Using Prospective Mixed-Methods to Investigate the Impact of the COVID-19 Pandemic on Cannabis Demand

Abstract

Following the COVID-19 pandemic, it is vital to understand how major global stressors impact substance use, including cannabis-related outcomes. The Marijuana Purchase Task assesses hypothetical cannabis demand (i.e., relative reinforcing value), and can detect contextual alterations. This study paired prospective cannabis demand assessment with qualitative inquiry to explore how COVID-19 impacted cannabis use behavior. Individuals previously enrolled in a laboratory cannabis administration study opted-in to a remote follow-up survey (n=41, 46% female). Participants were categorized as those who did/did not increase use based on self-reported changes in cannabis flower use and provided contextual explanations regarding pandemic-related influences on cannabis outcomes. General linear models with repeated measures examined mean differences in demand by occasion (i.e., before/during COVID-19), group (i.e., those who did/did not increase use), and their interaction. Those who increased use exhibited significantly higher demand during the pandemic; those who did not increase use exhibited similar demand across time revealing a group by time interaction. Thematic analysis contextualized quantitative findings, explaining external influences impacting use and demand (e.g., changes in cost, access, environment). COVID-19 differentially impacted cannabis use and demand, with pre-pandemic use affecting trajectories. Contextual influences (i.e., availability, free-time, income) facilitate use escalation under conditions of extreme global stress.

Introduction

In late 2019, severe acute respiratory syndrome coronavirus 2 (i.e., COVID-19) was discovered in Wuhan, Hubei Province, China (Deka & Kalita, 2020) and soon became a global pandemic (Cucinotta & Vanelli, 2020). Since its emergence, governments across the world, including in the United States, have implemented COVID-19 mitigation strategies. Such measures comprised social distancing, quarantine, mask mandates, and stay-at-home orders, among others. As a result, billions have faced social and physical isolation to mitigate the spread of COVID-19 (Sandford, 2020). Contemporaneously, a concerted effort has been made to ascertain how the pandemic has affected physical and mental health outcomes, including effects on substance use (Czeisler, 2020; Czeisler et al., 2021; Dumas et al., 2020).

Prior to the onset of COVID-19, cannabis use prevalence in the United States had been steadily increasing (Compton et al., 2016; Hasin, 2018; Hasin et al., 2017; Mitchell et al., 2020) while perceptions of cannabis’ harms have been precipitously declining (Carliner et al., 2017; Hasin, 2018). Chronic and/or heavy use has been associated with a host of negative outcomes. Thus, examining changes in pandemic-related cannabis use patterns has critical public health implications that can help inform how substance use behaviors may be affected during similar events in the future (Hasin & Walsh, 2021).

A behavioral economic framework may be a particularly useful lens through which to identify how COVID-19, and the necessary strategies to help mitigate its spread, have influenced cannabis use and related negative outcomes. Behavioral economic approaches combine principals from psychology and economics to study decision-making processes, including those pertaining to substance use (Bickel et al., 2014; Higgins et al., 2004; Hursh et al., 2005). Demand, or the relative value of a given reinforcer, is a core behavioral economic construct and crucial factor linked to cannabis use, problems, and cannabis use disorder (CUD) symptoms (Aston & Berey, 2022; Aston & Meshesha, 2020; González-Roz et al., 2023). Cannabis demand is measured using a hypothetical Marijuana Purchase Task (MPT) which assesses cannabis consumption across escalating monetary cost (Aston et al., 2015; Aston, Metrik, et al., 2021; Collins et al., 2014). Five common cannabis demand indices can be obtained from assessing MPT task performance including intensity (i.e., amount of cannabis consumed at $0), O_max (i.e., maximum expenditure on cannabis), P_max (i.e., price associated with maximum expenditure), breakpoint (i.e., price at which cannabis consumption is suppressed to zero), and elasticity (i.e., sensitivity of cannabis consumption to escalating costs).

Since the beginning of the COVID-19 pandemic, social distancing measures, stay-at-home orders, and quarantine guidelines exacerbated negative mental health symptoms (Galea et al., 2020) characterized by fears of poor health, financial instability, and compulsive reassurance-seeking (Taylor et al., 2020). This cluster of distress can manifest as excessive avoidance behaviors and coping difficulties (Taylor et al., 2020), which may contribute to increased substance use in general (McKay & Asmundson, 2020) and augmented cannabis’ reinforcing value as a means to cope with stressful life events specifically (e.g., unemployment-related distress; (Bazrafshan & Elahi, 2020; Crayne, 2020). Consequently, the COVID-19 pandemic may have created conditions wherein cannabis use to cope became more prevalent (Bartel et al., 2020; Leatherdale et al., 2021), while access to, and availability of, alternative sources of non-drug reinforcement simultaneously decreased due to strategies to reduce the spread of COVID-19 (e.g., social distancing, quarantine, isolation). Furthermore, there is reason to believe that both internal and external factors have also affected cannabis’ reinforcing value. However, to our knowledge no published study has examined potential within-person changes in cannabis demand during the COVID-19 pandemic, as well as its effect on other cannabis-related outcomes.

As recent findings suggest cannabis use has changed since the start of the pandemic (Cousijn et al., 2021). Several studies cited an increase in both use (Dumas et al., 2020; Mehra et al., 2023) and cannabis sales in states permitting recreational use (Schauer et al., 2021), while others have cited declining use levels (Boehnke et al., 2021), and still others maintenance of pre-pandemic use levels (Graupensperger et al., 2021; Vanderbruggen et al., 2020). Importantly, recent work has taken a different approach to cannabis use assessment over the course of the pandemic, examining changing use trajectories over time rather than prevalence. One study by Lee and colleagues (2023) found that among those endorsing regular cannabis use through the beginning of the pandemic, distinct use subgroups emerged with some individuals decreasing, maintaining, or increasing their cannabis use across the duration of the COVID-19 pandemic, suggesting that examining trajectories may allow for meaningful assessment of important subgroups that may be experiencing varying levels of risk.

