The “Next Day” Effects of Cannabis Use: A Systematic Review
Lambert Initiative for Cannabinoid Therapeutics and The University of Sydney, Sydney, New South Wales, Australia.
Brain and Mind Centre, The University of Sydney, Sydney, New South Wales, Australia.
School of Psychology, Faculty of Science, The University of Sydney, Sydney, New South Wales, Australia.
Abstract
Background:
Δ9-Tetrahydrocannabinol (THC), the main intoxicating component of cannabis, can cause cognitive and psychomotor impairment. Whether this impairment is still present many hours or even days after THC use requires clarification. Possible “next day” effects are of major significance in safety-sensitive workplaces. We therefore conducted a systematic review of studies investigating the “next day” effects of THC.
Methods:
Studies that measured performance on safety-sensitive tasks (e.g., driving, flying) and/or neuropsychological tests >8 h after THC (or cannabis) use using interventional designs were identified by searching two online databases from inception until March 28, 2022. Risk of bias (RoB) was evaluated using the relevant Cochrane tools. Results were described in terms of whether THC had a significant effect on performance relative to the primary comparator (i.e., placebo or baseline, as appropriate).
Results:
Twenty studies (n=458) involving 345 performance tests were reviewed. Most studies administered a single dose of THC (median [interquartile range]: 16 [11–26] mg) and assessed performance between >12 and 24 h post-treatment. N=209/345 tests conducted across 16 published studies showed no “next day” effects of THC. Nine of these 16 studies used randomized, double-blind, placebo-controlled designs. Half (N=8) had “some” RoB, and half (N=8) had a “high” RoB. Notably, N=88 of these 209 tests failed to demonstrate “acute” (i.e., <8 h post-treatment) THC-induced impairment. N=12/345 tests conducted across five published studies indicated negative (i.e., impairing) “next day” effects of THC. None of these five studies used randomized, double-blind, placebo-controlled designs and all were published >18 years ago (four, >30 years ago). Three had “some” RoB, and two had a “high” RoB. A further N=121/345 tests indicated “unclear” “next day” effects of THC with insufficient information provided to assess outcomes. The remaining N=3/345 tests indicated positive (i.e., enhancing) “next day” effects of THC.
Conclusions:
Some lower quality studies have reported “next day” effects of THC on cognitive function and safety-sensitive tasks. However, most studies, including some of higher quality, have found no such effect. Overall, it appears that there is limited scientific evidence to support the assertion that cannabis use impairs “next day” performance. Further studies involving improved methodologies are required to better address this issue.
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Keywords: cannabis, THC, cannabinoids, impairment, cognitive function, driving
Article notes
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Collection date 2023 Feb.
Introduction
Two hundred million people use cannabis each year.1 This includes those using cannabis for its euphorigenic effects (i.e., so-called “recreational” users) and, increasingly, those using it to treat medical conditions such as chronic pain, insomnia, and anxiety.2
The potential harms associated with cannabis use have been debated over many decades. One ongoing concern is that the major cannabis constituent, Δ9- tetrahydrocannabinol (THC), can induce intoxication and impair cognitive and psychomotor performance (e.g., reaction time, working memory, divided attention),3 increasing the risk of error, accident, and injury when operating a motor vehicle or engaging in other safety-sensitive tasks.4–6 Indeed, epidemiological studies suggest that “THC-positive” drivers are between ∼1.1 and 1.4 times more likely to become crash-involved than other drivers.7
The duration of THC-induced impairment, or length of time an individual should wait following cannabis use before performing safety-sensitive tasks, is a critical issue. A recent meta-regression analysis3 concluded that there was a “window of impairment” extending from ∼3 to 10 h after THC use, with the exact duration dependent on the following: (1) dose: higher THC doses produced longer lasting impairment; (2) route of administration: oral THC produced longer lasting impairment than inhaled THC (e.g., smoked, vaporized), owing to the fact that gastrointestinal absorption is slower than pulmonary absorption8,9; and (3) regularity of cannabis use: occasional cannabis users became more impaired than regular cannabis users (who appear to be more tolerant to the impairing effects of THC10). This review did not, however, include performance tests conducted >12 h after THC use.
