/hr) and overall SDLP (m) pre-dose compared to 24hr and 48hr post-

dose under the single-task (A-B) and dual-task (C-D) conditions. No significant difference in speed and

SDLP was observed between the cannabis and placebo conditions 24 and 48 hours after smoking under

both driving conditions. Mean SEM.

3.3.2 Collisions

Total number of collisions was analyzed using repeated measures mixed ANOVA (Table 7-8). Under

both driving conditions, no significant difference was observed for time, drug condition, and the

interaction (Figure 8).

Table 7. Repeated measures mixed ANOVA of the total number of collisions under the single-task

driving condition


Cannabis Placebo

Time (n=37) (n=37)

Baseline 0.14 ± 0.06 0.14 ± 0.10

64

+24 hr 0.14 ± 0.06 0.14 ± 0.10

+48 hr 0.14 ± 0.06 0

Main effects

df Error F p-value


Time 2 98 0.57 0.57

Time x Drug

condition

2 98 0.57 0.57

Table 8. Repeated measures mixed ANOVA of total number of collision under the dual-task driving

condition


Cannabis Placebo

Time (n=37) (n=37)

Baseline 0.08 ± 0.05 0

+24 hr 0 0

+48 hr 0.08 ± 0.05 0.07 ± 0.07

Main effects

df Error F p-value


Time 1.51 74.13 1.30 0.27

Time x Drug

condition

1.51 74.13 0.44 0.59

Figure 8. Total number of collisions pre-dose compared to 24hr and 48hr post-dose under the single-task

(A) and dual-task (B) conditions. Cannabis did not increase the number of collisions 24 and 48 hours after

smoking under both driving conditions. Mean SEM.

65

3.3.3 Straightaway Hazard: Mean Speed, Standard Deviation of Speed, and SDLP

Mean speed, standard deviation of speed, and SDLP during the straightaway hazard were analyzed using

repeated measures mixed MANOVA (Table 9-10). In the single-task condition, a significant multivariate

effect of time was found (V=0.53, F(6, 44)=8.32, p<0.001). The multivariate effects were not significant

for drug condition (V=0.05, F(3, 47)=0.88, p=0.46) and the interaction between time and condition

(V=0.142, F(6, 44)=1.218, p=0.316). Univariate analyses showed a significant main effect of time for

standard deviation of speed (F(1.46, 71.49)=4.34, p=0.03) and SDLP (F(1.73, 84.98)=27.68, p<0.001).

Post-hoc tests indicated, irrespective of the drug condition, an increase in deviation of speed 48 hours

after smoking compared to 24 hours after smoking (p<0.02). SDLP also increased at 48 hours post-dose

compared to baseline (p<0.001) and 24 hours after (p<0.001) (Figure 9A-C).

In the dual-task condition, a significant multivariate effect of time (V=0.80, F(6, 44)=28.86, p<0.001) was

observed while no effect of drug condition (V=0.01, F(3, 47)=0.22, p=0.88) and interaction (V=0.01, F(6,

44)=0.07, p=1.00) were found. Within-group univariate results demonstrated a significant main effect of

time on all three measures of the straightaway hazard. Following post-hoc analyses, mean speed increased

significantly at 48 hours after smoking compared to baseline regardless of the drug conditions (p=0.008).

Furthermore, in comparison to baseline and 48 hours post-dose, deviation of speed decreased (p<0.001

and p=0.002, respectively) while SDLP increased (p<0.001 and p<0.001, respectively) at 24 hours after

smoking (Figure 9D-F).


during the straightaway hazard under the single-task driving condition


Cannabis Placebo

Time (n=37) (n=14)

Mean speed Baseline 89.97 ± 88.34 ±

+24 hr 91.30 ± 90.21 ±

+48 hr 92.13 ± 89.90 ±

SD of speed Baseline 3.78 ± 0.26 2.89 ± 0.37

+24 hr 3.09 ± 0.18 3.12 ± 0.52

+48 hr 4.70 ± 0.51 3.42 ± 0.57

SDLP Baseline 0.17 ± 0.01 0.17 ± 0.02

+24 hr 0.17 ± 0.01 0.17 ± 0.01

+48 hr 0.22 ± 0.01 0.24 ± 0.02


df Error F p-value


66

Time 6 44 8.32 <0.001*

Time x Drug

condition

6 44 1.22 0.32

Univariate effects

df Error F p-value

Mean speed Drug condition 1 49 0.21 0.65

Time 1.72 84.30 1.99 0.15

Time x drug

condition

1.72 84.30 0.16 0.82

SD of speed Drug condition 1 49 1.96 0.17

Time 1.46 71.49 4.34 0.03*

Time x drug

condition

1.46 71.49 1.99 0.16


Time 1.73 84.98 27.68 <0.001*

Time x drug

condition

1.73 84.98 0.95 0.38


during the straightaway hazard under the dual-task driving condition


Cannabis Placebo

Time (n=37) (n=14)

Mean speed Baseline 85.75 ± 1.12 82.96 ± 2.96

+24 hr 88.28 ± 1.84 86.66 ± 4.66

+48 hr 88.50 ± 1.51 86.35 ± 4.16

SD of speed Baseline 5.25 ± 0.39 4.86 ± 0.64

+24 hr 3.98 ± 0.33 3.41 ± 0.50

+48 hr 4.994 ± 0.38 4.60 ± 0.49

SDLP Baseline 0.15 ± 0.01 0.14 ± 0.01

+24 hr 0.27 ± 0.01 0.27 ± 0.02

+48 hr 0.16 ± 0.01 0.15 ± 0.01


df Error F p-value


Time 6 44 28.86 <0.001*

Time x Drug

condition

6 44 0.07 1.00

Univariate effects

df Error F p-value

Mean speed Drug condition 1 49 0.48 0.49

Time 1.45 70.84 3.95 0.036

Time x drug

condition

1.45 70.84 0.12 0.84

67

SD of speed Drug condition 1 49 0.55 0.46

Time 1.73 84.87 10.88 <0.001*

Time x drug

condition

1.73 84.87 0.01 0.91


Time 2 98 92.38 <0.001*

Time x drug

condition

2 98 0.18 0.84

68

Figure 9. Comparison of mean speed (km/hr), standard deviation of speed, and SDLP (m) during the

straightaway hazard between active and placebo cannabis at baseline, and at 24hr and 48hr post-dose.

Measures collected under the single-task and dual-task conditions are shown on the left column and right

columns, respectively. No significant difference in driving behaviour during the straightaway hazards was

observed 24 and 48 hours following cannabis consumption under both driving conditions. Mean SEM.

69

3.3.4 Following Distance Behind a Slow Moving Vehicle

Repeated measures mixed ANOVA was used to analyze following distance behind a slow vehicle (Table

11-12). Under the single-task condition, there was no significant difference in the following distance

between the active and placebo groups (Figure 10A). Under the dual-task condition, results showed a

significant main effect of time (F(2, 98)=44.83, p=0.003) but no significant effects were observed for

drug condition and the interaction. Further post-hoc testing revealed that participants were following

further away from the slow moving vehicle 24 hours (p<0.001) and 48 hours (p=0.005) after smoking

compared to baseline; but there was no difference between the active and placebo groups (Figure 10B).


hazard under the single-task driving condition


Cannabis Placebo

Time (n=37) (n=14)

Baseline 9.97 ± 0.30 9.87 ± 0.86

+24 hr 9.71 ± 0.38 10.14 ± 0.82

+48 hr 9.54 ± 0.27 8.52 ± 0.73

Main effects

df Error F p-value


Time 2 98 2.22 0.11

Time x Drug

condition

2 98 1.13 0.33


hazard under the dual-task driving condition


Cannabis Placebo

Time (n=37) (n=14)

Baseline 8.48 ± 0.37 8.70 ± 0.82

+24 hr 10.27 ± 0.37 10.39 ± 0.92

+48 hr 9.78 ± 0.38 10.35 ± 0.42

Main effects

df Error F p-value


Time 1.47 72.10 7.55 0.003*

Time x Drug

condition

1.47 72.10 0.12 0.82

70

Figure 10. Following distance behind a slow moving vehicle pre-dose compared to 24hr and 48hr post-

dose under the single-task (A) and dual-task (B) conditions. No difference between the active and placebo

groups in slow-vehicle following distance was reported 24 and 48 hours after smoking. Mean SEM.

3.3.5 Braking Distance to a Risk Taking Hazard

Results of the repeated measures mixed ANOVA are presented in Table 13-14. In the single task

condition, there was a significant effect of time (F(2, 98)=44.83, p<0.001) and a significant interaction

effect between time and drug condition (F(2, 98)=5.41, p=0.006). No significant main effect of drug

condition was observed (F(1, 49)=0.002, p=0.97). Following post-hoc analyses, significant differences in

braking distance were found at baseline (p=0.036) and 48 hours (p=0.028) after smoking. Although the

results were significantly different at baseline, participants in the active group braked closer to the risk

taking hazard at baseline but further away at 48 hours after smoking compared to the placebo group

(Figure 11A). In contrast, no significant difference in braking distance to a risk taking hazard was

observed in the dual task condition between the two groups over time (Figure 11B).


single-task driving condition


Cannabis Placebo

Time (n=37) (n=14)

Baseline 53.97 ± 6.31 79.29 ± 9.31

+24 hr 132.19 ± 4.48 128.00 ± 6.34

+48 hr 131.74 ± 4.77 109.91 ± 9.45

Main effects

df Error F p-value


71

Time 2 98 44.83 <0.001*

Time x Drug

condition

2 98 5.41 0.006*


dual-task driving condition


Cannabis Placebo

Time (n=37) (n=14)

Baseline 124.39 ± 5.28 123.47 ± 10.68

+24 hr 124.92 ± 3.82 125.66 ± 5.91

+48 hr 132.61 ± 3.29 125.42 ± 6.40

Main effects

df Error F p-value


Time 2 98 0.46 0.64

Time x Drug

condition

2 98 0.29 0.75

Figure 11. Comparison of baking distance to a risk-taking hazard between pre-dose, and 24hr and 48hr

post-dose under the single-task (A) and dual-task (B) conditions. Under the single-task condition,

participants in the active group braked significantly closer to the risk-taking hazard at baseline but further

away 48 hours after smoking. No difference was observed under the dual-task condition. Mean SEM.

*p<0.05.