The primary aim of this prospective, mixed-methods study was to determine whether participants who increased their cannabis use from baseline to during COVID-19 reported concurrent increases in cannabis demand. Specifically, we hypothesized that participants who increased their cannabis use would exhibit greater demand during COVID-19 relative to pre-COVID-19 levels. Conversely, we hypothesized that participants who did not increase their cannabis use would exhibit decreased demand during COVID-19 relative to pre-COVID-19 levels. Qualitative data were collected to contextualize quantitative cannabis demand data by exploring how environmental factors influenced use and purchasing decisions. We hypothesized that cost and availability would be key factors impacting participants’ demand during the COVID-19 pandemic.

Method

Participants and Procedures

Adults from the community who frequently used cannabis were recruited in Rhode Island and Massachusetts via flyers and social media. Participants in the current study were enrolled in a larger laboratory cannabis administration study assessing behavioral economic demand and ad libitum cannabis consumption (Aston, Amlung, et al., 2021). Participants met the following inclusion criteria: ability to read and write in English, 18–50 years of age, past month cannabis use ≥ twice weekly on average, past 6-month cannabis use ≥ monthly on average, positive urine toxicology screen for THC at baseline, and purchase of cannabis ≥ twice in the past 6 months. Exclusionary criteria included current treatment-seeking for cannabis use, current possession of a medical cannabis card, Body Mass Index < 18.5 or > 30, pregnancy or lactation in females, refusal to use contraception during study participation, positive breath alcohol concentration, positive urine toxicology screen for drugs other than cannabis, smoking > 20 tobacco cigarettes per day, recent adverse reactions to cannabis, use of medications contraindicating cannabis use, and presence of psychotic symptoms or diagnosis of current depression, mania, or panic disorder as assessed by the Structured Clinical Interview for DSM–5 (First et al., 2015).

Participants completed self-report measures of cannabis use and demand at baseline from April 2018 – Feb 2020 (n = 90). Participants who completed the baseline session and consented to re-contact (n = 86) were invited to complete an online follow-up survey that re-assessed cannabis use and demand in addition to open-ended qualitative questions concerning how external contexts may have impacted cannabis use patterns and behaviors during the COVID-19 pandemic. Participants who opted-in were re-consented and entered into a raffle for a chance to win one of eight $15 Amazon gift cards upon completion of the survey. They were then emailed a link to complete the follow-up survey via Qualtrics. Data from the present study includes participants who completed the baseline appointment and opted-in to the online follow-up survey (n = 42), which were collected in May 2020. Study procedures were approved by the Institutional Review Board of Brown University.

Measures

Demographics.

Participants provided demographic information including age, income, employment, race, and ethnicity.

Cannabis Use.

The Marijuana History and Smoking Questionnaire assessed participants’ typical weekly flower cannabis use quantity in grams (Metrik et al., 2009). Person-level differences in cannabis use quantity were calculated by subtracting participants’ self-reported number of cannabis grams used per week at baseline from the number of cannabis grams used per week at follow-up. The difference score was subsequently recoded to create a dichotomous variable denoting whether participants did (difference scores > 0) or did not (difference scores < 0) increase their cannabis use during the COVID-19 pandemic. The binary group variable was coded as 1 and −1, respectively.

Marijuana Purchase Task

(Aston, Metrik, et al., 2021). Participants were provided with an instructional vignette describing stipulations associated with hypothetical purchasing and consumption of cannabis (e.g., “Assume that you can only get marijuana from this source. You cannot go to a different source for cheaper marijuana and you cannot use any marijuana you may have saved”). Respondents estimated the number of grams of cannabis they would consume in a typical week (7 days) across a range of 20 prices (i.e., $0 - $60 per gram). The following statement was added to the MPT version administered as part of the online follow-up survey: “Keep in mind that we are in the midst of a global pandemic with the spread of the COVID-19 virus, and respond to all questions accordingly.”

Qualitative Open-Ended Response Questions.

The follow-up survey included seven separate free text response questions specific to the impact of COVID-19 on cannabis use and related behaviors: How has your frequency of marijuana use been impacted? How has your mode of use been impacted? How has your location of use been impacted? How has the cost of marijuana been impacted? How has the amount you purchase been impacted? How has your access to marijuana been impacted? How has your current environment impacted your ability to purchase?

Data Analysis Plan

Quantitative Data.

Descriptive statistics were examined for missing data, distributional abnormalities, and outliers in SPSS version 29. Independent samples t-tests and chi-square tests were used to determine whether sociodemographic or cannabis use variables differed between participants who did or did not opt-in to complete the follow-up survey. Among those who completed the follow-up survey, 19 participants (46.3%) reported an increase in their cannabis use from baseline, whereas 22 participants (53.7%) reported a decrease (n=17) or no change (n=5). Paired sample t-tests were used to confirm that changes in cannabis use based on group from baseline to follow-up were statistically significant. Bivariate associations among focal study variables were also examined.

