Abstract
Background and aim
Video gaming (VG) and cannabis use are two behaviors that are particularly prevalent among adolescents and young adults, as they can both be sedentary activities that are used to help decompress. As such, this raises questions about the possible relationship between VG and cannabis use. The aim of the present review is to document the relationship between VG and cannabis use.
Methods
A scoping review identified 25 articles published between 2000 and February 2025, and presenting original findings on the relationship between VG and cannabis use.
Results
Results demonstrate that existing literature is heterogeneous in its methods and measures. Nonetheless, evidence suggests that a relationship does exist, as the majority of studies did find a positive relationship between VG and cannabis use, although several studies also found no significant relationship, and a few even found a negative relationship.
Discussion
Being a new and emerging subject, few studies exist exploring the relationship between VG and cannabis use. Thus, there is much that needs to be explored before drawing clear conclusions on what type of relationship exists between both behaviours. An inability to draw clear conclusions is, in part, due to a lack of consistency in the way both VG and cannabis use have been operationalized, and the use of convenience samples, which have created additional challenges that the field will need to address moving forward.
Introduction
Video gaming (VG) has grown exponentially in the past decade. In 2022, the global market of video games was valued at over 249 billion USD (Fortune Business Insights, 2022), compared to just 67 billion USD in 2012 (Gaudiosi, 2012). Participation rates have also increased, as 61% of Canadians played video games in the past month in 2020 (ESAC, 2020), compared to 54% in 2014 (ESAC, 2014), and 53% of Europeans played video games in 2022 (Video Games Europe, 2022), compared to 48% in 2012 (Ipsos MediaCT, 2012). The growing popularity in video games has been accompanied by growing concern by experts about the potential effects of excessive VG. These concerns have paved the way for the emergence of Gaming Disorder (GD) as a new disorder in the newest International Classification of Diseases-11 (ICD-11; WHO, 2019), as well as Internet Gaming Disorder (IGD) as a potential new disorder in the Diagnostic and Statistical Manual of Mental Disorders-5 (DSM-5; APA, 2013). A recent meta-analysis has estimated a GD prevalence rate of 2.4% worldwide (Kim et al., 2022). GD is targeted for individuals who show signs of problem VG, which is defined as sustained patterns of engagement in VG and impaired control that result in significant impairment or distress and physical and/or psychosocial harms, as well as continuation of VG despite negative consequences (e.g. APA, 2013; Mills, Marchica, Keough, & Derevensky, 2020; Porter, Starcevic, Berle, & Fenech, 2010; WHO, 2019). IGD shares a similar definition, although it is also characterized by preoccupation with VG, withdrawal symptoms, and tolerance (APA, 2013).
VG shares several resemblances with other potentially addictive behaviors that are found in both the ICD-11 and DSM-5, including psychoactive substances and gambling. In popular culture, though, VG is often linked to cannabis use in particular, with many people using both video games and cannabis concurrently, and video game developers often reference cannabis use in their games (Campbell, 2015; Wenzel, 2014). The combination of both cannabis use and VG in popular culture is perhaps because they can both be considered sedentary behaviors, meaning activities that are usually done while lying or sitting with very little movement (Neilson & Lin, 2019). Hence, they can both be used to help decompress and suppress negative affect, which can make the combination of both activities something that is attractive for some individuals (e.g. Grigsby, Lopez, Albers, Rogers, & Forster, 2023; Liebregts et al., 2015; Ropovik et al., 2023).
Problem cannabis use and problem VG have both been linked to similar characteristics, including male sex and/or gender, younger age, low self-esteem, impulsivity, depression, anxiety, poor interpersonal relationships/loneliness, and lower school performance/lower educational attainment (e.g. Grigsby et al., 2023; Leung, Chan, Hides, & Hall, 2020; Ropovik et al., 2023; Van Rooij et al., 2014). The similar characteristics found between problem VG and problem cannabis use could suggest the role of confounding variables in the relationship between the two variables. Neurological similarities have also been found between VG and cannabis use. A literature review reported that VG addiction increases brain activity in similar areas commonly found in substance-related addictions, and VG addiction also leads to changes in function and brain structure over time (Kuss & Griffiths, 2012). Both high levels of VG and cannabis use have been found to affect areas such as reward, impulse control, executive functioning, and motor skills (Volkow et al., 2016; Weinstein & Lejoyeux, 2015) Therefore, the compulsion for people to play video games may reflect a biological vulnerability, similar to that of cannabis use (Ko, Yen, Yen, Chen, & Chen, 2012).
