Abstract
Introduction
As cannabis is illegal in France, there is no regulation of the quality or composition of cannabis products on the illicit market. Although access to drug checking services for people who use drugs (PUD) is possible in several harm reduction (HR) structures for a large number of illicit substances, these structures seldom have the tools needed to adequately analyze organic substances such as cannabis.
Methods
We conducted an online survey among people who use cannabis. The survey questionnaire collected data on respondents’ socio-demographic characteristics, use of cannabis and other psychoactive substances, and their willingness to use a cannabis drug checking service. We constructed a multivariable logistic regression model to explore factors associated with the latter dimension.
Results
Among the 553 participants included in the analyses, 73.4% said they would be willing to use a cannabis checking service. Self-identifying as a woman was negatively associated with the desire to use such a service (ORa [95% CI] = 0.54 [0.35–0.86]). In contrast, having a tertiary education level (ORa [95% CI] = 2.14 [1.45–3.17]) and declaring therapeutic use of cannabis (sometimes/often: ORa [95% CI] = 1.71 [1.09–2.69]; always: ORa [95% CI] = 2.61 [1.25–5.49]) were positively associated factors.
Conclusions
Our results highlight the strong willingness of many people who use cannabis in France to control the quality of the cannabis they obtain, particularly persons who use cannabis for therapeutic reasons. The implementation of adequate cannabis checking services in HR structures must take into account the diversity of populations that consume cannabis; in particular, they should be designed in such a way as that more women and persons with a lower level of education will use them.
Keywords: Drug checking, Cannabis, Willingness, Online survey, France
Background
In France, there is no legal, regulated, cannabis market, and the use, sale and cultivation of cannabis remain strongly repressed [1]. The legal market for low-THC cannabis products has been growing for a decade, yet the regulatory framework remains limited [2]. When certain psychoactive substances are prohibited, there is no regulation of the production or the quality of related products sold on the illegal market. This means that people using drugs (PUD) cannot know with certainty the composition and purity of the illegal products they consume. In order to increase their profits, sellers may deliberately adulterate products. Specifically, they adulterate products with other active substances which reproduce expected effects, or with non-active substances which increase the performance of the product [3]. With the diversification of new psychoactive substances (NPS) on the unregulated market, existing substances are also sometimes replaced by others derived from them but whose toxicity is less well known [4]. For example, products sold as herbal cannabis can be adulterated with synthetic cannabinoids mimicking the pharmacology of phytocannabinoids [5, 6]. Moreover, products can be unintentionally contaminated due to poor production and storage conditions [3].
In the context of harm reduction (HR) associated with the use of unregulated substances, numerous drug checking services exist in Europe [7]. The types of analytical techniques used vary greatly; they can be ‘qualitative’ in nature, indicating the presence or absence of the expected molecules, or ‘quantitative’, indicating the precise dosages of the molecules present. Some of these services are provided to PUD from fixed locations; others are offered in mobile units and can therefore be used, for example, at party events. Drug checking services are valuable tools for monitoring the quality of products in circulation [8]. For example, between 2011 and 2021, a drug checking service in Zurich, Switzerland, identified unexpected substances in an average of 58% of the drug samples (approximately 10% of ecstasy samples, and close to 100% of heroin samples) provided by PUD for analysis [9]. These services are also valuable for helping PUD to adjust their substance consumption [8]. They provide alerts to PUD regarding the dosages of products in circulation or the presence of an undesirable molecule [7]. With this information, PUD can choose whether or not to consume the product, or can modify the quantity they consume. Studies attest to the potential behavioral impact of drug checking services on PUD, particularly on their intention to consume if analytical results do not match their expectations [10–14].
Research into the perceptions and motivations of PUD can guide the implementation of HR services to ensure these services meet the needs of the targeted population. In party events (e.g., music festivals), the use of illegal substances is frequent and drug checking services are sometimes implemented [15]. Cross-sectional studies of PUD who attend these party events show a high willingness to use drug checking services if they were available [10–12, 16]. In North America, in a context of overdose crisis, providing drug checking services for PUD seem to be a major public health issue. Quantitative studies show that PUD at high risk of overdose (i.e., who use substances by injection, who face social vulnerabilties, etc.) report a moderate to high intention to use drug checking services [17–19], depending on the type of drug checking service. Qualitative studies show that potential users of these drug checking services can be reluctant to use them, notably because of the time dedicated, the abandonment of a product sample, the lack of accuracy in measurement, the lack of service accessibility, or the fear of stigmatizing treatment or police presence [20, 21].
