ClinicalTrials.gg
CompletedNCT02849587Updated Jan 4, 2022Results posted

The Impact and Detection of Driving Impairments Associated With Acute Cannabis Smoking

A Phase 1/2 interventional study of Cannabis in Cannabis Intoxication, sponsored by University of California, San Diego. Completed at 1 site in United States. Open to participants aged 21 Years to 55 Years, including healthy volunteers. Per ClinicalTrials.gov, last updated 2022-01-04.

Sponsored by University of California, San Diego · Phase 1/2, Interventional, and Screening

Phase
Phase 1/2
Study type
Interventional
Enrollment
199
Allocation
Randomized
Ages
21 Years to 55 Years
Sex
All
01

Study summary

This study was authorized by the California Legislature (Assembly Bill 266, the Medical Marijuana Regulation and Safety Act to help with detection of driving under the influence of cannabis. One hundred and eighty healthy volunteers will inhale smoked cannabis with either 0% (placebo), 5.9%, or 13.4% Δ9-tetrahydrocannabinol (THC) at the beginning of the day, and then complete driving simulations, iPad-based performance assessments, and bodily fluid draws (e.g., blood, saliva, breath) before the cannabis smoking and a number of times over the subsequent 6 hours after cannabis smoking. The purpose is to determine (1) the relationship of the dose of Δ9-THC on driving performance and (2) the duration of driving impairment in terms of hours from initial use, (3) if saliva or expired air can serve as a useful substitute for blood sampling of Δ9-THC, and (4) if testing using an iPad can serve as a useful adjunct to the standardized field sobriety test in identifying acute impairment from cannabis.

Read the detailed description

There are several studies that suggest higher doses of whole-blood Δ9-tetrahydrocannabinol (Δ9-THC) concentration are associated with increased crash risk and crash culpability. However, attempts to define a cut-off point for blood Δ9-THC levels have proven to be challenging. Unlike alcohol, for which a level can be reasonably measured using a breathalyzer (and confirmed with a blood test), detection of a cut-off point for intoxication related to Δ9-THC concentration has eluded scientific verification. Recent evidence suggests blood Δ9-THC concentrations of 2-5 ng/mL are associated with substantial driving impairment, particularly in occasional smokers. Others have countered that this level leads to false positives, particularly in heavy cannabis users inasmuch as THC may be detectable in their blood specimens for 12-24 hours after inhalation. Given that 12 to 24 hours is beyond the likely period of driving impairment, this would appear to be a justifiable objection to a per se cut-off point for a Δ9-THC concentration indicative of impairment. Maximal driving impairment is found 20 to 40 minutes after smoking, and the risk of driving impairment decreases over the following hours, at least in those who smoke 18 mg Δ9-THC or less, the dose often used experimentally to duplicate a single joint. Other studies, however, report residual motor vehicle accident crash risk when cannabis is used within 4 hours prior to driving.

The roadside examination using the Standardized Field Sobriety Test (SFST) for proof of cannabis-related impairment has not been an ideal alternative to blood levels. Originally devised to evaluate impairment under the influence of alcohol, the SFST is comprised of three examinations administered in a standardized manner by law enforcement officers. The 'Horizontal Gaze Nystagmus' (HGN), the 'One Leg Stand' (OLS) and the 'Walk and Turn' test (WAT) require a person to follow instructions and perform motor activities. During the assessments, officers observe and record signs of impairment. In one study, Δ9-THC produced impairments on overall SFST performance in 50 % of the participants. In a separate study involving acute administration of cannabis, 30% of people failed the SFST. This discrepancy was thought to be in part due to the participant's cannabis use history, as well as low percentage of THC in the cannabis. The reported frequency of cannabis use varied from once a week to once every 2-6 months in the study where there was a failure on the SFST by 50% of the participants. The other study included more frequent users who smoked cannabis on at least four occasions per week.

Based upon the above, another means is needed to help law enforcement officers discern driving under the influence of cannabis. One future possibility is the development of performance-based measures of cannabis-related impairments. This will include testing of critical tracking, time estimation, balance and visual spatial learning. The investigators have selected brief measures in order to be practicably administered repeatedly over a short time period, as well as tests that have the potential to translate to a field-feasible tablet-based format, should there be benefit in possibly including these in future performance-based measures for use in the field by law enforcement officers (e.g., a cannabis-focused field sobriety test).