Some government agencies and experts in occupational safety caution that THC-induced impairment may persist for >24 h and recommend that individuals avoid performing safety-sensitive tasks for at least this long after cannabis use.11,12 This can impact upon those who are reliant on driving for their work and/or family life, and upon individuals employed in safety-sensitive positions (e.g., transit and construction workers, defense personnel), who may use cannabis “off-duty” (e.g., in the evening, on the weekend) to treat conditions such as insomnia and chronic pain. However, such advice does not appear to have been informed by a comprehensive review of the scientific evidence.
We therefore conducted a systematic review to better understand the “next day” (i.e., >8 h) effects of THC use on cognitive function and safety-sensitive tasks.
Methods
The methods of this review were developed in accordance with the Cochrane Handbook for Systematic Reviews of Interventions (Version 6.2, 2021).13
Literature search
Relevant studies were identified by searching the online databases Scopus and Web of Science (Thomas Reuters) from inception until March 28, 2022, using the Boolean expression in Supplementary File S1. Two investigators (D.M. and A.S.) independently screened all titles and abstracts against the following inclusion criteria: (1) English language; (2) full-length article; (3) original research; (4) interventional design; and (5) THC administration. Suitable records were then screened for eligibility by full text (see “Eligibility criteria” section). The final decision to include (or discard) a study was made between these two investigators; discrepancies were resolved in discussion with a third investigator (I.S.M.). One investigator (D.M.) also hand-searched the reference lists of the included publications and two previous reviews3,14 to ensure all relevant articles were captured.
Eligibility criteria
Studies that measured performance on “safety-sensitive” tasks (e.g., simulated or on-road driving performance, simulated aeroplane flying) and/or discrete neuropsychological tests > 8 h post (last)-THC (or cannabis) use using an interventional experimental design (any)15 were eligible for inclusion. The >8-h interval was selected to represent a typical overnight “recovery” period16 and to minimize overlap with a previous review investigating the shorter-term effects of THC (i.e., ≤12 h).3 No “upper limit” was imposed. All participant populations (e.g., clinical, “healthy”) and comparator conditions (e.g., placebo, baseline) were accepted. However, studies were excluded if THC was co-administered with another treatment (excluding placebo treatments, other cannabinoids or cannabis constituents, tobacco, or participants' usual medication) or if results were reported in another included article. Only full-length, English-language, original research articles published in scientific journals were accepted.
Note that if a study contained multiple “intervention arms,” more than one of which was eligible for inclusion, the separate “arms” were treated as discrete “studies,” termed trials, identifiable by the additional letters (e.g., a–d) in the citation.
Performance outcomes
All objective outcomes measured on safety-sensitive tasks and discrete neuropsychological tests >8 h post-THC administration were accepted. Outcomes measured ≤8 h post-THC administration (on eligible performance tests) were also included. Indeed, these data were used to determine whether the performance tests administered >8 h post-treatment were sensitive to the “acute” (i.e., <8 h post-treatment) effects of THC.
Quality assessment
Risk of bias (RoB) in included studies was evaluated by two independent assessors (D.M. and A.S.) using (1) the Revised Cochrane Risk of Bias tool (RoB 2.0)17 and (2) the RoB 2.0 for crossover trials,18 as appropriate. Both tools examine five potential sources of bias, that is, bias arising from (1) the randomization process; (2) deviations from the intended intervention; (3) missing outcome data; (4) measurement of the outcome; and (5) selective outcome reporting. The latter also examines bias arising from period or carryover effects. Both tools generate an overall “risk rating” (i.e., “low risk,” “some concerns,” “high risk”).
Data extraction
The extracted data included the following: (1) study design; (2) participant characteristics (e.g., age, sex, body weight, health status, cannabis use behavior); (3) treatment characteristics (e.g., type, composition, route of administration, THC dose); (4) task characteristics (e.g., test, outcomes, number of assessments, length of time between THC administration and the performance test[s]); and (5) standardization procedures employed, that is, the methods used to control participants' pre-trial and “within-trial” (i.e., up until the >8 h post-treatment assessment) sleep behavior and cannabis, alcohol, caffeine, and other psychoactive drug use. The latter were considered important as they have been shown to influence cognitive and psychomotor performance.3,19–21
Data synthesis
The results of the included studies were synthesized qualitatively, that is, described in terms of whether THC was found to have a statistically significant effect (i.e., p<0.05) on each performance test (i.e., any one of its outcome measures) relative to the primary comparator, taken as placebo in placebo-controlled trials and baseline (i.e., pre-treatment) elsewhere. If an outcome was analyzed within a complex model (e.g., including three or more treatments and[or] other factors, e.g., time) and no main effect of treatment or relevant interaction(s) was observed, the effect was assumed to be nonsignificant. If a main effect of treatment or relevant interaction was observed, statistical significance was ascertained on the basis of post-hoc comparisons.
