Cognitive performance and subjective effects the morning after last use of smoked cannabis by adults who use cannabis frequently: An observational study
Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, 250 College Street, Toronto, Ontario M5T 1R8, Canada
Department of Pharmacology and Toxicology, University of Toronto, 27 King’s College Circle, Toronto, Ontario M5S 3H7, Canada
Trent University, 1600 West Bank Drive, Peterborough, Ontario K9L 0G2, Canada
Addictions Division, Centre for Addiction and Mental Health, 100 Stokes Street, Toronto, Ontario M6J 1H4, Canada
Campbell Family Mental Health Research Institute, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
Department of Psychiatry, University of Toronto, 8th Floor, 250 College Street, Toronto, Ontario M5T 1R8, Canada
Institute of Medical Science, University of Toronto, Room 2374, 1 King’s College Circle, Ontario M5S 1A8, Canada
Department of Family and Community Medicine, Temerty Faculty of Medicine, University of Toronto, 5th floor, 500 University Avenue, Toronto, Ontario M5G 1V7, Canada
Waypoint Research Institute, Waypoint Centre for Mental Health Care, 500 Church Street, Penetanguishene, Ontario L9M 1G3, Canada
Dalla Lana School of Public Health, University of Toronto, 6th Floor, 155 College Street, Toronto, Ontario, M5T 3M7, Canada
Institute of Health Policy, Management and Evaluation, University of Toronto, 155 College Street, Suite 425, Toronto, Ontario M5T 3M6, Canada
Biostatistics Core, Centre for Addiction and Mental Health, 60 White Squirrel Way, Toronto, Ontario M6J 1H4, Canada
Abstract
Objectives
To examine next-day cognitive performance and subjective drug effects after smoking cannabis and to assess associations between performance and cannabinoid concentrations in blood and oral fluid.
Methods
In this observational study, healthy adults who regularly used cannabis (mean age 30 years; n = 65) smoked a legally purchased pre-rolled “joint” at night and were tested the next day, 12–15 h later. Healthy adults with no past-month cannabis use served as a matched control group (mean age 30; n = 65). Participants completed cognitive tasks (verbal free recall [VFR], Trail Making Test [TMT]), subjective effects questionnaires (including visual analogue scales [VAS]), and provided blood and oral fluid samples for quantification of delta-9-tetrahydrocannabinol (THC), cannabidiol (CBD), and metabolites. Linear regression models compared groups across cognitive/subjective outcomes, while Pearson correlations assessed associations between cannabinoid concentrations and performance.
Results
There were no significant group differences on any cognitive measure. The cannabis group had significantly elevated VAS ratings (e.g., feeling a drug effect, Δmean=12.54, p < 0.01) compared to controls. Within the cannabis group, smoking infused (higher-THC-content) “joints” and higher %THC cannabis were associated with poorer verbal recall performance (e.g., %THC correlated with delayed verbal recall, r = -0.36, p < 0.01). Higher blood THC and THC-COOH concentrations correlated with poorer VFR and slower TMT performance, whereas blood 11-OH-THC and oral fluid THC correlated with TMT performance only (all p ≤ 0.03).
Conclusions
There was no measurable next-day cognitive differences between groups, despite some subjective intoxication in the cannabis group. Nonetheless, higher THC potency and elevated cannabinoid concentrations were associated with poorer verbal memory and processing speed, suggesting potential next-day impairment with high-THC products.
Untitled section
Keywords: Cannabis, THC, Cognition, Subjective effects, Next-day effects, Residual effects
Highlights
- •Adults reporting frequent cannabis use were tested 12–15 h after smoking cannabis at home.
- •There was no evidence of cognitive impairment relative to a matched control group.
- •Subjective drug effect measures were elevated relative to the control group.
- •Higher THC levels were associated with worse cognitive performance.
Article notes
Untitled section
Received 2026 Mar 11; Revised 2026 Mar 18; Accepted 2026 Mar 19; Collection date 2026 Jun.
1.Introduction
An estimated 228 million adults used cannabis in 2022, making it one of the most widely used psychoactive substances worldwide (UNODC, 2024, Connor et al., 2021). Many jurisdictions have legalized cannabis for medical and non-medical use, which has led to changes in demographics of cannabis use, product types being used, and consumption patterns, all of which have significant public health implications (Goodman et al., 2024, Matheson and Le Foll, 2020). Potency of cannabis products, typically defined as percent of delta-9-tetrahydrocannabinol (THC, the primary intoxicating component of cannabis), has risen dramatically. In the United States, the mean THC potency of cannabis plant material increased from 8.9% in 2008–17.1% in 2017 (Chandra et al., 2019). Our team documented that inhalational cannabis products available to adults accesing cannabis in the Canadian province of Ontario were nearly all above 20% THC (Tassone et al., 2023, Antwi et al.,). These ongoing changes underscore the need to understand the health effects of cannabis and how adults who use cannabis can reduce harms associated with their use.