Few HR services in France offer a drug checking service tailored to people who use cannabis (PUC). However, studies show that a large proportion of adults (11.3%) in the French general population used cannabis at least once in 2020, and that 3.2% used it regularly (≥ 10 times per month) [22]. In addition, data on the use of a number of HR structures in Europe which offer drug checking show that many people who use these services (i.e., for substances different from cannabis) also consume cannabis [23, 24]. SINTES, the National Identification System for Toxics and Substances, is a monitoring and warning system coordinated by the French Monitoring Centre for Drugs and Drug Addiction (OFDT); it analyzes samples of products with suspected NPS sent for checking by HR associations, such as herbal cannabis adulterated with synthetic cannabinoids [25]. Between 2012 and 2013, the OFDT conducted a study on the cannabinoid composition of 253 samples of herbal cannabis and 190 samples of cannabis resin collected from PUC in seven French cities via the SINTES system, and they described the profiles of participants. Results highlighted that those who provided samples were mainly men, aged 30 years on average, with a stable source of income, and who consumed cannabis daily [26]. Only a small number of the HR structures providing drug checking services to PUD have the tools to adequately analyze organic products, such as weed and cannabis resin.
The composition of cannabis impacts associated risks for PUC in different ways. First, the dosage of delta-9‐tetrahydrocannabinol (THC), which is the main molecule involved in the substance’s psychoactive effects, influences effect potency and the severity of consumption-related complications, including the risk of dependence, a deterioration of mental health and poorer cognitive functions [27]. However, the pharmacological effects of cannabis are also modulated by all the other phytocannabinoid and terpenoid molecules present in the plant and therefore in the final product. These work in synergy to produce an overall pharmacological effect called the “entourage effect” [28]. While some molecules lead to additional or enhanced pharmacological effects as part of the entourage effect, research has shown that cannabidiol (CBD), and the THC/CBD ratio may moderate some of the cognitive and psychiatric effects of THC [29]. It is important to point out that in recent decades, an increase in the concentration of THC has been observed in products circulating in France [30] and elsewhere [31], while the concentration of CBD has remained stable. Some products labelled “CBD product” have also been found to contain high levels of THC [32]. Second, the emergence of synthetic cannabinoids on the unregulated market for cannabis has impacted risks for PUC [5, 6]. Specifically, the consumption of synthetic cannabinoids can lead to more adverse effects and greater clinical complications than cannabis of natural origin [33]. Finally, suboptimal cannabis cultivation, processing and storage conditions may lead to contamination of products with pathogenic or toxic components (e.g., bacteria, fungi, pesticides, heavy metals, etc.) that can be absorbed into the body [34, 35]. The clinical implications of these processes have not yet been examined in detail.
Offering drug checking services adapted to cannabis in its organic form could be a valuable HR tool for PUC, a population with generally limited knowledge of the cannabinoid concentration of the products they consume [36, 37]. Greater knowledge about cannabinoid concentration could help PUC to better assess the strength of expected effects, and therefore impacts the quantity consumed [38]. To date, few studies have been conducted on PUC’s interest in cannabis drug checking services and the profiles of PUC who would be willing to use them. The present study aimed to explore the factors associated with willingness to use a drug checking service for cannabis, using a sample of PUC living in France recruited online.