The results of post-hoc comparisons on main effects of treatment that included a time parameter were generalized across all included time points unless the individual time points were compared by treatment or the comparison incorporated baseline (i.e., pre-treatment) data (in the latter case, the comparison was considered ambiguous). If post-hoc comparisons were not performed, or there was any ambiguity in the reported result, the statistical significance of the effect was not presented in this review. Meta-analysis was not performed as studies often failed to report (or graph) the information required to calculate an effect estimate (most studies [80%] were also published >10 years ago [65%, >20 years ago], making it difficult to retrieve the missing data).
Each neuropsychological test was reviewed and categorized into one of the following cognitive domains as previously demonstrated by McCartney et al3 and shown in Supplementary Table S1: (1) divided attention; (2) executive function; (3) information processing; (4) tracking performance; (5) reaction time; (6) motor function; (7) sustained attention; (8) working memory; (9) perception; (10) learning and(or) memory; and (11) spatial reasoning.
The terms used to describe participants' cannabis use behavior (e.g., daily, weekly–daily, monthly, etc.) are also as per McCartney et al3 and defined in Supplementary Table S2. These categories were further collapsed into two main groupings: regular cannabis users (which included populations of daily users, weekly users, weekly–daily users) and other cannabis users (all other populations) to aid in synthesizing the available literature.
Note that the length of time between THC administration and the beginning of the performance test was calculated from: (1) the last THC exposure if more than one dose was administered before the performance test; and (2) the beginning of the “battery” if multiple tests were administered in succession and their individual start times were not reported.
Results
Overview of included studies
Twenty studies (n=458 participants; 79% male, excluding studies that did not report the sex of their participants) were included in this systematic review. These studies administered a total of 345 performance tests (i.e., across all trials and time points >8 h post-treatment). The study selection process is detailed in Supplementary File S1.
The characteristics of the included studies are summarized in Table 1. Briefly, most studies used randomized (N=11) or “nonrandomized” (i.e., randomization was not reported; N=5) double-blind, placebo-controlled designs; however, three were single blind and one used a “pre-/post-treatment” design. All included “healthy” participants, only (i.e., no studies of clinical populations were eligible for inclusion). Other (i.e., mostly occasional) cannabis users and populations with an average age ≤30 years were studied more often than regular (i.e., weekly, or more often) cannabis users and those with an average age >30 years, respectively (Table 1). Most studies administered THC by smoking (N=13); the remainder did so through oral ingestion (N=7) (all, but three22–24 gave a single dose of THC).