Acute cannabis exposure produces a mix of transient pleasant effects such as a subjective drug “high” (which may include feelings of relaxation and contentment) and potential dysphoric or undesirable effects such as paranoia, anxiety, and changes in cognition (Curran et al., 2016). Prior systematic reviews and meta-analyses have documented significant acute effects of cannabis exposure on verbal episodic memory (especially word list recall performance), spatial and verbal working memory, attention, and executive functions (Dellazizzo et al., 2022, Zhornitsky et al., 2021, Broyd et al., 2016). These cognitive effects are of particular interest given the potential for cannabis exposure to impair performance (McCartney et al., 2021), which may underlie the increased risk of motor vehicle collisions associated with cannabis use prior to driving (Hartman and Huestis, 2013, Asbridge et al., 2012, Brands et al., 2021). Laboratory experiments and cross-sectional studies have found converging evidence that cognitive effects of cannabis are sensitive to multiple factors, including prior exposure to cannabis, dose, and time since last use (Broyd et al., 2016, Matheson and Le Foll, 2023). One particular area of concern is whether cannabis use can have measurable residual or “next-day” performance effects (McCartney, Suraev, and McGregor, 2023).
Next-day effects of THC need to be distinguished from chronic effects of cannabis exposure; the former implies a residual pharmacological effect of the drug, while the latter assumes chronic changes in brain function that can lead to long-term neuropsychological and behavioural changes (Matheson and Le Foll, 2023). The pharmacological rationale for next-day/residual effects of cannabis is based on the sequestering of cannabinoids and their metabolites in adipose tissue and the slow redistribution of cannabinoids into the systemic circulation (Grotenhermen, 2003), along with evidence that THC can remain detectable in brain even when it is no longer detectable in the periphery (Mura et al., 2005). Yet, a recent systematic review of 20 human studies that measured performance on neuropsychological tests more than 8 h after cannabis exposure concluded that there was little evidence of next-day impairment (McCartney, Suraev, and McGregor, 2023). In contrast, multiple systematic reviews have found evidence for decreased cognitive performance associated with chronic use of cannabis (Figueiredo et al., 2020, Krzyzanowski and Purdon, 2020, Lovell et al., 2020, Platt et al., 2019, Scott et al., 2018).
Most studies of next-day cognitive effects of cannabis were conducted under placebo-controlled laboratory conditions (McCartney, Suraev, and McGregor, 2023), which are ideal for establishing causality, but may not accurately model real-world behaviour. Furthermore, few studies provided any analysis of residual blood cannabinoid concentrations. This is important as blood cannabinoid concentrations can help to distinguish between residual pharmacological effects of THC exposure and chronic effects of cannabis consumption (Matheson and Le Foll, 2023). Finally, different performance domains may be differentially susceptible to cannabis. In our prior publication using data from the present study (Zakala et al., 2026), we found no evidence of residual driving simulator impairment, but performance deficits may instead manifest in less complex tasks (e.g., because participants can engage in compensatory behaviours in more complex tasks, such as slowing down to compensate for reduced vehicular control). Understanding next-day cognitive performance differences is important because many individuals likely use cannabis in the evening and then engage in safety-sensitive tasks in the morning, such as operating machinery or other occupational tasks; even subtle residual cognitive impacts of evening cannabis use (e.g., in memory, attention, or executive functioning) could have implications for performance and safety in these real-world contexts.
The goal of this study was to examine cognitive performance the morning after last use of smoked cannabis in a group of adults who regularly used cannabis, compared to a control group with no recent cannabis use. We chose a naturalistic observational design to better model real-world next-day effects of smoked cannabis, in complement to our previous placebo-controlled human laboratory experiment that found no next-day cognitive effects of smoked cannabis at 12.5% THC (Matheson et al., 2020b). Subjective drug effect measures were included to contextualize the cognitive results (e.g., to determine if decreased cognitive performance was observed in the absence of self-reported drug effects). Further, we aimed to examine associations between residual concentrations of cannabinoids in blood/oral fluid and cognitive endpoints. We hypothesized that cognition would be impaired in the cannabis group as compared to the control group. We further hypothesized that blood and oral fluid cannabinoid concentrations would be associated with poorer cognitive task performance in the cannabis group.
2.Methods
In this observational human laboratory study, we examined the next-day effects of smoking cannabis in a group of participants who regularly used cannabis (cannabis group, CG), compared to a control group who had no recent cannabis use (healthy control group, HC). The study was conducted at the Centre for Addiction and Mental Health (CAMH) in Toronto, Ontario, Canada between January 2025 and August 2025, and was reviewed and approved by the CAMH Research Ethics Board (#091/2024) and the Health Canada Research Ethics Board (2024–010H).
2.1.Participants
Participants were healthy adults aged 19–45 years who held a G2 or full driver’s license (or equivalent from another jurisdiction) for at least a year (the license requirement was related to the driving simulator component of the study, which is presented elsewhere). All participants had to be willing to abstain from alcohol and other drugs (other than a non-psychoactive medication required for treatment of a medical condition; not including cannabis for the cannabis group only) for 48 h prior to the study session and to provide informed consent. Exclusion criteria shared across both groups included psychiatric comorbidities (determined by self-report), use of psychoactive medications (including opioids for pain), current or past alcohol or other drug dependence, or problematic substance/drug use (self-report), participation in past driving studies at CAMH, breath alcohol reading of greater than 0.0% on the test day, and pregnancy or breastfeeding. The cannabis group had to currently smoke cannabis on average 4–7 days per week, be willing to smoke cannabis at home 12–15 h before the first test session, be willing to smoke legally purchased cannabis in the form of a new pre-roll and to bring the remnant of the “joint” to the lab for weighing, and not be using cannabis for medical purposes. The control group was required to not have used cannabis in any form in the past month. Participants were matched for age and sex across groups. We did not restrict or standardize caffeine intake. A between-subjects design was chosen due to the difficulty in obtaining a baseline from participants who use cannabis frequently and may experience negative effects if abstaining from cannabis for a few days to allow blood THC levels to clear and for withdrawal-related effects to dissipate.