02

Conditions studied

  • Cannabis Intoxication

Keywords

  • Driving Under the Influence
  • Memory Impairment
  • Reaction Time
  • Time Perception
  • Cannabis
  • Marijuana
  • Whole Blood
  • Oral Fluid
  • Breath
  • Driving simulator
03

In context

Memory Disorders

269 studies on the registry are indexed under Memory Disorders; 62 are open to participants now.

This study's enrollment of 199 is above the median of 71 across 214 interventional studies indexed under Memory Disorders.

Browse Memory Disorders studies →

Lead sponsor

University of California, San Diego is the lead sponsor of 975 studies on the registry; 196 are open to participants now.

Of its 111 completed or terminated interventional studies of FDA-regulated products, 71 (64%) have results posted.

Counted across the registry records on this site, refreshed daily.

04

Who can participate

Ages eligible
21 Years to 55 Years
Sexes eligible
All
Accepts healthy volunteers
Yes

Go through the criteria one by one — yes, no or not sure — and take the list to your doctor or the study team. Kept in this browser only.

Inclusion criteria

  • Be a licensed driver.
  • Need to have acuity of 20/40 or better, with or without correction on a Snellen Visual Acuity eye chart.

Exclusion criteria

Exclusion Criteria:

  • At the discretion of the examining physician, individuals with significant cardiovascular, hepatic or renal disease, uncontrolled hypertension, and chronic pulmonary disease (eg, asthma, COPD) will be excluded.
  • Unwillingness to abstain from cannabis for 2 days prior to screening and experimental visits
  • Positive pregnancy test
  • A positive result on toxicity screening for cocaine, amphetamines, opiates, and phencyclidine (PCP) will exclude individuals from participation.
  • Unwilling to refrain from driving or operating heavy machinery for four hours after consuming study medication.
05

Study design

Phase
Phase 1 / Phase 2
Primary purpose
Screening
Allocation
Randomized
Intervention model
Parallel assignment
Masking
Triple (Participant, Investigator, Outcomes assessor)
Enrollment
199 participants (actual)

Study arms

  • Placebo comparator
    Placebo Cannabis

    Subjects will smoke cannabis with placebo THC (.02%) ad libitum

    Drug: Cannabis

  • Experimental
    Cannabis with 5.9% THC

    Subjects will smoke cannabis cigarettes with 5.9% THC ad libitum

    Drug: Cannabis

  • Experimental
    Cannabis with 13.4% THC

    Subjects will smoke cannabis cigarettes with 13.4% THC ad libitum

    Drug: Cannabis

Interventions

  • Participants will smoke a cannabis cigarette ad libitum as per their usual routine

    Also known as: Marijuana

06

What researchers measure

Primary outcomes

  1. Change in Composite Drive Score (CDS) From Pre-smoking Simulation

    The Composite Drive Score (CDS) is a z-score comprised of key variables from the simulator tasks (SDLP, speed deviation, and task accuracy during the modified Surrogate Reference Task (mSuRT); coherence from the car following task). This outcome reflects the change in CDS from the pre-smoking assessment, at each timepoint. The z-score indicates the number of standard deviations away from the mean from the baseline performance for the entire group (n = 191). A Z-score of 0 is equal to the mean of a reference population (in this case the pre-smoking performance for the entire group). Higher z-scores at each timepoint indicate worse performance (variables that went in the opposite direction were reflected in order to have all variables have the same direction). When examining the change in Composite Drive Score (this outcome variable), a higher score indicates a decline in performance (e.g., Time 2 minus Time 1).

    Time frame: Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking

Secondary outcomes

  1. Simulator: Standard Deviation of Lateral Position (SDLP)

    This measures the standard deviation of lateral (lane) position, or the degree to which the participant "swerves" within the road lane on the driving simulation during the modified Surrogate Reference Task (mSuRT). The range is from .39 to 3.33. A higher score indicates worse performance.

    Time frame: Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking

  2. Simulator: Speed Deviation

    The variability in speed during the modified Surrogate Reference Test (mSuRT). The speed is in miles per hour. Range is from .17 to 12.85. A higher score indicates worse performance.