Raw MPT data completed at baseline and during the COVID-19 pandemic were examined for outliers using standardized scores (Z scores > 3.29). A small percentage of outliers detected on the MPT at both timepoints (pre-COVID-19: 2.7%; during COVID-19: 2.5%) were determined to be legitimate high-magnitude values and were recoded to one unit greater than the next highest non-outlying value (Tabachnick & Fidell, 2000). Observed values for intensity, O_max, P_max, and breakpoint were estimated by directly examining MPT performance. Elasticity was derived by fitting individual curves in GraphPad Prism using the Koffarnus exponentiated demand equation (Koffarnus et al., 2015), Q = Q₀ × 10^k(e-αQ₀^{C -1)}, where Q = quantity consumed, Q₀ = derived intensity, k = a constant across individuals that denotes the range of the dependent variable (cannabis grams), C = the cost of the commodity, and α = elasticity or the rate constant determining the rate of decline in consumption based on increases in price (i.e., essential value). K was determined by subtracting the log₁₀-transformed average consumption at the highest price ($60) from the log₁₀-transformed average consumption at the lowest price used in curve fitting ($1) in both the baseline (k = 1.937) and follow-up (k = 2.041) datasets. The two k values were averaged for use in analyses: 1.989. Of those who completed the follow-up survey, elasticity could not be computed for one participant due to constant demand across all price points on the MPT (Stein et al., 2015). Thus, the final sample size for analyses was n=41. An R² value was generated to reflect percentage of variance accounted for by the demand equation (i.e., the adequacy of the fit of the model to the data) in each dataset.

The primary study aim was to determine whether pre- to peri-COVID changes in cannabis demand significantly differed among participants who did or did not increase their cannabis use. Thus, we tested a general linear model (GLM) with repeated measures using multivariate effect estimation to examine mean differences in cannabis demand (i.e., O_max, P_max , breakpoint, intensity, elasticity) based on occasion (i.e., before/during COVID-19), group (i.e., those who did/those who did not increase use), and their interaction. Assumptions of multivariate normality, linearity, non-redundancy across dependent variables, and homogeneity of variance were also examined. A full factorial model tested all main effects and two- (i.e., group*occasion) and three-way (i.e., group*occasion*cannabis demand) interactions. Subsequent post hoc repeated measures analyses of variance (i.e., RMANOVAs) with Bonferroni-corrected pairwise comparisons were tested to determine which specific demand indices differed between groups and across occasions.

Qualitative Data.

Qualitative data were deemed unusable if the response to a question was blank, invalid (e.g., Question: “How has your frequency of marijuana use been impacted?”; Response: “Yes”), or nonsensical (e.g., Question: “Any other change to your purchasing?”; Response: “Hi”). All potentially unusable qualitative data was reviewed by two separate coders who subsequently reported 100% agreement regarding responses that were unusable. Subsequently, usable open-ended responses were coded independently by at least two study staff. using applied thematic analysis (Guest et al., 2012). Using an open coding process, each text response was tagged based on group status and subsequently assessed to identify and compare key topics. Using a matrix framework, topics were grouped into categories representing the spectrum of responses (Skjott Linneberg & Korsgaard, 2019) which allowed for systematic comparison of similarities and differences between and within each group (Gysels & Higginson, 2011; Lindsay, 2019). Coders met to reach consensus and resolve coding discrepancies. Intensive coder discussion, coder adjudication, and simple coder consensus were employed to resolve inconsistencies and used as markers of agreement (Brinkmann & Kvale, 2014; Colditz et al., 2018; Harry et al., 2005; Sandelowski, M., Barroso, 2007). Themes in the data were then identified and compared between groups (Gysels & Higginson, 2011). Topics and themes were described but not quantified as quantitative summaries of qualitative data can be misleading as they do not provide accurate representation of the prevalence or frequency of a given behavior or belief (Hannah & Lautsch, 2011). Illustrative quotes were selected from each group to represent the breadth of each theme in order to contextualize quantitative findings.

Results

Quantitative Results.

Participants.

Sample descriptives are presented in Table 1. O_max, P_max, intensity, and elasticity were positively skewed and subsequently logarithmic transformed, which reduced skew and kurtosis to acceptable levels. The average amount of time between the baseline assessment and completion of the follow up survey was approximately 10 months. The amount of time between assessments did not significantly differ based on participants who did or did not increase their cannabis use from baseline to follow up (t(40) = .447, p = .432). There were no statistically significant differences in baseline sociodemographic characteristics between participants who did (n = 41) and did not (n = 44) complete the follow-up survey. At baseline, those who did not increase use were more likely to be unemployed than those who did increase use, however, there were no significant differences at follow-up.

Table 1.

Sample Descriptives

Variable	Did not complete follow-up survey (n = 44)	Completed follow-up surveya(n = 41)
		Increased cannabis use(n = 19)	Did not increase cannabis use(n = 22)
Age	24.16 (5.17), 18 – 37	23.47 (5.13), 18 – 37	21.82 (4.01)
Individual Annual Income, n (%)
$19,999 or less	28 (63.6)	12 (63.2)	18 (81.8)
$20,000 – 39,999	9 (20.5)	7 (36.8)	2 (9.1)
$40,000 – 59,999	5 (11.4)	-	2 (9.1)
$60,000 or higher	2 (4.5)	-	-
Employment, n (% employed)b
Baselined	27 (61.4)	5 (26.3)	15 (68.2)
Follow-Up	-	9 (39.1)	14 (60.9)
Sex, n (% Male)c	26 (59.1)	11 (57.9)	11 (50)
Ethnicity, n (% Latine)c	6 (13.6)	3 (15.8)	5 (22.7)
Race, n (%)c
Asian	1 (2.3)	2 (10.5)	1 (4.5)
Black/African American	10 (22.7)	4 (21.1)	-
Native Hawaiian / Pacific Islander	-	-	1 (4.5)
White	28 (63.6)	13 (68.4)	18 (81.8)
Other	4 (9.1)	-	2 (9.1)
Weekly Cannabis Use
Baseline typical grams used/weekd	4.80 (4.63), 0.5 – 28	1.81 (1.60), 0.13 – 5	5.89 (7.31), 0.75 – 28
Follow-up typical grams used/week	-	3.78 (3.24), 0.90 – 10	3.36 (5.16), 0.20 – 21

Notes: mean (SD), range presented unless noted otherwise.

