Cannabis and Cognitive Function in Multiple Sclerosis: Findings From a Large Consecutive Clinical Sample

ABSTRACT

Background

Cannabis is commonly used in persons with MS (pwMS) for symptom relief. Previous studies investigating the effects of cannabis on objective cognitive functioning in MS have yielded mixed results.

Aim

To examine associations of recreational cannabis use with objective cognitive performance in a large, consecutive clinical sample of pwMS.

Methods

In a cross‐sectional study, 847 pwMS provided information on cannabis consumption and were administered the Minimal Assessment of Cognitive Function in MS (MACFIMS) battery, assessing memory, executive function, language, and processing speed. Cognitive performance of cannabis users (N = 254) and nonusers (N = 593) was compared by means of a one‐way MANOVA. Multiple linear regressions then examined whether cannabis use independently predicted cognitive test results.

Results

A significant effect of cannabis use on cognitive performance was observed, F(11, 692) = 1.955, p = 0.030, Wilks λ = 0.970, with users performing significantly poorer than nonusers on the SDMT [F(1, 703) = 6.099, p = 0.014]. Regression models, taking into account covariates (age, education, disease duration, anxiety, and fatigue) revealed that cannabis independently predicted performance on the SDMT, PASAT‐3, and PASAT‐2, all p < 0.001. Models explained 15.8%, 7.1%, and 8.7% of variance, respectively.

Conclusion

This cross‐sectional study provides evidence that cannabis use is associated with poorer processing speed and working memory in pwMS, thereby presenting a possible additional risk factor for cognitive impairment. This finding takes on added concern in light of cannabis use increasing with its legalization, and the worldwide increase of cannabis potency.

1. Introduction

In 2018, Canada became the second country in the world, after Uruguay, to formally legalize the acquisition and consumption of cannabis [1]. Less restrictive laws have been associated with a growing interest by patients in using cannabis for a variety of medical conditions [2]. Owing to its purported benefits, such as relief from pain and spasticity, cannabis use is particularly widespread amongst persons with multiple sclerosis (pwMS). Recent findings indicate that over 50% of pwMS currently use cannabis [2], a prevalence almost four times higher than in the general population [3], and nearly twice as high as in those with Parkinson's disease [4].

These high figures raise concerns given that empirical support for the benefits of cannabis on MS‐related symptoms is limited, and only little is known about the side effects of the drug in association with neurological disease [5]. Heavy cannabis use has, for instance, been associated with a decrease in white matter integrity and abnormalities in subcortical structure morphology (e.g., shape of nucleus accumbens, hippocampus, and amygdala) in healthy adolescents and pwMS [6, 7, 8]. Moreover, studies have demonstrated that recreational cannabis use negatively relates to cognitive functioning, particularly attention, learning, and memory [9, 10, 11], A prospective study with over 1000 healthy participants revealed that long‐term cannabis users exhibited IQ decline, along with reduced learning abilities and processing speed, and smaller bilateral volume in total hippocampus [12]. Links have also been noted between reduced cognitive performance in chronic cannabis users and factors such as the frequency, amount, duration, and age at which cannabis use began [13, 14, 15]. In long‐term users, for instance, persistent deficits in memory and attention have been found to intensify with the duration of regular use [16, 17].

Given that cognitive impairment affects approximately 40%–80% of pwMS [18], research investigating risk factors for further cognitive decline is of crucial importance. A handful of studies suggest that recreational cannabis use is associated with more extensive cognitive impairment in pwMS, including deterioration in working memory, executive function, and visuospatial perception compared to nonusers [19, 20, 21]. Impaired processing speed [22] and greater memory dysfunction specifically in male cannabis users [23] have also been reported. Other studies, however, failed to find significant effects of cannabis use on cognition, particularly memory. A cross‐sectional study of recreational cannabis users, for example, reported no between‐group differences in visual memory performance (i.e., BVMT scores) [20, 24], while two others reported no differences on verbal memory measures [21, 25]. Furthermore, findings from a 4‐week treatment of pwMS with a pure Δ‐9‐THC product showed no decline in performance on the symbol digit modalities test (SDMT), attention, working memory, and visuospatial perception [26].

While informative, many of the earlier studies have small sample sizes limiting the generalizability of the results. Additionally, different studies report partially inconsistent findings, emphasizing the need for additional larger‐scale investigations. The current study expands on earlier findings by examining associations of cannabis use with objective indices of cognition in a large, consecutive clinical sample of pwMS.