| Studies (N) or participants (n) | Citations | |
|---|---|---|
| Study design | ||
| Randomized, DB, PC | N=11 | 23,25,26,28,29,31,34–37,39 |
| Nonrandomized,a DB, PC | N=5 | 22,27,30,32,38 |
| Nonrandomized, SB,b PC | N=3 | 24,33,40 |
| Pre-/post-trial | N=1 | 41 |
| Participant characteristics | ||
| Male | n=297 | — |
| Female | n=79 | — |
| Sex not specified | n=82 (N=4) | 31,32,40,41 |
| Average age ≤30 years | N=15 | 22–24,26,28–31,34–39,41 |
| Average age >30 years | N=4 | 25,31,32,40 |
| Average age not specified | N=2 | 27,33 |
| “Regular” cannabis usersc | N=4 | 22,28,29,37 |
| “Other” cannabis usersc | N=16 | 23–27,30–36,38–41 |
| Healthy population | N=20 | 22–41 |
| Treatment characteristics | ||
| Smoked cannabis or THC | N=13 | 22–24,28–31,33,35,37,38,40,41 |
| Ingested cannabis or THC | N=7 | 25–27,32,34,36,39 |
| THC dose unknown | N=5 | 22–24,30,35 |
| THC dose (mg) (median [IQR]) | 16 [11–26]d | — |
| Type of performance teste | ||
| Divided attention | N=6 | 22,25–27,30,33 |
| Executive function | N=4 | 23,30,34,35 |
| Information processing | N=11 | 22–28,30,33,34,36 |
| Tracking performance | N=1 | 33 |
| Reaction time | N=5 | 22,23,27,34,35 |
| Motor function | N=3 | 28,30,35 |
| Sustained attention | N=4 | 27,28,34,37 |
| Working memory | N=6 | 22,23,30,34–36 |
| Perception | N=3 | 22,24,30 |
| Learning and(or) memory | N=9 | 22–25,27,28,30,34,35 |
| Spatial reasoning | N=1 | 35 |
| Driving performance | N=4 | 29,37–39 |
| Flying performance | N=3 | 31,40,41 |
| Unknown | N=2 | 32,36 |
| Time of performance test | ||
| >8 to 12 h Post-treatment | N=7 | 22,24–27,33,37 |
| >12 to 24 h Post-treatment | N=16 | 23,25,28–41 |
| >24 to 48 h Post-treatment | N=8 | 23,26,28,29,31,34,35,40 |
| ≤8 h Post-treatment | N=18 | 23–26,28–41 |
| “Recovery” conditions | ||
| Supervised | N=8 | 22–24,27,30,35,36,39 |
| Unsupervised | N=10 | 26,28,29,31–34,38,40,41 |
| Unclear or not specified | N=2 | 25,37 |
The median (interquartile range [IQR]) (last) THC dose was 16 [11–26] mg (where reported; N=15). Two types of “safety-sensitive task” (simulated driving and flying) and a wide range of neuropsychological tests were administered. The number of tests conducted between >8–12, >12–24, and >24–48 h post-treatment was 98, 158, and 89, respectively. Eight studies supervised their participants throughout the >8 h “recovery” period; the remainder (N=12) allowed them to leave the laboratory between assessments. All appeared to assess performance the day following THC administration (i.e., the “next day” or longer). (Note that only the 12-, 10-, and 10-h assessments conducted in Schoedel et al,25 Ménétrey et al,26 and Nicholson et al,27 respectively, are presented in both the current and former3 review).
Risk of bias
The results of the RoB assessment are detailed in Supplementary File S2 and summarized in Figure 1. None of the included studies demonstrated an overall “low risk” of bias, although two, Matheson et al28 and Brands et al,29 received “low risk” ratings on four out of the five RoB domains assessed. Nine studies were found to have “some concerns,” and 11 had a “high risk” of bias. The most common problems were RoB arising from (1) missing outcome data; (2) selective outcome reporting; and (3) carryover effects—with studies often failing to indicate whether any participant discontinued in the trial, analyze their data in accordance with a pre-specified plan, and report the number of participants assigned to each treatment order. Only four studies justified their chosen sample size.
Standardization procedures
The “standardization procedures” employed, that is, methods used to control participants' pre-trial and “within-trial” (i.e., up until the >8 h post-treatment assessment) sleep behavior and cannabis, alcohol, caffeine, and other drug use, are summarized in Fig. 2. Studies that supervised their participants throughout the >8-h recovery period (N=8) achieved better within-trial standardization than those that did not (N=12). However, the latter tended to achieve better pre-trial standardization with most (N=9) controlling at least one pre-trial condition. Nicholson et al27 and Chait and Perry30 implemented the most robust standardization procedures; followed by Matheson et al28 and Brands et al.29 Three studies failed to report implementing any standardization procedure.25,31,32
“Acute Effects” of THC
It is important to consider whether the 345 performance tests administered >8 h post-treatment also demonstrated “acute” (i.e., <8 h post-treatment) effects of THC. Indeed, a lack of impairment at, say, 24 h is a more definitive illustration of no “next day” effects on a performance test if impairment had been evident on that same test at shorter durations following THC (i.e., <8 h post-treatment). The relevant results are detailed in Supplementary File S1 and summarized in Figure 3. We note the following: only 20% (N=42) of the tests that showed no “next day” effects of THC also demonstrated “acute” effects (i.e., initial impairment). Most did not (42%; N=88). The remainder either did not assess (17%; N=36) or adequately describe (21%; N=43) the acute effects of THC.