Methods
The data used for the present study came from CANNAVID 2, an online survey conducted during the second COVID-19 lockdown in France in collaboration with the HR association Bus 31/32, which is based in Marseille. The initial objective of CANNAVID2 was to retrospectively study the impact of COVID-related lockdowns in France on PUCs’ cannabis consumption and health. The survey was posted online between November 30, 2020 and January 30, 2021. To diversify recruitement, the survey was circulated on various French-language social media and press plaforms, including those aimed at a general audience and others specializing in cannabis and psychoactive substances. Recruitment criteria were as follows: over 18 years old, consumed cannabis daily before the country’s second COVID-19 lockdown (which commenced on October 30, 2020), and living in France. Survey respondents who did not answer the questions relating to age and gender were excluded. The survey questionnaire was in the French language and was self-administered. It was made accessible using the online survey tool “Limesurvey.org”. By clicking on the survey link, participants received an information notice regarding the study’s objectives and the protection of their data. No monetary compensation was given for participation. To guarantee anonymity, no identifying information was collected. The INSERM national ethics committee approved the study (IRB 00003888, n°20–676).
For the present analysis, we selected the following declarative data: sociodemographic characteristics (age, gender, education level, housing type (e.g., personal, temporary), professional activity, parenthood, area of residence (i.e., urban, rural), and receiving food aid), consumption of psychoactive substances (using the AUDIT-C questionnaire for alcohol use, and use in the previous month of tobacco, opioids, stimulants, benzodiazepines, ecstasy, ketamine, psychedelics, GHB/GBL and NPS, as well as adverse effects experienced, and previous use of drug checking services), and cannabis consumption (form, mode of consumption, frequency, therapeutic use, mode of supply, and willingness to use a cannabis drug checking service).
With regard to psychoactive substances that can be obtained legally through prescription (i.e., opioid medications, benzodiazepines), we did not distinguish between those which respondents declared had in fact been prescribed by a medical professional and those which they had obtained through non-prescription channels. All the declarative data used in the present analysis related to the situation of participants before the start of the second COVID-19 lockdown in France (which began on October 30, 2020). No question was obligatory and participants had the option of answering “I don’t know” to all questions. The average time to complete the questionnaire was approximately 20 min.
The study outcome was participants’ willingness to use a cannabis checking service. This was evaluated by the following question: “Would you be willing to use a drug checking service to have your cannabis analyzed?” (Yes vs. No). As only a small number of participants did not answer this question, they were classified in the “No” group. All categorical exploratory variables were dichotomized into “Yes” and “No” (see Tables 1 and 2), with the exception of the variables ‘Mode of cannabis consumption’, ‘Therapeutic use of cannabis’ and ‘Mode of supply’. For the dichotomized variables, missing data and “Don’t know” answers were recoded as ‘No’. Only the ‘age’ variable was used as a continuous variable.
Table 1.
Stratified descriptive analysis on willingness to use a drug checking service for cannabis (Yes vs. No), Chi2 test and Wilcoxon-Mann-Whitney test (N = 553)
| Variables | Total N(%) | Yes N(%) | No N(%) | p-value |
|---|---|---|---|---|
| Age (median [interquartiles]) | 26 [23–37] | 26 [23–36] | 27 [22–38] | 0.864 |
| Gender | 0.025 | |||
|
Man Woman |
438 (79.2) 115 (20.8) |
331 (81.5) 75 (18.5) |
107 (72.8) 40 (27.2) |
|
| Tertiary education qualification | 0.000 | |||