72

3.4 Cognitive Performance and Psychomotor Outcomes

3.4.1 Continuous Performance Test-X

Omission and commission errors committed during the CPT-X were analyzed using three-way repeated

measures mixed ANOVA (Table 15). There was no significant three-way interaction between time, error

type, and drug conditions (F(1.61, 78.72)=0.82, p=0.45). Similarly, no significant two-way interactions

between time and drug conditions (F(1.61, 79.01)=0.88, p=0.40). The main effect of error type was

significant (F(1, 49)=196.91, p<0.001) but time and drug conditions were not. The results indicated that

there was no significant difference in CPT-X errors between the active and placebo group at 24 hours and

48 hours after smoking (Figure 12).

Table 15. Three-way repeated measures mixed ANOVA of omission and commission errors committed

during the CPT-X test


Cannabis Placebo

Time (n=37) (n=14)

Omission error (%) Baseline 1.17 ± 0.33 0.58 ± 0.26

+24 hr 1.25 ± 0.22 0.58 ± 0.31

+48 hr 1.62 ± 0.40 0.82 ± 0.27

Commission error (%) Baseline 47.82 ± 3.75 42.81 ± 7.33

+24 hr 56.85 ± 4.32 46.54 ± 5.39

+48 hr 86.16 ± 3.97 44.45 ± 6.48

df Error F p-value

Three-way interaction

Time x Drug condition x Error Type 1.61 78.72 0.82 0.45

Two-way interactions

Time x Drug condition 1.61 79.01 0.88 0.40

Time x Error Type 1.61 78.72 2.95 0.69

Drug condition x Error Type 1 49 1.48 0.23

Main effects


Time 1.61 79.01 3.17 0.06

Error Type 1 49 196.91 <0.001*

73

Figure 12. Comparison of omission (A) and commission (B) errors in the CPT-X between pre-dose, and

24hr and 48hr post-dose. There was no significant difference in CPT-X errors between the active and

placebo group 24 and 48 hours following cannabis administration. Mean SEM.

Hit rate was analyzed alone using repeated measures mixed ANOVA and results are presented in Table

16. Cannabis did not significantly affect the hit rate in CPT-X at 24 hours and 48 hours post-dose (Figure

13).

Table 16. Repeated measures mixed ANOVA of hit rate in the CPT-X test


Cannabis Placebo

Time (n=37) (n=14)

Baseline 316.05 ± 6.63 323.09 ± 19.46

+24 hr 311.07 ± 7.83 320.60 ± 18.82

+48 hr 312.86 ± 8.21 314.78 ± 14.39

Main effects

df Error F p-value


Time 1.50 73.61 0.89 0.39

Time x Drug

condition

1.50 73.61 0.39 0.62

74

Figure 13. Hit rate in the CPT-X at baseline compared to 24hr and 48hr post-dose. No significant

difference in hit rate between the active and placebo conditions was observed 24 and 48 hours after

smoking. Mean SEM.

Lastly, hit rate variability and detectability were analyzed using repeated measures mixed MANOVA

(Table 17). No significant multivariate effect of time, drug condition, and the interaction were observed.

Results are represented in Figure 14.

Table 17. Repeated measures mixed MANOVA of variability and detectability scores in the CPT-X test


Cannabis Placebo

Time (n=37) (n=14)

Variability Baseline 5.49 ± 0.47 5.93 ± 1.36

+24 hr 6.56 ± 1.02 6.51 ± 1.71

+48 hr 7.85 ± 1.82 4.42 ± 0.65

Detectability Baseline 0.56 ± 0.07 0.75 ± 0.16

+24 hr 0.50 ± 0.07 0.67 ± 0.07

+48 hr 0.52 ± 0.07 0.64 ± 0.12


df Error F p-value


Time 4 46 0.62 0.65

Time x Drug

condition

4 46 1.06 0.39

Univariate effects

df Error F p-value

Variability Drug condition 1 49 0.34 0.56

Time 1.40 68.48 0.27 0.69

Time x drug

condition

1.40 68.48 1.75 0.19

Detectability Drug condition 1 49 2.03 0.16

Time 1.58 77.58 0.80 0.43

75

Time x drug

condition

1.58 77.58 0.18 0.78

Figure 14. Comparison of variability (A) and detectability (B) scores pre-dose, and 24hr and 48hr post-

dose between active and placebo cannabis. Cannabis did not significantly affect variability and

detectability scores 24 and 48 hours after cannabis consumption. Mean SEM.

3.4.2 Hopkin’s Verbal Learning Test-Revised

Measures of verbal learning and recall memory were analyzed together using repeated measures mixed

MANOVA. There was no significant multivariate effect for time (V=0.78, F(8, 42)=1.49, p=0.19), drug

condition (V=0.889, F(4,46)=1.29, p=0.29), and the interaction (V=.90, F(8, 42)=0.58, p=0.79). Results

are presented in Table 18 and Figure 15.

Table 18. Repeated measures mixed MANOVA of performance on the Revised Hopkin's Verbal

Learning Test


Cannabis Placebo

Time (n=37) (n=14)

Total recall Baseline 29.35 ± 0.68 31.86 ± 0.95

+24 hr 29.59 ± 0.63 31.00 ± 0.81

+48 hr 29.70 ± 0.74 32.29 ± 0.89

Learning Baseline 2.97 ± 0.25 2.93 ± 0.46

+24 hr 3.16 ± 0.24 3.00 ± 0.26

+48 hr 3.16 ± 0.29 2.71 ± 0.42

Percent retained (%) Baseline 96.36 ± 1.92 96.27 ± 2.04

+24 hr 94.97 ± 1.78 97.73 ± 1.89

+48 hr 94.51 ± 1.35 94.05 ± 2.54

76

Discrimination index Baseline 22.38 ± 0.38 23.57 ± 0.31

+24 hr 23.30 ± 0.22 23.86 ± 0.14

+48 hr 22.97 ± 0.32 23.43 ± 0.25


df Error F p-value


Time 8 42 1.49 0.19

Time x Drug

condition

8 42 0.58 0.79

Univariate effects

df Error F p-value

Total recall Drug condition 1 49 3.75 0.06

Time 2 98 1.10 0.34

Time x drug

condition

2 98 0.98 0.38

Learning Drug condition 1 49 0.48 0.49

Time 2 98 0.12 0.89

Time x drug

condition

2 98 0.21 0.81

Percent retained Drug condition 1 49 0.15 0.70

Time 2 98 0.63 0.53

Time x drug

condition

2 98 0.35 0.71

Discrimination index Drug condition 1 49 3.95 0.05

Time 2 98 1.70 0.19

Time x drug

condition

2 98 0.73 0.49

77

Figure 15. Total recall (A), learning score (B), percent retained (C), and discrimination index (D) in the

HVLT-R compared between active and placebo cannabis pre-dose, and at 24hr and 48hr post-dose. No

significant difference between the active and placebo groups was observed 24 and 48 hours after

smoking. Mean SEM.

3.4.3 Digit Symbol Substitution Test

Total number of trials completed and percent of correct trials in the DSST were analyzed using repeated

measures mixed MANOVA (Table 19). Results revealed a significant multivariate effect for time

(V=0.36, F(4, 46)=6.34, p<0.001) but not for drug condition (V=0.05, F=(2, 48)=1.23, p=0.30 ) and the

interaction (V=0.13, F(4, 46)=1.77, p=0.15). Within-subject univariate test and post-hoc analysis

demonstrated a significant increase in the total number of completed trials at 24 hours (p<0.001) and 48

hours (p=0.002) after smoking. However, there was no difference between the active and placebo groups

(Figure 16).

78

Table 19. Repeated measures mixed MANOVA of total completed trials and percent of correct trials in

the DSST test


Cannabis Placebo

Time (n=37) (n=14)

Total completed trials Baseline 30.78 ± 0.51 32.07 ± 0.84

+24 hr 32.73 ± 0.59 33.21 ± 0.96

+48 hr 33.14 ± 0.65 32.93 ± 1.38

Percent of correct trials Baseline 98. 68 ± 0.41 99.21 ± 0.35

+24 hr 98.84 ± 0.28 97.50 ± 0.75

+48 hr 98.78 ± 0.38 97.43 ± 0.89


df Error F p-value


Time 4 46 6.34 <0.001*

Time x Drug

condition

4 46 1.77 0.15

Univariate effects

df Error F p-value

Total completed trials Drug condition 1 49 0.24 0.62

Time 1.66 81.37 9.58 <0.001*

Time x drug

condition

1.66 81.37 1.62 0.21

Percent correct trials Drug condition 1 49 2.48 0.12

Time 1.94 95.10 1.81 0.17

Time x drug

condition

1.94 95.10 2.46 0.09

Figure 16. Comparison of the total number of trials completed (A) and percent of trials correct (B) in the

DSST pre-dose, and at 24hr and 48hr post-dose between active and placebo cannabis. No significant

difference in DSST performance between the active and placebo group was reported at 24 and 48 hours

after smoking. Mean SEM.

79

Repeated measures mixed ANOVA results for mean reaction time per trial during the DSST showed a

significant main effect of time (Table 20). Following post-hoc test, it was found that the mean reaction

time increased significantly at 24 hours (p<0.001) and 48 hours (p=0.009) post-dose compared to baseline

but no difference was observed between groups. Results are represented in Figure 17.

Table 20. Repeated measures mixed ANOVA of the mean reaction time during the DSST test


Cannabis Placebo

Time (n=37) (n=14)

Baseline 2348.43 ± 41.46 2277.00 ± 59.55

+24 hr 2201.60 ± 37.44 2136.86 ± 59.58

+48 hr 2177.43 ± 47.87 2227.21 ± 111.72

Main effects

df Error F p-value


Time 1.65 80.67 8.73 0.001*

Time x Drug

condition

1.65 80.67 1.79 0.18

Figure 17. Mean reaction time during the DSST pre-dose, and 24hr and 48hr post-dose compared

between active and placebo cannabis. At 24 and 48 hours following consumption, there was no significant

difference in reaction time between the active and placebo groups. Mean SEM.

3.4.4 Grooved Pegboard

Performances on the grooved pegboard task for the dominant and non-dominant hand were analyzed

using three-way repeated measures mixed ANOVA (Table 21). There was no significant three-way

interaction effect, nor a significant two-way interaction between the variables. A significant main effect of

80

hand used and time were observed. In particular, the non-dominant hand performed worse than the

dominant hand under both conditions and at all time points (p<0.001). Both hands completed the task

faster at 24 hours (p<0.001) and 48 hours (p=0.001) after smoking compared to baseline but the

difference was no significant between the active and placebo groups (Figure 18).