We hypothesize that our well‐powered study will reveal greater cognitive impairment across different domains, including processing speed, memory, and executive function, in cannabis users compared to nonusers.

2. Methods

2.1. Participants

Retrospective, observational data were obtained from a clinical database of patients with a confirmed diagnosis of MS [27] evaluated between 2006 and 2014 at a tertiary MS neuropsychiatry clinic.

2.2. Demographic and Clinical Data

Demographic and disease‐related variables, namely age, sex, education, employment status, disease course, disease duration, neurological disability (EDSS) [15], and current medications were collected from each participant's clinical database record. Cannabis users were pragmatically defined as those who inhale or ingest cannabis (CBD, THC, or both) with a frequency of at least once a month [28], thereby enhancing the probability of including and assessing people with ongoing exposure to the drug. Given that the following data result from secondary data analyses, there was no corroborative urine testing and no further details about participants' consumption behavior (e.g., frequency) were collected.

2.3. Outcomes

The primary outcome was objective cognitive function, quantified with the Minimal Assessment of Cognitive Function in Multiple Sclerosis (MACFIMS), which includes seven tests, covering the cognitive domains most commonly impaired in pwMS [29]. The full battery comprised the following: (a) language: Controlled Oral Word Association Test Language (COWAT) [30], (b) spatial processing: Judgment of Line Orientation Test (JOLO) [30], (c) learning/memory: California Verbal Learning Test (CVLT‐II) [31] and Visuospatial Memory Test—Revised (BVMT‐R 5 Brief) [32], processing speed/working memory: Symbol Digit Modalities Test (SDMT) [33] and Paced Auditory Serial Addition Test (PASAT) with 3.0‐ and 2.0‐s inter‐stimulus intervals [33, 34], executive function: Delis‐Kaplan Executive Function System (DKEFS) [35]. In addition, a measure of pre‐morbid intelligence was obtained with the Wechsler Test of Adult Reading (WTAR) [21, 25, 36], which evaluates an individual's reading ability, which is frequently maintained despite impairments in other cognitive functions.

As secondary outcomes, we included a series of self‐report surveys: the Hospital Anxiety and Depression Scale (HADS) [37], and the Modified Fatigue Intensity scale (MFIS) [38]. The HADS is a 14‐item scale designed to quantify depression and anxiety in medically ill patients in the past week. The MFIS has participants rate the extent to which fatigue has affected their life in the past 4 weeks on a questionnaire consisting of nine “physical” items, 10 “cognitive” items, and two “psychosocial” items [39].

2.4. Statistical Analysis

All analyses were conducted using IBM SPSS Statistics version 29. Baseline differences between cannabis users and nonusers were examined using independent sample t tests for continuous, normally distributed variables, and χ ² analyses for nominal data. Significance levels were set at p < 0.05. Multivariate analyses of variance (MANOVAs) were conducted to test whether cognitive performance (i.e., MACFIMS raw scores) differed between cannabis users and nonusers. To examine whether cannabis use predicts cognitive performance, multiple linear regressions, including above‐mentioned covariates, were run. For quality control, regression‐relevant assumptions, including normality of residuals, equal variances, homoscedasticity, and absence of multicollinearity, were evaluated before analyses were run. For exploratory purposes, an additional MANOVA examining possible effects of gender and cannabis compounds (CBD, THC) on cognitive function was run.

2.5. Ethics Approval

This study received approval from the Ethics Committees at Sunnybrook Health Sciences Centre, affiliated with the University of Toronto, Ontario, Canada. Informed, written consent was obtained after participants had been given a complete description of the study.

3. Results

3.1. Entire Sample

While the database comprised 1372 patients, cannabis use information was only available for n = 847, leaving n = 525 with missing data. The sub‐sample of 847 patients consisted of 77.2% women (n = 655), with an average age of 44.2 (SD = 11.5) years. Participants' mean disease duration was 10.2 years (SD = 9.0), and median EDSS was 2 (range = 0–8.5). Participants had completed an average of 16 years (SD = 2.7) of education (see Table 1). Based on self‐reports, 254 participants (30%) were defined as cannabis users, and the remaining 593 participants (70%) were assigned to the nonusers group.

TABLE 1.

Baseline demographics and clinical characteristics of cannabis users and nonusers.