The possibility of engaging in both behaviors simultaneously, combined with several shared risk factors, raises questions about the potential association between the two activities and the possibility that one potentially addictive behavior could exacerbate the other. The potential co-occurrence of problem VG and problem cannabis use is concerning, as it could lead to more adverse consequences, similarly to what has been found for other comorbid addictive disorders (e.g. Cowlishaw, Merkouris, Chapman, & Radermacher, 2014; Na, Lee, Choi, & Kim, 2017; Punia, DeVillaer, MacKillop, & Balodis, 2021). For example, Na et al. (2017) found that individuals who presented with an Alcohol Use Disorder and a GD were linked to several negative outcomes, such as dysfunctional impulsivity, depression, anxiety, and a more severe Alcohol Use Disorder. Given these findings, it is important to understand how VG and cannabis use relate to one another.
Previous literature reviews on the subject have focused solely on problem VG and its link to substance use behaviors as a whole (Burleigh, Griffiths, Sumich, Stavropoulos, & Kuss, 2019; Smith, Hummer, & Hulvershorn, 2015), but failed to explore VG across a continuum, beyond just problem VG. This is crucial as it provides greater insight into how VG and cannabis use relate to one another, which helps to better understand how problem VG and/or cannabis use may develop. Furthermore, it is important to explore more in depth the link between VG and cannabis use specifically, with the popularity of both VG and cannabis use continuing to increase in the general population, especially in high-income countries (CCSA, 2020; Hall, Stjepanović, Dawson, & Leung, 2023; Manthey, Freeman, Kilian, López-Pelayo, & Rehm, 2021; Wang, Qin, Xing, Zhu, & Jia, 2024; WHO, 2024). Despite both behaviors being traditionally linked to younger people, recent trends also show important increases in VG and cannabis use among all age groups (CCSA, 2020; Engelstätter & Ward, 2022; Hall et al., 2023; Manthey et al., 2021; Video Games Europe, 2022). VG has become more mainstream and more evenly distributed across the population, as generations who grew up with video games are now aging (Engelstätter & Ward, 2022), yet research studies have often primarily focused on adolescents and young adults. As for cannabis, the legalization of cannabis in some countries seems to contribute to increases in cannabis use in the population, especially among adult populations who are able to now purchase cannabis legally (e.g. Grigsby et al., 2023; Montgomery, Roberts, Margerison, & Anthony, 2022; Wang et al., 2024). For example, Canada reported an increase in cannabis use in the past 12 months from 14.8% in 2017, prior to legalization, to 22% in 2020, 2 years post-legalization (Rotermann, 2023). With these recent trends of growing popularity of both activities across the population and more countries legalizing cannabis there is an urgent need to understand the current state of knowledge on the potential association between VG and cannabis use. Thus, the aim of the present scoping review is to document the relationship between VG and cannabis use, to fill an important gap in the literature.
Methods
A scoping review was conducted as they are an effective way to provide a rapid overview of the current state of knowledge of a particular research area that has not been comprehensively reviewed before (Arksey & O’Malley, 2005). The search strategy used was developed using the methodological framework for scoping reviews proposed by Arksey and O’Malley (2005) and using the PRISMA-SCR guidelines for scoping reviews (Tricco et al., 2018). The search was conducted on November 5th, 2022, consulting several databases in related fields to find relevant articles published since 2000. An update was completed on February 13th, 2025. The complete list of databases can be found in Appendix. The search was conducted with keywords in title and abstract for cannabis (cannabi* or marijuana or THC or tetrahydrocannabinol or weed or pot or CBD) and for VG (“video gam*” or “computer gam*” or gaming or “online gam*” or “internet gam*” or “console gam*” or “internet gaming disorder” or “problem* video gam*” or “gaming addiction”). To be included, studies had to have analyzed original data (i.e. original research article, thesis/dissertations) specifically on the relationship between VG and cannabis use and had to be written in French or English. Studies that focused on internet use and/or substance use in general without reporting results specifically on VG and cannabis use were excluded from this review, as well as conference proceedings. There were no exclusion criteria related to study design or participant characteristics.
A double-blind review of titles and abstracts was conducted by two of the authors (EJ and AAL) with an inter-rater agreement of 96.5% for the original search and of 89.5% for the updated search. For the articles that were in conflict, there were discussions between the authors to make a final decision on inclusion of these articles. After assessing the titles and abstracts, the full-texts of selected articles were assessed through a double-blind review by two of the authors (EJ and EM) to determine final inclusion. Inter-rater agreement was 100% at this stage for both searches. Hand-sorting (i.e. consulting reference lists) was also conducted to identify other relevant articles that may have been overlooked in the database search. Data charting was then conducted for each included article for five main categories: (1) identification and characteristics of the article (e.g. title, authors, year of publication, etc.); (2) characteristics of participants (e.g. number of participants, age, recruitment strategy, etc.); (3) methods (e.g. aim, study procedure, measurement tools); (4) results (e.g. relationship observed, statistics reported, etc.); and (5) discussion (e.g. implications of results, limitations, etc.).