^aBased on participants who completed the follow-up survey and had valid MPT demand data at both time-points;

^bEmployment includes full and part-time employment;

^cBased on n=43 for participants who did not complete follow-up survey;

^dSignificant difference between participants that did versus did not increase their cannabis use; Independent samples t-tests and chi-square tests determined that participants did not significantly differ on any sociodemographic or cannabis use characteristics based on whether or not they completed the follow-up survey.

Differences in cannabis use between- and within-groups at baseline and follow-up are presented in Figure 1. Independent samples t-tests indicated that those who increased use used approximately four fewer grams per week on average than those who did not increase use at baseline (t(23.321) = −2.55, p = .018, Cohen’s d = 0.75). However, average cannabis grams used per week during COVID-19 did not differ significantly between groups (t(39) = −0.20, p = .844, Cohen’s d = 0.06). Likewise, paired samples t-tests indicated those who increased use reported using approximately two more grams per week on average during COVID-19 compared to baseline (t(18) = 3.65, p = .002, Cohen’s d = 0.84), whereas those who did not increase use reported using almost three fewer grams per week on average during COVID-19 compared to baseline (t(20) = 2.85, p = .01, Cohen’s d = 0.62).

Figure 1.

Self-reported cannabis use at baseline (pre-) and follow-up (during- COVID-19).

Preliminary Analyses.

Bivariate correlations among study variables are presented in Table 2. There were significant positive associations between each demand index at baseline and its corresponding value at follow-up: intensity (r = .37, p = .013 ), O_max (r = .59, p < .001), P_max (r = .42, p = .006), breakpoint (r = .42, p = .005 ) and elasticity (r = .48, p = .002).

Table 2.

Bivariate correlations among sociodemographic and behavioral economic variables at baseline and follow-up

	1.	2.	3.	4.	5.	6.	7.	8.	9.	10.	11.	12.	13.
Baseline Variables
1. Sexa	-
2. Age	.05	-
3. Employment Statusb	−.17	.31	-
4. Incomec	−.09	.49**	.32*	-
5. Intensityd	.13	.14	.14	.14	-
6. Omaxd	−.08	.21	.24	.26	.83**	-
7. Pmaxd	−.08	.31	−.07	.23	−.30	−.03	-
8. Breakpoint	−.25	.21	.23	.16	.20	.47**	.60**	-
9. Elasticityd	.09	−.16	−.26	−.26	−.81**	−.98**	.09	−.49**	-
Demand at Follow-Up
10. Intensity	.09	−.03	.13	.23	.39*	.25	−.12	−.17	−.20	-
11. Omaxd	.08	.20	.13	.17	.53**	.59**	.15	.25	−.50**	.61**	-
12. Pmaxd	−.07	.28	−.12	.08	−.07	.19	.42**	.37*	−.12	−.41**	.09	-
13. Breakpointd	−.05	.19	−.15	.10	.17	.29	.35*	.43**	−.24	−.19	.34*	.70**	-
14. Elasticityd	−.06	−.20	−.02	−.16	−.49**	−.56**	−.18	−.25	.48**	−.53**	−.96**	−.17	−.44**

Notes:

^*p < .05;

^**p < .01;

^a0=Female, 1=Male;

^b0=Not employed, 1=employed full- or part-time;

^cIndividual annual income, in USD;

^dLogarithmic transformed; n=41

General Linear Models.

Initially, scatter plots were examined to confirm linearity between pairs of dependent variables. Correlations based on the residual SSCP matrix confirmed non-redundancy among the demand indices. Homogeneity of variance was confirmed via Box’s Test of Equality of Covariance Matrices and, while significant (p = .012), did not exceed p < .001.

The full factorial model indicated a significant three-way group by occasion by cannabis demand interaction (F(4, 36) = 6.21, p < .001). The difference in means and the effect sizes for cannabis demand based on group and occasion were large in magnitude (η²_p = 0.41 (Funder & Ozer, 2019). Results from follow-up RMANOVAs with Bonferroni-corrected post hoc comparisons for each MPT demand index are presented below.

O_max.

There was a significant group by occasion interaction for O_max (F(1, 39) = 7.46, p = .009, η²_p = 0.16; Figure 2, Panel A). At baseline, those who increased use reported significantly lower O_max scores than those who did not increase use (mean difference = −0.46, p =.002). Yet, the difference in O_max scores among those who did versus those who did not increase use did not significantly differ at follow-up (mean difference = .10, p = .54). Within-groups, those who increased use reported significantly higher O_max scores at follow-up than baseline, (mean difference = 0.29, p = .005). Alternatively, those who did not increase use reported similar O_max scores at baseline and follow-up, (mean difference = 0.07, p = .419).

Figure 2:

Differences between participants who did or did not increase their cannabis use from baseline (prior to COVID-19) to follow-up (during COVID-19) based on MPT cannabis demand indices. Non-transformed MPT demand indices presented for graphical purposes. Y-axis values for Panels A-C represent USD; Y-axis for Panel D represents number of cannabis hits.

P_max.