Discussion
This systematic review found little by way of high-quality scientific evidence to support the assertion that cannabis use impairs “next day” performance. Indeed, of the 345 performance tests reviewed, only 12 indicated negative (i.e., impairing) “next day” effects of THC. Notably, the five studies that observed these effects were all published >18 years ago (four, >30 years ago) and found to have significant methodological limitations.
Only two investigations: the flight simulator studies of Leirer et al40 and Yesavage et al41 provided any evidence of THC-induced impairment persisting beyond 12 h. Both studies administered ∼20 mg THC to a poorly characterized participant population (i.e., their cannabis use behavior and sex were not reported) by smoking (cannabis) and reported impairment 24 h post-treatment. However, they also employed suboptimal designs (i.e., “pre-/post-treatment” and nonrandomized, single blind, placebo controlled) and inadequate standardization procedures (Fig. 2), one indicating a “high risk” of bias (due to missing outcome data and the randomization process employed).41 It can further be assumed that flight simulator technology was very rudimentary at this stage in history (i.e., ∼1990) and noted that these “next day” effects were not replicated in a third flight simulator study (employing a superior randomized, double-blind, placebo-controlled design) conducted by the same group of authors.31
Three additional investigations Nicholson et al,27 Chait et al,24 and Chait22 reported impaired cognitive performance between >8 and 12 h after THC use. Again, however, each of these studies employed suboptimal designs (Table 2) and had either a “high risk” of bias (due to missing outcome data)27 or inadequate standardization procedures22,24 (Fig. 2); two also involved an unknown dose of THC.22,24 Of further note is the fact that many of the effects observed across these three studies (N=4 out of 10)—and the only effect observed in Chait et al24—were on “time production” tests (i.e., during which participants estimate when a given amount of time has elapsed, e.g., 120 sec). These tests may be of limited relevance to driving and workplace safety. In addition, time estimations were often closer to the target on THC than placebo (i.e., arguably enhanced).22
The remaining “negative” effects could be due, in part, to certain methodological factors. For example, the oromucosal THC (5 and 15 mg) preparation used in Nicholson et al27 would be expected to elicit longer lasting impairment than inhaled THC.3,42 Chait22 also utilized an unusually demanding treatment protocol in which participants completed five separate “smoking sessions” over a 48-h period. Overall, however, these “next day” effects did not appear to be associated with a specific methodological factor (e.g., dose, route of administration or whether regular or occasional users were assessed) and should be interpreted with caution.
The “next day” effects of alcohol use have also received some scientific attention. Indeed, a recent meta-analysis showed that “alcohol hangover” had a small to moderate detrimental effect on cognitive performance (e.g., sustained attention, psychomotor speed, short-/long-term memory).43 The “next day” effects of THC use could not be quantified in this review as studies often failed to report the information required to calculate an effect estimate. However, the small number of significant effects observed would suggest that a THC “hangover” is unlikely to be more impairing than an alcohol hangover, which is generally tolerated among drivers and individuals employed in safety-sensitive positions.
A total of 209 performance tests conducted across 16 published studies showed no “next day” effects of THC.22,24,25,27–31,33–40 Most of these 16 studies used randomized double-blind, placebo-controlled designs (N=9),25,28,29,31,34–37,39 but still had methodological limitations. Indeed, half had a “high risk” of bias (often due to missing outcome data)27,31,33–36,38,39 and most used inadequate standardization procedures22,24,25,27,31,33–40 (Fig. 2). In addition, only three justified their chosen sample sizes (Fig. 1) (and none used noninferiority analysis to test the specific hypothesis that THC does not impair “next day” performance44).
One additional concern is that 42% of the tests showing no “next day” effects of THC also failed to demonstrate “acute” (i.e., <8 h post-treatment) THC-induced impairment (Fig. 3). This is important as “next day” effects seem unlikely to occur in the absence of initial impairment, which could reflect the use of lower THC doses and/or tests or cognitive domains that are relatively insensitive to the effects of THC. The collective results of these 16 studies should therefore be interpreted with some degree of caution.