|
No & Don’t know/missing Yes |
246 (44.5) 307 (55.5) |
162 (39.9) 244 (60.1) |
84 (57.1) 63 (42.9) |
|
| Professional activity & studies | 0.998 | |||
|
No & Don’t know/missing Yes |
143 (25.9) 410 (74.1) |
105 (25.9) 301 (74.1) |
38 (25.9) 109 (74.1) |
|
| Urban living environment | 0.282 | |||
|
No (rural, semi-urban) & Don’t know/missing Yes |
187 (33.8) 366 (66.2) |
132 (32.5) 274 (67.5) |
55 (37.4) 92 (62.6) |
|
| Personal accommodation | 0.770 | |||
|
No & Don’t know/missing Yes |
138 (25.0) 415 (75.0) |
100 (24.6) 306 (75.4) |
38 (25.9) 109 (74.1) |
|
| Living with a partner | 0.520 | |||
|
No & Don’t know/missing Yes |
330 (59.7) 223 (40.3) |
239 (58.9) 167 (41.1) |
91 (61.9) 56 (38.1) |
|
| Had children | 0.702 | |||
|
No & Don’t know/missing Yes |
434 (78.5) 119 (21.5) |
317 (78.1) 89 (21.9) |
117 (79.6) 30 (20.4) |
|
| Received food aid 1 | 0.432 | |||
|
No & Don’t know/missing Yes |
541 (97.8) 12 (2.2) |
396 (97.5) 10 (2.5) |
145 (98.6) 2 (1.4) |
|
| Principal form of cannabis consumed : herbal | 0.093 | |||
|
No, other & Don’t know/missing Yes |
162 (29.3) 391 (70.7) |
111 (27.3) 295 (72.7) |
51 (34.7) 96 (65.3) |
|
| Mode of cannabis consumption | 0.649 | |||
|
Joints with majority of tobacco Joints with a majority of cannabis Bong, pipe Not smoked: vaporisation, ingestion (missing data not shown, N = 6) |
367 (66.4) 121 (21.9) 20 (3.6) 39 (7.1) |
274 (67.5) 88 (21.7) 14 (3.4) 25 (6.2) |
93 (63.3) 33 (22.4) 6 (4.1) 14 (9.5) |
|
| Daily use of cannabis | 0.124 | |||
|
No & Don’t know/missing Yes |
77 (13.9) 476 (86.1) |
51 (12.7) 355 (87.4) |
26 (17.7) 121 (82.3) |
|
| Therapeutic use of cannabis | 0.049 | |||
|
Never Sometimes, often Always Don’t know & missing data |
129 (23.3) 318 (57.5) 62 (11.2) 44 (8.0) |
83 (20.4) 240 (59.1) 50 (12.3) 33 (8.1) |
46 (31.3) 78 (53.1) 12 (8.2) 11 (7.5) |
|
| Mode of cannabis supply | 0.572 | |||
|
Illicit market Home cultivation Friends, social circle Other, don’t know & missing data |
332 (60.0) 91 (16.5) 93 (16.8) 37 (6.7) |
250 (61.6) 62 (15.3) 67 (16.5) 27 (6.7) |
82 (55.8) 29 (19.7) 26 (17.7) 10 (6.8) |
|
| Harmful alcohol use 2 | 0.971 | |||
|
No & Don’t know/missing Yes |
78 (56.9) 59 (43.1) |
50 (56.8) 38 (43.2) |
28 (57.1) 21 (42.9) |
|
| Daily tobacco use | 0.449 | |||
|
No & Don’t know/missing Yes |
229 (41.4) 324 (58.6) |
172 (42.4) 234 (57.6) |
57 (38.8) 90 (61.2) |
|
| Opioid use 1 3 | 0.121 | |||
|
No & Don’t know/missing Yes |
506 (91.5) 47 (8.5) |
367 (90.4) 39 (9.6) |
139 (94.6) 8 (5.4) |
|
| Stimulant use 1 4 | 0.395 | |||
|
No & Don’t know/missing Yes |
434 (78.5) 119 (21.5) |
315 (77.6) 91 (22.4) |
119 (81.0) 28 (19.0) |
|
| Benzodiazepine use 1 | 0.223 | |||
|
No & Don’t know/missing Yes |
519 (93.9) 34 (6.1) |
378 (93.1) 28 (6.9) |
141 (95.9) 6 (4.1) |
|
| Use of other psychoactive substances 1 5 | 0.201 | |||
|
No & Don’t know/missing Yes |
356 (64.4) 197 (35.6) |
255 (62.8) 151 (37.2) |
101 (68.7) 46 (31.3) |
|
| Polysubstance use (≥ 2) 1 6 | 0.088 | |||
|
No & Don’t know/missing Yes |
391 (70.7) 162 (29.3) |
279 (68.7) 127 (31.3) |
112 (76.2) 35 (23.8) |
|
| Adverse effect(s) from consuming a psychoactive substance 1 6 | 0.037 | |||
|
No & Don’t know/missing Yes |
437 (79.0) 116 (21.0) |
312 (76.8) 94 (23.2) |
125 (85.0) 22 (15.0) |
|
| Had already used a drug checking service | 0.000 | |||
|
No & Don’t know/missing Yes |
505 (91.3) 48 (8.7) |
360 (88.7) 46 (11.3) |
145 (98.6) 2 (1.4) |
1 At least once during the month preceding the beginning of France’s second COVID-19 lockdown (October 30, 2020)
2 Based on the AUDIT-C questionnaire score (> 3 for men and > 2 for women)
3 Opioids included heroin, opioid agonist therapy (OAT), and opioid analgesics, whether prescribed or not
4 Stimulants included cocaine hydrochloride or free base, amphetamines, and prescribed or non-prescribed methylphenidate
5 Other psychoactive substances included ecstasy, psychedelics, ketamine, GHB/GBL, and new psychoactive substances (NPS)
6 Concerned psychoactive substances other than cannabis, tobacco and alcohol
Table 2.