The group by occasion interaction for P_max was not statistically significant (F(1, 39) = 3.83, p = .057, η²_p = 0.09; Figure 2, Panel B). At baseline, P_max scores did not differ significantly between those who did versus those who did not increase use (mean difference = 0.13, p = .224). Similarly, P_max scores did not differ significantly between groups at follow-up (mean difference = 0.10, p = .403). Within-groups, P_max scores at baseline and follow-up did not significantly differ for those who increased use (mean difference = 0.16, p = .068) or those who did not increase use (mean difference = 0.07, p = .396).

Breakpoint.

The group by occasion interaction for breakpoint was not statistically significant (F(1, 39) = 2.36, p = .132, η²_p = 0.06; Figure 2, Panel C). At baseline, those who increased use reported significantly lower breakpoint scores than those who did not increase use (mean difference = −12.19, p = .02). Yet, the difference in breakpoint scores among those who did versus those who did not increase use did not significantly differ at follow-up (mean difference = 3.19, p =.592). Within-groups, breakpoint scores at baseline and follow-up did not significantly differ for those who increased use (mean difference = 3.00, p = .488) or those who did not increase use (mean difference = 6.00, p = .140).

Intensity.

There was a significant group by occasion interaction for intensity (F(1, 39) = 15.59, p <.001, η²_p = 0.29; Figure 2, Panel D). At baseline, those who increased use reported significantly lower intensity scores than those who did not increase use (mean difference = −.611, p = .004). Yet, between-group intensity scores did not significantly differ at follow-up (mean difference = 0.19, p = .368). Within-groups, those who increased use reported significantly greater intensity at follow-up than baseline (mean difference = 0.53, p = <.001). Alternatively, those who did not increase use had similar intensity scores at baseline and follow-up (mean difference = −0.27, p = .058).

Elasticity.

There was a significant group by occasion interaction for elasticity (F(1, 39) = 12.98, p < .001, η²_p = 0.25; Figure 2, Panel E). At baseline, those who increased use reported significantly higher elasticity scores than those who did not increase use (mean difference = 0.58, p < .001). Yet, between-group elasticity scores did not significantly differ at follow-up (mean difference = 0.05, p = .773). Within-groups, those who increased use reported significantly lower elasticity scores at follow-up than baseline (mean difference = −0.44, p < .001). Alternatively, those who did not increase use had similar elasticity scores at baseline and follow-up, (mean difference = −0.09, p = .371).

Post hoc sensitivity analyses.

Those who did not increase use included a small subset of participants who reported no change in their cannabis use (n=5) from pre- to peri-pandemic. Thus, we tested an additional post hoc GLM using the procedures described above only including participants who reported increasing or decreasing their use from pre- to peri-pandemic (n=36). Removing these participants did not affect the statistical significance of primary variables of interest (i.e., cannabis demand indices).

Qualitative Results.

Qualitative free response data are presented below. Participants were not required to respond to every question, thus the qualitative results presented below reflect the total number of participants who responded to each question with usable data and are separated by group unless noted otherwise.

(1). How has your frequency of marijuana use been impacted?

Those who did not increase use (n=22). Use decreased/stopped. Those who did not increase use generally reported less use during the pandemic (51, 53, 78, 88), with one participant explaining that they have been “smoking a lot less than [they] usually would at school and with friends” (76). One participant reported complete cessation in use as they were “with family” (89). Use increased. While self-reported grams per week decreased among these participants, some reported a perception that their use increased marginally (79, 21, 81, 25), often due to “boredom” (91, 104), trouble sleeping (91, 50, 12, 50), reduced time demands (39, 92), and for one participant, “the stress of societal conditions due to the virus” (50). A few participants perceived that their use increased to “nearly constantly” (37) or “almost a daily habit” (12). The discrepancy between self-reported cannabis use based on the survey question and qualitative free response item may be attributed to inconsistencies in memory or self-attribution bias. When further evaluated, self-reported increases in use based on the free response item could often be attributed to a change in cannabis formulation, such as edibles (105), which was used more frequently than flower during the pandemic.

Those who increased use (n=17). Use decreased/stopped. Similar to responses from those who did not increase use, some participants who increased use actually perceived their use to be less frequent during the pandemic, citing “social-distancing” (96) and returning “home” (103) to live with family (36). Use increased. The majority of those who increased use qualitatively reported an increase in their use, consistent with their survey response concerning grams per week (100, 41, 72). Several participants attributed their increased use to always “being home” (38, 27), being “less socially active” (27), starting “earlier in the day” (97), and increased ability to “wake and bake” (43). Other factors included being “unemployed” (84), “not going to class” (86), having “fewer responsibilities” (19), and “news and isolation making [them] sad” (38).

Use level not impacted.

Participants across both groups reported that the pandemic had no impact on their use level (those who did not increase use: 29, 31, 58; those who increased use: 49, 6), stating that their use “more or less stayed the same” (7) and “remained around the same” (66).

(2). How has your mode of use been impacted?

Those who did not increase use (n=22). More vaporization of concentrates. Several participants reported switching to vaporizing concentrates (37, 39) for myriad reasons such as “living with family” as this formulation was more “discrete” (104) with less “odor” (31). Others explained relying heavily on their vaping device as it “lasts longer and was easier to obtain than plant-based marijuana” (76). More consumption of edibles. Several participants “switched from smoking to edibles” (89, 91) or endorsed using edibles or tinctures more (39, 7), often “out of concern for lung functioning” (7). One participant went so far as to say “if I had access, I would probably be only using edibles instead of smoking for lung health purposes” (53). More smoking flower. Some participants endorsed a change to using bowls to smoke flower (78, 76) due to increased smoking alone rather that with others (92), though one participant switched to smoking blunts (39).