	Entire sample (n = 847)	Cannabis users (n = 254)	Nonusers (n = 593)	t, χ 2, or H	p
Age, years (M ± SD)	44.24 ± 11.46	42.72 ± 11.26	45.32 ± 11.39	t = 4.23	< 0.001
Sex (n, % female)	655 (77.2)	188 (74.0)	467 (78.8)	χ 2 = 2.28	0.15
Education, years (M ± SD)	15.99 ± 2.93	15.55 ± 3.03	16.18 ± 2.87	t = 2.88	0.004
Premorbid IQ, WTAR standard score (M ± SD)	107.27 ± 11.34	107.15 ± 11.5	107.30 ± 11.3	t = 0.20	0.84
Currently employed (n, %)	445 (52.5)	143 (56.3)	302 (50.9)	χ 2 = 2.06	0.09
Disease course (n, %)
RRMS	700 (83.3)	213 (83.9)	487 (82.1)	χ 2 = 4.20	0.12
PPMS	72 (8.6)	26 (10.2)	46 (7.8)
SPMS	68 (8.1)	14 (5.5)	54 (9.1)
Disease duration, years (Med, IQR)	8 (12)	8 (13)	7 (10.63)	H = 3.01	0.083
EDSS (Med, IQR)	2 (2)	2 (2)	2 (1.5)	H = 2.88	0.90
DMT use (n, %)
Yes	629 (74.3)	190 (74.8)	439 (74.2)	χ 2 = 0.04	0.86
No	217 (25.7)	64 (25.2)	153 (25.8)
Cannabinoid used (n, %)
THC		32 (12.6)
CBD		47 (18.5)
THC and CBD		175 (68.9)
HADS depression (M ± SD)	7.07 ± 3.99	7.46 ± 3.97	6.90 ± 4.00	t = 1.90	0.058
HADS anxiety (M ± SD)	9.86 ± 4.29	10.45 ± 9.61	9.61 ± 4.23	t = 2.61	0.009
MFIS fatigue (M ± SD)	50.30 ± 16.59	53.48 ± 14.93	48.93 ± 16.64	t = 3.84	< 0.001

Abbreviations: DMT, disease‐modifying therapy; EDSS, Expanded Disability Status Scale; IQR, Interquartile Range; M, mean; Med, median; PPMS, primary progressive multiple sclerosis; RRMS, relapsing–remitting multiple sclerosis; SD, standard deviation; SPMS, secondary progressive multiple sclerosis.

3.2. Sample Comparisons: Cannabis Users vs. Nonusers

3.2.1. Demographics and Clinical Variables

Current cannabis users (n = 254) were younger than nonusers (M = 41.7, SD = 11.3 vs. M = 45.3, SD = 11.4, t = 4.23, p < 0.001) and completed fewer years of education (M = 15.6, SD = 3.0 vs. M = 16.2, SD = 2.8, t = 2.88, p = 0.004). Mean disease duration was shorter in cannabis users than in nonusers (M = 9.2, SD = 8.4 vs. M = 10.6, SD = 9.3, t = 2.04, p = 0.041). Furthermore, 56.3% of cannabis users reported being currently employed compared to 50.9% of nonusers (χ ² = 2.06, p = 0.087). There were no significant differences between these groups with respect to sex, MS disease course, premorbid IQ, EDSS, and DMT use. Detailed comparisons between cannabis users and nonusers are shown in Table 1.

3.2.2. Cognition

Firstly, data were submitted to a MANOVA with cannabis use as a between‐subjects factor and MACFIMS raw scores as independent variables. Results revealed a significant effect of cannabis use, F(11, 692) = 1.905, p = 0.036, Wilks λ = 0.970, with users performing significantly poorer than nonusers on the SDMT, F(1, 702) = 6.099, p = 0.014 (for a summary of cognitive test results in cannabis users and nonusers, see Table 2). To assess whether differences in cognitive performance are predicted independently by cannabis use, a series of multiple regression analyses was run. Demographic and clinical variables which differed significantly between both groups were included as covariates. The first model, which predicted SDMT scores with cannabis use (yes or no), age, disease duration, education (years), anxiety, and fatigue, was significant, F(5, 803) = 31.101, p < 0.001, and explained 15.8% of variance (adjusted R ²) in differences between SDMT scores. Cannabis use (yes vs. no) alone significantly predicted (𝛽 standardized = 0.90, p = 0.007) SDMT performance, and so did all included covariates. Benjamini–Hochberg procedure was applied to correct for multiple comparisons [40]. p values for all variables remained significant after correction. The model has a small to medium effect size (Cohen's f = 0.19) and power. Furthermore, models predicting PASAT‐3 and PASAT‐2 scores using cannabis and the above‐mentioned covariates reached significance [F(6, 777) = 10.826, p < 0.001; F(6, 701) = 12.163, p < 0.001]. The models explained 7.1% and 8.7% of the variance respectively. Again, cannabis use alone was a significant predictor of test performance (PASAT‐3: 𝛽 standardized = 0.97, p = 0.006; PASAT‐2: 𝛽 standardized = 0.107, p = 0.004). For all three measures of processing speed and working memory, cannabis use, lower education, and greater fatigue were associated with worse performance (for a summary of significant regression models, see Table 3). Predictor variables remained significant after Benjamini–Hochberg corrections were applied. Models predicting other cognitive test scores (memory, language, executive function) by cannabis use were not significant (all p > 0.05).