    Time frame: Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking

  3. Simulator: Correct Hits on mSuRT

    The number of times the participant touched the correct stimulus (circle) on the iPad, during modified Surrogate Reference Task (mSuRT). Range is from 8 to 32. A higher score is a better score.

    Time frame: Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking

  4. Simulator: Car Following - Coherence

    Coherence is the correlation (0 to 1) between the participant and the lead car (which speeds up and slows down), representing the participant's ability to accurately speed up and slow down similarly to the lead car. Range of scores is from .01 to .97. A higher score is a better score.

    Time frame: Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking

  5. Simulator: Response Delay - Car Following

    Time delay (in seconds) in responding to changes in the lead car's speed. Range is from -5.8 to 6.0. A higher score indicates a worse score.

    Time frame: Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking

  6. Simulator: Distance From Lead Car - Car Following

    The outcome is distance from the lead car (in virtual feet) during the Car Following Task

    Time frame: Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking

  7. Tablet Assessment: Dual Attention Missed Switches

    The participant follows a moving target (square) with her/his finger, and switches to following a new stimulus when it appears in the corner of the screen. Each participant was classified as to whether he/she missed any of these switches during the trial. The outcome is the proportion of participants within each group who missed at least one switch. The range is from 0 to 1. Higher indicates a worse score.

    Time frame: Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking

  8. Tablet Assessment: Lane Tracking Standard Deviation

    The participant is to rotate the iPad in order to keep a round object in the center, between two lines (lanes). This measure is the standard deviation of the position of the round object during the task (in essence, how much "swerving" there is within the lane). The range is from 8.2 to 189.4. A higher score indicates worse performance.

    Time frame: Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking

  9. Tablet Assessment: Visual Spatial Learning Test Number Correct

    Assessment of short-term memory for abstract figures. The participant is to memorize abstract figures and their locations on a 3 x 3 grid. After initial viewing (10 seconds), the figures go away for either 4, 12, or 24 seconds. The participant is then to identify which figures were in the initial viewing (from a list at the bottom of the screen), and place them at the correct location. This is the number of correctly identified figures. The range is from 0 to 12. A higher score indicates better performance.

    Time frame: Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking

  10. Tablet Assessment: Time Estimation

    The participant is to estimate the amount of time that has passed while performing a secondary task. This outcome is the ratio of 1) the estimated time that has passed (seconds), divided by 2) the actual amount of time that has passed. The range is from 0.204 to 1.89. A higher score indicates a better performance.

    Time frame: Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking

  11. Tablet Assessment: Balance

    While standing and keeping their feet still, this is a measure of the participant's "sway", which is the total distance that the participant's body moved (in meters) from his/her initial vertical position. This was measured using an accelerometer placed on the participant's back. The range of scores is from .222 to 1.661. A higher score indicates worse performance.

    Time frame: Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking

  12. THC Concentrations: Correlation Between Blood and Oral Fluid

    Spearman's correlation between THC concentrations in whole blood and oral fluid. Higher scores are better.

    Time frame: Approximately 15 minutes post-smoking

  13. THC Concentrations: Correlation Between Whole Blood and Breath

    Spearman's correlation between THC concentrations in whole blood and breath

    Time frame: Approximately 15 minutes post-smoking

07

Results

Posted Jan 4, 2022

Participant flow

Participant flow — Overall Study
MilestonePlacebo CannabisCannabis With 5.9% THCCannabis With 13.4% THC
Started657064
Completed636662
Not completed242
Withdrew: Oral thc > 5ng/ml prior to treatment (indicating likely recent use)232
Withdrew: Withdrawal by subject010

Outcome measures

PrimaryChange in Composite Drive Score (CDS) From Pre-smoking Simulation

The Composite Drive Score (CDS) is a z-score comprised of key variables from the simulator tasks (SDLP, speed deviation, and task accuracy during the modified Surrogate Reference Task (mSuRT); coherence from the car following task). This outcome reflects the change in CDS from the pre-smoking assessment, at each timepoint. The z-score indicates the number of standard deviations away from the mean from the baseline performance for the entire group (n = 191). A Z-score of 0 is equal to the mean of a reference population (in this case the pre-smoking performance for the entire group). Higher z-scores at each timepoint indicate worse performance (variables that went in the opposite direction were reflected in order to have all variables have the same direction). When examining the change in Composite Drive Score (this outcome variable), a higher score indicates a decline in performance (e.g., Time 2 minus Time 1).