Those who increased use (n=17). More vaporization of concentrates. Some participants who increased their use also endorsed vaporizing concentrates more than before the commencement of the pandemic (96, 100, 86). One participant attributed this increase in vaporization to living “with multiple roommates” (72). More consumption of edibles. In contrast to many of those who did not increase use adopting use of edibles, only one participant who increased their use cited an increase in their edible use (97). More smoking flower. Some participants actually endorsed more smoking of flower (69, 19), one attributing this to “less access to vape” (43), likely due to dispensary closures.

Mode not impacted.

Several participants across both groups did not switch formulations or adopt a new mode of use (those who did not increase use: 29, 25, 81, 88, 58, 79; those who increased use: 38, 66, 27, 84, 36, 23, 49), stating that their “mode of use has stayed generally consistent” (50) and was “unaffected” (41) by the pandemic.

(3). How has your location of use been impacted?

Those who did not increase use (n=20). Home. Some participants described that they now used cannabis at “home” (25, 104) and “very discretely inside” (76) due to being “quarantined at [their] parent’s house” (51) after moving home from college due to COVID-19 (81, 58), with one stating that they “definitely don’t want to go anywhere else for it” (92). Two participants took discretion to another level explaining that they “[hide] from family in the bathroom” (31, 37). Outside/Car. Two participants noted that they now smoke “outside” (53) but continue to “use edibles indoors” (105). Several other participants reported now using cannabis in their car due to “less smoking in social settings” (29) or “no longer having children in [the] car” (21). One participant explained that their “odds of driving under the influence are much higher in COVID-19, since I donť want to smoke at home, and I donť want to go to other people’s houses” (89).

Those who increased use (n=16). Home. Many participants who increased their use also stated that their primary cannabis use location became “home” (38, 27, 36, 84, 41, 97), often due to being “less social” (43) and not being able to use at “friend’s houses or parties” (100). Outside/Car. One participant explained that they “can no longer smoke inside and instead have to go outside” (85) while another reported “smoking more in the car” (86).

No change in location.

Several participants across both groups cited no change in their cannabis use location (those who did not increase use: 39, 7, 79, 88, 91; those who did increase use: 19, 72, 23, 49, 66) indicating that their use locale “has remained the same” (50) or “has not been affected” (96) during the pandemic.

(4) How has the cost of marijuana been impacted?

Those who did not increase use (n=20). Increased cost. Several participants who did not increase their use described how cannabis became more expensive (78, 81) which may help to explain reductions in their use. Several participants noted that “some people are selling for double the price they usually do” (#89) and that they “would have to pay triple now what they paid last time” (#37). One participant was informed by their supplier that prices were increased specifically “due to the virus” (#76), while others explained that they experienced cost increases due to “switching methods [which] lead to more up-front expense” (7). Reduced cost. Some participants cited reductions in cannabis’ cost (51) due to location changing to “a legal state” (58) and being “in a different city…if anything it is cheaper” (104). One participant explained that their cannabis cost declined “as edibles are cheaper than what I typically buy for flower” (91).

Those who increased use (n=14). Increased cost. Few participants who increased their use reported that cannabis’ cost increased (23), though some were “told that prices have increased” (103). Reduced cost. A few participants agreed that cannabis’ “cost has gone down” (100. 66), with one attributing this to a change in location by noting that “marijuana is now cheaper at home” (85).

No change in cost.

Many participants across both groups agreed that the cost had not been impacted by the pandemic (those who did not increase use: 92, 53, 25, 21, 29, 31, 79, 88, 105), with one participant commenting that the cost “has remained the same price as before the virus” (#58). Predictably, the majority of those who increased use stated that the pandemic has had “no impact” (97, 84, 86) and agreed that the cost remained stable (36, 49, 41, 6, 27) and was “relatively unaffected” (96).

(5). How has the amount you purchase been impacted?

Those who did not increase use (n=20). Purchase more. Several participants who did not increase their use cited an increase in their purchase amount (29, 39) for different reasons. For example, some anticipated impending increases in price (37) so reported purchasing in bulk (92), while others stated they now needed to share cannabis with relatives (#58) and preferred “to not have to go out and purchase as an errand once a week” (7). Purchase less. Most participants who did not increase their use noted a decline in purchasing amounts (78, 53, 51, 81) or less frequent purchasing (105) during the pandemic due to only needing to purchase for themselves (104). Participants also purchased less “due to the prices” (76), also having concentrates (104), and because “edibles are at a higher concentration” (91). One participant believed that the pandemic “might have permanently decreased the amount of marijuana [they] will purchase” as “the world feels really serious now and [they] don’t really have a desire to [use] as much as…before” (89).

Those who increased use (n=18). Purchase more. The majority of those who increased their cannabis use explained that their purchasing amount increased due to the pandemic (27, 86, 41, 23, 100) for a variety of reasons. Some participants explained that they “purchase more readily because expecting less availability and access” (38), “have been buying a larger amount” (85), or “when [they] do buy [they] will stock up” (43). Others described how they “would have purchased less if [they] were not at home” (103), implying that their location during the pandemic impacted the amount they purchase. Another participant explained endorsed having more disposable income to devote to cannabis during the pandemic “because of there being less places to go and things to do” (66). Purchase less. Only one participant who increased their use discussed purchasing less cannabis stating they “have purchased less marijuana since [they] came home” (96), also suggesting that their location during the pandemic impacted their purchase amount.

Amount purchased not impacted.

Several participants across both groups did not cite an increase in their cannabis purchase amount (those who did not increase use: 79, 88, 31, 21; those who did increase cannabis use: 6, 49, 36, 84, 69, 72, 97) explaining that “it has remained the same amount since before the virus” (50).

(6). How has your access to marijuana been impacted?

