Introduction
This
literature review will examine marijuana’s effects on driving performance,
determining impairment levels, and the use and effectiveness of Drug Recognition
Experts (DREs) and roadside testing in making determinations of driving under
the influence of marijuana. Marijuana use and acceptance is on the rise and
this has contributed to more incidence of drugged driving. 34 states have
legalized medical marijuana, and while some strains are produced with
relatively higher CBD to THC ratios to optimize their medical use, some strains
ostensibly sold for medical purposes may have a relatively high THC level that
has the potential for misuse. Legalization at the state level has been
expanding. Currently 11 states and Washington D.C. have legalized recreational
marijuana, while in 15 states decriminalization has been an ongoing process. When
combined with a change in public perception, this can lead to increased
incidence of driving under the influence of marijuana. A 2001 study examining
roadside testing found that of 209 positive drug tests, 113 indicated cannabis
(Steinmeyer, et al). A ten-year Swedish study found measurable THC levels
between 18 and 36 percent of suspected drugged drivers (Jones, et al. 2008) and
a UK lab sample of over 3,600 suspected drugged drivers showed 58% were
positive for cannabis (Wolff and Johnston, 2014).
What was once an
underlying marijuana subculture decades ago, has now reached a new level of
acceptance in overall society as research has dispelled some of the myths about
marijuana use and its negative consequences, and revealed suggested medical
uses and benefits. Marijuana awareness, and its use, are also becoming more
normalized with depictions in popular media in the form of news reports and
specials, programming focusing both specifically and tangentially on its use,
movie and TV characters using marijuana in a normalized context similar to how
drinking has been portrayed, and websites that describe and rate different
strains of marijuana as well as provide growing and usage tips. This
normalization may contribute to some users minimizing the risks of driving
while high.
Research
into Driving Effects
Marijuana users have
believed, and research has shown, that frequent users who are experienced
drivers are able to compensate to a certain degree for marijuana’s effects
while driving (Robbe, 1998; Kelly, 2004; Sewell, et al, 2009; Wolff and
Johnston, 2014; Micallef et al, 2018) and some users forward the argument that
driving high is safer than driving drunk (Kelly, 2004) . However, marijuana can
impair driving performance, but typically in a way that differs from the effect
of alcohol on driving performance. In research, impairment identification
testing while under the influence of THC typically measures car following
(maintaining distance with a car under varying speeds) and the standard
deviation in lateral position (SDLP), or lane tracking (amount of weaving off
center within the lane), as well as some other driving related tasks. Studies
typically provided THC in two ways, either in 100-300 microgram/kilogram of
subject body weight, or in 10-30 milligram doses of THC, irrespective of
subject body weight.
Many studies when
examining driving performance find significant effects on car following and
SDLP. Robbe (1998) found at higher doses of THC tracking and following were
significantly negatively affected compared to a control group and Ramaekers et
al’s (2000) research revealed that low doses only moderately impair drivers
actual driving performance in those areas Micallef, et al (2018), also found
THC had a significant effect on lane tracking. However, a 2001 Netherlands
study didn’t find any significant difference in visual search frequency with a
100 microgram/Kg THC dose (Lamers, et al). In 2009, Sewell and colleagues
reviewed marijuana driving impairment studies and found, beside marijuana
effects on driving being dose dependent, that there were differences in the
type of impairment between alcohol and marijuana. Marijuana’s effects are more
pronounced with tasks requiring a higher automatic driving function as opposed
to alcohol’s more pronounced effects on conscious, cognitive function. SLP is affected
by marijuana and not subject to compensatory behavior the way other driving
functions are, and other effects like poor speedometer monitoring, increased
decision time in passing, and increased time in responding to a light change or
sudden sound were also present. Alcohol was implicated more in pursuit
tracking, divided attention, signal detection, hazard perception, and lowered
concentration, reaction time, and hand-eye coordination.
