Physical and Cognitive Performance Impairment with Cannabis Consumption in Adults Over 12 hours

doi:10.21203/rs.3.rs-4823508/v1

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Research Article

Physical and Cognitive Performance Impairment with Cannabis Consumption in Adults Over 12 hours

https://doi.org/10.21203/rs.3.rs-4823508/v1

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Background

Assessing the impact of cannabis on cognitive and physical performance is imperative, especially in safety-sensitive environments. This study investigated the degree and duration of performance impairment after cannabis consumption.

Methods

Fourteen cannabis users were subjected to physical and cognitive testing before and after smoking cannabis. Tests included assessment of intoxication, vital signs, psychomotor abilities, and muscle function. Blood, urine and saliva were analyzed for Delta-9-tetrahydrocannabinol (THC) and Carboxy-THC at baseline, and 1-, 6-, and 12-hours post-consumption.

Results

Blood THC levels peaked significantly at 1 hour and declined by 6 hours (p < 0.001), whereas Carboxy-THC levels showed a less pronounced but consistent variation over time (p = 0.005). Urine Carboxy-THC levels displayed a non-significant similar trend (p = 0.068). Acute cannabis use significantly (p = 0.01 – p < 0.001) raised systolic blood pressure and heart rate, increased force variability, reduced rate of force development, and compromised balance and muscle endurance up to 12 hours post-consumption.

Conclusions

Acute cannabis consumption results in physical impairments, impacting essential functions required for safety-sensitive tasks. The sustained presence of Carboxy-THC indicates prolonged pharmacological effects and necessitates cautious policy-making for workplaces.

Trial Registration

This study was not registered as a clinical trial as the ClinicalTrials.gov indicates that the study must answer yes to all four questions on their checklist. Although, our study was interventional, it was not conducted in the US nor involved a new FDA investigational new drug application, and the cannabis was not manufactured or exported from the US. The focus of the study was on the recreational use of a single cannabis cigarette on subsequent physiological or work performance and safety measures over 12 hours.

marijuana

intoxication

strength

endurance

motor control

blood pressure

health policy

cannabis testing

Cannabis consumption has seen a substantial rise in popularity across Canada and globally, partly due to diminishing social stigma and the legalization movements, notably in Canada after the passing of the Cannabis Act in 2018 (Rotermann et al. 2019). This legislative change has led to increased usage among all age groups and genders, with a marked increase noted particularly in the male demographic aged 18–24 (Rotermann et al. 2019). The increase in cannabis use has not been limited to leisure, as evidenced by reports that 26% of Canadians admitted to using cannabis before or during work hours (Canada 2018).

The escalation in cannabis use among working-aged adults has been corroborated by data from both North America and Europe, highlighting a global shift in cannabis consumption trends among adults (Rotermann et al. 2019; Addiction 2019; Hasin et al. 2019). With the evolving legal and social landscapes surrounding cannabis, there is a pressing need to understand the impact of cannabis-related impairment on workplace safety and employee performance (Frone and Trinidad 2012; Medicine 2017). This is especially crucial as the workplace dynamics and safety protocols must adapt to these changes.

There is significant evidence to suggest that workplace injuries and accidents are correlated with cannabis use. Studies like those by Normand and Salyards have found that workers testing positive for cannabis had higher rates of accidents and injuries (Normand and Salyards 1989). The introduction of random drug tests in safety-sensitive positions revealed that a significant portion of employees tested positive for cannabis, highlighting ongoing challenges in managing cannabis consumption among employees who engage in high-risk tasks (TTC 2019).

The effects of cannabis on cognitive and psychomotor abilities are well-documented but complex. Cannabis impairs learning, memory, attention, and concentration, as reviewed by Crane et al. (2013). The primary psychoactive components of cannabis, such as Delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD), cannabinol (CBN), and others, interact with the cannabinoid receptor type 1 (CB1) in the central and peripheral nervous systems, affecting motor output and cognitive functions (McLaughlin et al. 2000). This interaction can lead to diminished motor skills and delayed cognitive processing, which are critical in safety-sensitive roles (McLaughlin et al. 2000, Karila et al. 2014, Hart et al. 2001).

Research also shows that cannabis consumption can adversely affect driving ability, with impaired motor skills evident even days after use. This is particularly concerning for tasks that require high levels of precision and critical decision-making (Bondallaz et al. 2016). Furthermore, studies have reported that the effects of cannabis, such as impairment in motor control and executive function, can last for several hours to days, complicating the assessment of when an individual is 'fit for duty' (Johannes et al. 2006).

Despite extensive research, gaps remain in our understanding of cannabis' impact over the long term and across different levels of potency and consumption patterns. The literature suggests that while acute effects are evident, the residual impact of cannabis can vary significantly, affecting individuals’ performance in complex tasks over extended periods (Bolla et al. 2002). This calls for a more detailed investigation into the prolonged acute stages of cannabis impairment, especially in relation to high-potency strains and frequent users (Schreiner et al. 2012, Heishman et al. 1990).

As the legal and workplace landscapes continue to evolve with cannabis legalization, there is a crucial need for ongoing research to inform policy and practice. This study aims to investigate the degree and duration of impairment caused by cannabis on both physical and cognitive performance in adults, examining the effects immediately after use and up to 12 hours post-consumption. By understanding these dynamics, we can better tailor workplace policies and safety protocols to effectively manage and mitigate the risks associated with cannabis use in professional settings.