TABLE 2.

Cognitive assessment scores in cannabis users and non‐users.

Cognitive domain	Cognitive test	Cannabis users (n = 254)	Nonusers (n = 593)	F	p
		Mean (SD)	Mean (SD)
Learning and memory	CVLT‐II immediate recall	52.66 (11.64)	54.37 (11.70)	1.90	0.17
	CVLT‐II delayed recall	11.60 (3.71)	11.18 (3.68)	0.976	0.324
	BVMT‐R total recall	23.23 (7.17)	24.13 (6.72)	3.33	0.068
	BVMT‐R delayed recall	8.82 (2.76)	9.09 (2.64)	2.167	0.141
Verbal fluency	COWAT total score	38.12 (10.71)	37.62 (10.63)	1.86	0.173
Visuospatial perception	JOLO total score	26.05 (4.21)	26.17 (4.07)	0.025	0.875
Executive functioning	D‐KEFS Sorting	37.09 (10.37)	37.69 (9.21)	1.31	0.254
	D‐KEFS Description	9.87 (2.56)	10.04 (2.35)	1.13	0.287
Processing speed	SDMT	49.86 (11.86)	51.81 (11.95)	6.10	0.014
	PASAT 3.0	41.30 (10.76)	42.18 (10.79)	1.79	0.182
	PASAT 2.0	30.61 (9.44)	31.80 (9.58)	3.01	0.083

Note: p ≤ 0.05 are highlighted in bold.

Abbreviations: BVMT‐R, Brief Visuospatial Memory Test‐Revised; COWAT, Controlled Oral Word Association Test; CVLT, California Verbal Learning Test; D‐KEFS, Delis‐Kaplan Executive Functions Test; JLO, Judgment of Line Orientation; PASAT, Paced Auditory Serial Addition Test; SDMT, Symbol Digit Modalities Test.

TABLE 3.

Summary of significant regression models predicting performance on the SDMT, PASAT‐3, and PASAT‐2.

	SDMT				PASAT‐3				PASAT‐2
	B a	95% CI	β b	p	B	95% CI	β	p	B	95% CI	β	p
Cannabis use (yes/no)	2.78	[0.96, 4.61]	0.10	0.003	2.58	[0.74, 4.42]	0.097	0.006	2.19	[0.70, 3.67]	0.11	0.004
Age	−0.26	[−0.35, −1.80]	−0.04	< 0.001	−0.017	[−0.10, −0.07]	−0.015	0.71	0.005	[−0.06, −0.08]	0.01	0.88
Education (years)	0.54	[0.26, 0.83]	0.12	< 0.001	0.78	[0.49, 1.07]	0.19	< 0.001	0.59	[0.35, 0.82]	0.18	< 0.001
Disease duration	−0.14	[−0.25, −0.03]	−0.09	0.011	−0.08	[−0.19, −0.03]	−0.06	0.13	−0.09	[−0.17, −0.003]	−0.08	0.06
HADS anxiety	0.49	[0.28, 0.71]	0.16	< 0.001	0.08	[−0.14, 0.30]	0.03	0.49	0.10	[−0.08, 0.28]	0.05	0.046
MFIS fatigue	−0.17	[−0.23, −0.11]	−0.21	< 0.001	−0.12	[−0.18, −0.06]	−0.16	< 0.001	−0.12	[−0.17, −0.8]	−0.21	< 0.001

Note: p ≤ 0.05 are highlighted in bold.