Time frame:
Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking
Reported as:
Mean · z-score
Change in Composite Drive Score (CDS) From Pre-smoking Simulation
z-scorePlacebo5.9% THC13.4% THC
Pre-smoke-.09 ± .64.12 ± .58.01 ± .52
30 minutes-.17 ± .61.46 ± .60.21 ± .60
1h 30min-.13 ± .61.40 ± .66.32 ± .59
3h 30min-.23 ± .59.15 ± .64.04 ± .57
4h 30min-.07 ± .66.09 ± .57.05 ± .59
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = <0.001
SecondarySimulator: Standard Deviation of Lateral Position (SDLP)

This measures the standard deviation of lateral (lane) position, or the degree to which the participant "swerves" within the road lane on the driving simulation during the modified Surrogate Reference Task (mSuRT). The range is from .39 to 3.33. A higher score indicates worse performance.

Time frame:
Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking
Reported as:
Mean · z-score
Simulator: Standard Deviation of Lateral Position (SDLP)
z-scorePlacebo5.9% THC13.4% THC
Pre-smoking1.09 ± .361.20 ± .361.11 ± 0.35
30 min1.07 ± .331.24 ± .361.19 ± .36
1h 30min1.06 ± .311.31 ± .391.23 ± .42
3h 30min1.10 ± .311.25 ± .351.20 ± .42
4h 30min1.10 ± .361.25 ± .371.18 ± .42
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = 0.022Raw data converted to z-score based on pre-smoking performance of entire sample.
SecondarySimulator: Speed Deviation

The variability in speed during the modified Surrogate Reference Test (mSuRT). The speed is in miles per hour. Range is from .17 to 12.85. A higher score indicates worse performance.

Time frame:
Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking
Reported as:
Mean · miles per hour
Simulator: Speed Deviation
miles per hourPlacebo5.9% THC13.4% THC
Pre-smoking2.13 ± 1.812.61 ± 1.972.63 ± 1.98
30 min2.03 ± 1.313.04 ± 1.712.99 ± 2.05
1h 30min2.49 ± 1.702.97 ± 1.933.01 ± 2.03
3h 30min2.15 ± 1.893.04 ± 2.162.65 ± 1.72
4h 30min2.34 ± 1.822.92 ± 2.102.34 ± 1.71
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = 0.283
SecondarySimulator: Correct Hits on mSuRT

The number of times the participant touched the correct stimulus (circle) on the iPad, during modified Surrogate Reference Task (mSuRT). Range is from 8 to 32. A higher score is a better score.

Time frame:
Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking
Reported as:
Mean · count of correct responses
Simulator: Correct Hits on mSuRT
count of correct responsesPlacebo5.9% THC13.4% THC
Pre-smoking30.7 ± 1.8029.9 ± 2.7630.6 ± 1.42
30 min30.9 ± 1.7128.7 ± 4.2330.3 ± 2.54
1h 30min30.3 ± 2.1629.6 ± 2.5630.4 ± 1.69
3h 30min30.4 ± 2.7329.7 ± 2.6130.7 ± 1.40
4h 30min31.0 ± 1.4430.3 ± 2.6531.1 ± 1.05
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized estimating equations model · p = 0.0503
SecondarySimulator: Car Following - Coherence

Coherence is the correlation (0 to 1) between the participant and the lead car (which speeds up and slows down), representing the participant's ability to accurately speed up and slow down similarly to the lead car. Range of scores is from .01 to .97. A higher score is a better score.

Time frame:
Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking
Reported as:
Mean · Correlation coefficient
Simulator: Car Following - Coherence
Correlation coefficientPlacebo5.9% THC13.4% THC
Pre-smoking.76 ± .19.73 ± .18.76 ± .15
30 min.79 ± .13.66 ± .20.71 ± .17
1h 30min.77 ± .16.65 ± .23.68 ± .19
3h 30min.80 ± .15.74 ± .18.74 ± .17
4h 30min.75 ± .16.74 ± .18.71 ± .17
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = 0.024
SecondarySimulator: Response Delay - Car Following

Time delay (in seconds) in responding to changes in the lead car's speed. Range is from -5.8 to 6.0. A higher score indicates a worse score.