Articles are divided by sample age group to facilitate comparisons, where the group “adolescents” is for articles with samples between 11 and 18 years old, inclusively, “young adults” for samples specific to those between 18 and 30 years old, inclusively, “adults” for samples with adults of all ages 18+ years old, and “other age brackets” for samples that included adolescents with young adults and/or adults.
Results
The original systematic search produced 600 articles, with an added 46 articles following the update. After removing duplicates, 368 articles were left from the original search and 38 articles from the updated search, which were all reviewed for title and abstract. Of the articles reviewed at this stage, 31 articles were retained from the original search and 12 articles were retained from the updated search. The full-text of the retained articles were reviewed, and 18 articles were selected from the original search and 4 articles were selected from the updated search for final inclusion. An additional three articles were added as a result of hand-sorting for a total of 25 articles analyzed in this scoping review (see Fig. 1).
Flow-chart of the data extraction methodology
Citation: Journal of Behavioral Addictions 2025; 10.1556/2006.2025.00040
The characteristics of the included articles are presented in detail in Table 1. All studies were conducted in western countries (i.e. Europe and North America), and no study was conducted with a full sample that derives from a political context where cannabis was legalized. All studies were conducted in countries where cannabis was either illegal at the time of data collection (10/25; Castren et al., 2022; Coeffec et al., 2015; Doggett, Qian, Godin, De Groh, & Leatherdale, 2019; Horvath et al., 2021; Konkoly Thege, Hodgins, & Wild, 2016; Kotyuk et al., 2020; Mills et al., 2020; Munoz-Miralles et al., 2016; Ohannessian, 2015; Walther, Morgenstern, & Hanewinkel, 2012), partially legalized in specific locations/decriminalized (3/25; Liebregts et al., 2015; Merelle et al., 2017; Van Rooij et al., 2014), decriminalized (3/25; Gallimberti et al., 2016; Perales, Maldonado, López-Quirantes, & López-Torrecillas, 2021; Sucha, Dolejš, Dostál, Pipová, & Pontes, 2024), or where legislation was mixed within the sample (e.g. different states, countries; 8/25; Hozman, 2020; Kaur, Rutherford, Martins, & Keyes, 2020; Liu, 2014; Nagata et al., 2025; Ream, Elliott, & Dunlap, 2011a, Ream, Elliott, & Dunlap, 2011b; Skarupova, Blinka, & Ťápal, 2018; Strizek et al., 2020). One study evaluated posts on an online community and so it is not possible to know the origin of the individuals who posted on the online platform (Le et al., 2024).
Articles that collected data exploring cannabis use and video gaming (VG), classified by population
| Author, year | Sample population/country | Design/sample characteristics | Type of VG modalities | VG measure | Cannabis measure | Cannabis legislation | Results | Relationship observed |
| Castren et al. (2022) | Adolescents Recruited: Schools in Finland | Cross-Sectional N = 4,160 Age = 15–16 years old Female 51% | Computer, mobile, console, or other electronic device games | Self-perceived excessive gaming (3 questions) | Cannabis use in past year (use or no use) | Illegal | aOR [95% CI]: 0.71 [0.40–1.25] | Cannabis use was not significantly associated with excessive gaming. |
| Coeffec et al. (2015) | Adolescents Recruited: Schools in France | Cross-sectional N = 1,423 Age range: 11–17 years old | Computer, console, online, arcade and mobile games | Time spent VG on school and non-school days PUVG | CAST | Illegal | Time spent VG on school day and problem cannabis: Time spent VG not on school day and problem cannabis: Problem cannabis use and problem VG: Multiple regression (problem VG as dependent variable) Problem cannabis: | Time spent VG positively correlated with problem cannabis use. Problem VG not associated with problem cannabis use. |