Nevertheless, two recent studies, both finding no “next day” effects of THC, were identified as having employed good-quality research methods: Matheson et al28 and Brands et al.29 These studies were conducted within the same investigation: a randomized double-blind, placebo-controlled trial in which participants (weekly–daily cannabis users) smoked either 70.3±21.3 or 94.0±16.4 mg THC (cannabis) ad libitum. Both studies had “some” RoB—but received “low risk” ratings on four of the five domains assessed (Fig. 1).
They also justified their chosen sample size (n=91) (Fig. 1) and employed relatively robust standardization procedures (Fig. 2). Motor function, learning and(or) memory, information processing, sustained attention, and simulated driving performance were not impaired 24 or 48 h post-treatment in these investigations. Some positive (i.e., enhancing) effects were unexpectedly observed 48 h post-treatment. In addition, only learning and(or) memory demonstrated “acute” (i.e., <8 h post-treatment) impairment. However, these findings provide some confirmation that high doses of inhaled THC are unlikely to impair “next day” performance in regular cannabis users.
Further high-quality studies investigating the “next day” effects of THC in both occasional and medicinal cannabis uses are, of course, required, as are studies involving the administration of oral THC. Until the results of such studies become available, there remains some justification for a cautious regulatory approach. However, policy makers should bear in mind that the implementation of very conservative workplace regulations can have serious consequences (e.g., termination of employment with a positive drug test) and impact the quality of life of individuals who are required to abstain from medicinal cannabis use to treat conditions such as insomnia or chronic pain for fear of a positive workplace or roadside drug test.
The following factors might also be considered in future studies of this nature. First, while most of the studies conducted to date have administered a single dose of THC, many individuals (in particular, regular cannabis users) do not consume THC in this manner under real-world conditions. High-quality studies involving daily users of medical and nonmedical cannabis would therefore be valuable. Second, performance on safety-sensitive tasks (e.g., driving, flying) and neuropsychological tests may be susceptible to “practice” (learning) and “fatigue” (loss of motivation) effects over time, and these might be better controlled in future studies. Indeed, in addition to masking “acute” effects of THC, practice effects might be attenuated under the influence of THC such that “next day” effects appear to be present.
Conclusion
A small number of lower-quality studies have observed negative (i.e., impairing) ‘next day’ effects of THC on cognitive function and safety-sensitive tasks. However, higher-quality studies, and a large majority of performance tests, have not. Overall, it appears that there is limited scientific evidence to support the assertion that cannabis use impairs ‘next day’ performance. However, further research, in particular, studies involving both occasional and medicinal cannabis users and oral THC administration, is strongly recommended.
Supplementary Material
Abbreviations Used
- IQR
- interquartile range
- RoB
- risk of bias
- THC
- Δ9-tetrahydrocannabinol
Funding Information
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. D.M., A.S.S., and I.S.M. receive salary support from the Lambert Initiative for Cannabinoid Therapeutics, a philanthropically funded center for medicinal cannabis research at the University of Sydney.
Supplementary Material
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Boxed Text
Cite this article as: McCartney D, Suraev A, McGregor IS (2023) The “Next Day” effects of cannabis use: a systematic review, Cannabis and Cannabinoid Research 8:1, 92–114, DOI: 10.1089/can.2022.0185.
References
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References
- 1. United Nations: Office on Drugs and Crime. World Drug Report 2021. Vienna, Austria, 2021.
- 2. Lintzeris N, Mills L, Suraev A, et al. Medical cannabis use in the Australian community following introduction of legal access: The 2018–2019 Online Cross-Sectional Cannabis as Medicine Survey (CAMS-18). Harm Reduct J 2020;17(1):37.
- 3. McCartney D, Arkell T, Irwin C, et al. Determining the magnitude and duration of acute Δ9-tetrahydrocannabinol (Δ9-THC)-induced driving and cognitive impairment: A systematic and meta-analytic review. Neurosci Biobehav Rev 2021;126:175–193.
- 4. Rogeberg O, Elvik R. Response to Li, et al. (2017): Cannabis use and crash risk in drivers. Addiction 2017;112(7):1316.