Factors associated with willingness to use a drug checking service for cannabis, univariable and multivariable logistic regression models
| Variables | OR [95%CI] | aOR [95%CI] |
|---|---|---|
| Gender: Women (Ref: Men) | 0.60 [0.39–0.94]* | 0.54 [0.35–0.86]** |
| Tertiary educational qualification: Yes (Ref: No & Don’t know/missing) | 2.01 [1.37–2.94]*** | 2.14 [1.45–3.17]*** |
| Form: Herbal cannabis (Ref: Resin, other & Don’t know/missing) | 1.41 [0.94–2.11] | - |
| Daily use of cannabis: Yes (Ref: No & Don’t know/missing) | 1.50 [0.89–2.50] | - |
| Therapeutic use (Ref: never) | ||
|
Sometimes, often Always Don’t know & Missing data |
1.71 [1.10–2.65]* 2.31 [1.12–4.77]* 1.66 [0.77–3.60] |
1.71 [1.09–2.69]* 2.61 [1.25–5.49]* 1.74 [0.79–3.82] |
| Mode of supply (Ref: illicit market) | ||
|
Home cultivation Friends, social circle Others, Don’t know & Missing Data |
0.70 [0.42–1.16] 0.85 [0.50–1.42] 0.89 [0.41–1.91] |
- - - |
| Polysubstance use 1 2 : Yes (Ref: No & Don’t know/missing) | 1.46 [0.94–2.25] | - |
| Adverse effects 1 2 : Yes (Ref: No & Don’t know/missing) | 1.71 [1.03–2.85]* | - |
OR: odd ratio; aOR: adjusted odd ratio; CI: confidence interval
1 At least once during the month preceding the beginning of the second French COVID-19 lockdown (October 30, 2020)
2 Concerned psychoactive substances other than cannabis, tobacco and alcohol
* p < 0.05; **p < 0.01; ***p < 0.001
All analyses were conducted using STATA-17 software (64 bit). First, we performed descriptive analyses of the sample (frequencies and medians) stratified on the outcome. We compared the two groups using the chi-square test of independence for each categorical variable; the Wilcoxon-Mann-Whitney test was used for the continuous variable ‘age’ which did not have a normal distribution. We then constructed a multivariable logistic regression model to determine the association between each candidate variable and the outcome; to do this, all variables associated with the p-value < 0.2 threshold in the bivariate analyses were selected for the multivariable model. The variable “having already used a drug analysis service” was not selected due to a too low number of participants replying “yes”; selecting it might have artificially increased the confidence intervals. Once the candidate variables were selected and integrated into the model, the final model was constructed by a backward elimination procedure, in order to retain only the variables associated with the threshold p < 0.05.
Results
Study sample
Of the 1190 persons who clicked on the link, a total of 553 completed the questionnaire and were included in the analyses. Participant characteristics are described in Table 1.
Over three-quarters (79.2%) of the participants self-identified as men; median age was 26 years, a quarter of the participants being under 23 and a quarter over 37. A little over half (55.5%) had tertiary education and almost three-quarters (74.1%) were professionally active or were currently studying. Three-quarters (75.0%) reported having their own home, and 66.2% lived in an urban area. Only 2.2% had received food aid, 40.3% lived with a partner, and only 21.5% had children.