| Doggett et al. (2019) | Adolescents Recruited: Schools in Canada | Cross-sectional N = 46,957 Age = Grade 9–12 Female 50% | Not specified | Time spent VG per day | Cannabis use in past year (non-user, rare/sporadic, monthly, weekly or daily user) | Illegal | Time spent VG (M, [SD]): Non-cannabis user = 1.32 [1.92] Rare/sporadic user = 0.95 [1.60] Monthly user = 1.08 [1.70] Weekly user = 1.38 [1.97] Daily user = 2.45 [3.08] Chi-square/ANOVA: Proportional ORs [95% CI]: Females = 1.06 [1.03–1.09]*** Males = 1.01 [0.99–1.03] | Mean time spent VG per day was significantly greater with higher levels of cannabis use frequency. Time spent VG is positively associated with more frequent cannabis use for females but not significant for males. |
| Gallimberti et al. (2016) | Adolescents Recruited: Schools in Italy | Cross-sectional N = 1,156 M = 12.03 years old Male 53.4% | Not specified | Substance use DSM-IV criteria-based questions for problem VG | Lifetime cannabis use (yes or no) | Decriminalized | OR [95% CI]: 0.57 [0.00–1.21] | No significant association between problem VG and lifetime cannabis use. |
| Horvath et al. (2021) | Adolescents Recruited: Schools in Hungary | Cross-sectional N = 2,768 M = 16.73 years old Female 52.1% | Online/offline computer, console, mobile, etc. | Abbreviated 5-item version of IGDT-10 Frequency of VG on school days and on weekend days | Lifetime cannabis use (yes or no) Cannabis use in past month (yes or no) | Illegal | Lifetime cannabis use: Frequency of gaming on school days: Frequency of gaming on weekend days: GD symptom severity: Past month cannabis use: Frequency of gaming on school days: Frequency of gaming on weekend days: GD symptom severity: | Lifetime cannabis use is positively significantly correlated with frequency of gaming on school days and GD symptom severity, but not significantly associated with frequency of gaming on weekend days. Past month cannabis use is positively significantly correlated with frequency of gaming on school days and weekend days, and GD symptom severity. |
| Kaur et al. (2020) | Adolescents Recruited: Schools in USA | Cross-sectional N = 44,482 Age: Grade 9, 10, and 12 Female 50.8% | Computer, mobile, console or other gaming devices | Time spent VG per day | Cannabis use in past 30 days (yes or no) Cannabis vaping in past 30 days (yes or no) | Mixed (legal, decriminalized or illegal) | Past 30 day cannabis use (aRR [95% CI]): Hours gaming 0 = REF 1–2 h = 0.92 [0.79–1.07] 3 h+ = 1.02 [0.89–1.17] Past 30 day cannabis vaping (aRR [95% CI]): Hours gaming 0 = REF 1–2 h = 0.67 [0.42–1.07] 3 h+ = 0.70 [0.46–1.06] Predicted frequency of cannabis use in past 30 days (expected log count [95% CI]): Hours gaming 0 = REF 1–2 h = 0.133 [0.084–0.182]* 3 h+ = 0.14 [0.096–0.185]* Predicted frequency of cannabis vaping in past 30 days (expected log count [95% CI]): Hours gaming 0 = REF 1–2 h = 0.045 [ 3 h+ = | Past 30 day cannabis use and cannabis vaping was not significantly associated with number of hours spent VG. Among past substance users, increased hours spent gaming is associated with increased frequency of cannabis use in the past 30 days, whereas 3+ hours of gaming is associated with decreased frequency of cannabis vaping in the past 30 days. |
| Liu (2014) | Adolescents Recruited: Schools in the USA T1-T3 | Longitudinal N = 10,828 T1 M = 15.8 years old Female 52.9% | Video or computer gaming | Hours spent gaming per week (21, 35, and 42 h/week each used as cut off point for heavy gaming) | Cannabis use in past month (yes or no) | Mixed (decriminalized or illegal) | 21 h/week cut-off for heavy gaming: Cannabis use (M/%): Normal gaming group = 3.025 Heavy gaming group = 2.464 P Value = 0.801 Regression model predicting cannabis use 5 years later (T3): Coef. = 35 h/week cut-off for heavy gaming: Cannabis use (M/%): Normal gaming group = 4.013 Heavy gaming group = 5.476 P Value = 0.689 Regression model predicting cannabis use 5 years later (T3): Coef. = 42 h/week cut-off for heavy gaming: Cannabis use (M/%): Normal gaming group = 0.568 Heavy gaming group = 5.519 P value = 0.345 Regression model predicting cannabis use 5 years later (T3): Coef. = | Using a 21, 35, or 42 h/week cut-off for heavy gaming, the normal and heavy gaming groups did not significantly differ in cannabis use in the past 30 days. Using a 21 h/week cut-off for heavy gaming, there was no difference between groups in predicting cannabis use in the past 30 days 5 years later. Using a 35 h/week cut-off for heavy gaming, the heavy gaming group was 22.2% less likely to have used cannabis in past 30 days 5 years later. Using a 42 h/week cut-off for heavy gaming, the heavy gaming group was 14.7% less likely to have used cannabis in past 30 days 5 years later. |