Participants

Based on an “a priori'' statistical analysis (G*power version 3.1.9.2, Dusseldorf Germany) to obtain a small magnitude effect size, it was determined that approximately 18 adult participants were needed to achieve an effect size of 0.3 (theoretical assumption), considering the interaction between two groups and four times, alpha (α) of 0.05 and a power of 0.8. Based on convenience sampling, 28 participants (Experimental group: 16 frequent cannabis users and 12 non-smoking controls) were recruited for this study (Table 1). Participants were frequent cannabis consumers, which was defined as smoking or ingesting edibles three or more times per week on average over the last six months. McCartney et. (2021) define regular cannabis consumers as individuals who use cannabis on a weekly basis or more. Exclusion criteria included participants with the following: 1) history of neurological or psychiatric disorders, 2) engagement in psychological treatment (within the previous 6 months), 3) current or past diagnoses of psychotic disorders, 4) participants taking medications that could influence psychometric testing, 5) participants with any history of alcohol or other substance use disorder (other than cannabis use disorder) 6) female participants were excluded if they were pregnant, looking to become pregnant, or breastfeeding. Participants were not allowed to consume cannabis 12 hours before testing and during the entire day of testing (post-smoking intervention started at either 9 or 10 AM and final testing was completed at 9 or 10 PM [21:00–22:00]) respectively.

The experimental protocol and consent form was emailed initially and then verbally explained to all participants upon arrival to the first session. Participants then read and signed the informed consent form prior to experimentation. All data was anonymized such that the researcher could not identify individuals when conducting the analyses. This research was approved by the institution’s Human Research Ethics Board (#2022.157) and conducted according to the latest version of the Declaration of Helsinki.

Experimental Design

Testing was conducted over a three-day period with each participant involved for a 14-hour period within one day (Fig. 1). Testing commenced at either 8 or 9 AM with groups of four individuals in each one-hour session. Testing prior to the intervention (cannabis smoking at either 9 or 10 AM) and post-intervention (post-testing at 1-, 6- and 12-hours post-smoking intervention) involved measures of body mass, height, perceived feelings of intoxication, resting blood pressure (BP) and heart rate (HR), reaction time (RT), stork balance test on a padded mat with eyes open, and on a concrete floor with eyes closed, dominant limb handgrip maximal voluntary isometric contraction (MVIC) strength, maintenance of 10%, 20% and 40% of handgrip MVIC for 10-seconds and handgrip endurance test to task failure (inability to maintain prescribed force for three seconds) at 40% MVIC. Blood, urine, and saliva testing were also conducted by certified nurses at each testing period.

Independent Variable (Cannabis Intervention)

Following the pre-tests at 8 or 9 AM, participants were brought to a different location within the facility to smoke an indica marijuana strain cannabis cigarette (Ezee Chill pre-roll: God Father OG). Cannabis was provided by a consumer company (Atlantic Cultivation Inc.). According to the manufacturer web site (https://www.leafly.ca/strains/godfather-og), the effects of this strain are sedating and relaxing. The pre-rolled cigarette contained 3.5 grams of dried cannabis, with 15.9 mg/g concentration of THC, which is the primary psychoactive cannabinoid extracted from the cannabis (marijuana) plant and 0.9 mg/g concentrations of CBD. Smoking was monitored by a researcher to ensure full inhalation. The researcher also monitored for any adverse reactions (none occurred as they were relatively frequent users). There were also two trained registered nurses on site for further follow up and monitoring of participants at all times. After cannabis consumption, participants returned to the testing site for the remaining testing periods.

Dependent Variables (Measures)

Anthropometric Data

Body mass was measured with a commercially available scale (Accuweight Moreno Valley, CA 92551, USA) and height was measured with a measuring tape attached to a wall. Participants were queried regarding age, sex, and activity level, which was defined as either a) sedentary: no regular weekly exercise, b) recreationally active: 2–3 regular exercise sessions per week, or c) trained: >3 training sessions per week.

Blood Pressure (BP) and Heart Rate (HR)

Participants were requested to remain seated and relaxed for a 2-minute period before the blood pressure device (Omron Healthcare, Inc. 2-3-13 Konan, Minato-ku, Tokyo Shinagawa Front Building 7F) was initiated. While seated and relaxed, their skin was prepared and electromyography (EMG) electrodes were placed over the forearm flexors (more detail provided in the EMG section). The cuff was placed on the left arm directly superior to the cubital fossa with the arm relaxed and extended with the palm supinated and the arm resting on a table at shoulder height. The BP device automatically inflated and deflated and provided the systolic and diastolic BP as well as HR.

Subjective Perceived Feelings of Intoxication

Participants were asked while relaxing prior to the BP measurement about their perceived level of intoxication. They were asked to mark a line on a 10 cm horizontal line that was designated from 0 -100%. They were asked how “high” or “stoned” they felt with zero being absolutely no feeling of intoxication while 100% was the most “stoned” or “high” (intoxicated or inebriated) they had ever felt. The terms “stoned” or “high” were used as these words are common vernacular among these individuals.

Reaction time (RT)

RT was measured on a laptop computer (Dell Lenovo computer) using a web application (Web site: faculty.washington.edu/chudler/java/redgreen.html). The participant had to tap the trackpad as quickly as possible when a green light appeared on a simulated traffic light. Five attempts were permitted and the average of the five attempts was used for analysis. If one measure was considered an outlier (e.g., more than 100 ms slower than the other four attempts), it was not considered in the average. If more than one attempt was considered an outlier then another five attempts were conducted. The day-to-day reliability of the RT using an intraclass correlation coefficient (ICC) with prior testing from this laboratory group has been reported to be between 0.79 and 0.93 (Behm et al. 2004).