The main form of cannabis used was herb (70.7%) and the main mode of consumption smoking (91.9%). Two-thirds (66.4%) of participants smoked it in the form of mixed tobacco-cannabis joints (with a greater percentage of tobacco). A large majority (86.1%) reported consuming cannabis daily. Over half (57.5%) the participants declared having sometimes or often consumed cannabis for therapeutic use, 11.2% declared they used it exclusively for therapeutic use, and 8.0% responded “I don’t know” to the therapeutic use question. The illicit market (60.0%) was the main source of cannabis supply, while 16.5% of participants said they obtained their supply by growing it themselves.
With regard to the use of psychoactive substances other than cannabis during the previous month, 8.5% of the participants declared having used opioids (heroin, opioid agonist treatment, opioid analgesics), 21.5% stimulants (cocaine hydrochloride or free base, amphetamines, methylphenidate), 35.6% ecstasy, psychedelic substances, ketamine, GHB/GBL or NPS, and 6.1% benzodiazepines. Over half (58.6%) reported daily tobacco use, and 43.1% had harmful alcohol use according to the AUDIT-C questionnaire score. Just under a third (29.3%) reported polysubstance use, defined here as using at least two different psychoactive substances (other than alcohol, tobacco and cannabis) in the previous month. Moreover, 21.0% of the full sample reported having experienced at least one adverse effect from a psychoactive substance they consumed (other than alcohol, tobacco and cannabis) in the previous month. Only 8.7% of participants declared having already had products (all types) checked by an HR structure.
Factors associated with willingness to use a cannabis drug checking service
Concerning the study outcome, nearly three-quarters (73.4%) of participants reported they were willing to use a drug checking service adapted to cannabis. Bivariate analyses revealed that compared to participants who were not willing, those who were willing were more likely to identify as men (72.8% Vs. 81.5%, p = 0.025); to have a tertiary education qualification (42.9% vs. 60.1%, respectively, p < 0.001); to declare using cannabis for therapeutic use “sometimes or often” and “always” (53.1% vs. 59.1% and 8.2% vs. 12.3%, p = 0.049); to report at least one adverse effect after consuming a psychoactive substance other than cannabis, alcohol and tobacco during the previous month (15.0% vs. 23.2%, p = 0.037 ); and to have already had a product analyzed by an HR drug checking service (1.4% vs. 11.3%, p < 0.001).
We selected the variables ‘gender’, ‘tertiary education qualification’, ‘form of cannabis’, ‘daily cannabis use’, ‘therapeutic use’, ‘mode of supply’, ‘polysubstance use (other than cannabis, tobacco and alcohol)’, and ‘product-related adverse effects (other than cannabis, tobacco and alcohol)’ as candidate variables for the multivariable model. The results of the multivariable analysis using logistic regression are presented in Table 2.
Having a tertiary education qualification (adjusted Odds Ratio [95% Confidence Interval] = 2.14 [1.45–3.17]), and declaring using cannabis for therapeutic use “sometimes or often” (ORa [95% CI] = 1.71 [1.09–2.69]) and “always” (aOR [95% CI] = 2.61 [1.25–5.49]) were positively associated with an interest in using a cannabis drug checking service. Conversely, self-identifying as a woman (aOR [95% CI] = 0.54 [0.35–0.86]) was negatively associated.
Discussion
The results from the online questionnaire survey CANNAVID 2 show that large majority (73%) of our study sample of PUC living in France were willing to use a cannabis drug checking service. Gender, educational level and motivations for using cannabis were factors associated with this willingness. To our knowledge, this is the first study worldwide to specifically explore PUC’s interest in a drug checking service for cannabis. In comparison, the international literature generally shows a high willingness to use drug checking services (if they were available) among PUD frequenting party events [10–12, 16], and a more variable willingness among PUD who inject substances [17–21]. Indeed, several factors can shape this willingness, particularly those related to structural vulnerabilities (i.e., poverty, criminalization, stigmatization, etc.), so that the needs of some specific groups of PUD are not adequatly met [20, 21]. Although the objective was not to explore the willingness to use cannabis drug checking, the OFDT’s study of the cannabinoid composition of products from the illegal market, conducted between 2012 and 2013, showed that participants who had their cannabis checked were mainly men, aged 30 years on average, with a stable source of income, and who consumed cannabis daily [26].