| Merelle et al. (2017) | Adolescents Recruited: Schools in Netherlands | Cross-sectional N = 21,053 M = 14.4 years old Female 50.6% | Online/offline computer, console, mobile gaming | Abbreviated version of CIUS | Cannabis use in past month (yes or no) | Legal in specific areas/decriminalized | Regression model OR [95% CI] = 0.96 [0.72–1.27] | Cannabis use was not significantly associated with problem VG. |
| Nagata et al. (2025) | Adolescents Recruited: Schools in USA | Longitudinal N = 8,006 Age T1: 11–12 years old Female 47.9% | Not specified | Question on weekday and weekend use of single and multi-player video games (average calculated) | Adapted iSay Sip Inventory (past 12 month use – yes or no) | Mixed (legal, decriminalized or illegal) | Single-player VG: OR 1.10 (95% CI: 0.98–1.24) Multiplayer VG: OR 1.06 (95% CI: 0.94–1.19) | More use of single-player and multiplayer video games was not associated with higher odds of using cannabis at follow-up. |
| Ohannessian (2015) | Adolescents Recruited: Schools in USA | Longitudinal N = 1,031 M = 16.15 years old Female 52.5% | Console and computer gaming | Time spent VG per day (scale from 1 = none to 6 = 4+ hours/day) | Cannabis use in past 6 months (scale from 0 = no use to 7 = every day) | Illegal | VG and Cannabis use for boys T1: VG and Cannabis use for girls T1: VG and Cannabis use for boys T2: VG and Cannabis use for girls T2: Path analysis of T1 VG predicting cannabis use at T2 was insignificant for both boys and girls | VG and cannabis use was not significantly correlated for both boys and girls VG at T1 did not predict cannabis use at T2. |
| Sucha et al. (2024) | Adolescents Recruited: Schools in Czech Republic | Cross-sectional N = 3,950 Range = 11–19 years old Male 49.11% | Not specified | IGDS9-SF Question on daily time spent VG | Adjusted Scale of Risk Behaviour in Adolescents (Lifetime use – yes or no) | Decriminalized | Cannabis use lifetime: Non-gamers = 38.7%*** Non-disordered gamers = 30.6% Disordered gamers = 35.4% | Significantly more non-gamers have used cannabis in their lifetime than non-disordered gamers and disordered gamers. Potential U-shaped relationship but only non-gamers were significantly different. |
| Strizek et al. (2020) | Adolescents Recruited: Schools across Europe | Cross-sectional N = 86,274 Age = 16 years old Male 49.7% | Online games | PPS Frequency of online VG in past week and # of hours per day PGI | Lifetime cannabis use (yes or no) | Mixed (decriminalized or illegal) | Cannabis and problem VG: OR [95% CI] = 0.88 [0.80–0.96]* | Lifetime cannabis use was negatively associated with problem VG. |
| Van Rooij et al. (2014) | Adolescents Recruited: Schools in Netherlands | Cross-sectional N = 8,478 M age = 14.2 Male 49% | Online/offline computer/console games, and casual browser games | Weekly VG use and average number of hours per VG session VAT | Cannabis use in past month (yes or no) | Legal in specific areas/decriminalized | Boys cannabis use and problem VG: Girls cannabis use and problem VG: Fisher's exact test = 0.00** RR = 8.96 | Participants who use cannabis are more likely to have problem VG. |
| Munoz-Miralles et al. (2016) | Adolescents and young adults Recruited: Schools in Spain | Cross-sectional N = 4,347 Range = 12–20 years old Female 48.6% | Not specified | CERV | Lifetime cannabis use (yes or no) | Illegal | Problem VG and lifetime cannabis use = 8.0% Problem VG and no lifetime cannabis use = 5.9% Chi-square p value: 0.095 | Problem VG and lifetime cannabis use are not significantly associated. |
| Walther et al. (2012) | Adolescents and young adults Recruited: High and vocational schools in Germany | Cross-sectional N = 2,553 Age range: 12–25 Male 50.7% | Computer/console VG | Adjusted version of the KFN-CSAS-II (11+ = problem, <11 = non-problem) | Frequency of cannabis use in the past year | Illegal | Cannabis use and problem VG: | Problem VG positively associated with cannabis use in the past year. |
| Kotyuk et al. (2020) | Young adults Recruited: High schools, colleges and universities in Hungary | Cross-sectional N = 3,003 Age range: 18–28 M age = 21 Male 42.6% | Online games | POGQ-SF | Use of cannabis in the past month | Illegal | Cannabis use and problem VG ( | Positive association between cannabis use and severity of problem VG. |