Static Stork balance test

Two trials each of the Static Stork balance test were conducted with eyes open and eyes closed with no shoes (stocking feet). With eyes open, the participant stood on a 45 cm² square foam pad with a thickness of 10 cm. The eyes closed Static Stork balance test was conducted on a concrete floor. While standing, the participant placed their hands on the hips, then they positioned the non-supporting foot against the inside knee of the supporting leg. The participant was provided one minute to practice the balance test. The dependent variable was time which was monitored with a stopwatch. Timing began when the non-supporting foot was placed against the inside (approximately knee height) of the supporting leg. The timing was stopped if a) hand(s) came off the hips b) supporting foot swiveled or moved (hops) in any direction, or c) non-supporting foot lost contact with the knee. The two trials of the balance tests were conducted on both legs. The longest time was used for analysis. Reliability has been reported to be excellent ICCs ranging from 0.91 to 0.93 (Aranha 2019).

Handgrip Maximum Voluntary Isometric Contractions (MVIC)

While standing, participants gripped a custom designed (Technical Services of Memorial University of Newfoundland) isometric handgrip device with their dominant hand (hand used for writing). They initially performed two handgrip MVICs and if the second MVIC was more than 5% greater than the first MVIC then a third MVIC was performed. One minute recovery was provided between MVICs. The steel bar grip was attached to a Wheatstone bridge strain gauge (Omega Engineering Inc., LCCA 250, St. Eustache, Quebec, Canada). During the 4-second MVICs, the participant would squeeze the handgrip dynamometer as hard and fast as possible with the arm situated away (abducted) from the body to prevent bracing. Researchers provided consistent verbal encouragement; vocalizing “harder” three times within the 4-second MVIC.

Peak force and rate of force development from 0–50, 50–100, 100–150, and 150–200 ms were recorded. The differential voltage (± 0.03% linearity and 3 mv/V) from the handgrip dynamometer was calibrated to Newtons and all forces detected by the handgrip dynamometer strain gauge were amplified (500x) (Biopac Systems Inc., DA 150), and analog to digital converter (MP150WSW) and monitored on computer. All data was stored on a computer at a sampling rate of 2000 Hz. Data was recorded and analyzed with a commercially designed software program (Acq-Knowledge III, Biopac Systems Inc.). This laboratory has previously reported excellent intersession reliability (ICCs of 0.98–0.99) using these techniques (Behm et al. 1996; Behm et al. 2002; Low et al. 2019).

Movement (Submaximal Force) Control

Two minutes following the MVIC, the participants were tested for movement control (isometric force steadiness) by viewing a computer monitor and maintaining relative forces of 10-, 20- and 40% of MVIC for 10-seconds each. One minute of recovery was allocated between each contraction intensity. In order to minimize the possibility of fatigue, the order was not randomized as the 10% and 20% MVICs were considered very light or low intensity contractions.

The data (6-second period commencing 2-seconds after the start of the contraction and ending 2-seconds before the end of the contraction) was analyzed for the average relative deviation from the prescribed force ((prescribed force - average force) x 100 = % difference from prescribed force)). The same time period was analyzed for the standard deviation (SD) of the force as a measure of force output variability. Prior research from this laboratory has reported day-to-day reliability (intraclass correlation coefficient: ICC) of the matching force test to be 0.8, with a between test (single session) reliability of 0.88 (Behm et al. 2004).

Handgrip Endurance

The 40% handgrip MVIC was maintained until task failure. The first 10-seconds was analyzed for the movement control measures but the participant then continued to maintain the relative force till exhaustion (task failure). Task failure was defined as the inability to maintain the prescribe force (second time the participant could not maintain the prescribed force for 3-s). Maximum endurance time was recorded.

Electromyography (EMG)

Surface EMG (s-EMG) was used in this study to record muscle activity of the forearm and finger flexors. A number of forearm flexor muscles are involved in wrist stabilization and finger flexion with the handgrip (e.g., flexor carpal radialis, flexor carpal ulnaris, flexor pollicis longus muscle, flexor digitorum profundus, flexor digitorum superficialis, and palmaris longus muscles) and located generally on the palmar side of the forearm (Basmaijan 1981). Before electrodes were placed on the skin, investigators prepared the area by shaving, abrading, and cleaning the skin with an isopropyl alcohol swab before letting it dry (Hermens et al. 1999). Self-adhesive Cl/AgCl bipolar electrodes (MeditraceTM 130 ECG conductive adhesive electrodes, Syracuse, USA) were used in parallel with the muscle fibers and systematically placed according to SENIAM guidelines (Hermens et al. 1999). The electrodes were placed parallel and edge-to-edge for an inter-electrode spacing of 20 mm. The electrodes were placed at 80% of the longitudinal distance from the radial head to the medial epicondyle of the humerus and 80% of the lateral to medial side distance of the palmar forearm at that location (medial side). The ground electrode was placed on the medial epicondyle of the humerus, and all leads were taped to the skin to help minimize any movement artifacts in the s-EMG signal. EMG signals were amplified 1000x and filtered with a 3-pole Butterworth filter with cut-off frequencies of 10–500 Hz (bi-polar differential amplifier, input impedance = 2MΩ, common-mode rejection ratio > 110 dB min (50/60 Hz), noise > 5 µV), (Biopac Systems Inc., DA 150, and analog to digital converter (MP150WSW)). Analog signals were digitally converted at a sampling rate of 5 kHz and sampled at 2000 Hz (Biopac Systems Inc., DA 150, and analog to digital converter (MP150WSW). EMG integral and the mean amplitude of the root mean square (RMS) were measured over a 1-second window that included the peak force (500 ms before and 500 ms after the peak force output). The median frequency was obtained from a scan that included 5-250 Hz. These EMG parameters were also monitored for the middle 6-seconds of the 10-, 20- and 40% MVIC movement control contractions. Finally, during the 40% MVIC endurance (fatigue) protocol, these EMG measures were analysed for each quartile of the handgrip duration. A commercial software program (AcqKnowledge III, Biopac Systems Inc., Holliston, MA) was used to analyze the digitally converted analog data.