Our results suggest that men and people with tertiary education qualifications tended to be more willing to use a cannabis drug checking service. In terms of access to HR services, barriers specific to women who consume drugs, such as increased stigmatization due to their identity as women drug users, could negatively weigh on their decision to use HR services, including drug checking services [39]. In addition, several studies have highlighted that the drugs culture is gendered, including for cannabis; men are more likely to try to obtain substances on their own, and are generally better included in the social dynamics of consumption and of sharing drugs-related resources [40–42]. Furthermore, education level is strongly linked to the ability to seek out and use information on health, and consequently, most likely influences choices in terms of health behaviors [43]. Some studies found that men were generally more likely than women to use mobile drug checking services at party events and at fixed locations [13, 23, 44]. Furthermore, two of those studies found that those who used the services were more likely to have a tertiary education degree or to have completed vocational training and to be in employment or in training [13, 23]. Other studies also found that men were more likely than women to be willing to use mobile drug checking services at music festivals if they were available [11, 16]. Any implementation of HR interventions, for example cannabis drug checking services, should take into account these gender- and education-based structural barriers to access. More specifically, such interventions should be adapted to promote the inclusion of women and people with lower levels of education.
Our results also suggest that persons using cannabis for therapeutic reasons might be more willing to use cannabis checking services. Irrespective of the regulations regarding access to medical cannabis in different jurisdictions, many people use the substance for self-medication to treat a wide variety of symptoms, including pain, anxiety, depressive symptoms, as well as sleep and appetite disorders [45–47]. Between 2021 and 2024, the French National Medicines Safety Agency (ANSM) implemented an experimental medical cannabis program with a view to establishing a regulatory framework for future generalized access to medical cannabis in community pharmacies (https://ansm.sante.fr/dossiers-thematiques/cannabis-a-usage-medical). It is also important to highlight that in countries where medical cannabis is already legal, for example in several states in North America, PUC still use the unregulated market to obtain product because of barriers to obtaining a prescription and to dispensing in pharmacies [48]. In France, 10% of PUC participating in a previous online survey reported using cannabis exclusively for therapeutic reasons. These persons were also more likely to grow cannabis themselves and consume it through non-smoking modes than other PUC [45]. This would suggest that PUC who use cannabis for therapeutic purposes look for ways to reduce the potential negative impact of their consumption on their health. It is also possible that therapeutic users, unlike other PUC, pay more attention to the composition of their cannabis products, and look for cannabinoid concentrations which they believe best meets their therapeutic needs [49]. Without access to pharmaceutical grade products, access to a cannabis drug checking service could allow this population to adapt their use of unregulated products.
The high willingness to use a cannabis drug checking service in our study may reflect concern about the lack of regulation of the quality of cannabis in France, given that the sale and use of this substance is illegal in the country. In the absence of a regulated legal cannabis market, increasing the number of drug checking services and ensuring they are adapted to adequately analyze organic psychoactive substances such as cannabis, could be one strategy to monitor the quality of cannabis in circulation. Not only would they help ensure that PUC are vigilant about the contents of their products, they would also push the drug market toward ensuring better quality products [7, 8, 50]. These services could be implemented in several ways. Given that the use of other substances is relatively frequent in our sample, and that, conversely, PUD in drug checking services often consume cannabis [23, 24], cannabis analysis could be incorporated into existing drug checking services. In addition, specific schedules, areas and modalities of intervention could be arranged to make these services more accessible to different PUC subgroups, in particular for women and gender minorities and for socially disadvantaged people. Furthermore, new cannabis collection and analysis sites could be implemented specifically for PUC, particularly those who use cannabis for therapeutic purposes, through cannabis-focused community associations. However, the analysis of organic cannabis poses additional technical and financial challenges for drug checking services which are more generally designed to analyze primarily powder, crystal and pill forms. Indeed, implementing these services adapted to organic cannabis requires additional tools, methods and expertise, which can be even more costly and time-consuming. The different components of cannabis that need to be analyzed– i.e., natural cannabinoids, synthetic cannabinoids and contaminants (e.g., bacteria, fungi, pesticides, heavy metals, etc.)– all require specific tools and methods. The implementation of these services is therefore contingent on the allocation of additional funding from public health authorities.