Time frame:
Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking
Reported as:
Mean · seconds
Simulator: Response Delay - Car Following
secondsPlacebo5.9% THC13.4% THC
Pre-smoking2.92 ± 1.153.32 ± 1.233.58 ± 1.24
30 min2.86 ± 1.053.44 ± 1.153.55 ± 1.06
1h 30min2.80 ± .993.25 ± 1.283.49 ± 1.04
3h 30min2.61 ± 1.042.83 ± 1.053.23 ± 1.18
4h 30min2.93 ± 1.053.00 ± 1.103.50 ± 1.17
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = 0.716The outcome was standardized prior to analyses.
SecondarySimulator: Distance From Lead Car - Car Following

The outcome is distance from the lead car (in virtual feet) during the Car Following Task

Time frame:
Participants are assessed pre-smoking, and then approximately 30m, 1h 30m, 3h 30m and 4h 30m post-smoking
Reported as:
Mean · feet
Simulator: Distance From Lead Car - Car Following
feetPlacebo5.9% THC13.4% THC
Pre-smoking153 ± 41156 ± 41163 ± 35
30 min143 ± 36165 ± 39164 ± 39
1h 30min144 ± 34160 ± 38165 ± 36
3h 30min129 ± 33137 ± 37150 ± 34
4h 30min138 ± 34136 ± 37151 ± 36
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = 0.005The outcome was standardized prior to analysis.
SecondaryTablet Assessment: Dual Attention Missed Switches

The participant follows a moving target (square) with her/his finger, and switches to following a new stimulus when it appears in the corner of the screen. Each participant was classified as to whether he/she missed any of these switches during the trial. The outcome is the proportion of participants within each group who missed at least one switch. The range is from 0 to 1. Higher indicates a worse score.

Time frame:
Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking
Reported as:
Mean · Proportion of participants
Tablet Assessment: Dual Attention Missed Switches
Proportion of participantsPlacebo5.9% THC13.4% THC
Pre-smoking0.095 (0.039 to 0.202)0.145 (0.073 to 0.263)0.167 (0.087 to 0.290)
1 hour0.095 (0.039 to 0.202)0.194 (0.108 to 0.317)0.183 (0.099 to 0.309)
2 hours0.175 (0.095 to 0.295)0.161 (0.084 to 0.281)0.233 (0.138 to 0.363)
4 hours0.191 (0.106 to 0.313)0.177 (0.096 to 0.299)0.167 (0.087 to 0.290)
5 hours0.095 (0.039 to 0.202)0.129 (0.061 to 0.244)0.183 (0.099 to 0.309)
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized Estimating Equations model · p = .366
SecondaryTablet Assessment: Lane Tracking Standard Deviation

The participant is to rotate the iPad in order to keep a round object in the center, between two lines (lanes). This measure is the standard deviation of the position of the round object during the task (in essence, how much "swerving" there is within the lane). The range is from 8.2 to 189.4. A higher score indicates worse performance.

Time frame:
Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking
Reported as:
Mean · standard deviation of position
Tablet Assessment: Lane Tracking Standard Deviation
standard deviation of positionPlacebo5.9% THC13.4% THC
Pre-smoking26.9 ± 9.5330.9 ± 23.727.2 ± 9.67
1 hour28.7 ± 13.430.9 ± 15.732.1 ± 21.7
2 hours28.4 ± 10.327.6 ± 10.227.4 ± 10.4
4 hours28.1 ± 13.329.9 ± 15.528.6 ± 14.8
5 hours26.4 ± 10.825.4 ± 8.3925.3 ± 13.8
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = .225Outcome was log10 transformed prior to analyses.
SecondaryTablet Assessment: Visual Spatial Learning Test Number Correct

Assessment of short-term memory for abstract figures. The participant is to memorize abstract figures and their locations on a 3 x 3 grid. After initial viewing (10 seconds), the figures go away for either 4, 12, or 24 seconds. The participant is then to identify which figures were in the initial viewing (from a list at the bottom of the screen), and place them at the correct location. This is the number of correctly identified figures. The range is from 0 to 12. A higher score indicates better performance.