Table 21. Three-way repeated measures mixed ANOVA of performance time on the grooved pegboard

task


Cannabis Placebo

Time (n=37) (n=14)

Dominant hand Baseline 57418.79 ± 1017.09 56647.14 ± 1742.28

+24 hr 52423.51 ± 944.13 54492.86 ± 1437.86

+48 hr 53775.41 ± 918.42 54741.43 ± 1561.84

Non-dominant hand Baseline 61212.68 ± 1436.98 62365.71 ± 2558.64

+24 hr 89105.57 ± 1138.56 61428.57 ± 1495.57

+48 hr 57560.00 ± 1022.51 58962.86 ± 1841.50

df Error F p-value


Time x Drug condition x Hand used 2 98 0.28 0.76


Time x Drug condition 2 98 0.43 0.65

Time x Hand used 2 98 1.26 0.29

Drug condition x Hand used 1 49 1.14 0.29

Main effects


Time 2 98 12.02 <0.001*

Hand used 1 49 50.08 <0.001*

Figure 18. Time taken to complete the Groove Pegboard Task by the dominant hand (A) and the non-

dominant hand (B). Compared to placebo, cannabis did not significantly affect performance on the groove

pegboard task 24 and 48 hours after smoking. Mean SEM.

81

3.5 Pharmacodynamic Outcomes

3.5.1 Visual Analog Scales

The VAS contained 7 subscales, corresponding to the 7 statements of cannabis effects. Scores from all

subscales were analyzed using three-way repeated measures mixed ANOVA (Table 22). Results revealed

no significant three-way interaction between time, subscales, and drug condition (F(1.94, 92.97)=0.05,

p=0.95) and no significant two-way interactions. There was no significant difference in subjective

cannabis effects reported by the participants between the active and placebo groups at 24 hours and 48

hours after smoking.

Table 22. Three-way repeated measures mixed ANOVA of response on the Visual Analog Scales


Cannabis Placebo

Time (n=37) (n=14)

Drug effects Baseline 0 0

+24 hr 0.72 ± 0.60 0

+48 hr 0 0

High Baseline 0 0

+24 hr 0.33 ± 0.33 0

+48 hr 0 0

Good effects Baseline 0 0

+24 hr 0.75 ± 0.52 0

+48 hr 0 0

Bad effects Baseline 0 0

+24 hr 0.44 ± 0.31 0.29 ± 0.29

+48 hr 0 0

Drug liking Baseline 1.31 ± 1.31 0

+24 hr 3.61 ± 2.82 3.5 ± 3.5

+48 hr 4.5 ± 2.98 3.5 ± 3.5

Rush Baseline 0 0

+24 hr 0 0

+48 hr 0 0

Feels like cannabis Baseline 0 0

+24 hr 0.33 ± 0.28 0

+48 hr 0 0

df Error F p-value


Time x Drug condition x Subscales 1.937 92.97 0.05 0.95



Time x Subscales 1.78 85.32 0.03 0.96

Drug condition x Subscales 1.05 50.14 0.07 0.81

82

Main effects


Time 1.78 85.32 1.00 0.36

Subscales 1.05 50.14 3.72 0.06*

3.5.2 Addiction Research Centre Inventory

The ARCI measured subjective drug effects at the time of testing and scores were translated into 7

subscales of drug state. Three-way repeated measures mixed ANOVA were used to analyze scores from

all subscales (Table 23). No significant three-way interaction (F(3.48, 170.49)=0.96, p=0.48) was

reported. There was also no significant two-way interactions and main effects of time and drug condition.

Results are represented in Figure 19.

Table 23. Three-way repeated measures mixed ANOVA of response on the Addiction Research Centre

Inventory


Cannabis Placebo

Time (n=37) (n=14)

Amphetamine subscale Baseline 41.44 ± 4.01 38.09 ± 5.43

+24 hr 36.33 ± 3.98 26.19 ± 4.75

+48 hr 37.54 ± 4.27 32.54 ± 6.53

MBG subscale Baseline 30.57 ± 4.09 26.34 ± 5.76

+24 hr 27.70 ± 3.82 15.63 ± 4.28

+48 hr 28.21 ± 3.97 28.13 ± 6.61

LSD subscale Baseline 18.56 ± 1.42 18.88 ± 1.61

+24 hr 20.46 ± 1.62 19.90 ± 2.39

+48 hr 19.50 ± 1.46 18.37 ± 2.08

BG subscale Baseline 51.35 ± 2.89 51.10 ± 4.60

+24 hr 50.73 ± 3.22 43.96 ± 4.37

+48 hr 50.94 ± 3.24 46.70 ± 5.32

PCAG subscale Baseline 25.59 ± 2.67 22.86 ± 3.02

+24 hr 25.41 ± 2.72 30.95 ± 3.80

+48 hr 21.62 ± 2.52 22.86 ± 4.18

Euphoria subscale Baseline 20.85 ± 4.24 15.31 ± 5.70

+24 hr 20.08 ± 3.93 10.21 ± 4.35

+48 hr 18.83 ± 3.99 18.37 ± 5.88

Sedation subscale Baseline 10.56 ± 2.53 6.49 ± 3.08

+24 hr 10.07 ± 2.72 11.69 ± 3.86

+48 hr 6.63 ± 2.30 6.49 ± 3.98

df Error F p-value




83


Time x Subscales 3.48 170.49 1.95 0.11


Main effects


Time 2 98 1.20 0.30

Subscales 1.63 79.71 35.39 <0.001*

84

Figure 19. Subjective drug effects measured by the Addiction Centre Research Inventory. Scores on

seven subscales were compared between the active and placebo conditions at baseline, and at 24 and 48

hours post-dose. There was no significant difference in subjective drug effects between the active and

placebo groups 24 and 48 hours after smoking. Mean SEM.

85

3.5.3 Profile of Mood States

The POMS test examined participant’s mood states at each time point. Scores from all 10 mood subscales

were analyzed using three-way repeated measures ANOVA (Table 24). Following the Greenhouse-

Geisser correction, the analysis reported no significant three-way interaction of the three factors (F(4.54,

222.27)=1.844, p=0.11) and no significant interaction between time and condition ((F(1.60, 78.44)=1.286,

p=0.28). There was a significant interaction between time and subscales observed (F(4.53, 222.27=3.26,

p=0.009) and post-hoc analyses were performed to further dissect the results. At 24 hours after smoking,

participants felt less friendly, less vigorous, less elated, and less aroused compared to baseline. At 48

hours after smoking, participants were less tense or anxious, less friendly, and less fatigued than baseline.

Participants also felt more fatigued and less aroused at 24 hours compared to 48 hours post-dose (Table

24). However, no mood states were significantly different between the active and placebo groups (Figure

20).

Table 24. Three-way repeated measures mixed ANOVA of response on the Profile of Mood States

questionnaire


Cannabis Placebo

Time (n=37) (n=14)

Tension/Anxiety Baseline 11.79 ± 1.21 7.74 ± 0.93

+24 hr 9.38 ± 1.21 8.14 ± 1.50

+48 hr 9.01 ± 1.06 6.55 ± 1.35

Anger/Hostility Baseline 4.67 ± 1.35 1.79 ± 0.69

+24 hr 3.38 ± 1.35 1.79 ± 0.81

+48 hr 4.05 ± 1.40 2.83 ± 1.12

Depression Baseline 2.93 ± 1.00 4.40 ± 3.12

+24 hr 2.52 ± 1.02 2.74 ± 1.93

+48 hr 2.34 ± 1.29 1.19 ± 0.69

Friendliness Baseline 53.64 ± 3.45 50.00 ± 6.18

+24 hr 52.54 ± 3.65 39.96 ± 6.23

+48 hr 51.77 ± 3.68 43.08 ± 6.84

Fatigue Baseline 13.32 ± 2.05 6.89 ± 1.93

+24 hr 11.87 ± 3.09 13.27 ± 3.56

+48 hr 7.82 ± 1.75 5.10 ± 2.72

Confusion Baseline 14.19 ± 1.46 9.69 ± 2.07

+24 hr 12.26 ± 1.61 9.18 ± 2.08

+48 hr 11.97 ± 1.43 8.67 ± 1.86

Vigor Baseline 32.94 ± 3.11 31.48 ± 6.00

+24 hr 30.24 ± 3.19 19.64 ± 8.09

+48 hr 31.51 ± 3.79 27.23 ± 6.11

Elation Baseline 35.14 ± 2.55 34.23 ± 5.99

+24 hr 32.65 ± 3.26 24.70 ± 5.60

+48 hr 34.46 ± 3.66 31.84 ± 6.28

86

Arousal Baseline 50.87 ± 1.02 51.79 ± 1.72

+24 hr 50.24 ± 1.34 47.52 ± 1.71

+48 hr 51.44 ± 1.11 50.98 ± 1.77

Positive mood Baseline 79.38 ± 1.03 78.06 ± 3.24

+24 hr 78.96 ± 1.18 76.53 ± 2.29

+48 hr 79.60 ± 1.37 79.68 ± 1.92

df Error F p-value





Time x Subscales 4.54 222.27 3.26 0.009*


Main effects


Time 1.60 78.44 8.94 0.001*

Subscales 1.88 91.88 235.37 <0.001*

87

Figure 20. Mood states measured by the Profile of Mood State. Scores on 10 subscales were compared

between the active and placebo group at baseline, and at 24 and 48 hours post-dose. Following the

Greenhouse-Geisser correction, no significant difference was observed between the active and placebo

group in any mood state 24 and 48 hours following cannabis use. Mean SEM.

88

3.6 Physiological Outcomes

3.6.1 Heart Rate

Heart rate measured at before smoking and at 24 hours and 48 hours after smoking were compared

between the active and placebo groups. Repeated measures mixed ANOVA showed no significant effect

of drug condition (F(1, 49)=1.58, p=0.22) and the interaction between time and condition (F(2, 98)=2.25,

p=0.11). Results are presented in Table 25 and Figure 21.