| Liebregts et al. (2015) | Young adults Recruited: Cannabis coffeeshops in Netherlands | Qualitative N = 47 M = 21 years old Range = 18–30 years old Female 34% | Not specified | N/A | In-depth qualitative interviews with cannabis users on how cannabis influences leisure time | Legal in specific areas/decriminalized | 18/47 participants could be characterized as “gamers”, playing at least weekly Some participants spoke about using cannabis while gaming to enhance experience or moderate emotional arousal | Results indicate a possible link between cannabis dependence and gaming dependence. |
| Mills et al. (2020) | Young adults Recruited: colleges and universities, online panel members, and greater Montreal community in Canada | Cross-sectional N = 1,621 Age range: 18–27 Female 54.7% | Not specified | Number of hours VG per week in past year IGDS-SF (3+ = at-risk, 1–2 = low-risk, 0 = non-problem) | Modified version of ASSIST (past year frequency) | Illegal | Cannabis use and VG participation: Cannabis use and Problem VG: | A greater proportion of video gamers reported using cannabis, but no difference is found among problem VG groups. |
| Perales et al. (2021) | Young adults Recruited: University in Spain | Cross-sectional N = 856 M = 21.2 years old Male 37.6% | Not specified | MultiCAGE CAD-4 | CAST SDS | Decriminalized | Severity of cannabis dependence and problem VG: IRR = 1.08** Cannabis abuse and problem VG: IRR = 1.07*** | Cannabis abuse and severity of cannabis dependence are significantly associated with problem VG. |
| Skarupova et al. (2018) | Adolescents and adults Recruited: Online survey of VG in Czech-Republic and Slovakia | Cross-sectional N = 4,004 Age range: 11–57 M = 22.2 years old Male 92.4% | Online console/computer games | AEQ | Frequency of VG under the influence of cannabis in past 12 months (use or no use) | Mixed (decriminalized or illegal) | Problem VG t-test (Cohen's d) Cannabis: Time spent VG t-test (Cohen's d) Cannabis: | Concurrent users of cannabis and VG did not significantly differ in problem VG compared to non-concurrent users. Concurrent users of cannabis and VG did not significantly differ in VG hours per week compared to non-concurrent users. |
| Hozman (2020) | Adults Recruited: Schools during their adolescence in USA (longitudinal cohort) | Longitudinal (wave 3 and 4 only) N wave 3 = 2,744 N wave 4 = 3,249 Age range: Wave 3 = 18–26 years old Wave 4 = 24–32 years old Male wave 4: 46.01% | Not specified | Weekly VG use | Use of cannabis in past 12 months (yes or no) | Mixed (decriminalized or illegal) | Wave 3 weekly hours of gaming predicting cannabis use in last 12 months at Wave 4: Wave 4 weekly hours of gaming predicting cannabis use in last 12 months at Wave 4: | A significant positive association between wave 4 weekly hours of gaming and cannabis use in the last 12 months, but no significant association between wave 3 weekly hours of gaming and wave 4 cannabis use. |
| Konkoly Thege et al. (2016) | Adults Recruited: Online panel members and computer assisted telephone survey in Alberta, Canada | Cross-sectional N = 2,728 M = 44.5 years old Female 62.2% | Online/offline console and computer games | Question on perception of lifetime experience with problem VG | Question on perception of lifetime experience with problem cannabis use | Illegal | Prevalence of problem VG and perceived problem cannabis use = 13.5% | Among those having at least one problem behavior (alcohol, tobacco, cannabis, cocaine, gambling, shopping, VG, eating, sex, and work) 13.5% have both problem VG and cannabis use. |
| Ream et al. (2011a) | Adults Recruited: Panel members from online polling company in USA | Cross-sectional N = 3,380 M = 40.6 years old Male 58% | Computer, console and mobile games | Frequency VG in past month, hours per day on days played (their top 5 games only) PVP | Adapted Version of NSDUH Cannabis use past 30 days Frequency of concurrent use while VG in past month | Mixed (decriminalized or illegal) | Adjusted model Problem cannabis and problem VG: Concurrent use and cannabis use problems: Concurrent use and problem VG: Days of cannabis use past 30 days and problem VG: Days of cannabis use past 30 days and concurrent use: | Problem cannabis use positively associated with problem VG, but days of cannabis use was not associated with problem VG or concurrent use. In adjusted model, concurrent use was associated with cannabis use problems, but not associated with problem VG. |