Research has shown the
driving impairment effects are dose, and frequency of past use, dependent, as
well as demonstrating significant effects differences from placebo or control
groups at the THC levels used for testing. But how marijuana contributes to car
crashes also requires examination. In 2014, Romano and Pollini, examining 12
years of crash data, found 26% of single car fatal crashes involved a drug
other than alcohol, with cannabinoids present in approximately a quarter of
those cases. However, previous work has not provided a clear indication of marijuana’s
influence. Kelly (2004) in a review of driving studies found inconsistent
associations of THC with traffic accident involvement. A 2005 multivariate
study found that once accounting for things like speed, seatbelt use, and BAC,
marijuana use was no longer a significant factor in car crash injury. However,
it was a significant factor in those that identified as habitual marijuana
users (Blows, et al). In 2014, Wolff and Johnston reviewing a meta-analysis
showed that drivers were twice as likely to be involved in a car accident with
a THC blood plasma level of 5 micrograms/liter. Huestis (2015) in her review of
two recent meta analyses found a significantly increased crash risk (2-2.6
times more likely) with a measurable amount of THC and a six-fold increased
risk at a 5 microgram/liter level. However, in 2016 Rogeberg and Elvik found that
marijuana involvement in crash risk is low to moderate, similar to a BAC level
of .04-.05.
While the possibility of
increased risk of car crashes may yet to be determined because of dose
dependent effects and other factors, research has been consistent on the
effects of combining a small amount of alcohol with marijuana. BACs of .04-.05
when combined with even low levels of THC significantly increased the severity
of driving impairment, resulting in impairment equal to a BAC of .08-1.9
(Robbe, 1998; Ramaekers, et al, 2000; Blows et al, 2005; Sewell, 2009; Huestis,
2015).
Determining
and Setting Intoxication and Impairment Standards and Limits
As a
practical application, identifying and utilizing THC levels in determining
impairment for drivers in the real world is important for state legislatures
and municipalities in legalization states, as well as for those adjoining states,
and other states considering legalization, as the country continues to progress
toward greater medical and recreational legalization. Standards are typically
expressed as THC parts per volume of oral fluid or serum/plasma concentrations,
either as nanograms/milliliter or as micrograms/liter (note that these are
equivalent measures-1 nanogram/milliliter = 1 microgram/liter). Setting driving
limits typically take two approaches; a per se approach, where any amount of
THC above a preset limit indicates a violation of the law, similar to the .08
BAC limit currently used in the U.S. but could also resemble a zero-tolerance
level where any detectable THC amount is a violation of law. The other approach
is to determine a THC fluid concentration that indicates impairment, often
based on driving performance deficits comparable to a specified BAC level.
The approaches vary
around the world, and approaches and levels can change or be set by a
combination of research, politics, and public opinion. In 2007, a toxicology
lab survey in 24 states found cutoff and confirmation levels of THC ranged from
2 to 70 ng/ml. While recommending that a 2 ng/ml confirmation level be used in
drugged driving investigations, it is a level based more on good analytic
methodology and lab practice than in an indication of impairment (Farrell, et
al, 2007). While European workplace testing typically has a cutoff (the drug
screening point where a concentration above the cutoff indicates a positive
test for the substance, and below that point is a negative result) of 10 ng/ml
(Moore, 2012) European driving limits varied widely; Sweden (a zero-tolerance
country) sets a cutoff at .3 micrograms/liter, Germany-.5, France-1.0,
Norway-1.3(declaring it an impairment limit), Switzerland-1.5 (declaring it a
prosecution limit), and Portugual-3. A Swiss study of drug impaired drivers
found that a 5 microgram/liter fluid level correlated to observable driving
impairment (Wolff and Johnston, 2014). However, a German study from 2007
suggested a range of 7-10 micrograms/liter as a non-zero per se limit after
finding that it correlated to an impairment comparable to a .05 BAC and that
concentrations below 10 micrograms/liter were not associated with increased
accident risk (Grotenherman, et al). Huestis (2015), in reflecting on an appropriate
measure for the U.S. suggests a two-tiered approach, similar to what is used in
some European countries and Australia. that when combined with driver education,
has been shown to deter drugged driving. It provides for a small fine and
driver education for exceeding a per se limit and provides for a more severe
penalty and criminal prosecution for demonstrated impairment.
Testing
for Marijuana Intoxicated Drivers
Regardless
of where the cutoff points are established, the concern for law enforcement is
utilizing the tools at their disposal to identify drivers who are intoxicated or
impaired. Drug Recognition Experts (DREs) and roadside testing can be utilized both
on active patrol and at driving checkpoints. DRE use is expanding and the
options for roadside testing include oral fluid (saliva) testing with point of
collection testing (POCT) that can provide results in minutes. Time can be an
important factor as THC concentration levels peak approximately 15 minutes
after smoking but then go on a rapid decline over the first hour after smoking,
and drops even further between one and three hours after smoking. However,
while THC levels drop off quickly, the subjective high of the user declines at a
much slower rate, meaning people who have a broad range of THC levels may
exhibit the same level of being high, and thus impairment.