Table 25. Repeated measures mixed ANOVA of heart rate


Cannabis Placebo

Time (n=37) (n=14)

Baseline 76.16 ± 1.59 68.71 ± 2.03

+24 hr 73.54 ± 1.71 72.14 ± 2.33

+48 hr 75.51 ± 2.10 74.29 ± 2.70

Main effects

df Error F p-value


Time 2 98 1.25 0.29

Time x Drug

condition

2 98 2.25 0.11

Figure 21. Fluctuation in heart rate pre-dose, and 24hr and 48hr post-dose compared between active and

placebo cannabis. At 24 and 48 hours after smoking, no significant difference in heart rate was observed

between the two drug conditions. Mean SEM.

89

3.6.2 Blood Pressure

Systolic blood pressure and diastolic blood pressures were analyzed together using three-way repeated

measures mixed ANOVA (Table 26). No significant three-way interaction, two-way interaction effects,

and main effect of condition were observed. Results are represented in Figures 22.

Table 26. Three-way repeated measures mixed ANOVA of blood pressures


Cannabis Placebo

Time (n=37) (n=14)

Systolic BP Baseline 118.43 ± 1.98 117.21 ± 3.54

+24 hr 117.81 ± 1.97 117.43 ± 3.17

+48 hr 119.32 ± 1.79 116.50 ± 3.00

Diastolic BP Baseline 68.76 ± 1.84 69.00 ± 2.10

+24 hr 67.27 ± 1.63 69.00 ± 1.54

+48 hr 38.22 ± 1.34 68.07 ± 2.77

df Error F p-value


Time x Drug condition x Subscales 2 98 0.05 0.95



Time x BP Type 2 98 0.10 0.91

Drug condition x BP Type 1 49 0.51 0.48

Main effects


Time 2 98 0.08 0.93

BP Type 1 49 1146.80 <0.001*

Figure 22. Changes in systolic (A) and diastolic (B) blood pressure at baseline, and at 24hr and 48hr

post-dose. There was no significant difference in blood pressure between the active and placebo groups

24 and 48 hours after smoking. Mean SEM.

90

3.6.3 Body Temperature and Respiration Rate

Repeated measures mixed ANOVA were used to separately analyze body temperature and respiration

measured before smoking and at 24 and 48 hours after smoking. There was no significant drug condition

effect, nor a significant interaction found in either analyses. Results are represented in Table 27 and

Figure 23.

Table 27. Repeated measures mixed ANOVA of body temperature and respiration rate

Descriptive statistics (Mean ± SEM)

Cannabis Placebo

Time (n=37) (n=14)

Body temperature Baseline 36.39 ± 0.07 36.30 ± 0.16

+24 hr 36.35 ± 0.06 36.36 ± 0.11

+48 hr 36.46 ± 0.06 36.33 ± 0.11

Respiration rate Baseline 16.73 ± 0.35 16.71 ± 0.62

+24 hr 16.84 ± 0.42 17.00 ± 0.69

+48 hr 16.76 ± 0.48 16.50 ± 0.67

Main effects

df Error F p-value

Body temperature Drug condition 1 49 0.38 0.54

Time 1.74 85.21 0.43 0.62

Time x drug

condition

1.74 85.21 0.81 0.43

Respiration rate Drug condition 1 49 0.003 0.96

Time 1.66 81.37 0.36 0.66

Time x drug

condition

1.66 81.37 0.18 0.79

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Figure 23. Changes in body temperature (A) and respiration rate (B) between the active and placebo

conditions at baseline, and at 24 and 48 hours post-dose. No significant difference was observed between

the two drug conditions 24 and 48 hours following cannabis consumption. Mean SEM.

3.7 Frequency of DUIC

On the self-report driving questionnaire, 29 participants (57%) included in this analysis reported DUIC at

least once in the 12 months prior to the start of their participation in the study. On average, the participant

engaged in DUIC four times within the past year. The remaining 22 participants reported to have never

driven immediately after smoking within the same time period.

3.8 Cannabis Strength

In a self-report questionnaire, participants were instructed to guess the drug condition to which they were

assigned and the strength of the cigarette smoked. 44 out of 51 (86.3%) participants correctly perceived

their drug condition. Out of the 7 participants who guessed incorrectly, 4 were in the active condition and

3 were in the placebo condition.

Of the 37 participants who received active cannabis, 29 considered the cannabis provided in the study to

have the same or somewhat similar potency as the cannabis they normally smoke. However,

approximately one fourth of the participants considered the cannabis provided to be either much weaker

(n=6) or much stronger (n=2) than the cannabis they usually consume (Figure 24).

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Figure 24. Self-report of cannabis strength by participants who received active cannabis. Majority of the

participants considered the cannabis provided in the study to have similar potency as the cannabis they

normally smoke.

3.9 Adverse Events

Of the 54 participants who completed the study, 37 participants experienced adverse events during the

study. A total of 74 adverse events were reported. 30 events were possibly, probably, or remotely related

to the investigational product or the study protocol and 44 were unrelated (Figure 25). Related adverse

events that were most frequently reported included headache, fatigue or somnolence, dizziness or light-

headedness, cardiovascular events such as tachycardia and low blood pressure, and discomfort to blood

draws (Figure 26). A chi-square test was performed and no relati-onship was observed between drug

conditions and the number of related adverse events reported (Χ2 (1, N=72)=1.55, p=0.21). Unrelated

adverse events generally occurred before drug administration, between the eligibility assessment and

practice day. No serious adverse event was reported.

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Figure 25. Reported adverse events in relation to the investigational product or study protocol.

Figure 26. Adverse events related to the investigational product or study procedures. There was no

significant difference in the number of adverse event reported between the active and placebo groups.

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4 Discussion

Recent developments in the ongoing debate on the legal status of cannabis in Canada and the United

States have renewed concerns among members of law enforcement, political groups, and the public

regarding the impact of cannabis on driving behaviour and collision risks. Such concerns have triggered

discussions on amending traffic safety laws and per se limits regarding DUIC in many jurisdictions390.

Accumulating epidemiological evidence has indicated that cannabis consumption is associated with an

increase in collision risks300,301, while laboratory studies have shown signs of impairment in essential

driving skills such as learning, memory, attention, and motor coordination after acute

intoxication15,19,20,377,391. Due to the unique pharmacokinetics of THC, the impairing effects of cannabis on

driving performance may not be limited to the time period immediately after use. However, little evidence

exists to guide estimates of how long these impairments last. It is important to understand the full scope

of driving risks associated with cannabis use before adopting new traffic policies to prevent dangers of

impaired driving. This current study is one of the few simulation studies and the first high-fidelity

driving-simulator study that investigates the residual effects of cannabis on driving behaviour after a

single dose of cannabis. While most available studies on the effects of cannabis focused on acute

intoxication, this study is the first of its kind to examine the duration of cannabis effects up to 48 hours

after use.

The target population of the study is young adult drivers between the ages of 19 to 25 because they have

the highest risks of motor vehicle collisions and are more likely to drive under the influence of cannabis

compared to other age groups26,285. Based on the self-report driving behaviour questionnaire, 57% of

participants reported having engaged in DUIC within 12 months prior to their participation, a rate that is

approximately double those reported in the past (15-39%)282,290,291,392,393,. Compared to a recent study, the

rate of DUIC reported by Bergeon and Paquette were similar but higher than that found in our study292.

This is likely due to the frequency of cannabis use in subjects recruited, where all self-admitted cannabis

users were included in their study with no restriction on the level of use. Moreover, the average number of

DUIC within a 12 months period reported in this study is lower than those found in previous studies (4 vs

8-10, respectively). This could be attributed to the difference in sample population studied, where

participants in previous studies were recruited from a wider age range of 15-39 years282,294.

To be considered eligible for our study, participants must be regular cannabis users who smoke on

average 1-4 days per week. The lower limit ensures that these individuals not only have had previous

cannabis exposure, but also have experience in cannabis use and self-dose titration. On the other hand,

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heavy chronic cannabis users have been found to display tolerance to the effects of cannabis along with

an increased risk of dependence28,275,338,340. The higher limit reduces the likelihood that participants exhibit

tolerance or withdraw effects while avoiding ethical concerns in administering cannabis to individuals at

risk of substance dependence. Given that close to half of the participants were excluded due to substance

dependence, the current criteria on frequency of use seems to act as an effective safeguard of the ethical

considerations noted.

In previous studies, the dosage of THC in cannabis cigarettes used generally ranged from 1.7% to 6.7%.

However, continuing advances in sophisticated cultivation techniques have significantly increased the

potency of cannabis available to recreational users. In the United States, the average THC concentrations

have increased from 1-2% in the 1970s to 8-9% in the 2000s394,395, equivalent to roughly a 6-7 fold

increase after adjusting for the quality of cannabis396. In Canada, the average THC dosage in cannabis

seized in 2008 was 11%397, similar to that reported in the United State in the same year398. Although

cannabis users generally titrate the amount of cannabis smoked regardless of the THC concentration399,

this study replicated as strictly as possible the smoking conditions under which young drivers are exposed

in order to maintain the external validity of the research. During the study, participants smoked a cannabis

cigarette containing 12.5 2% THC, which is considered by Health Canada as a moderate dose of

cannabis400 that is reflective of the concentrations available on the market. Participants were instructed to

smoke ad libitum and until they experienced the same level of “high” as they would normally feel. This

helped to simulate the way that cannabis is consumed recreationally and controlled for individual

variabilities, allowing those who were more sensitive to the effects of cannabis to titrate their own dose.

Compared to some studies that used a standardized smoking procedure (e.g. fixed number of puffs and

fixed breath hold durations), the results of this study are more transferrable to the effects of cannabis in

the real world. According to the self-report cannabis strength questionnaire, the majority of the

participants (78%) reported that the active cannabis had similar potency to the cannabis they normally

smoke. This suggests that the strength of cannabis and the dosing regimen used in the study are reflective

of those used by recreational smokers.