Time frame:
Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking
Reported as:
Mean · number of correct responses
Tablet Assessment: Visual Spatial Learning Test Number Correct
number of correct responsesPlacebo5.9% THC13.4% THC
Pre-smoking9.9 ± 2.39.7 ± 2.710.1 ± 2.2
1 hour9.1 ± 2.88.4 ± 2.69.3 ± 2.7
2 hours8.9 ± 3.18.7 ± 2.68.9 ± 2.7
4 hours8.5 ± 3.08.3 ± 2.98.8 ± 2.5
5 hours9.3 ± 2.98.5 ± 3.09.5 ± 3.0
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = .592The outcome was transformed using logit function prior to analyses. Model included treatment (3 groups), time (5 times), and their interaction.
SecondaryTablet Assessment: Time Estimation

The participant is to estimate the amount of time that has passed while performing a secondary task. This outcome is the ratio of 1) the estimated time that has passed (seconds), divided by 2) the actual amount of time that has passed. The range is from 0.204 to 1.89. A higher score indicates a better performance.

Time frame:
Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking
Reported as:
Mean · Ratio of estimated/actual time
Tablet Assessment: Time Estimation
Ratio of estimated/actual timePlacebo5.9% THC13.4% THC
Pre-smoking0.75 ± 0.190.83 ± 0.300.77 ± 0.22
1 hour0.79 ± 0.210.89 ± 0.300.85 ± 0.24
2 hours0.83 ± 0.200.96 ± 0.300.87 ± 0.27
4 hours0.85 ± 0.230.93 ± 0.230.86 ± 0.21
5 hours0.83 ± 0.200.89 ± 0.280.85 ± 0.21
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = .294
SecondaryTablet Assessment: Balance

While standing and keeping their feet still, this is a measure of the participant's "sway", which is the total distance that the participant's body moved (in meters) from his/her initial vertical position. This was measured using an accelerometer placed on the participant's back. The range of scores is from .222 to 1.661. A higher score indicates worse performance.

Time frame:
Participants assessed pre-smoking and 1 hour, 2 hours, 4 hours, and 5 hours after smoking
Reported as:
Mean · meters
Tablet Assessment: Balance
metersPlacebo5.9% THC13.4% THC
Pre-smoking0.358 ± 0.0580.360 ± 0.0670.356 ± 0.058
1 hour0.342 ± 0.0540.376 ± 0.0900.363 ± 0.129
2 hours0.351 ± 0.0530.394 ± 0.1610.414 ± 0.254
4 hours0.354 ± 0.0580.386 ± 0.1310.377 ± 0.133
5 hours0.368 ± 0.0590.371 ± 0.0540.365 ± 0.072
Statistical analysis
  • Placebo vs 5.9% THC vs 13.4% THC · Generalized least squares model · p = .144
SecondaryTHC Concentrations: Correlation Between Blood and Oral Fluid

Spearman's correlation between THC concentrations in whole blood and oral fluid. Higher scores are better.

Time frame:
Approximately 15 minutes post-smoking
Reported as:
Number · Spearman's rho
THC Concentrations: Correlation Between Blood and Oral Fluid
Spearman's rhoPlacebo5.9% THC13.4% THC
THC Concentrations: Correlation Between Blood and Oral Fluid0.217 (-0.034 to 0.443)0.414 (0.190 to 0.598)0.249 (-0.003 to 0.471)
Statistical analysis
  • Placebo · Spearman's correlation · p = 0.090
  • 5.9% THC · Spearman's correlation · p = .0006
  • 13.4% THC · Spearman's correlation · p = 0.053
SecondaryTHC Concentrations: Correlation Between Whole Blood and Breath

Spearman's correlation between THC concentrations in whole blood and breath

Time frame:
Approximately 15 minutes post-smoking
Reported as:
Number · Spearman's rho
THC Concentrations: Correlation Between Whole Blood and Breath
Spearman's rhoPlacebo5.9% THC13.4% THC
THC Concentrations: Correlation Between Whole Blood and Breath0.134 (-0.120 to 0.371)-0.258 (-0.472 to -0.015)-0.176 (-0.410 to 0.079)
Statistical analysis
  • Placebo · Spearman's correlation · p = 0.300
  • 5.9% THC · Spearman's correlation · p = 0.038
  • 13.4% THC · Spearman's correlation · p = 0.175

Adverse events

Collected over One day (acute administration). Non-serious events are listed at a 0% frequency threshold.