- 5. Rogeberg O. A meta-analysis of the crash risk of cannabis-positive drivers in culpability studies—avoiding interpretational bias. Accid Anal Prev 2019;123:69–78.
- 6. Rogeberg O, Elvik R. The effects of cannabis intoxication on motor vehicle collision revisited and revised. Addiction 2016;111(8):1348–1359.
- 7. Arkell T, McCartney D, McGregor I. Medical cannabis and driving. Aust J Gen Pract 2021;50(6):357–362.
- 8. Spindle T, Cone E, Schlienz N, et al. Acute pharmacokinetic profile of smoked and vaporized cannabis in human blood and oral fluid. J Anal Toxicol 2019;43(4):233–258.
- 9. Vandrey R, Herrmann E, Mitchell J, et al. Pharmacokinetic profile of oral cannabis in humans: Blood and oral fluid disposition and relation to pharmacodynamic outcomes. J Anal Toxicol 2017;41(2):83–99.
- 10. Colizzi M, Bhattacharyya S. Cannabis use and the development of tolerance: A systematic review of human evidence. Neurosci Biobehav Rev 2018;93:1–25.
- 11. Occupational and Environmental Medical Association of Canada. Position Statement on the Implications of Cannabis Use for Safety-Sensitive Work. 2018. Available from: https://oemac.org/wp-content/uploads/2018/09/Position-Statement-on-the-Implications-of-cannabis-use.pdf [last accessed: November 14, 2022].
- 12. Beckson M, Hagtvedt R, Els C. Cannabis use before safety-sensitive work: What delay is prudent? Neurosci Biobehav Rev 2022;133:104488.
- 13. Higgins J, Thomas J, Chandler J, et al. Cochrane Handbook for Systematic Reviews of Interventions Version 6.2 (updated February 2021). Cochran; 2021.
- 14. Pope Jr H, Gruber A, Yurgelun-Todd D. The residual neuropsychological effects of cannabis: The current status of research. Drug Alcohol Depend 1995;38(1):25–34.
- 15. Aggarwal R, Ranganathan P. Study designs: Part 4. Interventional studies. Perspect Clin Res 2019;10(3):137–139.
- 16. Kronholm E, Härmä M, Hublin C, et al. Self-reported sleep duration in Finnish general population. J Sleep Res 2006;15(3):276–290.
- 17. Higgins J, Savović J, Page M, et al. Chapter 8: Assessing Risk of Bias in a Randomized Trial. In: Cochrane Handbook for Systematic Reviews of Interventions Version 62 (updated February 2021). (Higgins J, Thomas J, Chandler J, et al. eds.) Cochran; 2021.
- 18. Higgins J, Eldridge S, Li T. Chapter 23: Including Variants on Randomized Trials. In: Cochrane Handbook for Systematic Reviews of Interventions Version 62 (updated February 2021). (Higgins J, Thomas J, Chandler J, et al. eds.) Cochran; 2021.
- 19. Goel N, Rao H, Durmer J, et al. Neurocognitive consequences of sleep deprivation. Semin Neurol 2009;29(4):320–339.
- 20. Moskowitz H, Florentino D. A Review of the Literature on the Effects of Low Doses of Alcohol on Driving-Related Skills 2000 (DOT-HS-809-028; NTIS-PB2000105778). Department of Transportation: Washington, DC, USA; 2000.
- 21. Irwin C, Khalesi S, Desbrow B, et al. Effects of acute caffeine consumption following sleep loss on cognitive, physical, occupational and driving performance: A systematic review and meta-analysis. Neurosci Biobehav Rev 2020;108:877–888.
- 22. Chait LD. Subjective and behavioral effects of marijuana the morning after smoking. Psychopharmacology 1990;100(3):328–333.
- 23. Heishman S, Huestis M, Henningfield J, et al. Acute and residual effects of marijuana: Profiles of plasma THC levels, physiological, subjective, and performance measures. Pharmacol Biochem Behav 1990;37(3):561–565.
- 24. Chait L, Fischman M, Schuster C. “Hangover” effects the morning after marijuana smoking. Drug Alcohol Depend 1985;15(3):229–238.