Cannabinoid Testing:

This study investigated the temporal pattern of Tetrahydrocannabinol (THC) and Carboxy-THC levels in blood and urine following cannabis consumption at baseline and at 1-, 6-, and 12-hours post-consumption. The analyses were aimed at understanding the pharmacokinetic profiles of THC and its primary metabolite, Carboxy-THC, which is known for its longer detection window in the body. We used oral fluid, urine, and blood tests to detect THC levels in recruited participants. A registered practicing nurse was responsible for administering oral fluid, urine and blood tests to detect THC levels in the participants. This was conducted at baseline (pre-consumption), 1 hour, 6 hours and 12 hours post-consumption of cannabis. Moreover, the nurse monitored the symptoms and to ensure if further medical attention is required. The samples were stored in a university laboratory freezer at the temperature of -80°C.

Blood Cannabinoids Lab Processing:

Extraction and analysis of THC, THCA, OH-THC, CBD, and CBDV in whole blood was performed according to a method developed in-house by Dynacare labs. Briefly, 100 µL of each sample was crushed and mixed with methanol containing the Cannabinoids Working Internal standard. Samples were vortexed for 60 seconds, then allowed to equilibrate at room temperature for 10 minutes. For both blood and urine samples the following procedure was the same. Subsequently (after the 10 minutes of equilibration for blood and the 60 seconds of urine vortex respectively), samples were centrifuged at 4500 RPM for 5 minutes. Supernatant was transferred into an HPLC vial and injected onto the Prominence HPLC System (Shimadzu) followed by subsequent analysis on the 6500 + QTRAP LC-MS/MS (SCIEX). All analytical data were collected and processed. The concentration of cannabinoids in the samples were determined using linear regression with a weighting factor of 1/x. The limit of quantitation (LoQ) for all cannabinoids was 2 ng/mL, with an analytical measuring range of 2.0 to 5000 ng/mL.

Urine Cannabinoids Lab Processing:

Extraction and analysis of THC, THCA, OH-THC, CBD, CBDA and OH-CBD in urine was performed according to a method developed in-house by Dynacare labs (Ottawa, Ontario, Canada). Briefly, 100 µL of each sample along with the addition of Cannabinoids Working internal Standard (IS) in methanol, was hydrolyzed using both enzyme and alkaline digestion method. After hydrolysis, the sample was neutralized and vortexed for 60 seconds. As mentioned in the previous section, subsequent analysis was the same for blood and urine.

Saliva Test:

The VeriCheck Oral Fluid THC Test was utilized to measure THC levels in the participants’ saliva. This single-use, one-step test kit is designed for on-site, instant screening, advertised to detect THC concentrations as low as 10 ng/mL (https://www.drugtestkits.ca/vericheck-oral-fluid-saliva-thc-test). The test does not require any additional sponges or activation steps, and it includes an integrated flow line to ensure that a sufficient quantity of oral fluid is collected.

Statistical Analyses

Data were analyzed using the statistical software Jamovi (The Jamovi Project (2022), Jamovi, Version 2.3.18.0 (1) https://www.jamovi.org.) All the continuous characterization data were presented with marginal means and standard deviations and compared using a one-way ANOVA. The categorical characterization data were shown based on absolute and relative frequency and compared using the chi-square test. The inferential statistics were given based on regression estimates and a 95% confidence interval (CI).

For physical performance measures, generalized linear mixed models were used. Initially, a visual inspection of the data based on histogram graphs was done to see the symmetry of the data. Since all the outcomes were continuous variables, the data were analyzed using the Gamma distribution that fits asymmetric data better. The group (i.e., experimental vs. control) and time (i.e., pre-test, 1-, 6-, and 12-hours) and the interaction effect (group × time) were defined as fixed effects. Besides, the participants’ intercepts were used as a random effect for addressing individual variations in the repeated measures model.

When the interaction effect was detected, the estimates were analyzed using the pre-test and the control group as reference levels. Based on the specific interaction regression estimates and CI, the observed effects were described based on the variations. All comparisons adopted a significance level of p < 0.05. Beta (β) scores represent the variation in the experimental group vs. the variation in the control group between pre-intervention and 1h.

The effects of time and treatment on THC metabolite concentrations were statistically analyzed using a two-way Analysis of Variance (ANOVA). The factors analyzed were 'time post-consumption' as a within-subject factor and 'treatment' (placebo vs. cannabis) as a between-subject factor. Given the repeated measures design, the assumption of sphericity was verified using Mauchly's test of sphericity. Where sphericity was not assumed, degrees of freedom were corrected using Greenhouse-Geisser estimates. Post hoc comparisons were conducted using the Bonferroni correction method to adjust for multiple testing and control type I error, with the level of significance set at p < 0.05.

Regarding the 28 participants’ characteristics, average cannabis consumption was the only variable that differed between groups, with the experimental group showing a significantly (p = 0.012) higher consumption (Table 1).

Table 1

Participants’ characteristics.
Characteristics	Control (13)	Experimental (15)	Total (28)	p-value
Age (years)	32.3 (12.5)	32.5 (8.2)	32.4 (10.2)	0.968
Height (m)	1.72 (0.08)	1.77 (0.09)	1.75 (0.09)	0.179
Weight (Kg)	83.2 (18.0)	83.6 (18.1)	83.4 (17.7)	0.959
BMI (Kg/m²)	28.2 (5.6)	26.7 (5.4)	27.4 (5.4)	0.476
Categorical variables
Sex (M/F)	9/4	12/3	21/7	0.512
Physical activity level: Absolute number (relative %)
No regular activity	0 (0.0)	1 (3.6)	1 (3.6)	0.631
2–3 times / week	8 (28.6)	9 (32.1)	17 (60.7)
≥ 5 times / week	5 (17.9)	5 (17.9)	10 (35.7)
Average cannabis use (absolute/relative)
No use	8 (28.6)	0 (0.0)	8 (28.6)	0.012
1 time / month	1 (3.6)	0 (0.0)	1 (3.6)
1 time / week	1 (3.6)	1 (3.6)	2 (7.1)
1 time / year	1 (3.6)	0 (0.0)	1 (3.6)
3 times / year	1 (3.6)	0 (0.0)	1 (3.6)
≥ 3 times / week	1 (3.6)	14 (50.0)	15 (53.6)
Note. P-values for the continuous variables based on independent t-test and chi-squared test for the categorical variables.