Those who did not increase use (n=22). More difficult to obtain. The majority of participants who did not increase their use noted how the pandemic impacted their cannabis access (25, 88, 81) and made it “harder to get” (78) because “dispensaries are still closed” (7, 12) and that their supplier had been impacted by “[contracting] the virus” (76). Participants also attributed issues with access to being in a new location to comply with COVID-19 recommendations (91) and difficulty leaving the house to “drive to it” (37). One participant stated they would “not be willing to buy from anyone other than a friend during these times and…would still let the marijuana sit for weeks before [they] would consider it safe” (89). Finally, some noted that the pandemic impacted their access to certain formulations. One participant explained that they “cannot get edibles at the store anymore since they are closed” (21), while another participant noted that “there have been some times where it is hard to find people who sell wax” (39). Easier to obtain. Unsurprisingly, only one participant who did not increase their use stated that cannabis has become “easier” to obtain (58).

Those who increased use (n=18). More difficult to obtain. Several participants who increased their use explained why the pandemic made cannabis difficult to obtain (43, 23, 66), several attributing their decreased access to being at home (36) and “living with [their] parents” (103). Many others agreed that dispensaries were widely affected (38, 84), explaining that “the closure of dispensaries…has affected their plans to get more” (72). Easier to obtain. A few participants stated that cannabis was easier to obtain (100) because there were “more people to buy marijuana from” (85) due to being “on a college campus” (19).

Access not impacted.

Many participants across both groups reported that the pandemic did not impact access to cannabis (those who did not increase use: 105, 53, 31, 79, 29, 51, 104, 92; those who increased use: 6, 49, 86, 27, 69, 97), indicating that access “has remained the same…since before the virus” (50) and “is similar to what it was on campus” (96).

(7). How has your current environment impacted your ability to purchase?

Those who did not increase use (n=21). Environment decreased purchase ability. Importantly, no participants who did not increase their use reported that their environment facilitated obtainment of cannabis during the pandemic. However, the majority of those who did not increase use described how their environment impeded their ability to purchase cannabis during the pandemic (25, 58, 78, 7). Several participants relayed that the change in their environment resulted in concerns about cannabis use around unaware family members (53), necessitating being “way more sneaky about purchases” (76). Several participants attributed their new environment to limiting cannabis access due to restrictive legality in their new state (88) and noting it is “harder to find access in the suburbs” (91). One participant explained that due to their location, they “would have to drive to someone else’s house meaning [they] would be putting [themselves] at risk since it would probably be a dealer who has had contact with lots of other people” (89). Participants also explained that changing their location often limited financial resources to devote to cannabis purchases, with one participant stating they “don’t have biweekly income anymore” (37) and another noting that “under quarantine it is harder to get the money and to move around the city to buy it” (81).

Those who increased use (n=18). Environment increased purchase ability. One participant reported an increased ability to purchase cannabis, stating their new environment “has increased my ability because there is a lot of marijuana in California and it is legal here” (100). Environment decreased purchase ability. Many participants who increased their use described various reasons why their environment impacted their ability to purchase cannabis (43). For example, in some instances a change in environment coincided with the presence of family unsupportive of cannabis use (103), with one participant explaining that their “parents disagree with the concept of smoking marijuana so [they] have to be more secretive…to buy marijuana now” (96) and another participant indicating that they “can only buy at times where [they] know it won’t be suspicious…to leave the house” (36). One participant also indicated that changing location limited their financial resources, stating that they were “not making money anymore as a service worker so no income” (38). Others noted that changing locations impeded the ability to obtain cannabis (66), with one participant explaining that “there is a bigger legal risk where [they] now live” (85).

Environment did not impact purchase ability.

Many participants across both groups did not believe their environment had impacted their cannabis purchasing ability (those who did not increase use: 39, 29, 105, 31, 12, 104, 50, 51; those who increased use: 84, 23, 49, 86, 19, 6, 69, 72, 97, 27), indicating that purchasing had “been unaffected” (92).

DISCUSSION

The present prospective mixed-methods study demonstrated pandemic-related alterations in cannabis demand and use. Importantly, there were significant between-group differences in cannabis demand pre-pandemic. Yet, during the pandemic these significant differences disappeared as demand among those who did not increase their cannabis use remained relatively stable, while demand grew for those who did increase their cannabis use. Examining demand without accounting for pre-pandemic levels obscures meaningful group differences in how the pandemic impacted cannabis use behavior (Lee et al., 2023). These results align with findings from a recent scoping review suggesting that pandemic-related impacts on cannabis use are complex and require consideration of nuance rather than crude assumptions of increased or decreased use (Manthey et al., 2021; Newport et al., 2023). Moreover, the differential pandemic-related impact on demand was further explicated via qualitative data indicating that factors including changes in geographical location, living conditions, employment, finances, and access, among others, all have the propensity to alter cannabis use patterns.

Collectively, those who increased use used less cannabis flower pre-pandemic, and thus arguably had more room to increase their cannabis use during COVID-19. This increase may be attributed to a host of internal and situational factors that arose in the qualitative portion of this research, including adopting new cannabis formulations and modes, selecting modes with more discretion (Aston et al., 2019; Morean et al., 2017), and mandatory location changes which often resulted in environments unsupportive of cannabis use for various reasons (Merrill et al., 2022). For some participants who did not increase their use, the switch from smoking plant-based cannabis was made to reduce possible effects on lung health due to concerns over respiratory distress from COVID-19. Formulation switching was often accompanied by a reduction in flower use. Relatedly, sharing cannabis flower is a commonly endorsed practice among those who use cannabis (Aston, Metrik, et al., 2021), however, participants in this investigation often noted that they were less willing to share joints or blunts due to the potential for virus transmission, consistent with findings from other work (Assaf et al., 2023).