| Ream et al. (2011b) | Adults Recruited: Panel members from online polling company in USA | Cross-sectional N = 1,196 M age = 40.6 Male 64% | Computer, console and mobile games | Frequency VG in past month, hours per day on days played (their top 5 games only) PVP | Adapted Version of NSDUH Cannabis use past 30 days Frequency and number of hrs/day of concurrent use while VG in past month | Mixed (decriminalized or illegal) | Multivariate model Days of concurrent use: Cannabis days used: Cannabis use problem: Hrs/day of concurrent use: Cannabis days used: Cannabis use problems: | Number of cannabis days used, and problem use of cannabis positively associated with the number of days of concurrent use. |
| Le et al. (2024) | N/A Recruited: Reddit posts on r/StopGaming community | Qualitative N = 1,057 posts, N = 104 posts with GD and cannabis keywords Median age (of posts that indicated age) = 27 years old | Not specified | Posts with keywords relating to IGD | Posts with keywords relating to cannabis use | N/A | Multivariate logistic regression model: 31% IGD vs 32% non-IGD OR: 0.98 [95% CI: 0.88–1.10] z = −0.377, | Cannabis use related posts are not significantly associated to IGD. |
*
Note: N = number of participants, aOR = Adjusted odds ratio, CI = Confidence interval, PUVG = Problem Use of Video Games Questionnaire, CAST = Cannabis Abuse Screening Test, M = Mean, SD = Standard deviation, OR = Odds ratio, DSM = Diagnostic and Statistical Manual of Mental Disorders, IGDT-10 = Internet Gaming Disorder Test-10, GD = Gaming disorder, REF = Reference, aRR = adjusted relative risk, USA = United States of America, Coef. = Coefficient, CIUS = Compulsive Internet Use Scale, PPS = Perceived Problem Scale, PGI = Problem Gaming Index, VAT = Video Game Addiction Test, RR = Relative risk, CERV = Questionnaire of experiences related to video games, IGDS9-SF = Internet Gaming Disorder Scale – Short-Form, KFN-CSAS-II = Video Game Dependency Scale, POGQ-SF = Problematic Online Gaming Questionnaire Short-Form, IGDS-SF = Internet Gaming Disorder Scale Short-Form, ASSIST = Alcohol, Smoking, and Substance Involvement Screening Test, SDS = Severity of Cannabis Dependence Scale, IRR = Incidence rate ratio, AEQ = Addiction Engagement Questionnaire, PVP = Problem Video Game Playing, NSDUH = National Survey of Drug Use and Health, IGD = Internet Gaming Disorder.
Only two studies used a qualitative design (Le et al., 2024; Liebregts et al., 2015), with all other studies using a quantitative design. Few studies had a representative sample of the general population (3/25; Hozman, 2020; Konkoly Thege et al., 2016; Liu, 2014), and some studies had a representative sample of the study population (e.g. representative of school-going adolescents, representative of adult video gamers; 8/25; Castren et al., 2022; Horvath et al., 2021; Kaur et al., 2020; Ream et al., 2011a, Ream et al., 2011b; Strizek et al., 2020; Sucha et al., 2024; Van Rooij et al., 2014). The majority of studies included console and computer games in their definition of VG (15/25; Castren et al., 2022; Coeffec et al., 2015; Horvath et al., 2021; Kaur et al., 2020; Konkoly Thege et al., 2016; Kotyuk et al., 2020; Liu, 2014; Merelle et al., 2017; Ohannessian, 2015; Ream et al., 2011a, Ream et al., 2011b; Skarupova et al., 2018; Strizek et al., 2020; Van Rooij et al., 2014; Walther et al., 2012), with the other studies not specifying their definition of VG (10/25; Doggett et al., 2019; Gallimberti et al., 2016; Hozman, 2020; Le et al., 2024; Liebregts et al., 2015; Mills et al., 2020; Munoz-Miralles et al., 2016; Nagata et al., 2025; Perales et al., 2021; Sucha et al., 2024). Some studies also included mobile and/or arcade games in their definition (7/25; Castren et al., 2022; Coeffec et al., 2015; Horvath et al., 2021; Kaur et al., 2020; Merelle et al., 2017; Ream et al., 2011a, Ream et al., 2011b), whereas three studies only included online games in their definition (Kotyuk et al., 2020; Skarupova et al., 2018; Strizek et al., 2020).