Adverse event summary by group
GroupDeathsSeriousOther
Placebo Cannabis0/65 (0%)0/65 (0%)2/65 (3.1%)
Cannabis With 5.9% THC0/70 (0%)0/70 (0%)15/70 (21.4%)
Cannabis With 13.4% THC0/64 (0%)0/64 (0%)5/64 (7.8%)
Most frequent other events
Showing 10 of 14
Most frequent other events
EventPlacebo CannabisCannabis With 5.9% THCCannabis With 13.4% THC
Heart Rate AbnormalCardiac disorders0/6512/701/64
DizzinessNervous system disorders0/653/703/64
Blood Pressure DecreasedVascular disorders0/653/701/64
AnxietyPsychiatric disorders0/652/700/64
NauseaGastrointestinal disorders0/652/701/64
SweatsNervous system disorders0/652/700/64
Blood Pressure IncreasedVascular disorders0/652/700/64
CoughRespiratory, thoracic and mediastinal disorders0/650/701/64
Swollen armInjury, poisoning and procedural complications0/650/701/64
Discomfort in armInjury, poisoning and procedural complications1/651/700/64

Baseline characteristics

Age, Continuous
Age, Continuous(years)Placebo5.9% THC13.4% THCTotal
Mean28.1 ± 7.330.7 ± 8.830.9 ± 8.629.9 ± 8.3
Sex: Female, Male
Sex: Female, Male(Participants)Placebo5.9% THC13.4% THCTotal
Female31192373
Male324739118
Race/Ethnicity, Customized
Race/Ethnicity, Customized(Participants)Placebo5.9% THC13.4% THCTotal
African American86418
Asian58417
Hispanic15192256
Indigenous5218
Multiracial2327
Non-Hispanic White28282783
Unknown0022
Region of Enrollment
Region of Enrollment(participants)Placebo5.9% THC13.4% THCTotal
United States636662191
08

Study locations

1 site
  • Center for Medicinal Cannabis Research, UC San Diego
    San Diego, California 92103, United States
09