The development and advancements in simulation technology have drastically improved the ability of

scientists to measure driving performance objectively and accurately. Beginning in the 1960s, driving

simulators have steadily gained popularity in driving-related research401. Although remarkable at the time,

older generations of driving simulators were unresponsive to driver actions and did not provide realistic

vehicle dynamics391,402. Crancer et al. were one of the first to study the effects of cannabis on driving

using a driving console, which contained a visual display, steering wheel, speedometer, turn signals,

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acceleration pedal, and brake pedal. While participants were instructed to follow a projected video, the

stimuli presented on the screen were not affected by the participants’ responses and maneuvers of the

driving console361. Since then, technological improvements in driving simulators have generated

significantly more detailed data and increased the validity of simulators in driving research. The

VSM500M car simulator used in this study is a high-fidelity driving simulator with high-quality 180°

visual display, 3D surround sound, and interactive motion platforms. This simulator provides a fully

immersive driving experience that is able to capture realistic driving behaviour. Although there certainly

are some disparities between simulated driving and real driving, several studies have validated that

performances on driving simulators are good predictors of on-road behaviour403–407. Moreover, the

simulator offers several logistical benefits compared to on-road driving. First, scenarios are

programmable, which allows experimenters to measure specific outcomes of interest while maintaining

consistency across scenarios. This is something that could not be achieved with on-road testing. Secondly,

driving simulators can collect a large amount of measurements simultaneously while reducing

experimenter bias. During each driving session, video and audio recordings were obtained. This allows

every driving scenario to be reviewed and analyzed even after participants have completed the study.

Lastly, participants are not exposed to real traffic risks and dangerous consequences of impaired driving.

Altogether, the high-fidelity simulator used in this study provides a realistic, comprehensive, and safe

driving environment, making the findings of this study important in understanding the impact of cannabis

on driving outcomes.

4.1 Driving Outcomes

Based on preliminary findings of 51 participants with complete residual data, cannabis did not affect

simulated driving performance 24 hours after smoking. However, cannabis significantly increased the

braking distance behind a risk-taking hazard 48 hours post-dose under the single-task condition. Despite

the statistical significance, this result should be interpreted with caution. The lack of effects on most

driving measures was not surprising because the current analysis was only based on approximately half of

the target sample size, which was calculated to be 114 in order to have sufficient power to detect the

residual effects of cannabis (Section 2.7). Even with the current sample size, it is interesting that some

residual effects have been observed.

While driving under the single-task condition 48 hours after smoking, participants braked significantly

further away from a risk-taking hazard, suggesting a more cautious driving behaviour compared to the

placebo group. Although baseline measures were also significantly different, the result was the opposite,

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where the active group actually braked closer to the hazard compared to the placebo group (Figure 12A).

Interestingly, it appears that the difference observed at 48 hours is due to a decrease in braking distance in

the placebo group back to baseline rather than an increase in the active group. This may be that

participants who smoked cannabis fail to display learning effects and appropriate risk evaluation; hence,

maintaining a further distance. However, these results need to be interpreted with caution. It is surprising

that no difference was observed 24 hours after smoking, as one would expect to see residual effects

present at 24 hours and persisting until 48 hours following use. Therefore, it is possible that the observed

effect could be due to chance. It is also possible these results may be attributed to the unique

pharmacokinetics of THC, which first accumulates in adipose tissues and is then released over time.

Future analysis incorporating blood THC concentration and a full sample size would provide a better

understanding of this observation.

Little information is available regarding the residual effects of cannabis on simulated driving

performance. Therefore, limited comparisons can be made between the results of the current study and

those found in the literature. In one study, Rafaelsen et al. examined the effect of cannabis resin on

simulated car driving in eight occasional users. Although the study only measured performance up to 16

hours after consumption, cannabis did not affect mean speed beyond 4 hours after use313. This is

consistent with our findings. In a series of three studies, Yesavage and colleagues investigated the carry-

over effects of cannabis on flying skills, and found contradictory evidence on the impairing effects at 24

hours after smoking386–388. In one study, Leirer et al. demonstrated that 20mg of THC impaired flying

performance only until 4 hours after smoking. No residual effects were observed 24 hours later, which is

consistent with our study. On the basis of this finding, the authors concluded that reactional cannabis

users may not necessarily have difficulties operating complex human machines such as airplanes388. On

the other hand, conflicting results were produced by the same group of authors in two other studies.

Yesavage et al. examined the performance on a flight simulator landing task in 10 licensed pilots. Overall,

pilots who smoked cannabis demonstrated more difficulty in controlling the aircraft at 24 hours post-

exposure386. In our study, SDLP and standard deviation of speed were measures of vehicle control.

Contrary to their findings, our preliminary results showed that cannabis did not affect drivers’ ability to

control the car 24 hours after smoking. It is important to note that the study by Yesavage et al. did not

have a control group, and the impairing effects observed could merely be an effect of repeated testing

rather than a drug effect. In a subsequent study, nine pilots were tested on a more difficult flying task after

smoking either a cannabis cigarette containing 20mg of THC or a placebo cigarette. In contrast to our

results, the authors showed that cannabis impaired flying performance up to 24 hours after smoking387.

One explanation for such inconsistency could be the small sample size, which ranged from 8 to 10

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subjects across these studies. Therefore, the results of our study will provide a more solid understanding

and contribute significantly to the current body of literature.

Although the residual effects of cannabis on simulated driving performance at 24 hours after smoking

have been somewhat contradictory, its effects at 48 hours appear to be more consistent. Similarly to our

current findings, previous studies also found that cannabis does not affect drivers’ speed and ability to

control the vehicle 48 hours post-dose387,388. However, since residual effects at 48 hours may be more

subtle and require greater power to be detected, future analysis with the full target sample is required to

draw any conclusions.

In addition, although there is no difference in the number of collisions between the active and placebo

groups, it is worth mentioning that a relatively high collision rate was observed at baseline, especially

under the single-task condition (Figure 9A-B). One possible explanation could be due to unfamiliarity

with the driving scenarios and hazards. Even though practice trials were administered, they did not

include the hazards that were present in the testing trials. As a result, participants may have performed

worse during baseline when they were exposed to the driving hazards for the first time, which could have

masked the true effect of cannabis on collision risks.

Furthermore, studies have shown that drivers become progressively drowsier and less attentive during

long, monotonous drives because of little visual stimulation408,409. With a lower traffic density, drivers

also tend to have a greater sense of monotony, making them more likely to display risky behaviour409. The

straightaway section of the driving trial was precisely designed to capture such behaviours. In particular,

it has been speculated that the effects of cannabis may be more prominent on long, monotonous drives.

However, our current results do not support this speculation. Given that the straightaway hazard was only

2-3 minutes in length per trial, it is possible that the effects of cannabis may become more visible over a

longer drive.

Although cannabis did not affect most driving measures collected in this study, some significant main

effects were noted. Under the single-task condition, overall SDLP was significantly higher 48 hours after

smoking compared to 24 hours post-dose in both groups. This could have been the result of practice

effects, where participants became more comfortable, and subsequently more careless in maneuvering the

simulator during the last session. Similar results observed under the dual-task condition further confirm

this possibility.

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During the straightaway hazard, participants in both groups significantly increased standard deviation of

speed 48 hours after smoking under the single-task condition. Interestingly, the increase was slightly

higher in the active group. Although the difference was not statistically significant compared to placebo, a

potential trend was observed. Once the full sample size is reached, it is possible that a significant effect

could be detected. Similar to the overall SDLP, lane deviation (SDLP) during this section of the driving

trial also increased at 48 hours after smoking regardless of the drug condition. This again could be due to

practice effects developed over consecutive testing sessions. On the other hand, slightly different results

were reported under the dual-task condition. First, mean speed during the straightaway hazard gradually

increased over time and was significantly higher 48 hours after smoking in both groups. This is consistent

with previous driving research where individuals tend to drive faster on interstate or rural highways that

have low traffic volumes408,410. Although a gradual increase in mean speed was also observed under the

single-task condition, the results did not reach statistical significance at any time point. This suggests that

the distraction task has made the driving trial more complex, leading to more driving errors and risky

behaviours. Secondly, under the dual-task condition, standard deviation of speed and SDLP appeared to

be more affected at 24 hours after smoking than at 48 hours. It is possible that the nature of the counting

task and participants’ attitude towards it could alter driving behaviours at different time points during the

study, as the majority of participants commented that they disliked this task and felt excited that it was

the their last time completing the task during the 48 hour session.

Under the dual-task condition, participants in both the active and placebo groups significantly increased

their following distance behind the slow moving vehicle 24 and 48 hours after smoking. The same was

not observed under the single-task condition. This suggests that participants may have been aware of the

distraction and may have driven more cautiously to compensate for the disturbance. This idea is supported

by visual observations and audio recordings, as participants tend to stop or slow down in their counting

while following or attempting to pass the slow vehicle.

In addition to the effects of cannabis on braking distance, a significant main effect of time under the

single-task condition revealed that participants braked significantly further away from the hazard 24 and

48 hours after smoking. This could be a result of stimulus sensitization. After their first exposure to the

risk-taking hazard in the first driving trial, participants may have anticipated the possible danger

associated with the hazard and approached with more caution in subsequent driving trials by braking

further away (Figure 12A).

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4.2 Cognitive and Psychomotor Measures

Overall, cannabis did not significantly affect performance on driving-related cognitive and psychomotor

tasks at 24 and 48 hours after smoking. This is not unexpected because the current analysis is based on

less than half of the target sample size.

Results of the CPT-X showed that cannabis did not significantly affect attention, vigilance, and general

executive functioning 24 and 48 hours after smoking. This is consistent with the work done by Barnett et

al. and Fant et al321,385. In the first study, eight male subjects smoked a cannabis cigarette containing either

1, 2, or 2.5% of THC and were assessed up to 24 hours later on a visual search task and critical tracking

task, both of which require high attention and cognitive efficiency. The authors found that cannabis did

not impair performance on these tasks beyond 7.1 hours after smoking385. Similarly, while cannabis

significantly decreased central and peripheral tracking speed in a smooth-pursuit eye movement test

immediately after use, Fant et al. found no impairing effects at 24 hours321. In contrast, one study reported

performance decrements in a serial addition and subtraction task 24 hours after smoking cannabis

cigarettes containing 2.57% THC331. This discrepancy could be attributed to the small sample size of the

study (only three subjects) and the nature of the tests administered. Although the serial arithmetic task

partially requires attention and processing speed, it may be assessing different cognitive domains than that

measured by the CPT-X. Despite the lack of significance, participants in the active group appeared to

have committed greater commission error 24 and 48 hours post-dose (Figure 13B). Moreover,

performance variability in the placebo group seemed to be returning to baseline at 48 hours, while the

same was not observed in the active group (Figure 15A). This supports the previously mentioned idea that

cannabis may inhibit some learning or practice effects that are normally acquired over time. Once the full

sample is recruited, these differences may become more apparent.