Recruitment relied primarily on ads placed on local transit and by contacting people who had expressed interest in previous studies and consented to being contacted. Interested participants completed an electronic screener using Research Electronic Data Capture (REDCap) (Harris et al., 2009), and those who passed the screener were invited to the lab for an in-person eligibility assessment. Following consenting procedures, participants completed a 14-panel urine screen (CLIAwaved) for determination of use of any psychoactive medications and a breathalyzer test (Alert J5™; Alcohol Countermeasure Systems) for confirmation of recent alcohol abstinence. Age and driver’s licence status were verified, past-month cannabis use was measured using the Timeline Follow Back (Sobell and Sobell, 1992), and females underwent a pregnancy test. A brief medical assessment was conducted, which included measurement of height, weight, heart rate, blood pressure, and concomitant medications.
2.2.Study procedures
Following screening and enrolment, eligible participants returned for a single laboratory visit. Participants in the cannabis group were instructed to purchase a single pre-roll (cannabis “joint”) from a legal retailer (they were permitted to choose their preferred cannabis), record the time that they started and stopped smoking the cannabis, and arrive for their test session 12–15 h after stopping. Participants brought the cannabis packaging so that we could verify details about the product, such as the THC and CBD content, whether the cannabis pre-roll was infused (i.e., cannabis flower that has been coated with cannabinoid concentrates or distillates to increase the THC potency), and to confirm the product was sourced legally. The remnant of the cannabis “joint” was weighed to estimate amount smoked, which was determined by subtracting the weight of the remnant from the initial weight of the pre-roll (based on the packaging). Filter weights were obtained by contacting the manufacturer, or purchasing the product separately and weighing the filter. For one product with a glass filter, an accurate weight was not possible, so the weight of the filter was based on another glass filter for which a weight was obtained from the manufacturer. To estimate the amount of THC liberated from the cannabis “joint”, the change in weight was multiplied by the percent THC as indicated on the packaging. The control group was scheduled in the morning (wherever possible) to minimize between-group variability due to time of day.
Both groups underwent nearly identical procedures. The study visit included a urine drug screen, a Breathalyzer test, the Marijuana Withdrawal Checklist (MWC) (Budney et al., 1999, Budney et al., 2003), and the Pittsburgh Sleep Quality Index (Buysse et al., 1989). Participants drove in a simulator (which is described in our previous publication) (Zakala et al., 2026), completed cognitive tasks and subjective effects questionnaires, and provided blood and oral fluid samples. Given the possibility of residual impairment, participants in the cannabis group were brought to the study visit and sent home in a taxi.
2.3.Outcome measures
2.3.1.Cognitive performance
The verbal free recall (VFR) task (Hindocha et al., 2017, Shapiro et al., 1999) measures the number of words that a participant can remember from a list of 12 words that are read aloud three times (during three “trials”). Recall is assessed immediately after hearing words (“VFR1”) and after a delay (“VFRD”). Other test variables include the total number of words recalled across three trials (“VFRT”), a learning score that assesses improvement in recall across the three trials (“VFRL”), and the percent of words retained after the delay, relative to the maximum number of words recalled during the first three learning trials (“VFRP”). This test is sensitive to the effects of cannabis (Matheson et al., 2020a, Di Ciano et al., 2025), and we have observed that participants retain fewer words after acute cannabis exposure (Wickens et al., 2022, Matheson et al., 2020a). For a detailed description of this task, see Di Ciano et al. (2025).
The Trail Making Task (TMT) (Bowie and Harvey, 2006) is a pen and paper test used to measure processing speed, sequencing, mental flexibility, and visual-motor skills. In this task, the time taken to connect numbers to other numbers in ascending order (TMTA) or numbers to letters in ascending order is measured (TMTB). A third variable measures the difference in time taken to complete TMTA and TMTB (TMTBA).
2.3.2.Subjective effects
The Addition Research Centre Inventory (ARCI) is a validated measure of the subjective effects of drugs (Haertzen et al., 1963, Haertzen and Hickey, 1987), which is composed of the following subscales: Pentobarbital-Chlorpromazine-Alcohol (PCAG), Sedation, Benzedrine (BG), LSD, Amphetamine, Morphine-Benzedrine (MBG), Euphoria, and Marijuana (MAR).
The Profile of Mood States (POMS) (Spielberger, 1972) is a validated measure of subjective mood states, which is composed of the following subscales: Tension-Anxiety, Depression-Dejection, Anger-Hostility, Vigor, Fatigue, and Confusion-Bewilderment.
Visual Analogue Scales (VAS) were used to capture other subjective drug effects. Participants rated their agreement with each statement on a scale of 0 (not at all) to 100 (extremely). The VAS items used were: “I feel this effect” (“effect”), “I feel the good effects” (“good”), “I feel the bad effect” (“bad”), “I feel the rush” (“rush”), “I feel dizzy” (“dizzy”), “I feel exhilarated” (“exhilarated”), “I feel drowsy” (“drowsy”), “I feel nauseated” (“nausea”), “How positive is your mood now (“positive”), and “How negative is your mood now” (“negative”).