Intoxication, Heart Rate, and Blood Pressure

There were interaction effects for the cannabis intoxication perception (χ²₍₃₎ = 19.20; p < 0.001), systolic blood pressure (χ²₍₃₎ = 9.30; p = 0.026), and heart rate (χ²₍₃₎ = 15.62; p = 0.001). On average, the experimental group perceived their extent of intoxication to be rated at 53.0, 13.0, and 2.8, at 1- (95% CI = 43.84–63.84; p < 0.001), 6- (95% CI = 6.43–16.67; p = 0.022), and 12-hours respectively (95% CI = -1.08–5.93; p = 0.175) (Fig. 2A). The systolic blood pressure was 8.5 mmHg (95% CI = 1.04–15.93; p = 0.026) higher in the experimental vs. the control group one hour after smoking but not at 6- or 12-hours (Fig. 2B). The heart rate was higher both at 1- (β = 6.71; 95% CI = 0.43–12.99; p = 0.036) and 6-hours (β = 13.12; 95% CI = 6.59–19.65; p < 0.001) (Fig. 2C).

Figure 2. Means and 95% confidence intervals for the perception of cannabis intoxication (A), systolic pressure (B), and heart rate (C) at all times were evaluated for the control (grey line) and experimental (black line) groups. Note. “*” Indicates a p-value smaller than 0.05 for the interaction effect based on the variation from the pre-test compared between groups.

Muscle Strength and Endurance

The single 4-s MVIC force or EMG activity had no main effects or interactions. Regarding RFD, there was an interaction effect for all the testing times (χ²₍₃₎ = 16.00–221.14; p < 0.001). For the RFD at 50, 100, and 150 ms, the experimental group showed a reduction at 6- (β_50ms = -604.1; 95% CI = -789 – -419 / β_100ms = -1059.3; 95% CI = -1241 – -877/ β_150ms = -730.0; 95% CI = -890 – -569 / p < 0.001) and 12-hours (β_50ms = 752.6; 95% CI = -1097.6 – -407.5 / β_100ms = -1001.3; 95% CI = -1169 – -833 / β_150ms = -601.7; 95% CI = -773 – -430 / p < 0.001) after smoking compared to the control group (Figs. 3A, 3B, and 3C, respectively). While at 200 ms, the experimental group showed an increase after 1-hour (β = 296.5; p < 0.001) and reductions after 6- (β = -280.3; p < 0.001) and 12-hours (β = -219.4; p < 0.001) (Fig. 3D).

There was an interaction effect for the endurance test duration (χ²₍₃₎ = 10.42; p = 0.015), with the experimental group sustaining the 40% MVIC for 27.3-seconds (95% CI = -47.51 – -7.08) less than the control group at 12 hours after cannabis smoking (Fig. 4A). Muscle activity, as represented by the EMG RMS, also presented a significant interaction at the second (F_(3,78) = 3.93; p = 0.011) and third quartile times of the endurance test (F_(3,75) = 3.90; p = 0.012) at 6- (β_Q2 = -0.014; 95% CI = -0.023 – -0.004 / p = 0.004 / β_Q3 = -0.014; 95% CI = -0.025 – -0.003 / p = 0.011) and 12-hours (β_Q2 = -0.013; 95% CI = -0.022 – -0.004 / p = 0.004 / β_Q3 = -0.017; 95% CI = -0.029 – -0.006 / p = 0.002) after smoking with an average reduction in the EMG RMS of the experimental vs. the control groups respectively (Figs. 4B and 4C).

Muscle Force Control

A significant interaction for force variability (as measured by force SD) with 40% MVIC (χ²₍₃₎ = 12.01; p = 0.007) indicated that the experimental group averaged 1.8 (95% CI = 0.29–3.32; p = 0.019) and 2.2 N (95% CI = 0.52–3.81; p = 0.010) higher SD at 1- and 6-hours after smoking than the control group (Fig. 4D).

Reaction time and balance

RT had no significant main effects or interactions. For the balance with eyes open and the non-dominant limb, a significant interaction (χ²₍₃₎ = 13.70; p = 0.003) revealed balance test duration reductions of -12.0 (95% CI = -20.88 – -3.15) -18.6 (95% CI = -32.75 – -4.42), and − 16.9 (95% CI = -31.10 – -2.82) seconds after 1-, 6-, and 12-hours respectively, in the experimental group (Fig. 4E).

Cannabinoid Testing:

Blood THC Levels

The analysis of temporal changes in blood THC concentrations across four time points relative to cannabis consumption revealed a statistically significant variation (F_{(3, 39)} = 43.983, p < 0.001)(Fig. 5). Post hoc analysis revealed that blood THC levels were significantly higher at 1-hour post-consumption compared to baseline (p = 0.002). However, there were no significant differences between baseline measures versus 6- and 12-hours. Moreover, blood THC at 1 hour was significantly greater than at 6-hours (p = 0.0076) and 12-hours (p = 0.0079) with no statistically significant difference between the 6- and 12-hour measures.

Blood Carboxy-THC Levels

The analysis of the blood Carboxy-THC concentrations across four time points relative to cannabis consumption indicated a significant variation over time (F_{(3, 39)} = 5.054, p = 0.005) (Fig. 6). Post hoc analysis indicated that there were no statistically significant differences in the levels of Carboxy-THC in blood between any of the time points tested.