Abbreviations: PASAT‐2, PASAT‐3, Paced Auditory Serial Addition Test (PASAT) with 3.0‐ and 2.0‐s interstimulus intervals; SDMT, Symbol Digit Modalities Test.

^a Unstandardized regression weights.

^b Standardized regression weights; standardization is based on z‐scores with mean = 0 and standard deviation = 1.

Additional analyses were run to examine a potential cannabis‐sex interaction associated with impaired cognition. However, no significant interaction effect was observed, F(10, 660) = 1.260, p = 0.203, Wilks λ = 0.981, η ² _p  = 0.019. Furthermore, no between‐group differences were observed when comparing the cognitive performance of participants using THC (n = 32), CBD (n = 47) or both (n = 175), F(11, 251) = 0.940, p = 0.546, Wilks λ = 0.940, η ² _p  = 0.045.

3.2.3. Patient‐Reported Outcomes

Compared to nonusers, cannabis users reported greater anxiety (M = 10.5, SD = 4.4 vs. M = 9.6, SD = 4.2, t = 2.61, p = 0.009) and greater fatigue (M = 53.5, SD = 15.0 vs. M = 48.9, SD = 16.9, t = 3.84, p < 0.001). Depression scores were higher for cannabis users than nonusers, but differences did not reach significance (M = 7.5, SD = 4.0 vs. M = 6.9, SD = 4.0, t = 1.90, p = 0.058).

4. Discussion

Research on the neurocognitive effects of cannabis continues to grow rapidly. This is a pertinent area of research, especially in pwMS, considering the high prevalence of cognitive impairment in this population and the potential detrimental effects cannabis can have on cognitive function. While evidence from clinical trials emphasizes the beneficial results of cannabinoids in reducing spasticity and pain [41, 42], existing literature also suggests possible impairments in cognition [8, 23]. A recent systematic review stresses the need for additional, high‐quality studies to fully understand the impact of cannabis use on cognition in pwMS [19], allowing clinicians to make evidence‐based, informed recommendations to their patients. Our findings should therefore be viewed in the context of a paucity of large sample data assessing the interplay of cannabis and cognitive function in the MS literature.

Our main findings indicate that cannabis use predicts performance on measures of processing speed and working memory, that is, the SDMT, PASAT‐3, and PASAT‐2. Cannabis use is associated with a significant decrease in cognitive performance on these tasks, even when controlling for potential demographic and clinical confounding factors (i.e., age, education, disease duration, anxiety, and fatigue). These results confirm findings from previous work showing detrimental effects of cannabis use on processing speed [22, 23]. A retrospective analysis of data from a computerized variant of the SDMT provided the first evidence for street cannabis use negatively affecting processing speed in pwMS. A small sample of 10 current cannabis users was matched on demographic and disease variables to four pwMS who did not use cannabis (total N = 40). Nonusers performed nearly 50% better on the SDMT than users did. These initial findings were extended in a subsequent study with 50 pwMS (25 cannabis users, 25 nonusers), revealing poorer performance in cannabis users on measures of processing speed as well as working memory, executive function, and visuospatial perception [20]. In line with this, a cross‐sectional study showed that pwMS who smoked cannabis (N = 20) displayed more extensive working memory problems and poorer performance on the 2‐s PASAT [25]. Additional evidence came from a randomized placebo‐controlled trial, which primarily focused on the short‐term effect of smoked cannabis on spasticity symptoms in a sample of 37 pwMS. Secondary outcome was performance on the 3‐s PASAT, where cannabis users performed significantly poorer than nonusers [42]. Overall, previous findings strongly suggest that cannabis‐using pwMS present with more cognitive deficits across different domains than pwMS who are drug naïve.

Our findings significantly contribute to the existing literature in the field. Contrary to previous studies with small sample sizes, we compiled and analyzed data from over 800 pwMS, of whom one third self‐identified as cannabis users. Access to such a large, consecutive clinical sample allows for more reliable results with smaller margins of error and lower standard deviations. Consistent with prior research in the field [8, 20, 36], our sample predominantly included participants with relapsing–remitting multiple sclerosis and lower levels of disability, reflecting the characteristics typically observed in the general MS population. While it remains unclear whether cannabis use affects cognition globally, the present findings indicate the detrimental effects on processing speed and working memory in pwMS. In this context, mention should be made of recent findings suggesting that cannabis and sex interact in the pathogenesis of cognitive impairment in MS, with memory deficits being most prominent in male cannabis users [23]. This intriguing finding could, however, not be replicated in our dataset, as no significant differences between male and female participants were observed.