2.3.3.Blood and oral fluid cannabinoids
Blood was collected by a registered nurse or phlebotomist and then transferred to cryotubes for storage at −80°C. Oral fluid was collected in Quantisal vials (following instructions from the manufacturer, which relies primarily on the passive drool method) and stored at −80°C. We chose to measure THC and other cannabinoids in whole blood and oral fluid, as these are two common biological matrices used for cannabinoid concentration at the roadside. Whole blood and oral fluid samples were periodically shipped to an external lab partner for quantification of THC, THC-COOH, 11-OH-THC, and CBD. For all measures, the limit of quantification was 0.2 ng/mL. For participants with values below this limit, a value of 0.1 ng/mL was substituted. Details of the analysis can be found in our previous report (Di Ciano et al., 2024).
2.4.Data analysis
Statistical analysis was performed using statistical software R (v4.5) with packages “crosstable” and “emmeans”. Demographic data were compared between groups using Welch’s two-sample t-tests, chi-square tests, or Fisher’s exact tests, as appropriate. Linear regression models were used with the cognitive and subjective effects measures as the dependent variables and the grouping variable as the predictor, adjusting for sex, age and either highest education achieved (cognitive measures) or years of driving experience (subjective measures). The marginal means for each group, contrasts, and effect sizes between the groups were estimated from the models. Cohen’s d was the effect size measure, where 0.2 is considered a small effect, 0.5 a medium effect, and 0.8 a large effect (Cohen, 1992). In order to examine if unplanned between-groups differences in education and race might impact the between-groups comparisons, we conducted an additional sensitivity analysis including a recoded race variable (Asian, white, other) and a recoded education variable (high school/college or university) in the models. Since results did not meaningfully change, these results are only briefly described. Correlation between the outcome measures and blood/oral fluid concentrations of THC and metabolites was analyzed and the Pearson correlation coefficients were reported (only three participants had CBD concentrations above the LOQ, so correlations with CBD concentrations were not run). There were no missing data.
3.Results
3.1.Participant characteristics
In each group, 65 participants completed all study procedures (32 females and 33 males, based on self-reported sex assigned at birth) with a mean age around 30 years (CG mean=30.6, SD=7.2, range=19–44; HC mean=30.3, SD=6.6 years, range=20–45). There were no significant between-group differences in family income, years of driving, number of hours slept the night before, or number of hours slept in the last week. However, there were significant between-group differences in race (p < 0.01) and education (p < 0.01). The cannabis group was predominantly white (55.4%) with college or technical education (58.5%), whereas the control group was predominantly Asian (61.5%) with either undergraduate (41.5%) or advanced university (36.9%) education.
In the cannabis group, the cannabis products smoked had a mean (SD) of 30.0 (6.7) % THC and 0.6 (2.5) % CBD. Most participants reported using cannabis once a day (36.9%) or more than once a day (30.8%) and had been using cannabis for 11.6 (7.1) years. Mean (SD) blood cannabinoid concentrations were: 2.75 (3.97) ng/mL THC, 6.87 (15.48) ng/mL 11-OH-THC, 28.83 (44.78) ng/mL THC-COOH, and 0.26 (0.97) ng/mL CBD. Mean (SD) oral fluid THC concentration was 31.24 (75.12) ng/mL. Participants smoked mean (SD) 13 (0.9) hours before arriving for the study session (range: 12.2–15.4 h). More details about the study samples can be found in our previous publication (Zakala et al., 2026).
3.2.Cognitive effects
After adjusting for sex, age, and education, there were no significant group differences in any cognitive outcome variable (all p > 0.05). See Table 1.
| Outcome | CG (n = 65) | HC (n = 65) | CG-HC | Sensb | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| EMM | SE | EMM | SE | MD | SE | t | p | Cohen’s da | p | |
| VFR1 (no. of words) | 9.49 | 0.36 | 9.63 | 0.42 | -0.14 | 0.41 | -0.33 | 0.74 | -0.08 | 0.73 |
| VFRT (no. of words) | 26.61 | 0.91 | 26.95 | 1.04 | -0.33 | 1.03 | -0.32 | 0.75 | -0.07 | 0.58 |
| VFRL (no. of words) | 1.04 | 0.29 | 1.10 | 0.33 | -0.06 | 0.32 | -0.17 | 0.86 | -0.04 | 0.70 |
| VFRD (no. of words) | 9.28 | 0.46 | 9.55 | 0.52 | -0.28 | 0.52 | -0.53 | 0.60 | -0.12 | 0.52 |
| VFRP (no. of words) | 0.87 | 0.03 | 0.88 | 0.04 | -0.02 | 0.04 | -0.41 | 0.68 | -0.10 | 0.79 |
| TMTA (time, s) | 39.87 | 3.41 | 43.18 | 3.88 | -3.31 | 3.87 | -0.86 | 0.39 | -0.20 | 0.61 |
| TMTB (time, s) | 57.49 | 4.21 | 62.05 | 4.80 | -4.56 | 4.78 | -0.95 | 0.34 | -0.22 | 0.69 |
| TMTBA (time, s) | 17.62 | 4.33 | 18.87 | 4.94 | -1.25 | 4.91 | -0.25 | 0.80 | -0.06 | 0.98 |
Within the cannabis group, there was evidence that smoking infused cannabis “joints” had an impact on verbal free recall performance. Compared to the group that did not smoke infused “joints” (n = 48), the group that smoked infused “joints” (n = 17) recalled significantly fewer words after a delay (VFRD mean difference [standard error]=1.87 [0.66] words, t(57) = 2.82, p < 0.01, Cohen’s d= 0.84) and retained a smaller percentage of words (VFRP Δmean=13.00 [5.00] %, t(57) = 2.64, p = 0.01, Cohen’s d= 0.78), which were both large effects. Other verbal recall variables did not differ between groups and there were no between-group differences in TMT performance. See Table 2.