Urine Carboxy-THC Levels

The investigation into the temporal dynamics of Carboxy-THC concentrations in urine revealed a non-significant trend (F_{(3, 39)} = 2.566, p = 0.068).

The major findings of the present study were the cannabis-related impairments with some deficits up to 12 hours after consuming one marijuana cigarette. Blood THC levels were significantly higher at 1-hour post-consumption compared to baseline but there were no significant differences between baseline measures versus 6- and 12-hours. Blood Carboxy-THC Levels followed a similar trend but did not achieve statistical significance. The hypothesis was partially confirmed as smoking cannabis increased systolic blood pressure (1-hour), heart rate (1- and 6-hours), force variability when attempting to maintain 40% MVIC (1- and 6-hours) as well as decreases in RFD (50-, 100-, 150- and 200-ms) at all force-time periods (6- and 12-hours), 40% MVIC endurance time (12-hours) and associated endurance task EMG (12-hours) and eyes open non-dominant leg balance (1-, 6- and 12-hours). Although the participants expressed minimal to no perception of intoxication at 12 hours post-consumption, there were still negative physical performance manifestations.

The increase in heart rate (tachycardia) and blood pressure (hypertension) are in accord with prior studies. Hindocha et al.’s (Hindocha et al. 2017) participants, who smoked a mixture of 66.67 mg cannabis and 311 mg tobacco were tested within an hour experiencing increases in heart rate and diastolic blood pressure, but no significant change in systolic blood pressure. In another study, three experienced marijuana smokers (averaged 4.7 marijuana cigarettes per month) smoked 4 marijuana cigarettes (2 each at 9:00 and 13:00) with concentrations of 2.57% THC and were tested over 6 hours on day one as well as the following day. Similar to the present study, heart rate was elevated immediately after smoking and returned to baseline after 6 hours (Heishman et al. 1990). After vaporizing and smoking cannabis containing THC doses of 0, 10, and 25mg, heart rate peaked within 30-minutes and returned to baseline within 3- to 4-hours (Spindle et al. 2018). A review by Franz and Frishman (Franz and Frishman 2016), reported that marijuana cigarettes increase heart rate, supine systolic and diastolic blood pressures, and forearm blood flow due to increased sympathetic nervous system activity. Complications include a decreased time to exercise-induced angina with stable angina patients and an association with triggering myocardial infarctions in young male patients (4.8-fold greater incidence for 1-hour after marijuana consumption) due to coronary arterial vasospasm. Hence, individuals who experience chronic tachycardia and hypertension should carefully consider the effects of cannabis and perhaps refrain from cannabis use.

While cannabis use is more prevalent in some high-risk sport athletes there is no direct evidence of athletic performance-enhancing effects (Ware et al. 2018). To the contrary, there seems to be overwhelming evidence for performance impairments, with the present study highlighting difficulties with matching and maintaining a 40% MVIC force. Chung et al. (Chung et al. 2020) demonstrated that young adults’ acute subjective marijuana “high” (intoxication) impaired performance with visuospatial working memory, information processing and psychomotor speed (digit symbol substitution task), which were related to slight decreases in cognitive functioning. Marijuana decreased the accurate detection of circular lights on the first day of testing but not the second day (Heishman et al. 1990). Cognitive and psychomotor deficits peaked at 30-60-minutes post-cannabis administration, not returning to baseline for 6 to 8 hours in some cases (Spindle et al. 2018). Very high dosages can cause persistent, negative effects on verbal and visual memory, executive functioning, visuoperception, psychomotor speed, and manual dexterity (Bolla et al. 2002).

In terms of motor control, driving performance (as example of a complex motor task involving integration of both sensory and motor control) under the influence of cannabis has been comprehensively investigated. A narrative review by Bondallaz et al. (Bondallaz et al. 2016) reported dose-dependent impairments in road tracking due to increased lane position variability and deficits in the ability to maintain a constant velocity suggesting alterations in the activation of specific brain areas and networks that are adversely affected by cannabis smoking. They reported that days after discontinuing cannabis consumption, driving skills were still negatively affected, proposing that more complex tasks may be affected for longer durations (Bondallaz et al. 2016). Another narrative review by Chow et al. (Chow et al. 2019) indicated that whereas acute and infrequent cannabis use can induce cognitive and psychomotor impairment when driving, this is not consistently the case for chronic heavy use. McCartney et al.’s (McCartney et al. 2021) systematic meta-analysis found that regular cannabis users experienced fewer driving impairments than occasional cannabis users. Their systematic review suggested that individuals should wait at least 5-hrs following inhaled cannabis use before performing safety-sensitive tasks. Another review by Arkell et al. (Arkell et al. 2021) reported that THC impairs driving performance and can increase crash risks for up to 8-hours especially with occasional users. Ogourtsova et al. (Ogourtsova et al. 2018) found that with young recreational cannabis users, smoking a 100-mg dose of cannabis had no significant effect on simple driving-related tasks, but there were significant deficits with complex tasks, which persisted up to 5 hours after use. The Prashad and Filbey (Prashad and Filbey 2017) review states that cannabis use affects cortico-striatal networks that are essential for producing movement. Hence, our findings of persistent (6 hours) motor control deficits in regular cannabis users also emphasizes that tasks involving precision with submaximal intensity contractions should not be performed for at least 6-hours after smoking.