The study has limitations. First, participants in CANNAVID2 were recruited through community forums and social networks whose members were mainly people who use psychoactive substances. Accordingly, our study sample is not representative of the French general population. More specifically, three-quarters of our sample consumed cannabis daily; this contrasts with only 2.1% of participants in a general population survey conducted by Santé Publique France (the national public health agency) in 2020 [22]. In addition, quite a large portion of our sample (16.5%) declared that they cultivated the cannabis consumed themselves, and a substantial proportion also reported past-month use of stimulants (21.5%) and past-month use of other psychoactive substances (35.6%) (psychedelics, ecstasy, ketamine, NPS, etc.). Furthermore, as participants in CANNAVID2 consumed many different psychoactive substances and engaged with social support networks, we assume they were already exposed to information relating to the consumption of psychoactive substances and were already aware of various HR tools, including drug checking services. Second, assessing PUC’s willingness to use a drug checking service for cannabis was not main objective of CANNAVID 2. Because of the large number of questionnaire items in the CANNAVID2 survey, no supplementary questions were included regarding the intention to use such a service in the future.
Considering the above-mentionned limitations, it would be worthwhile to conduct further quantitative and qualitative studies to better assess the value of cannabis drug checking services and to better guide their design and implementation. In particular, further studies could explore the reasons for using or not using such services in detail, the intended frequency of use, as well as preferences in terms of accessibility. In addition, the potential impact on PUC’s consumption behavior could be assessed. Furthermore, future studies that include a more representative sample of PUC (e.g., not necessarily regular users of cannabis), as well as cross-national studies, could enhance the generalizability and the comparability of the findings. Finally, further studies on the quality of cannabis on the illegal market, including cannabinoid composition (THC, CBD) and presence of adulterants (synthetic cannabinoids) and contaminants (e.g., bacteria, fungi, pesticides, heavy metals, etc.), could inform the analytical techniques and procedures that need to be implemented.
Conclusion
The evolution of the illegal cannabis market in France and the continued uncertainty surrounding the quality of the products in circulation highlight the need for the development of interventions aimed at protecting the health of PUC. Drug checking provides people who use drugs with detailed information about the composition of the psychoactive substances they acquire; in this way, it helps them to adapt their consumption according to the percentages of desired and undesired substances in their product sample. Although our study is not representative of all people who use cannabis in France, our results suggest that a drug checking service adapted to cannabis would be a valuable HR tool for many people who regularly use the substance, in particular those who use it for therapeutic purposes. In our study, people who self-identified as women and those who did not have tertiary education were less willing to use using a cannabis drug checking service. Accordingly, when implementing this type of service - and HR interventions in general - the diversity of socio-demographic and gender profiles should be considered in order to increase the engagement of different populations.
Acknowledgements
The authors would like to thank all the participants in the CANNAVID2 survey, to the scientific committee of CANNAVID2 and to the community associations who contributed in the dissemination of the survey. We also thank Jude Sweeney for the English revision and copyediting of the manuscript. MB received support from the French Research Institute of Public Health (IReSP) and the French National Institute of Cancer (INCa) as part of a call for applications for a doctoral grant launched in 2020 (AAC20-SPA-02). MB also received support from the French government under the'France 2030' investment plan, as part of the Initiative d'Excellence d'Aix-Marseille Université - A*MIDEX (AMX-20-IET-014); this work was supported by a doctoral grant from the Aix-Marseille Institute of Public Health Sciences - ISSPAM.
Abbreviations
- THC
Delta-9‐tetrahydrocannabinol
- CBD
Cannabidiol
- HR
Harm Reduction
- PUD
People who use drugs
- PUC
People who use cannabis
Author contributions
All authors designed the study. ML and VM collected the data. MB, CD and PR analyzed the data. MB wrote the first draft of the manuscript. All authors reviewed and approved the final version of the manuscript.
Funding
This research received no external funding.
Data availability
The data presented in this study are available upon request from the authors. Data are not publicly available due to privacy and ethical restrictions.
Declarations
Conflict of interest
The authors have no conflict of interest to declare regarding this study.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The data presented in this study are available upon request from the authors. Data are not publicly available due to privacy and ethical restrictions.