| Outcome | No (n = 48) | Yes (n = 17) | No-Yes | ||||||
|---|---|---|---|---|---|---|---|---|---|
| EMM | SE | EMM | SE | MD | SE | t | p | Cohen’s da | |
| VFR1 | 9.59 | 0.45 | 9.18 | 0.51 | 0.41 | 0.53 | 0.77 | 0.44 | 0.23 |
| VFRT | 26.99 | 1.17 | 25.47 | 1.31 | 1.52 | 1.36 | 1.12 | 0.27 | 0.33 |
| VFRL | 1.17 | 0.37 | 1.04 | 0.42 | 0.13 | 0.43 | 0.30 | 0.77 | 0.09 |
| VFRD | 9.96 | 0.57 | 8.10 | 0.64 | 1.87 | 0.66 | 2.82 | < 0.01 | 0.84 |
| VFRP | 0.92 | 0.04 | 0.78 | 0.05 | 0.13 | 0.05 | 2.64 | < 0.01 | 0.78 |
| TMTA | 38.36 | 3.37 | 40.37 | 3.77 | -2.01 | 3.91 | -0.51 | 0.61 | -0.15 |
| TMTB | 57.21 | 5.28 | 58.19 | 5.92 | -0.98 | 6.13 | -0.16 | 0.87 | -0.05 |
| TMTBA | 18.85 | 4.51 | 17.82 | 5.06 | 1.03 | 5.24 | 0.20 | 0.85 | 0.06 |
3.3.Correlations between cognition and cannabinoid measures
There were negative correlations between the %THC in the “joint” and verbal delayed recall (VFRD r = -0.36, p < 0.01), as well as percent words retained (VFRP r = -0.28, p = 0.02). However, %THC was not correlated with other cognitive measures, and there were no significant correlations with %CBD in the “joint” or estimated THC inhaled from the “joint”. See Table 3.
| Outcome | %THC | %CBD | THC inhaled | |||
| r | p | r | p | r | p | |
| VFR1 | -0.16 | 0.20 | 0.06 | 0.64 | -0.20 | 0.12 |
| VFRT | -0.19 | 0.14 | 0.07 | 0.61 | -0.13 | 0.31 |
| VFRL | -0.02 | 0.87 | 0.04 | 0.75 | 0.24 | 0.06 |
| VFRD | -0.36 | < 0.01 | 0.09 | 0.49 | -0.03 | 0.80 |
| VFRP | -0.28 | 0.02 | 0.06 | 0.65 | 0.03 | 0.85 |
| TMTA | 0.09 | 0.48 | 0.12 | 0.34 | 0.20 | 0.11 |
| TMTB | 0.01 | 0.95 | 0.17 | 0.19 | 0.18 | 0.15 |
| TMTBA | -0.06 | 0.64 | 0.10 | 0.43 | 0.06 | 0.67 |
Blood THC concentrations were negatively correlated with verbal recall delayed performance (VFRD r = -0.40, p < 0.01) and percent words retained (VFRP r = -0.31, p = 0.01) and positively correlated with TMTA (r = 0.46, p < 0.01) and TMTB (r = 0.31, p = 0.01) performance. Blood THC-COOH was negatively correlated with verbal recall delayed performance (VFRD r = -.029, p = 0.02) and positively correlated with TMTA performance (r = 0.30, p = 0.02). Blood 11-OH-THC was positively correlated with TMTB (r = 0.27, p = 0.03) and TMTBA (r = 0.30, p = 0.02) performance. Finally, oral fluid THC was positively correlated with TMTA (r = 0.35, p < 0.01) and TMTB (r = 0.29, p = 0.02) performance. See Table 4.
| Outcome | Bl-THC | Bl-THC-COOH | Bl-11-OH-THC | OF-THC | ||||
| r | p | r | p | r | p | r | p | |
| VFR1 | -0.17 | 0.18 | -0.13 | 0.31 | -0.15 | 0.25 | -0.18 | 0.16 |
| VFRT | -0.20 | 0.10 | -0.18 | 0.16 | -0.09 | 0.48 | -0.16 | 0.21 |
| VFRL | -0.04 | 0.76 | -0.02 | 0.87 | -0.005 | 0.97 | 0.06 | 0.63 |
| VFRD | -0.40 | < 0.01 | -0.29 | 0.02 | -0.10 | 0.45 | -0.16 | 0.21 |
| VFRP | -0.31 | 0.01 | -0.20 | 0.11 | -0.06 | 0.64 | -0.07 | 0.58 |
| TMTA | 0.46 | < 0.01 | 0.30 | 0.02 | 0.02 | 0.90 | 0.35 | < 0.01 |
| TMTB | 0.31 | 0.01 | 0.20 | 0.11 | 0.27 | 0.03 | 0.29 | 0.02 |
| TMTBA | 0.01 | 0.96 | 0.005 | 0.97 | 0.30 | 0.02 | 0.06 | 0.63 |
3.4.Subjective effects
There were no group differences in subjective mood or drug effects as measured by the POMS and ARCI, with the exception of higher mean ratings of the ARCI Marijuana subscale in the cannabis group (Δmean=2.42, t(125) = 3.48 [0.30], p < 0.01, Cohen’s d= 0.62).