Physical distancing measures and stay-at-home orders increased feelings of isolation and anxiety (Killgore et al., 2020; McKay & Asmundson, 2020). Recent prospective work showed self-reported isolation and coping motives during the pandemic were positively related to increased cannabis use among young adults, even after controlling for baseline cannabis use prior to the pandemic (Bartel et al., 2020). Other work has shown individuals with more anxiety symptoms continued hypothetical cannabis consumption despite increasing cost (Snell et al., 2021). As such, some individuals may find cannabis more reinforcing during COVID-19 as social isolation, life stressors, and adverse mental health symptoms have and continue to become more prominent. In this regard, recent work demonstrated that individuals with increased cannabis demand who endorsed using cannabis to cope were at increased risk of experiencing negative cannabis-related consequences during COVID-19 (Vedelago et al., 2022).

Behavioral economics emphasizes the import of external context on decision-making processes and posits that the availability and value of alternative reinforcers is a key determinant in the decision to engage in substance use (Herrnstein, 1974; Murphy et al., 2013; Vuchinich & Heather, 2003). Pandemic-related regulations (e.g., stay-at-home orders) have been associated with less cannabis use among some adolescents due to decreased availability and an inability to socialize in person (Chu et al., 2020), findings replicated in the current investigation. Moreover, COVID-19 and associated mitigation strategies led to large scale unemployment (Vigo et al., 2020) that may have limited financial resources available for purchasing cannabis (Rehm et al., 2020). Consistent with prior work (Chu et al., 2020), results from the present investigation also indicate that unemployment can result in increased cannabis use due to fewer responsibilities and more leisure time.

While the present study contributes to the cannabis demand literature by demonstrating differential shifts in demand as a function of extreme environmental changes attributed to the pandemic, it is not without limitations. First, the study examined a small sample of individuals who endorsed cannabis use. While replication may be difficult, it is unlikely that COVID-19 will be the last pandemic or global stressor that society will face, thus even work with smaller samples can be leveraged to inform public policy surrounding response to future global catastrophes. Second, participants had to opt-in to complete the survey during the pandemic, which may have resulted in a self-selection bias among the participants in this study. Despite this, participants did not significantly differ on sociodemographic or cannabis use characteristics as a function of survey completion. Third, demand was only assessed at two timepoints. While these timepoints were meaningful in that they provided a naturalistic experiment by comparing pre- and peri-pandemic cannabis use behaviors, the pandemic still continues to impact virtually all aspects of life. As such, demand for cannabis likely continues to shift in response to changes in cannabis access, cost, and availability of alternative reinforcers. Fourth, this study focused on quantity of flower use to differentiate participants. Participants endorsed using other modes and formulations, however, the current study did not quantitatively assess changes in other cannabis formulations. Thus, other work may consider incorporating other cannabis use variables to distinguish participants. Similarly, this investigation employed a MPT specific to cannabis flower (Aston, Metrik, et al., 2021). As such, we were unable to assess demand for other cannabis products (Ferguson et al., 2021). Importantly, while the MPT instructional set instructs participants to assume they will not have the opportunity to use or purchase other substances, including other formulations (e.g., edibles, concentrates), prior to and following task completion, it is possible that changes in use of other cannabis formulations impacted trait demand for cannabis flower. Subsequent work should aim to comprehensively assess cannabis formulation use and demand, potentially via an experimental cannabis marketplace (Coughlin, Jennings, et al., 2024) in order to specifically understand how the presence of multiple cannabis formulations impact demand. Fifth, the present sample consisted of physically healthy adults who endorsed frequent cannabis use, thus it is unclear how cannabis use or demand may have changed during the pandemic among adults endorsing less frequent use or among those with severe cannabis use disorder. Sixth, the open-ended qualitative questions were specific to assessment of changes in use and purchasing that were attributed to COVID-19. As such, changes in use and purchasing that were due to other variables are unknown. Finally, the majority of the sample comprised White young adults. As individuals of minoritized race were disproportionally negatively impacted by the COVID-19 pandemic in numerous ways including significantly increased intensive care unit admission rates (Magesh et al., 2021), increased rates of being uninsured (Magesh et al., 2021), and significantly increased mortality risk (Golestaneh et al., 2020), it is also possible that cannabis demand manifests differently as a function of disparities associated with minoritized status. As such, efforts to recruit diversified samples to participate in subsequent behavioral economic studies is critical, as those of minoritized status face unique barriers in times of extreme global distress.

Demand is a mutable construct impacted by myriad external and internal influences (Acuff et al., 2020). Indeed, the present study demonstrates how salient contextual factors – including changes in the cost of cannabis and its accessibility due to the COVID-19 pandemic – can differentially impact both cannabis use and demand. Collectively, large scale global events, such as COVID-19, have the propensity to greatly alter substance use patterns, and tailored intervention efforts are critical to mitigate rapid rises in use. Public policy efforts to increase alternative non-drug reinforcers (Gebru et al., 2023) hold great promise in the prevention of cannabis use escalation in the face of extreme societal shifts.

Table 3.

Qualitative Open-Ended Survey Questions

Please answer the following questions about how your marijuana use has been impacted by the COVID-19 pandemic.

How has your frequency of marijuana use been impacted?

How has your mode of use been impacted?

How has your location of use been impacted?

Any other changes you have noticed?

Please answer the following questions about how your marijuana purchasing has been impacted by the COVID-19 pandemic.

How has the cost of marijuana been impacted?

How has the amount you purchase been impacted?

How has your access to marijuana been impacted?

How has your current environment impacted your ability to purchase?

Any other changes to your purchasing?