Although there was no significant effect on reaction time in the present study, RFD was adversely affected for up to 12 hours post-consumption. In contrast, Hindocha et al. (Hindocha et al. 2017) found a prolonged reaction time in a spatial working memory test after smoking 16.1% THC in regular consumers (≥once per month and ≤ 3 times a week). Reviews also report cannabis-induced reaction time impairments in Canadian (Brubacher et al. 2020) and Muslim (Nassif 2021) youth. However, Kvolseth (Kvalseth 1977) had six experienced marijuana users induce 0, 6.5, and 19.5–26.0 mg THC with no effects on simple and complex reaction time but participants did experience increased error rates for the linear and rotary movements as the dose level increased. Based on the present results, while simple reaction time was not affected with regular cannabis users, activities that involved either focus and muscle contraction with a 40% MVIC load (match a force line on a screen) or maximal RFD to produce a peak load were impaired. According to Prashad and Filbey’s (Prashad and Filbey 2017) review, whilst many reaction time studies do not report significant deficits, impairments were apparent with tasks that require focus and critical decision making.

Hence, while cannabis-induced deficits are more pronounced with more cognitively complex tasks like driving (Bolla et al. 2002; Bondallaz et al. 2016; Chung et al. 2020; Ogourtsova et al. 2018), the present results reveal that activities involving either precision (motor control) or maximal RFD with force can also be negatively impacted. Compared to low load tasks that can be accomplished with low motor unit recruitment and rate coding involving low levels of muscle activation, maximal RFD involves high motor unit recruitment especially of type II motor units firing at higher frequencies and synchronization (Behm 1995, 2004; Behm and Sale 1993).

MVIC forces and EMG activity were also not adversely affected by the cannabis, which is partially in accord with the Burr et al. (Burr et al. 2021), review that generally demonstrated either null or detrimental effects on exercise performance in strength and aerobic-type activities. As the MVIC was only a 4-second duration, impairments to focus and concentration would probably not have a substantial impact on corticospinal excitability or muscle activation.

Only one of the four balance tests, (eyes open with non-dominant leg) at 1-, 6- and 12-hours) displayed a deficit. Balance is controlled by sensory (vision, proprioception and vestibular components) and motor responses to the perceived perturbation to the equilibrium (Anderson and Behm 2005; Ferber et al. 2002; Hrysomallis 2011). When balance is perturbed, the system needs to respond quickly (reaction time) with appropriate muscle contractile force (strength) to offset the perturbation (Anderson and Behm 2005). While RFD was adversely affected, muscle strength (MVIC peak force) and reaction time were not significantly impaired by the cannabis inhalation, which generally seemed sufficient to maintain a similar duration of balance in three of the four tests.

Exercise endurance was only adversely affected at the 12-hours post-consumption period. There is scant literature on the effects of cannabis on muscular endurance. A single cannabis dose (35 mg of inhaled vaporized 18.2% THC cannabis) had no significant or meaningful effect on exercise endurance in adults with advanced chronic obstructive pulmonary disease (COPD) (Abdallah et al. 2018). We expected significant endurance impairments at 1- and perhaps 6-hours post-inhalation as the task was a continuation of the 40% MVIC force matching task, which showed significant impairments and thus would have involved focus and concentration that typically is adversely affected by cannabis (Arkell et al. 2021; Bolla et al. 2002; Chung et al. 2020; Crane et al. 2013; Hart et al. 2001). However, in addition to the need for focus and concentration to maintain the 40% MVIC force output, there would also be discomfort and pain from the prolonged exertion (86.8 ± 50.4–106.2 ± 73.9-s). The pain would arise from activation of nociceptors by the increased acidity (H + ion accumulation), contraction-induced ischemia, prolonged pressure, and other factors (Astokorki and Mauger 2017; Behennah et al. 2018; Ciubotariu et al. 2004) that could decrease corticospinal excitability to the affected muscle fibers (Del et al. 2007). The present results did show diminished EMG activity during the endurance task. As cannabis can decrease pain (Legare et al. 2022; Pantoja-Ruiz et al. 2022), it may have offset the debilitating effects of pain on corticospinal excitability (Del et al. 2007) and perception of effort (Steele 2020) for the first 6 hours of testing. At 12 hours, the pain modulation may have desisted and difficulties with focus, attention and concentration may have played a greater role.

Moreover, this study demonstrated significant temporal changes in the concentrations of THC and its metabolite Carboxy-THC following cannabis consumption, with blood THC levels peaking sharply at one-hour post-consumption indicating the peak absorption phase of the compound. There was a non-significant higher level of blood Carboxy-THC at 1-hour post-consumption. The gradual decline in mean blood THC and Carboxy-THC levels at 6 and 12 hours, suggests the progression of metabolic clearance, while high inter-individual variability underscores the complex nature of THC pharmacokinetics. The urine analysis for Carboxy-THC presented a non-significant trend over time, suggesting delayed excretion. These differences may be influenced by a range of factors, including individual metabolism rates, body composition, frequency of use, and dosage consumed. These pharmacokinetic patterns underscore the rapid absorption and metabolism of THC, followed by the more prolonged presence of its metabolite, which could have implications for detection and interpretation of cannabis use in various contexts.

It's worth noting that the saliva test kit we used to detect THC levels at multiple time intervals post-consumption failed to detect THC, leading to its classification as not useful for our purposes. This outcome contrasts with findings from three other studies, which demonstrated the utility of saliva tests in detecting THC. For instance, a study found that saliva THC levels could reflect impairment in simulated driving scenarios (Di Ciano et al 2023). Another study introduced a novel biosensor technology capable of detecting THC in saliva with high sensitivity, suitable for roadside testing (Lee et al 2016). A different study presented a rapid, non-invasive electrochemical sensing system, confirming the ability of saliva tests to identify THC levels correlating with intoxication (Churcher et al 2023). Despite the positive outcomes in these studies, our research encountered limitations with the saliva test kit used, suggesting potential variability in test sensitivity or methodology. In discussing these results, it's crucial to consider the specific conditions and technologies employed in each study, which may account for the discrepancies observed. This comparative analysis not only highlights the challenges of developing reliable saliva-based THC tests but also underscores the need for further validation and standardization in this area to ensure consistent and accurate detection across different testing platforms.