Based on the Hopkin’s Verbal Learning Test, cannabis did not affect verbal learning and recall memory

during the two days following cannabis administration. This result has been reported across multiple

studies320,321,331,350,383,384. Chait et al. examined the morning after effect of cannabis on free recall in 14

male occasional users. While cannabis decreased the number of words recalled immediately after

smoking, the effects disappeared within 9 hours383. In two other studies conducted by the same group of

authors, performance on a series of memory tests including forward and backward digit span, free recall,

and semantic memory tasks was not significantly affected by cannabis the morning after smoking320,384.

Similarly, in a larger study with 60 volunteers, Kurzthaler et al. also found that the decrements observed

in verbal and visual memory immediately after smoking were completely recovered within 24 hours of

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use350. Despite consistent evidence in acute memory impairments, these effects may not persist beyond a

short time-frame after consumption.

Similar to our observations, performance on the DSST has been previously shown to be unaffected by the

residual effects of cannabis320,383,384. However, a trend was observed for the percent of correct trials in our

study (p=0.091). Once the full sample size is recruited upon study completion, this effect may become

more apparent.

To our knowledge, only one study examined the residual effects of cannabis on hand-eye coordination

and motor skills. Participants in the study smoked either a cannabis cigarette containing 290ug/kg of THC

or a placebo cigarette and were tested up to 24 hours later on the trial making test and efficiency test

system. The authors reported that cannabis did not have any residual effects on perceptual motor speed

and accuracy350. Similarly, results of our study demonstrated that cannabis did not impair performance on

the grooved pegboard task 24 and 48 hours after smoking. Likely as a result of practice effects,

participants in both groups completed the task significantly faster 24 and 48 hours post-dose.

4.3 Pharmacodynamic Measures

It is hypothesized that, while individuals experience subjective drug effects acutely after cannabis

consumption, they are often unaware of any intoxication the following day. This is generally supported by

the results of this study and those found in the literature. In an experiment with 10 healthy volunteers who

smoked cannabis containing either 0, 1.8% or 3.6% of THC, visual analog scores for “drug effect”,

“high”, “drug liking”, and “stoned” were highest at 0.25 hour after smoking, and only remained

significantly elevated up to 1.75 and 3.5 hours for the low and high dose, respectively321. Likewise,

Heishman et al. also found that the increase in drug high, stoned, drug liking, and impaired VAS

subscales immediately after smoking gradually declined to baseline before the next morning. No

differences in subjective effects measured by the VAS were reported at 24 hours331. In our study, the

significant increase in all VAS subscale scores in the active condition immediately after smoking signifies

that the drug has been properly administered and was eliciting its effects. As expected, at 24 and 48 hours

after smoking, no difference was observed between the active and placebo groups in any VAS subscales.

The ARCI is another tool used to measure subjective drug effects. It is sensitive to the effects of a variety

of psychoactive drugs, including cannabis. Given the results from the VAS, it is not surprising that

cannabis also did not affect scores on the ARCI subscales 24 and 48 hours post-dose. This is consistent

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with the findings of several studies321,331,384. In contrast, one study by Chait et al. found that scores on the

BG and Amphetamine subscales were significantly higher in the active condition the following

morning383. Because assessments in the study were only conducted up to 9 hours after smoking, it is

uncertain whether these effects persisted any longer. It is interesting to note that in most previous studies

examining the residual effects of cannabis, the ARCI used included an additional marijuana subscale,

which may be particularly more sensitive to the effects of cannabis. Incorporating this subscale in future

studies may be useful and more informative to any residual subjective cannabis effects.

Results from the POMS revealed some interesting fluctuations of mood throughout the study. Although

the three-way interaction failed to reach statistical significance after the Greenhouse-Geisser correction, a

trend was observed. Little information is available on the residual effects of cannabis on mood states, as

findings in previous studies have not exceeded 12 hours after use320,383,384. Even so, results have been

mixed and are difficult to interpret. In one study, scores on the elation and positive mood subscales were

significantly higher in the following morning 9 hours after smoking383. Whether the effects lasted beyond

this time-frame was not examined in the study and is questionable. Because these effects were not

observed acutely after smoking, the authors believed they were a carried over disgruntlement in subjects

who received the placebo cigarette383. Another study reported a slightly lower depression score in the

active condition compared to placebo 12 hours after smoking, which was also suspected to be a residual

disgruntlement in participants who did not receive the active drug384. On the other hand, in a third study,

the POMS was found to be insensitive to the effects of cannabis 12 hours after consumption320. Although

cannabis did not appear to affect mood states at 24 and 48 hours, some significant main effects of time

were observed in this study. At 24 hours after smoking, participants in both groups felt less friendly, less

vigorous, less elated, and less aroused compared to baseline. However, these effects were much more

apparent in the placebo group, and may be caused by a dissatisfaction in not receiving the active drug. At

48 hours post-dose, participants in both groups were less anxious, less friendly, and less fatigued than

before smoking. In comparison to 24 hours post-dose, participants also felt less fatigued and more

aroused. This could be an artifact of the experimental procedure, where participants may have become

accustomed to the testing environment, becoming less tense/anxious, and may have been excited to

complete the last session. Because mood fluctuations can be affected by a variety of factors, caution

should be applied when interpreting any effects in future analysis. Nevertheless, with an increase in

sample size, more will be revealed regarding the residual effects of cannabis on changes in mood states.

In addition, subjective drug effects have also been assessed in some flight simulations studies. Out of nine

pilots, seven showed some degree of impairment at 24 hours, but only reported awareness of drug

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effects387386. In another study, subjective measures of high, alertness, anxiety, and happiness did not differ

between pre-drug and 24 hours post-drug386.

4.4 Physiological Measures

Tachycardia has been described as one of the most reliable physiological signs of acute cannabis

intoxication332; however, the duration of effect is generally within four hours after smoking320,321,331,383,384.

Similarly, residual effects on other physiological measures such as changes in blood pressure321,331 and

body temperature331 have not been observed 24 and 48 hours after use. Therefore, results of our study

supported the hypothesis that no physiological effects would be observed at 24 and 48 hours following a

single dose of smoked cannabis.

4.5 Challenges and Limitations

While the results of the current study have important implications on traffic safety and policies, there are

a few limitations that must be considered.

Relatively little research is available on the residual effects of cannabis on driving behaviours to guide

effect size estimation. An estimated sample size required to detect a medium effect size (d=0.5) with a

power of 0.8 was calculated to be 114. Since the interim analysis was based on less than half of the target

sample size, it is not surprising that the preliminary results were limited. Based on the current sample

means, a post-hoc power analysis using overall SDLP, one of the most sensitive measures of driving

impairment348,369,370, revealed a low power of 0.19. The full sample, once achieved, may be able to

provide sufficient power to detect some subtle residual effects of cannabis on driving performance.

Additionally, it will provide valuable information on effect size estimation for future cannabis and driving

research.

Simulated driving is a laboratory-based task that approximates real driving, and may have reduced

external validity. Since there were no serious consequences or punishments associated with dangerous

driving behaviours, participants may have driven differently than on the road. Particularly with male

participants, who have a greater tendency to treat the simulator as a video game. Despite being instructed

to drive as they would normally in a real car, a few participants still behaved more hazardously (e.g.

drove much faster than the speed limit or attempted to pass the slow vehicle when it was unsafe).

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However, the driving simulator has been proven as a validated predictor of on-road driving, and some

have even indicated a better correlation between actual driving with simulated driving performance than

with on-road testing403,404,407. In conjunction with safety considerations and the consistency in data

measurements, the driving simulator remains a good tool to assess driving behaviour.

The design of the driving scenarios also had some limitations. First, driving scenarios were created under

a rural setting on a two-lane highway, which may have limited generalizability to other roadway

conditions. Specifically, driving behaviours under a more complex city or high-traffic environment may

not have been captured in the current study. This could explain the discrepancy with previous findings in

simulated flying performance, which requires more intricate maneuvers and a more complex set of

psychomotor skills. However, the rural setting was chosen to minimize simulation sickness, assess

driving behaviours in a long, monotonous drive, and provide accurate measures of SDLP in a controlled

single-lane drive. Secondly, although practice driving trials were administered prior to baseline to reduce

practice effects, these scenarios did not include any traffic and hazards present in the testing trials. As a

result, participants were exposed to the driving hazards for the first time during baseline, and expectation

or anticipation of these hazards in subsequent trials may have altered driving behaviours. In future

studies, practice driving trials could be programmed with hazards to further eliminate practice effects

and prevent masking of the true cannabis effects. Moreover, driving scenarios could also incorporate

multiple driving environments, which allows researchers to explore driving behaviours under the

influence of cannabis within different driving conditions and to assess which condition is more sensitive

to the effects of cannabis. Nevertheless, it is important to keep in mind that addition of these tasks could

increase time commitment and conflict with study recruitment. Since many individuals lost interest in the

study because of the amount of time involved or conflicts with their work schedule, longer test sessions

could further diminish interests and may lead to a more biased sample of individuals who have time to

participate (e.g. students or unemployed).

Given the psychoactive properties of cannabis, maintaining the blind was one major challenge in the

study. As high as 86% of the participants correctly judged their own drug condition and expectations in

drug reward could affect subjective and behavioural responses independently of pharmacological actions

of the 152,411However, the study was designed with multiple protective measures to maintain the blind and

the integrity of the data. First, the placebo cannabis is composed of real cannabis plant product rather than

synthetic ingredients to taste and smell like active cannabis. Secondly, both cigarettes were prepared

under the same conditions. Specifically, each cigarette was rolled with two layers of rolling paper to

conceal the appearance and color of the investigational products. The same brand of rolling paper was

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also used throughout the entire study. Moreover, participants were informed that the cannabis they

received may be stronger, equally strong, or less strong than what they normally consume, and were never

given the THC dose of the active cigarettes. Collectively, these help to reduce stimulus expectancies412

and lower certainty in participants' speculations of the drug condition assigned.

In addition, several other procedures were also implemented from the experimenter's perspective to

maintain the blind. During each session, tasks that could contribute to unblinding, such as administering

the VAS and cannabis strength questionnaire, assessing vital signs, and reviewing urine toxicology

screens, were delegated to one study personnel. On the other hand, tests that require absolute objectivity

such as assessing simulated driving performance were conducted by another study personnel, who

remained blinded to the condition throughout the study. Moreover, participants were instructed to assist

with the blinding by not reporting any comments with regard to their speculation of the drug condition.