In contrast, nearly all VAS measures (9 of 10) differed between groups. The cannabis group had higher mean ratings of “effect” (Δmean=12.54 [2.77], t(125) = 4.54, p < 0.01, Cohen’s d= 0.81), “good” (Δmean=31.24 [5.14], t(125) = 6.08, p < 0.01, Cohen’s d= 1.08), “bad” (Δmean=16.21 [3.28], t(125) = 4.95, p < 0.01, Cohen’s d= 0.88), “rush” (Δmean=13.31 [3.23], t(125) = 4.12, p < 0.01, Cohen’s d= 0.73), “dizzy” (Δmean=6.56 [2.74], t(125) = 2.39, p = 0.02, Cohen’s d= 0.43), “exhilarated” (Δmean=12.94 [4.48], t(125) = 2.89, p < 0.01, Cohen’s d= 0.51), “drowsy” (Δmean=15.19 [3.89], t(125) = 3.90, p < 0.01, Cohen’s d= 0.70), “nauseated” (Δmean=6.10 [2.93], t(125) = 2.08, p = 0.04, Cohen’s d= 0.37), and “positive” (Δmean=9.96 [4.23], t(125) = 2.35, p = 0.020, Cohen’s d= 0.42). See Table 5.
| Outcome | CG (n = 65) | HC (n = 65) | CG-HC | Sensb | ||||||
| EMM | SE | EMM | SE | MD | SE | t | p | Cohen’s da | p | |
| ARCI | ||||||||||
| PCAG | 3.42 | 0.28 | 2.74 | 0.28 | 0.67 | 0.40 | 1.67 | 0.10 | 0.30 | 0.38 |
| SEDN | 1.28 | 0.19 | 0.76 | 0.19 | 0.52 | 0.27 | 1.88 | 0.06 | 0.34 | 0.32 |
| BG | 6.20 | 0.25 | 6.40 | 0.25 | -0.20 | 0.36 | -0.57 | 0.57 | -0.10 | 0.94 |
| LSD | 2.60 | 0.15 | 2.65 | 0.15 | -0.05 | 0.21 | -0.25 | 0.80 | -0.05 | 0.38 |
| AMPH | 3.71 | 0.24 | 3.34 | 0.24 | 0.37 | 0.35 | 1.07 | 0.29 | 0.19 | 0.21 |
| MBG | 6.24 | 0.47 | 5.55 | 0.47 | 0.69 | 0.67 | 1.03 | 0.30 | 0.18 | 0.06 |
| EUPHOR | 2.06 | 0.23 | 1.74 | 0.23 | 0.32 | 0.32 | 1.01 | 0.32 | 0.18 | 0.24 |
| MAR | 2.42 | 0.21 | 1.37 | 0.21 | 1.05 | 0.30 | 3.48 | < 0.01 | 0.62 | < 0.01 |
| POMS | ||||||||||
| TA | 3.48 | 0.35 | 3.54 | 0.35 | -0.07 | 0.50 | -0.13 | 0.90 | -0.02 | 0.96 |
| DD | 2.75 | 0.48 | 1.86 | 0.48 | 0.90 | 0.69 | 1.30 | 0.20 | 0.23 | 0.59 |
| AH | 1.37 | 0.35 | 1.44 | 0.35 | -0.07 | 0.49 | -0.14 | 0.89 | -0.02 | 0.80 |
| VIGOR | 14.84 | 0.70 | 14.68 | 0.70 | 0.16 | 0.99 | 0.16 | 0.87 | 0.03 | 0.75 |
| FAT | 3.30 | 0.45 | 3.24 | 0.45 | 0.05 | 0.64 | 0.08 | 0.93 | 0.02 | 0.76 |
| CB | 4.27 | 0.33 | 3.88 | 0.33 | 0.39 | 0.47 | 0.83 | 0.41 | 0.15 | 0.44 |
| VAS | ||||||||||
| EFFECT | 13.78 | 1.94 | 1.24 | 1.94 | 12.54 | 2.77 | 4.54 | < 0.01 | 0.81 | < 0.01 |
| GOOD | 35.60 | 3.61 | 4.37 | 3.61 | 31.24 | 5.14 | 6.08 | < 0.01 | 1.08 | < 0.01 |
| BAD | 17.03 | 2.30 | 0.82 | 2.30 | 16.21 | 3.28 | 4.95 | < 0.01 | 0.88 | < 0.01 |
| RUSH | 14.81 | 2.27 | 1.50 | 2.27 | 13.31 | 3.23 | 4.12 | < 0.01 | 0.73 | < 0.01 |
| DIZZY | 9.24 | 1.93 | 2.69 | 1.93 | 6.56 | 2.74 | 2.39 | 0.02 | 0.43 | < 0.01 |
| EXH | 22.44 | 3.14 | 9.50 | 3.14 | 12.94 | 4.48 | 2.89 | < 0.01 | 0.51 | 0.05 |
| DROWSY | 22.90 | 2.73 | 7.71 | 2.73 | 15.19 | 3.89 | 3.90 | < 0.01 | 0.70 | < 0.01 |
| NAUS | 8.41 | 2.06 | 2.31 | 2.06 | 6.10 | 2.93 | 2.08 | 0.04 | 0.37 | 0.02 |
| POS | 72.52 | 2.97 | 62.57 | 2.97 | 9.96 | 4.23 | 2.35 | 0.02 | 0.42 | 0.19 |
| NEG | 10.61 | 1.96 | 7.72 | 1.96 | 2.88 | 2.79 | 1.03 | 0.30 | 0.18 | 0.35 |
3.5.Sensitivity analysis
In order to examine if between-groups differences in race and education impacted between-groups differences in cognitive performance or subjective effects, we ran additional models including race and education. As seen in the final column of Table 1, Table 5, including these variables in our models did not meaningfully impact our results; no between-groups differences in cognition emerged, and only two subjective effects variables changed. In the race- and education-adjusted models, there were no longer significant between-groups differences in VAS “exhilarated” (Δmean= 11.47 [5.89], t(122) = 1.95, p = 0.05) or VAS “positive” (Δmean=7.17 [5.38], t(122) = 1.33, p = 0.19).