References and documents

Publications

  • Hartman RL, Huestis MA. Cannabis effects on driving skills. Clin Chem. 2013 Mar;59(3):478-92. doi: 10.1373/clinchem.2012.194381. Epub 2012 Dec 7. PubMed 23220273 ↗
  • Papafotiou K, Carter JD, Stough C. An evaluation of the sensitivity of the Standardised Field Sobriety Tests (SFSTs) to detect impairment due to marijuana intoxication. Psychopharmacology (Berl). 2005 Jun;180(1):107-14. doi: 10.1007/s00213-004-2119-9. Epub 2004 Dec 24. PubMed 15619106 ↗
  • Fabritius M, Chtioui H, Battistella G, Annoni JM, Dao K, Favrat B, Fornari E, Lauer E, Maeder P, Giroud C. Comparison of cannabinoid concentrations in oral fluid and whole blood between occasional and regular cannabis smokers prior to and after smoking a cannabis joint. Anal Bioanal Chem. 2013 Dec;405(30):9791-803. doi: 10.1007/s00216-013-7412-1. Epub 2013 Nov 8. PubMed 24202191 ↗
  • Beck O, Stephanson N, Sandqvist S, Franck J. Detection of drugs of abuse in exhaled breath from users following recovery from intoxication. J Anal Toxicol. 2012 Nov-Dec;36(9):638-46. doi: 10.1093/jat/bks079. Epub 2012 Oct 7. PubMed 23045289 ↗
  • Marcotte TD, Heaton RK, Wolfson T, Taylor MJ, Alhassoon O, Arfaa K, Ellis RJ, Grant I. The impact of HIV-related neuropsychological dysfunction on driving behavior. The HNRC Group. J Int Neuropsychol Soc. 1999 Nov;5(7):579-92. doi: 10.1017/s1355617799577011. PubMed 10645701 ↗
  • Marcotte TD, Rosenthal TJ, Roberts E, Lampinen S, Scott JC, Allen RW, Corey-Bloom J. The contribution of cognition and spasticity to driving performance in multiple sclerosis. Arch Phys Med Rehabil. 2008 Sep;89(9):1753-8. doi: 10.1016/j.apmr.2007.12.049. PubMed 18760160 ↗
  • Hubbard JA, Hoffman MA, Ellis SE, Sobolesky PM, Smith BE, Suhandynata RT, Sones EG, Sanford SK, Umlauf A, Huestis MA, Grelotti DJ, Grant I, Marcotte TD, Fitzgerald RL. Biomarkers of Recent Cannabis Use in Blood, Oral Fluid and Breath. J Anal Toxicol. 2021 Sep 17;45(8):820-828. doi: 10.1093/jat/bkab080. PubMed 34185831 ↗
  • Hoffman MA, Hubbard JA, Sobolesky PM, Smith BE, Suhandynata RT, Sanford S, Sones EG, Ellis S, Umlauf A, Huestis MA, Grelotti DJ, Grant I, Marcotte TD, Fitzgerald RL. Blood and Oral Fluid Cannabinoid Profiles of Frequent and Occasional Cannabis Smokers. J Anal Toxicol. 2021 Sep 17;45(8):851-862. doi: 10.1093/jat/bkab078. PubMed 34173005 ↗
  • Hubbard JA, Smith BE, Sobolesky PM, Kim S, Hoffman MA, Stone J, Huestis MA, Grelotti DJ, Grant I, Marcotte TD, Fitzgerald RL. Validation of a liquid chromatography tandem mass spectrometry (LC-MS/MS) method to detect cannabinoids in whole blood and breath. Clin Chem Lab Med. 2020 Apr 28;58(5):673-681. doi: 10.1515/cclm-2019-0600. PubMed 31527291 ↗
  • Sobolesky PM, Smith BE, Hubbard JA, Stone J, Marcotte TD, Grelotti DJ, Grant I, Fitzgerald RL. Validation of a liquid chromatography-tandem mass spectrometry method for analyzing cannabinoids in oral fluid. Clin Chim Acta. 2019 Apr;491:30-38. doi: 10.1016/j.cca.2019.01.002. Epub 2019 Jan 4. PubMed 30615854 ↗
  • Marcotte TD, Umlauf A, Grelotti DJ, Sones EG, Mastropietro KF, Suhandynata RT, Huestis MA, Grant I, Fitzgerald RL. Evaluation of Field Sobriety Tests for Identifying Drivers Under the Influence of Cannabis: A Randomized Clinical Trial. JAMA Psychiatry. 2023 Sep 1;80(9):914-923. doi: 10.1001/jamapsychiatry.2023.2345. PubMed 37531115 ↗
  • Marcotte TD, Umlauf A, Grelotti DJ, Sones EG, Sobolesky PM, Smith BE, Hoffman MA, Hubbard JA, Severson J, Huestis MA, Grant I, Fitzgerald RL. Driving Performance and Cannabis Users' Perception of Safety: A Randomized Clinical Trial. JAMA Psychiatry. 2022 Mar 1;79(3):201-209. doi: 10.1001/jamapsychiatry.2021.4037. PubMed 35080588 ↗

Study documents

  • Protocol and statistical analysis plan · May 21, 2020

Documents are hosted by the registry — open the source record to download them.

Individual participant data

Plan to share: Yes — Data to facilitate meta-analyses

Supporting information: Study protocol, Statistical analysis plan, Informed consent form

Time frame: Upon manuscript publications

Access criteria: Approved researchers

10

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Jan 4, 2022, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
11

Registry details

Key details

Study ID
NCT02849587
Responsible party
Thomas D. Marcotte, PhD (Professor, University of California, San Diego) — Principal investigator
First posted
Jul 29, 2016
Start date
Feb 24, 2017
Primary completion
Jun 17, 2019
Completion
Jun 17, 2019
Results posted
Jan 4, 2022
Last update
Jan 4, 2022

Study contacts

Thomas D Marcotte, PhD
principal investigator · University of California, San Diego

Oversight

Data monitoring committee
Yes
FDA-regulated drug
Yes
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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Studies of the drug tested here: Cannabis sativa subsp. indica TOP

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