- 25. Schoedel K, Szeto I, Setnik B, et al. Abuse potential assessment of cannabidiol (CBD) in recreational polydrug users: A randomized, double-blind, controlled trial. Epilepsy Behav 2018;88:162–171.
- 26. Ménétrey A, Augsburger M, Favrat B, et al. Assessment of driving capability through the use of clinical and psychomotor tests in relation to blood cannabinoids levels following oral administration of 20 mg dronabinol or of a cannabis decoction made with 20 or 60 mg Δ9-THC. J Anal Toxicol 2005;29(5):327–338.
- 27. Nicholson A, Turner C, Stone B, et al. Effect of Δ-9-tetrahydrocannabinol and cannabidiol on nocturnal sleep and early-morning behavior in young adults. J Clin Psychopharmacol 2004;24(3):305–313.
- 28. Matheson J, Mann R, Sproule B, et al. Acute and residual mood and cognitive performance of young adults following smoked cannabis. Pharmacol Biochem Behav 2020;194:172937.
- 29. Brands B, Mann R, Wickens C, et al. Acute and residual effects of smoked cannabis: Impact on driving speed and lateral control, heart rate, and self-reported drug effects. Drug Alcohol Depend 2019;205:107641.
- 30. Chait L, Perry J. Acute and residual effects of alcohol and marijuana, alone and in combination, on mood and performance. Psychopharmacology 1994;115(3):340–349.
- 31. Leirer VO, Yesavage J, Morrow D. Marijuana, aging, and task difficulty effects on pilot performance. Aviat Space Environ Med 1989;60(12):1145–1152.
- 32. Kielholz P, Hobi V, Ladewig D, et al. An experimental investigation about the effect of cannabis on car driving behaviour. Pharmacopsychiatry 1973;6(01):91–103.
- 33. Barnett G, Licko V, Thompson T. Behavioral pharmacokinetics of marijuana. Psychopharmacology 1985;85(1):51–56.
- 34. Curran V, Brignell C, Fletcher S, et al. Cognitive and subjective dose-response effects of acute oral Δ 9-tetrahydrocannabinol (THC) in infrequent cannabis users. Psychopharmacology 2002;164(1):61–70.
- 35. Fant R, Heishman S, Bunker E, et al. Acute and residual effects of marijuana in humans. Pharmacol Biochem Behav 1998;60(4):777–784.
- 36. Rafaelsen L, Christrup H, Bech P, et al. Effects of cannabis and alcohol on psychological tests. Nature 1973;242(5393):117–118.
- 37. Hartley S, Simon N, Larabi A, et al. Effect of smoked cannabis on vigilance and accident risk using simulated driving in occasional and chronic users and the pharmacokinetic-pharmacodynamic relationship. Clin Chem 2019;65(5):684–693.
- 38. Ronen A, Gershon P, Drobiner H, et al. Effects of THC on driving performance, physiological state and subjective feelings relative to alcohol. Accid Anal Prev 2008;40(3):926–934.
- 39. Rafaelsen O, Bech P, Christiansen J, et al. Cannabis and alcohol: Effects on simulated car driving. Science 1973;179(4076):920–923.
- 40. Leirer VO, Yesavage J, Morrow D. Marijuana carry-over effects on aircraft pilot performance. Aviat Space Environ Med 1991;62(3):221–227.
- 41. Yesavage J, Leirer O, Denari M, et al. Carry-over effects of marijuana intoxication on aircraft pilot performance: A preliminary report. Am J Psychiatry 1985;142(11):1325–1329.
- 42. Karschner EL, Darwin WD, Goodwin RS, et al. Plasma cannabinoid pharmacokinetics following controlled oral delta9-tetrahydrocannabinol and oromucosal cannabis extract administration. Clin Chem 2011;57(1):66–75.
- 43. Gunn C, Mackus M, Griffin C, et al. A systematic review of the next-day effects of heavy alcohol consumption on cognitive performance. Addiction 2018;113(12):2182–2193.
- 44. McCartney D, Suraev A, Doohan P, et al. Effects of cannabidiol on simulated driving and cognitive performance: A dose-ranging randomised controlled trial. J Psychopharmacol [Epub ahead of print]; DOI: 10.1177/02698811221095356.