Lastly, since certain study personnel were still running participants at the time of the interim analysis,

only one study team member who did not interact directly with the participants received the

randomization code along with the SPSS syntax. Corresponding SPSS outputs were then returned and

analyzed without any indication of drug conditions.

4.6 Conclusion

In summary, preliminary findings of the present study showed limited residual effects of cannabis on

driving-related skills 24 and 48 hours after smoking a single dose. Although cannabis significantly

increased braking distance 48 hours after smoking, caution should be applied when interpreting this

result. Interesting trends were also observed on the CPT-X, DSST, and POMS, which could suggest some

possible residual effects of cannabis on attention, general cognitive functioning, and mood states. Future

analyses with the full sample is required to provide a more clear understanding of any residual effects of

cannabis on driving performance in young drivers. More importantly, results of the current study will

provide greater insights on whether these residual effects translate to clinically significant impairments

that would warrant changes in traffic policies.

4.7 Future Directions

Currently, an important extension study has been initiated to evaluate the effects of alcohol on driving

performance using the same protocol. Results of this sub-study will serve to validate that the present

106

study protocol is well equipped to detect impairments of driving-related skills. Additionally, driving

performance under the influence of cannabis can be compared to that of a well-known impairing

substance, providing more information on how collision risks can be impacted differently by different

factors. Furthermore, a combination of alcohol and cannabis is often detected in drivers involved in motor

vehicle accidents27,285,287,288, and may produce additive, synergistic, or longer lasting impairments20,21,378.

While a higher dose may be required to cause impairment when these substances are taken alone,

detrimental effects may be observed when a lower dose of each is mixed together. An upcoming study

that examines the interaction effects of alcohol and cannabis will seek to answer these questions.

Tolerance to some cannabis effects has been well documented in heavy, chronic users. While this study

focused on occasional smokers, future studies should explore the residual effects of cannabis on heavy

smokers, who may experience different levels or different types of impairment on driving performance.

Based on the recruitment results of this study, as high as 57.3% of callers were ineligible because they

smoke 5 or more days a week, which may be a frequency that is more representative of the general

cannabis using population. Consequently, investigating driving behaviours in this group of individuals

may better reflect the impact of cannabis on driving performance in the real-world. Alternatively, future

studies could also examine cannabis users who smoke less frequently than once per week.

Lastly, although smoking and vaporizing are the most popular methods of cannabis consumption, oral

administration of cannabis is also used by many individuals. Since the pharmacokinetics differ greatly

between smoked and orally administered cannabis, with the latter having a slower onset but longer

duration of action, the residual effects of an oral dose of cannabis on driving behaviours would be

especially important and should be explored in future research.

107

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Appendices

Appendix A: Study Advertisements

127

Online advertisements:

I. CAMH website study posting

128

II. Clinicaltrial.gov study posting

III. Kijiji posting

129

IV. Craigslist posting

V. Toronto’s Backpage

130

Print Advertisement

I. Postcard - Front side

131

I. Postcard - Back side

II. Now Magazine

132

III. Print Posting

133

IV. TTC poster - Wide

IV. TTC poster - Vertical

134

Appendix B: Telephone Screening Forms

135

Telephone pre-screen cover page

Telephone pre-screen form

136

137

138

Appendix C: Participant Information Sheet

139

DRIVING STUDY

PARTICIPANT INFORMATION SHEET

Appointment Date and Time: ______ ________ ____

Thank you for your interest in this study! Please find below some things to remember in advance

of your participation.

The study takes place at the Centre for Addiction and Mental Health at 33 Russell Street,

Toronto (Room 1054). The study consists of five sessions, the first of which can occur at any

time prior to the rest. The remaining sessions, however, must occur on four consecutive days.

The first session is a medical examination and lasts about 2 ½ hours. The second session is also

short (about 2 ½ hours) and involves answering some questionnaires and performing some tasks

to test memory and attention (for example), and to practice driving. The third session is where

you will be asked to smoke, and this day is longer (requires at least 8 hours of your time). The

final two sessions are shorter (2 ½ hours), and you will be asked to perform some tests of

memory and attention, and to drive the simulator.

It is important that you…

Bring your valid driver’s license on Session 1.

Do not use cannabis, alcohol, or other drugs that are not required for medical reasons for

48 hours prior to attending Session 2, and for the remainder of the study (e.g. do not

smoke again until your participation is completed). Compliance will be confirmed by

laboratory analysis of blood, urine, and breath samples. You do not need to change your

regular cannabis smoking habits until 48 hours prior to attending Session 2. Do not use caffeine after 8 pm the evening before attending any study day.

Refrain from driving a motor vehicle on the days you attend sessions 3, 4, and 5 (before

or after the session).

If at any time you wish to cancel or reschedule your appointment, or if you have any questions,

please call 416-535-8501 extension 36587 or email [email protected]

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Appendix D: Informed Consent Form

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STUDY INFORMATION and INFORMED CONSENT

Name of Study: Acute and residual effects of cannabis on young drivers’ performance of driving-related

skills.

Responsible Investigators: Robert E. Mann 416-535-8501 ext. 34496

Bernard Le Foll 416-535-8501 ext. 34772

Bruna Brands 416-535-8501 ext. 36860

This study will take place at the Centre for Addiction and Mental Health at 33 Russell St., Toronto,

Ontario. One-hundred forty-two subjects will take part in this study. This study is funded by the Canadian

Institutes of Health Research (CIHR).

Please take the time to read this information sheet carefully and ask any questions that you may have

before deciding whether you wish to participate in this study.

Study Drug Administration

During the course of this study you will be asked to smoke a cannabis or placebo cigarette. A placebo is

an inactive substance that is made to look and taste like the real substance. The placebo cannabis does not

contain the active drug THC. You will have a 2-to-1 chance of receiving a cannabis or placebo cigarette.

Please inform the medical doctor of any medications or natural health products that you are taking. If you

are a woman with the ability to have children, you will be required to use an approved method of birth

control for the duration of the study. These methods include abstinence, hormonal contraceptives, and

barrier devices or having a partner who has had a vasectomy or is using male contraceptives. Pregnancy

testing after sessions 1 and 2 must be negative in order to proceed with the study. If you are eligible for

the study you will also be asked not to drive to CAMH on sessions 3, 4, and 5. You will be provided with

a taxi chit or TTC tokens.

Purpose

The purpose of this study is to examine driving behaviour under the influence of cannabis using a driving

simulator system.

Study Procedures

The study will involve five (5) sessions with different procedures required for each study day. Completion

of all 5 sessions will require a total of about 17 hours of your time.

If you choose to withdraw from the study at any time or you are withdrawn from the study by us, you

must let study staff know if you wish to have any data, blood or urine samples you have provided

destroyed.

You will be asked to refrain from personal use of cannabis, alcohol or other drugs not required for

medical reasons, outside of the laboratory, for 48 hours prior to Session 2, and until your participation in

this study is completed.

Session 1 (Eligibility Screening Day): On the screening day you will undergo an assessment to determine

whether you are eligible to participate in the study. You will undergo a physical exam by a medical

doctor, and you will be asked for information about

• your past and present drug use (including when you last used cannabis)

• current medications

• psychiatric symptoms and history

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As well you will be asked to give some samples of blood (total about 15 mL or 3 teaspoons) for

biochemistry and haematology, and urine for drug screening. If you are female, you will be asked to also

provide a urine sample for pregnancy testing. The blood sample(s) will be drawn by a needle from a vein

in your arm. You will be asked to submit to a breathalyzer test for alcohol, and vital signs will be taken

(e.g. blood pressure, heart rate).

Completion of procedures will take about 2 ½ hours of your time.

Session 2 (Practice Day):

You will be asked to provide a urine sample to confirm your ongoing eligibility.

You will be asked information about demographics (age, education, occupation), and to complete a series

of questionnaires designed to assess driving behaviour and individual difference as well as mood and

cognitive functioning (e.g. memory and attention).

You will be given two 10-minute driving simulator practice sessions in the CAMH driving laboratory.

During one of these sessions, you will be asked to complete a counting task, and if you agree an audio

recording of your voice will be taken.

Please initial one of the two following alternatives:

I agree to have my voice recorded _______

I do not agree to have my voice recorded _______

Completion of procedures will take about 2 ½ hours of your time.

Session 3 (Testing Day 1):

You will return to CAMH the following morning and be asked to give blood and urine samples for drug

screening, to submit to a breathalyzer test for alcohol, and vital signs will be taken. You will have a small

tube inserted into your vein by a nurse (intravenous catheter) so that blood can be taken throughout the

day. The blood samples will be analyzed to determine the quantity of THC (the active drug found in

cannabis) in your blood. Blood samples and vital signs will be taken before smoking, and 5 minutes after

smoking the cannabis or placebo cigarette, then 15, 30 minutes, and hourly thereafter. After the 6th hour

measurement, the intravenous catheter will be removed. A total of 10 blood samples will be collected of

10mL (or 2 teaspoons) each, for a total of 100 mL (or less than ½ cup) for the whole day.

If you agree to participate in the supplemental study on genetic influences, an additional sample of blood

(about 20mL or 4 teaspoons) will be collected for these analyses at the time other blood is drawn.

Before smoking, you will be given a 5-minute practice driving simulator session followed by two 10-

minute driving simulation testing sessions in the CAMH driving laboratory, where your driving will be

recorded by the simulator system.

You will then be given a cannabis or placebo cigarette and will be asked to smoke it in the CAMH

smoking laboratory.

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You will be asked to complete a questionnaire to measure drug effects as well as mood and cognitive

functioning (e.g. memory and attention).

After smoking, you will be given two 10-minute driving simulation testing sessions in the CAMH driving

laboratory, where your driving will be recorded by the simulator system. During one of these sessions,

you will be asked to complete a counting task, and if you agree, an audio recording of your voice will be

taken.

You will be asked again to complete a questionnaire to measure drug effects as well as mood and

cognitive functioning (e.g. memory and attention).

Completion of procedures will require approximately 8 hours of your time.

Session 4 (Testing Day 2): You will return to the lab the following morning to complete the 24 hour

measurements.

You will be asked to give blood (about 10mL or 2 teaspoons) and urine samples for drug screening and to

measure THC. The blood sample will be drawn by a needle from a vein in your arm. You will be asked

to submit to a breathalyzer test for alcohol, and vital signs will be taken.