PwMS most commonly use cannabis to manage sleep disturbances, pain, spasticity, and anxiety [43, 44]—and it appears as if these patient‐perceived benefits outweigh the negative effects on cognitive function. Interestingly, the present data show significantly higher anxiety scores in cannabis users compared to nonusers, raising the question of whether cannabis use actually reduces anxiety or, on the contrary, increases the likelihood of presenting with anxiety. The directionality of these associations remains debatable. While some studies have provided epidemiological evidence for heavy cannabis use increasing the risk of anxiety and mood disorders in the general population [45], others found no longitudinal associations between the variables [46]. Further studies in pwMS are warranted to disentangle associations of cannabis use and incidence of depression/anxiety.

Also worth mentioning is the marked continuous increase in concentrations of delta‐9‐tetrahydrocannabinol (Δ⁹‐THC), the principal psychoactive agent contained in cannabis, since the 1970 [47]. In the province of Ontario, where we recruited our sample, the majority of THC‐based products contain more than 15% high potency THC [48], an observation consistent with the reported increase in cannabis potency worldwide [49]. This concerning trend might further contribute to the adverse effects cannabis use has on cognitive functioning in general, and in pwMS more specifically. Previous findings suggest that cannabis‐related cognitive deficits in pwMS are associated with THC use specifically [49, 50]. Animal models suggest that THC binds to cannabinoid receptors in the brain, disrupting the regulation of endocannabinoid production, thereby interfering with the proper functioning of various brain activities, such as memory, reward processing, or mood regulation [51]. No significant differences between participants solely using THC versus CBD were observed in the present study, possibly due to small sample sizes and the self‐reported nature of cannabinoids used by participants.

Our study has some limitations. Data were not collected for the sole purpose of examining the effects of cannabis on cognitive function and, as such, we lack objective confirmatory laboratory evidence of cannabis use, the breakdown of THC and CBD, and data concerning the frequency and duration of use. Future studies should incorporate urine samples, able to detect cannabis metabolites up to a month after consumption, and saliva testing effective for the last 4–6 h.

Given that cannabis use was defined with a frequency of at least once a month, data ignore patients with a chronic use of cannabis that consume less than monthly or have stopped consuming more than 1 month before inclusion. Recent data, however, indicate that after 28 days of cannabis withdrawal, urine levels of cannabis metabolites are close to zero and cognitive function already significantly improves [36].

Moreover, our data do not permit differentiation between the long‐lasting effects of non‐psychoactive metabolites and those resulting from acute or ongoing recreational consumption. In line with this, it is noteworthy that over one‐third of patients chose not to disclose information about their cannabis usage, possibly due to fears of judgment or criminalization. These same concerns may have prompted other patients to provide inaccurate statements regarding their cannabis consumption. The majority of patients were referred to the clinic to examine their cognitive function and/or to address neuropsychiatric symptoms, which may have resulted in a sample selection bias, possibly limiting the generalizability of results. While the large sample size increases the validity of our findings, the cross‐sectional nature of the sample does not allow us to determine causality. Nevertheless, a compelling picture emerges in a large sample of consecutive clinic attendees of cannabis negatively affecting processing speed and working memory in pwMS. While further well powered longitudinal studies are needed to enhance our understanding of this relationship, the evidence suggests that people with MS and the medical personnel who tend to them should approach the use of cannabis with caution, mindful of the potential for further cognitive compromise.

Author Contributions

Anne Kever: writing – review and editing, writing – original draft, methodology, software, formal analysis, data curation, visualization, validation, investigation. Cecilia Meza: methodology, writing – review and editing, formal analysis. Anthony Feinstein: conceptualization, funding acquisition, investigation, writing – review and editing, supervision, resources, project administration.

Conflicts of Interest

Anthony Feinstein reports grants from the MS Society of Canada, book royalties from Johns Hopkins University Press, Cambridge University Press, Amadeus Press, and Glitterati Editions, and speaker's honoraria from Novartis. The other authors declare no conflicts of interest.

Kever A., Meza C., and Feinstein A., “Cannabis and Cognitive Function in Multiple Sclerosis: Findings From a Large Consecutive Clinical Sample,” European Journal of Neurology 32, no. 7 (2025): e70142, 10.1111/ene.70142.

Data Availability Statement

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.