DRE Effectiveness
According
to Brown, (2001), the DRE program was first started as a partnership between the
LAPD and National Highway Traffic Safety Administration (NHTSA) in the 80’s and
the program became more popular in the 90’s, resulting in the majority of states
utilizing DREs in law enforcement agencies. The International Association of
Chiefs of Police (IACP) is the national certifying agency for DREs and
instructors.
There are three phases of
training and DREs must re-certify based on the past two years of their
evaluations. Typically, DREs are called in during a DUI traffic stop when the
suspected driver appears intoxicated from something other than alcohol. The DRE
evaluation is a 12-step process that involves a BAC test, pulse checks, eye
examinations, temperature, muscle rigidity, and ingestion exams, interviews
with the suspect and arresting officer, a standardized field sobriety test
(SFST), the DRE’s opinion, and a toxicology test. Some studies have
demonstrated moderate to high effectiveness in determining intoxication and
drug classification. A 1995 Phoenix PD study compared DRE opinions to the
toxicology reports and found DREs identified at least one of the drugs in 91%
of the samples confirmed as containing drugs and overall the DREs impaired decisions
were correct 83.5 %. Marijuana was the drug most often missed though, and the
study notes it’s unknown whether this was due to DRE accuracy, or the time
course of the drug (Burns and Adler, 1995). A 2002 study found that when DREs
reports were stripped of all information except DRE observations, the DREs
tested were 95% accurate in determining intoxication and 81% accurate in
identifying the cannabis category. Beirness, et al (2009) examined over 1,300
Canadian DRE evaluations and found the DREs were 95% accurate in determining
true positives, 80% accurate in determining true negatives, and 92% accurate on
drug classification, compared to lab results.
However, in 2009 Porath-Waller,
Beirness, and Beasley were examining whether a simpler approach to the DRE
evaluation could be utilized, focusing on the most relevant of the twelve
physiological testing criteria for the three most common classifications; stimulants,
cannabis, and narcotics. They found nine of the criteria were more predictive
of drug category including pulse rate,
condition of the eyes and eyelids, lack of convergence, hippus, reaction to
light, rebound dilation, systolic blood pressure, and the presence of injection
sites with an overall accuracy of 81% across the three drug classifications,
however only 72% accuracy in identifying cannabis.
Other
research has focused on the SFST. In 2014, Porath-Waller and Beirness examined
three components of the SFST in determining THC impairment; the Horizontal Gaze
Nystagmus (HGN), the One Leg Stand (OLS), and the Walk And Turn (WAT). Their
results showed only the OLS was a significant predictor of THC. In a two-year
study,
Declues et al (2016) found that while SFTSs are sensitive to marijuana
impairment that there was no correlation between SFTS performance and an
average 9 ng/ml THC level, however the number of SFTS cues were greater the higher
the THC level. Their study found that the WAT was a better indicator of
marijuana intoxication that the OLS (contrary to DRE evaluation studies) and
the Lack Of Convergence (circular tracking with eye cross) was also a strong
indicator. Hartman et al (2016) arrived at somewhat different conclusions. In
their study they found no difference in SFST performance between those above
and below 5 ng/ml. They found the Finger To Nose test was the best predictor of
cannabis intoxication, along with MRB eyelid tremors, OLS sway, pupil rebound
dilation and two or more WAT cues.
Brown, in 2001, did raise
an issue related to the accuracy of DRE’s and whether they can provide valid,
reliable, expert testimony. He argues because DREs are labeled as experts and
are construed by juries to be giving expert testimony then the basis of their
evaluations should be subjected to Daubert or Frye tests of evidence
admissibility. Brown considers the program would or should not pass these tests
as they have not faced peer reviewed evaluations, or general acceptance in the
relevant scientific community. However, some court rulings have concluded that
the twelve-step evaluation is not scientifically novel enough to warrant
putting it to the test of admissibility. Brown believes that with reviews of
different DRE programs indicating correct hit rates of between 47 and 86%, and
with only a 75% correct hit rate needed for re-certification, that DRE
evaluations should not be considered reliable scientific, technical, or
specialized knowledge and should continue to face challenges of admissibility
in court.