4.Discussion
This study examined cognitive performance and self-reported subjective effects the morning after smoking cannabis in adults who regularly used cannabis, compared to a control group with no recent cannabis use. We also examined whether product characteristics and blood/oral fluid cannabinoid concentrations were associated with performance. While cognitive performance did not differ significantly between groups, the cannabis group reported elevated subjective effects on multiple VAS items, suggesting some residual intoxication 12–15 h post-use. Within the cannabis group, smoking infused “joints” and using products with higher percent THC were associated with poorer verbal recall (delayed recall and percent retained). Higher blood THC and THC-COOH concentrations were linked to poorer verbal recall and trail-making performance, whereas elevated blood 11-OH-THC and oral-fluid THC were associated with worse trail-making performance only. Overall, adults who regularly use cannabis may show no measurable next-day cognitive impairment relative to controls, despite subjective effects. However, substantial within-group variability suggests residual impairment may occur with higher-potency products and higher cannabinoid concentrations.
Contrary to our hypothesis, we found no cognitive performance differences between the cannabis group (tested 12–15 h after last use) and controls. This aligns with a systematic review reporting little evidence of next-day performance effects of cannabis exposure (McCartney, Suraev, and McGregor, 2023), but contrasts with systematic reviews finding worse cognitive performance in adolescents and adults who use cannabis compared to control groups, especially in the domain of memory (Figueiredo et al., 2020, Krzyzanowski and Purdon, 2020, Lovell et al., 2020, Platt et al., 2019, Scott et al., 2018). Both groups were age-matched (mean ~30 years old) and the cannabis group reported a mean 11.6 years of use. One possibility is that a later age of cannabis use initiation in our cannabis use group precluded cognitive differences, as earlier initiation has been associated with greater cognitive changes (Crane et al., 2013). However, two meta-analyses in adolescents/young adults (Scott et al., 2018) and adults (Lovell et al., 2020) found no association between age of initiation and cognitive effects. Although education differed between groups, this was statistically controlled, and the cannabis group had lower education, making it unlikely to account for the null findings. Group differences in race could also influence results, as prior literature has suggested that cultural differences and cumulative social inequalities could lead to poorer cognitive task performance in racial minority participants compared to white participants (Rea-Sandin et al., 2021, Zahodne et al., 2016), yet our sensitivity analysis suggested that group differences in race did not meaningfully impact our results. Finally, it is possible that the lack of between-groups differences reflects the limitation of our study design in distinguishing between next-day effects and chronic effects of cannabis. For example, it is possible that the two groups may have differed in cognitive performance if more time had elapsed since last cannabis use in the cannabis group.
Despite the lack of between-group differences, higher THC concentrations were linked to poorer performance within the cannabis group. Smoking infused “joints” (plant material mixed with concentrates or distillates to raise THC content) was associated with worse verbal recall performance, and percent THC in the cannabis products was negatively correlated with verbal recall performance. Blood THC and THC-COOH concentrations were negatively correlated with both verbal recall and TMT performance, while blood 11-OH-THC and oral fluid THC were negatively correlated with TMT performance only. Our results align with prior work showing that a positive urine THC screen, but not other indicators of cannabis use (e.g., total lifetime use, age of initiation), was associated with poorer working memory in a large adult sample, suggesting that residual concentrations of cannabinoids may explain cognitive decrements more than cumulative exposure to cannabis (Owens et al., 2019). Furthermore, our results align with prior systematic reviews concluding that negative cognitive effects of cannabis are often dose-dependent and may emerge only at higher THC doses (Broyd et al., 2016, McCartney et al., 2021). The fact that we saw significant evidence of poorer verbal recall performance in participants who smoked infused (i.e., higher-THC) products compared to those smoking regular pre-rolled “joints” suggests that next-day impairing effects of cannabis may emerge only with very potent cannabis products, which would help to explain why previous studies of next-day effects (using lower-potency cannabis products) generally had negative findings (McCartney, Suraev, and McGregor, 2023). Our findings thus suggest caution should be taken the morning after using very high-potency cannabis products, as there may be residual impairment in verbal memory. This effect was seen most consistently for delayed verbal recall, which may warrant further investigation.