You will be given two 10-minute driving simulation testing sessions in the CAMH driving laboratory,

when your driving will be recorded by the simulator system. During one of these sessions, you will be

asked to complete a counting task, and if you agree an audio recording of your voice will be taken.


Session 5 (Testing Day 3): You will return to CAMH the following morning to complete the 48 hour

measurements.

You will be asked to give blood (about 10mL or 2 teaspoons) and urine samples for drug screening and to

measure THC. The blood sample will be drawn by a needle from a vein in your arm. You will be asked to

submit to a breathalyzer test for alcohol, and vital signs will be taken.



You will be given two 10-minute driving simulation testing sessions in the CAMH driving laboratory,

when your driving will be recorded by the simulator system. During one of these sessions, you will be

asked to complete a counting task, and if you agree an audio recording of your voice will be taken.


Ongoing Eligibility

To participate in this study you must be between 19 and 25 years old ,must have held a valid Ontario class

G2 or G driver’s licence (or the equivalent from another province, state, or country) for at least twelve

months, and must use cannabis between one and four times per week.

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You must not have a history of substance dependence or be currently dependent on cannabis or other

substances of abuse.

You must not be a regular user of medications that affect brain function (e.g., antidepressants,

benzodiazepines, stimulants).

If you have a psychiatric disorder needing treatment, or have a family history of schizophrenia you will be

excluded from the study and will be referred to the psychiatric evaluation centre.

You will be excluded from the study at any point if you test positive for alcohol based on a breathalyzer

test or if your laboratory results after the screening day indicate that you have used a substance that

affects brain function other than cannabis.

You will be excluded from the study if you are pregnant, trying to become pregnant, or currently

breastfeeding.

Confidentiality

You have been invited to participate in this study because you are a cannabis user. Although we have

received permission from Health Canada to use cannabis in this study, cannabis remains an illegal

substance. Your identity will be kept confidential to the full extent provided by law. In addition, neither

your name nor any other personal identifier will be used in any reports or publications arising from this

study. The data produced from this study will be stored in a secure, locked location and on anonymized

datasets on a password-protected computer file. Only members of the research team will have access to

the data. Following completion of the research study the data will be kept as long as required by CAMH

and then destroyed. Published study results will not reveal your identity.

As part of continuing review of the research, your study records may also be assessed on behalf of the

Research Ethics Board and, if applicable, by the Health Canada Therapeutics Products Programme. A

person from the research ethics team may contact you (if your contact information is available) to ask you

questions about the research study and your consent to participate. The person assessing your file or

contacting you must maintain your confidentiality to the extent permitted by law. Furthermore, as part of

the Research Services Quality Assurance Program, this study may be monitored and/or audited by a

member of the Quality Assurance Team. Your research records and CAMH records may be reviewed

during which confidentiality will be maintained as per CAMH policies and extent permitted by law.

If you agree, you will be registered in a centralized, secure database used to connect people interested in

participating in studies with CAMH researchers. The CAMH Research Registry is used to help

researchers identify individuals who may be interested in participating in approved research studies. By

sharing your experiences with researchers, we will gain new insights into issues that may be important to

you and to others who share similar experiences. If you choose to join, you will be asked to complete a

separate informed consent form.

□ I am interested

□ I am not interested

You can also authorize us to keep your contact information in our lab database and contact you regarding

the participation in future studies. If you consent to participate in another study, to avoid repeating the

same assessments and reduce your time commitment, we may share the results of common assessments

completed within the past 3 months. If you decline sharing information, you can still consent to

participate in this study.

□ I agree

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□ I decline

Compensation

You will receive $200 for completing the study. If you decide not to continue in the study or if the study

physician withdraws you from the study you will receive up to $25 for completing each of sessions 1 and

2, and up to $50 for completing each of sessions 3, 4, and 5.

Risks

Although we do not foresee serious risks or discomfort arising from your participation, some minor risks

that may occur are:

• An adverse reaction to the cannabis, which can include commonly reported reactions such as

increased heart rate, decreased blood pressure, drowsiness, and/or increased anxiety.

• Coughing and/or throat irritation due to smoking cannabis.

• Small risk of bruising at the site where blood is drawn.

• Small risk of infection at the site where blood is drawn.

• Some participants may find driving the simulator system to be frustrating.

• Some subjects may feel strange or funny while driving the simulator system.

Epidemiological studies have linked cannabis use with other mental health issues such as psychosis and

schizophrenia. There is a potential risk that exposure to cannabis would trigger some mental health

problems. Those conditions could require long term treatment. For this reason, we are recruiting only

participants that are already using cannabis and we are excluding participants that have schizophrenia or

for whom there is a high risk due to family history. Schizophrenia and psychosis is a chronic condition

requiring long term treatment.

Benefits

There are no direct benefits to you for participation in this study. However, some participants may find

driving the simulator system to be fun or exciting. Also, there may be societal benefits if results of this

study aid in reduction of collisions.

Voluntary Participation

Your participation in this study is voluntary. You may choose to withdraw from the study at any time. In

addition, the investigators or their staff responsible for this study may, at their discretion, end your

participation at any time. This could be due to medical reasons or for not following study procedures. If

your participation ends early for whatever reason, you will be compensated as described above. Your

choice to withdraw or your dismissal by us will not affect any treatment needs that you might have at the

Centre for Addiction and Mental Health now or in the future. If you choose to withdraw from the study

or you are withdrawn from the study by us, you must make it known to study research staff if you wish to

have any data, blood or urine samples you have provided destroyed.

Supplemental Participation in Study of Genetic Influences on Cannabis Effects

We are also asking if you would agree to provide an additional 2 samples of blood (about 20 mL or 4

teaspoons) on the Screening Day for an investigation of how your genes can affect your response to

cannabis, including how genes may influence your performance on the driving simulator task and other

measures we will collect. You may choose to withdraw from this supplemental study at any time. If you

choose to withdraw from this study or you are withdrawn from the study by us, you must make it known

to study research staff if you wish to have the data and blood sample you have provided for this purpose

destroyed. If you agree to participate in this substudy, please indicate your approval below, and also

complete the additional consent form for the Supplemental Study of Genetic Influences on Cannabis

Effects. Otherwise, please indicate that you do not want to participate in this supplemental study and the

additional sample of blood will not be collected.

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Please initial one of the two following alternatives:

I agree to participate in the supplemental study of genetic influences on cannabis effects. ____

I do not wish to participate in this supplemental study. ____

New Information

If any changes are made to the study or new information becomes available, you will be informed in a

timely fashion.

Additional Information

A description of this clinical trial will be available on http://www.clinicaltrials.gov, as required by U.S.

Law. This Web site will not include information that can identify you. At most, the Web site will include

a summary of the results. You can search this Web site at any time.

If you have questions about the study that are not answered in these Information Sheets, please ask us. In

addition, if you have questions in the future you may contact the study investigators at these telephone

numbers: Robert E. Mann 416-535-8501 ext. 34496; Bernard Le Foll 416-535-8501 ext. 34772; Bruna

Brands 416-535-8501 ext. 36860. Dr. Padraig Darby, Chair, Research Ethics Board, Centre for Addiction

and Mental Health, may be contacted by research subjects to discuss their rights. Dr. Darby may be

reached by telephone at 416-535-8501 ext. 36876.

INFORMED CONSENT

I, _________________________, have read (or had read to me) the Information Sheet for the study

named ‘Acute and residual effects of cannabis on young drivers’ performance of driving-related skills.’


simulator system. My role in the study is as a research volunteer to help the investigators collect

information on cannabis effects on driver behaviour by smoking a cannabis or placebo cigarette, acting as

a driver, providing urine and blood samples, and completing some questionnaires. My questions, if any,

have been answered to my satisfaction. By signing this consent form I do not waive any of my rights.

If I have any further questions I understand that I can contact the study investigators: Robert Mann 416-

535-8501 ext. 34496; Bernard Le Foll 416-535-8501 ext. 34772; Bruna Brands 416-535-8501 ext. 36860.

Dr. Padraig Darby, Chair, Research Ethics Board, Centre for Addiction and Mental Health, may be

contacted by research subjects to discuss their rights. Dr. Darby may be reached by telephone at 416-535-

8501 ext. 36876.

I voluntarily consent to participate in this research study.

Research Volunteer:

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Signature: ______________________________________

Date: __________________________________________

Name: _________________________________________

Please Print

Person Obtaining Consent:

Signature: ______________________________________

Date: __________________________________________

Name: _________________________________________

Please Print

I have been given a copy of this form to keep.

SUPPLEMENTAL INFORMED CONSENT – GENETIC INFLUENCES FOR THE CANNABIS AND

DRIVING STUDY

I, _________________________, have read (or had read to me) the Information Sheet for the study

named ‘Acute and residual effects of cannabis on young drivers’ performance of driving-related skills.’


simulator system. My role in the study is as a research volunteer to help the investigators collect

information on cannabis effects on driver behaviour by smoking a cannabis or placebo cigarette, acting as

a driver, providing urine and blood samples, and completing some questionnaires. I also understand that

the investigators will be conducting a supplemental study of genetic influences on the effects of cannabis,

including how it affects performance on the driving simulator task and other measures. I understand that

by agreeing to participate in this supplemental study I allow the investigators to collect an additional 20

mL (or 4 teaspoons) of my blood to conduct these analyses on the Screening Day, and these samples

and/or genetic data extracted from me may be shared with other authorized collaborators. My questions,

if any, have been answered to my satisfaction. By signing this consent form I do not waive any of my

rights.

If I have any further questions I understand that I can contact the study investigators: Robert Mann 416-

535-8501 ext. 34496; Bernard Le Foll 416-535-8501 ext. 34772; Bruna Brands 416-535-8501 ext. 36860.

Dr. Padraig Darby, Chair, Research Ethics Board, Centre for Addiction and Mental Health, may be

contacted by research subjects to discuss their rights. Dr. Darby may be reached by telephone at 416-535-

8501 ext. 36876.

I voluntarily consent to participate in this research study.

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Research Volunteer:

Signature: ______________________________________

Date: __________________________________________

Name: _________________________________________

Please Print

Person Obtaining Consent:

Signature: ______________________________________

Date: __________________________________________

Name: _________________________________________

Please Print

I have been given a copy of this form to keep.

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