ROADSIDE TESTING
THC can be found in high
levels in the saliva immediately after smoking, and similar to blood serum
levels, declines quickly in the first hour and steadily downward over a few
hours (Cone, 1993). Roadside testing has focused on oral fluid testing as
opposed to urine or blood for a number of reason including, it is less
intrusive, a smaller amount of fluid is needed for a sample, it’s easier to administer,
can identify parent drugs, not just metabolites, has a close correlation to
serum drug concentrations, and provides quicker results (Cone, 1993;
Verstraete, 2005; Bosker, 2009; Huestis, 2011). A 2001 German study of roadside
testing found they were 97.6% accurate compared to lab results, with no false
negatives and only 2.4% false positives. In a 2009 Australian study of random
roadside testing, cannabis was the third most common drug, found in 26% of
drugged drivers. Their results showed that oral fluid testing correctly
identified targeted drugs 98% of the time.
But there are some
caveats to oral fluid testing. Delays in testing may yield negative results if
cutoffs are set too low, (Cone and Huestis, 2007) and there is a lack of
conclusive evidence tying THC levels to the subjective high, (Cone, 1993) and thus,
possible impairment. Verstraete (2005) considers that there should be a better
correlation between drug presence and impairment, better discrimination for
cannabis, better proficiency in testing, and safeguards against passive
contamination before oral fluid testing will be forensically reliable. Earlier
devices suffered from poor accuracy and current devices still lacked adequate
reliability (Boker et al, 2009) but Huestis (2011) predicts that the move to
oral fluid testing will expand as better tests become available.
Evaluations of more
recent devices provided varying results. A 2007 study of the RapiScan tester
demonstrated a 96% accuracy for positive samples and 100% accuracy for negative
samples but was more sensitive to stimulants than cannabis (Dewey et al, 2007).
Couch and associates’ 2008 study of ten different tests including RapiScan,
DrugWipe, and OraLab showed nine of the ten devices were accurate in
identifying THC but all had a much higher cutoff than the 4 ng/ml suggested by
SAMSHA. A European Union 2011 study evaluated eight testers on sensitivity
(ability to detect a positive result), specificity (distinguishing between
negative and positive samples) and accuracy (the rate of true results compared
to false results). Cutoff levels for the devices varied between 5 to 100 ng/ml.
Specificity ranged between 90 and 100% but sensitivity was poor, ranging from
20-60%, resulting in accuracy between 78-88% for the five best performing
devices. None of these multidrug testers had over 80% in each of the three
measurement categories. A 2012 Italian study of four different devices found
the sensitivity ranged from 38-92% accurate compared to lab results. In 2019, a
Brazilian study analyzed four devices for ease of use, operational success, and
acceptable analysis and collection time, using feedback from patrol officers.
Three of the four devices were rated in the 80th percentile in these
categories. To complicate things, some drugged drivers may be trying to
confound the test by using different fluids or mouthwashes to dilute a possible
sample. de Castro (2014) found that a commercial product designed to dilute for
the test was ineffective, but a plain water mouthwash at 3 hours after use was
effective in dropping THC to below 25 ng/ml. However, developments continue to
be made in oral fluid testing. Plouffe et al (2017) describe a new roadside
testing technique they were developing, utilizing existing fluorescent
scanners, that’s highly reliable, can utilize a cutoff of 1 ng/ml or lower, and
from sample insertion to readout, take less than 10 minutes to complete.
IMPLICATIONS
As
improvements are made in oral fluid roadside testing, the role of a DRE may be
scaled back to assisting in drug investigations or in cases involving an indeterminate
drug, as may be the case as synthetic designer drugs continue to be developed
and find their way into the recreational market. But in order to make oral
fluid testing a viable means of deterring, detecting and stopping drugged
driving, yet distinguishing from residual THC in the system that has no effect
on driving performance, reasonable, science-based decisions will need to be
made regarding per se or impairment levels, and the proper testing device for
the intended purpose, such as the suitability of using the device for a DUID
checkpoint. Jurisdictions should also be prepared for legal challenges to the
admissibility of testimony from DREs as well as challenges to the reliability
of some testing devices. Despite some drawbacks still present in oral fluid
testing devices and the validity in determining impairment by THC level, it is
the direction that roadside testing is moving. As such, jurisdictions and
legislatures will need to stay current on the best testing equipment, and best
practices and research, in this continually emerging field.
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