Unexpectedly, we saw significant subjective effects in the cannabis group. The ARCI Marijuana subscale (though no other POMS or ARCI subscales) and nearly all VAS items (e.g., feeling a drug effect, feeling a rush, feeling exhilarated) were significantly greater in the cannabis group compared to controls. This contrasts with prior laboratory studies finding no clear evidence of residual self-reported intoxication > 8 h after last use of cannabis (Chait, 1990, Chait and Perry, 1994, Fant et al., 1998, Heishman et al., 1990), including more recent work from our team that measured subjective drug effects 24 and 48 h after smoking in the lab (Brands et al., 2019, Matheson et al., 2020b). It is possible the residual subjective effects in the present study reflect higher THC potency of the cannabis products consumed; the products used by the cannabis group had a mean potency of 30.0% THC, whereas previous laboratory studies of residual subjective effects administered cannabis with potencies ranging from 2.1% (Chait, 1990) to 12.5% THC (Matheson et al., 2020b). While the VAS scores in the cannabis group were all relatively low (8.4–35.6 on a scale from 0 to 100), some ratings were within the range of acute VAS effects we observed in a previous human laboratory study that administered 12.5% THC smoked cannabis (Fares et al., 2021). For example, mean VAS “good effects” rating in the present study was 35.6, which is between the ratings observed at 3 h (42.6) and 4 h (27.4) after smoking in our previous lab study (Fares et al., 2021). Future studies will need to replicate this finding of residual subjective intoxication, likely associated with higher-potency cannabis products, and determine if there is any practical significance of these effects.
Some key limitations are important to keep in mind. First, due to the cross-sectional nature of the design, we cannot infer causality, and cannot be sure if group differences are related to next-day impacts of cannabis smoking, chronic impact of cannabis use, or other factors. It should be noted that there were no between-groups differences in cognitive performance in this study, and effects were restricted to the cannabis group so it is not likely that this limitation had a great effect on the interpretation of the data. However, while the groups were matched on age and sex and had similar driving experience and sleep characteristics, there were significant differences in race and education, and there could be other unmeasured group differences. Use of a crossover design would be difficult because the cannabis group (who used cannabis very frequently) would experience negative effects (which could confound cognitive results) when abstaining from cannabis for a duration of time needed to obtain a proper baseline. Despite this, there is merit to an observational design which mimics real-world use of cannabis. Second, since the cannabis group participants smoked at home, we cannot be sure exactly when they smoked, how much they smoked, or whether they were acutely impaired or intoxicated at the time of smoking. Participants provided this information by self-report, but we were not able to independently verify it. While these may seem like significant limitations, it is important to keep in mind that naturalistic studies like this one are an important complement to placebo-controlled laboratory studies, as they avoid a number of potential confounds of laboratory experiments (e.g., consuming cannabis in an unfamiliar location, using atypical doses or cannabis products, biases related to being observed while smoking). Third, cognitive performance testing was limited to the verbal free recall task and the Trail-Making Task; including other cognitive tasks (e.g., divided attention tasks, complex tasks of executive functioning) could have yielded different results. Fourth, all participants smoked pre-rolled “joints”, which likely limits generalizability assuming that next-day effects differ depending on route of administration. For example, when administered orally, THC peaks much later and likely takes longer to eliminate (Huestis, 2007), and a prior systematic review concluded that oral THC exposure is associated with a longer duration of cognitive effects (McCartney et al., 2021). Future studies should examine how differences in route administration impact next-day effects of cannabis. Finally, participants in the cannabis group used cannabis 4–7 days/week; our findings may not generalize to individuals who use cannabis less frequently. Indeed, there may be differences between adults who do not use cannabis and those who use rarely or occasionally, given that occasional use is less likely to produce tolerance to the effects of cannabis.
In sum, we did not find evidence of differences in cognitive performance between a group of adults who regularly used cannabis (tested 12–15 h after smoking cannabis at home) and an age- and sex-matched control group endorsing no recent cannabis use. However, we did see evidence of residual subjective drug effects (between-group differences) and significant associations between higher THC concentrations and worse cognitive performance (within-cannabis-group effect). Delayed verbal recall performance was the most consistently negatively impacted by higher THC concentrations. Our results suggest that next-day cognitive effects of smoked cannabis may emerge with higher THC potency products (e.g., infused “joints”) and at higher quantities of use (i.e., higher residual blood THC concentrations). These findings have important public health implications given the rising potency of cannabis products, which we suggest may be associated with residual cognitive effects that have not been observed in prior literature with lower-potency cannabis.
Funding sources
This study was funded by the Transport Canada ERSTPP program. The funder had no role in study design, data collection, analysis, or interpretation, or writing of the manuscript.
Declaration of Competing Interest
Dr. Bernard Le Foll has obtained funding from Indivior for a clinical trial sponsored by Indivior. Dr. Le Foll has in-kind donations of placebo edibles from Indiva. Dr. Le Foll has obtained industry funding from Canopy Growth Corporation (through research grants handled by the Centre for Addiction and Mental Health and the University of Toronto). He has participated in a session of a National Advisory Board Meeting (Emerging Trends BUP-XR) for Indivior Canada and is part of Steering Board for a clinical trial for Indivior. He has been consultant for Shinogi, ThirdBridge and Changemark. He is part of a scientific advisory board for NFL Biosciences. He got travel support to attend an event by Bioprojet. He is supported by CAMH, Waypoint Centre for Mental Health Care, a clinician-scientist award from the department of Family and Community Medicine of the University of Toronto and a Chair in Addiction Psychiatry from the department of Psychiatry of University of Toronto.
Dr. Christine Wickens serves on the Executive Committee of the International Council on Alcohol, Drugs and Traffic Safety (ICADTS) and on the Canadian Society of Forensic Science’s Drugs and Driving Committee, which acts as an advisory body to the Department of Justice with respect to issues of drug impaired driving. She also served on the Board of Directors of the Canadian Association of Road Safety Professionals (CARSP).
No other authors have any conflicts to declare.
Data Availability
The datasets used and/or analysed during this study are available from the corresponding author on reasonable request.
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Associated Data
Data Availability Statement
The datasets used and/or analysed during this study are available from the corresponding author on reasonable request.