Relevance to Cannabis Consumers and Testing, Clinical and Legal Implications:

Urinalysis testing in the workplace has been adopted widely by employers in the United States to deter employee drug use and promote ‘drug-free’ workplaces. Urinalysis testing is not recommended as a diagnostic tool to identify employees who represent a job safety risk from cannabis use. Blood testing for active THC can be considered by employers who wish to identify employees whose performance may be impaired by their cannabis use (Macdonald et al 2010). Blood levels may be useful for official reporting but are not reliable for determining whether an individual is impaired. This can only be accomplished with neurocognitive testing. There can be no assurance that neurologic effects in a given consumer will not persist from the inter-shift period into the following workday (Goldsmith et al 2015). In Canada, an oral fluid drug screener is also used by law enforcement to determine driving impairment. It can detect the presence of some drugs in oral fluid, including THC (Government of Canada).

Limitations

There are some limitations to our study to acknowledge. The present study results apply to regular users as it was difficult to find individuals who were infrequent users of cannabis. From our experience in the recruitment process, individuals either used cannabis regularly or almost not at all. It would have been interesting to compare frequent and infrequent users but we were not successful in that endeavor. The 12-hour testing period was not conducive for everyone and thus although our statistical power analysis indicated sufficient numbers of participants, more participants may have provided even greater statistical power. Data was collected in a gymnasium, which is not a typical environment for a recreational cannabis smoker and thus the unfamiliar environment may have impacted the subjective feelings of intoxication. Participants smoked cannabis around other participants that they did not know and this could have affected their subjective feelings as well. It would be valuable to explore physical tests more similar to the work environment or real-life scenario such as dynamic (timed up and go) instead of static balance, an agility test instead of only reaction time, and some cognitive tasks such as the Stroop word color test or trial making test. Using these approaches, it will be possible to evaluate if the results found in this study are similar using more complex tasks. Another limitation is the smoking of only one cigarette (low dosage), which may not be similar to the typical dosage of frequent cannabis users.

Regular cannabis users who smoked a pre-rolled cigarette with 3.5 grams of dried cannabis, with 15.9 mg/g concentration of THC, and 0.9 mg/g concentrations of CBD experienced increases in systolic blood pressure (1-hour), heart rate (1- and 6-hours), force maintenance variability (1- and 6-hours) as well as decreases in RFD (6- and 12-hours), 40% MVIC endurance time (12-hours), associated endurance task EMG (12-hours) and EOND balance (1-, 6- and 12-hours). Although their perception of the level of cannabis-induced intoxication was nil or negligible at 12 hours post-consumption, significant physical impairments were still apparent. The study also demonstrated a significant, time-dependent change in THC levels post-cannabis consumption, suggesting a window of impairment that could be relevant for clinical and legal assessments. Cannabis smokers cannot rely on their subjective feelings of cannabis intoxication to guide them in their ability to perform physical tasks. It is recommended that individuals who regularly smoke cannabis should not indulge for at least 12 hours prior to activities that necessitate steady submaximal forces, muscle endurance, or high RFD with some caution for balance as well. Individuals with chronic tachycardia and hypertension should be warned not to smoke marijuana. Future studies should consider individual metabolic variations and the development of impairment assessment tools aligned with the pharmacokinetic profiles of cannabis constituents.

Ethics approval and consent to participate

Consent for publication

All authors have read, revised and approved this manuscript for submission for publication. There are no individual data in the manuscript.

Availability of data and material

All data is available as supplementary material and will also be made available on request to the corresponding author.

Conflicts of interest/competing interests

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. Funding Declaration

Partial funding was provided by Atlantic Cultivation Inc. and then administered and augmented with a MITACS Accelerate grant. This study was supported by a grant from Dr. David Behm’s Discovery Grant from the Natural Science and Engineering Research Council of Canada: RGPIN-03728 as well as a MITACS grant: IT29312 (Principal Investigator Dr. Wahl).

Author Contributions: Conceptualization, WAA, MW, JTW, DGB.; formal analysis, WAA, MW, SHA, MB, JCAS, AZ; funding acquisition, MW, JTW, DGB.; methodology, WAA, MW, JTW, DGB; project administration, JAA, MW, DGB; resources, MW, DGB; supervision, DGB.; writing—original draft, JAA, DGB; writing—review and editing, all authors. All authors have read and agreed to the published version of the manuscript.

Acknowledgements

We thank the participants for their time and efforts.

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No competing interests reported.

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Physical and Cognitive Performance Impairment with Cannabis Consumption in Adults Over 12 hours

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Abstract

Background

Methods

Results

Conclusions

Trial Registration

Figures

Background

Methods

Participants

Experimental Design

Independent Variable (Cannabis Intervention)

Dependent Variables (Measures)

Anthropometric Data

Blood Pressure (BP) and Heart Rate (HR)

Subjective Perceived Feelings of Intoxication

Reaction time (RT)

Static Stork balance test

Handgrip Maximum Voluntary Isometric Contractions (MVIC)

Movement (Submaximal Force) Control

Handgrip Endurance

Electromyography (EMG)

Cannabinoid Testing:

Statistical Analyses

Results

Intoxication, Heart Rate, and Blood Pressure

Muscle Strength and Endurance

Muscle Force Control

Reaction time and balance

Blood THC Levels

Blood Carboxy-THC Levels

Urine Carboxy-THC Levels

Discussion

Relevance to Cannabis Consumers and Testing, Clinical and Legal Implications:

Limitations

Conclusions

Declarations

References

Additional Declarations

Supplementary Files

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