A wide range of VG measures were used among quantitative studies. Among studies that evaluated VG use (13/23), the majority evaluated time spent VG per day/gaming session (8/13; Doggett et al., 2019; Kaur et al., 2020; Nagata et al., 2025; Ohannessian, 2015; Ream et al., 2011a, Ream et al., 2011b; Strizek et al., 2020; Van Rooij et al., 2014). Other measures of VG use used were frequency of VG per week (3/13; Hozman, 2020; Strizek et al., 2020; Van Rooij et al., 2014), frequency in the past month (2/13; Ream et al., 2011a; Ream et al., 2011b), time spent VG per week (2/13; Liu, 2014; Mills et al., 2020), and one study evaluated time spent VG on days with or without school (Coeffec et al., 2015), while another study evaluated frequency on school and non-school days (Horvath et al., 2021). Among studies that evaluated problem VG (17/23), a wide range of scales were used to measure problem VG. Four studies used DSM-based measures (Gallimberti et al., 2016; Horvath et al., 2021; Mills et al., 2020; Sucha et al., 2024), three studies used a self-perceived problem VG measure (Castren et al., 2022; Konkoly Thege et al., 2016; Strizek et al., 2020), and two used the Problem Video Game Playing (PVP; Ream et al., 2011a; Ream et al., 2011b), whereas other studies each used distinct measurement scales (Coeffec et al., 2015; Kotyuk et al., 2020; Merelle et al., 2017; Munoz-Miralles et al., 2016; Perales et al., 2021; Skarupova et al., 2018; Strizek et al., 2020; Van Rooij et al., 2014; Walther et al., 2012).
When it comes to cannabis use, the vast majority of quantitative studies evaluated cannabis use (20/23). To measure cannabis use, several studies measured use of cannabis in the past month (6/20; Horvath et al., 2021; Kaur et al., 2020; Kotyuk et al., 2020; Liu, 2014; Merelle et al., 2017; Van Rooij et al., 2014), some measured lifetime use of cannabis (5/20; Gallimberti et al., 2016; Horvath et al., 2021; Munoz-Miralles et al., 2016; Sucha et al., 2024; Strizek et al., 2020), and three studies measured cannabis use in the past year (Castren et al., 2022; Hozman, 2020; Nagata et al., 2025). A few studies measured frequency of cannabis use in the past year (3/20; Doggett et al., 2019; Mills et al., 2020; Walther et al., 2012), in the past 6 months (1/20; Ohannessian, 2015), or in the past month (2/20; Ream et al., 2011a; Ream et al., 2011b). Finally, three studies looked at concurrent use of cannabis while VG, with two studies measuring frequency of concurrent use in the past month (Ream et al., 2011a; Ream et al., 2011b), and one study measuring concurrent use in the past year (Skarupova et al., 2018). Five studies evaluated problem cannabis use. Two studies used an adapted version of the National Survey of Drug Use and Health (NSDUS; Ream et al., 2011a; Ream et al., 2011b), two studies used the Cannabis Abuse Screening Test (CAST; Coeffec et al., 2015; Perales et al., 2021), with one of those studies additionally using the Severity of Cannabis Dependence Scale (SDS; Perales et al., 2021), and one study used a self-perceived cannabis use problem questionnaire (Konkoly Thege et al., 2016).
Overall, the results from this scoping review demonstrate that there is growing interest in the relationship between VG and cannabis use, with the majority of articles being published in the past decade (20/25; Castren et al., 2022; Coeffec et al., 2015; Doggett et al., 2019; Gallimberti et al., 2016; Horvath et al., 2021; Hozman, 2020; Kaur et al., 2020; Konkoly Thege et al., 2016; Kotyuk et al., 2020; Le et al., 2024; Liebregts et al., 2015; Merelle et al., 2017; Mills et al., 2020; Munoz-Miralles et al., 2016; Nagata et al., 2025; Ohannessian, 2015; Perales et al., 2021; Skarupova et al., 2018; Strizek et al., 2020; Sucha et al., 2024). To help the reader navigate the diversity of existing literature on this topic, results are broken down by sample age group (i.e. adolescents, young adults, adults, other age brackets) and further divided by problem VG and problem cannabis use, and VG use and cannabis use.
VG and cannabis use in adolescents (11–18 years old)
Twelve studies reported on the relationship between VG and cannabis use within an adolescent population, showing mixed results. Of those studies, six focused on problem VG (Castren et al., 2022; Gallimberti et al., 2016; Merelle et al., 2017; Strizek et al., 2020; Sucha et al., 2024; Van Rooij et al., 2014), four focused on VG use (Doggett et al., 2019; Kaur et al., 2020; Liu, 2014; Ohannessian, 2015), and two looked at both problem and VG use (Coeffec et al., 2015; Horvath et al., 2021). Two studies found that problem VG was positively associated with cannabis use (Horvath et al., 2021; Van Rooij et al., 2014), three studies found no association (Castren et al., 2022; Gallimberti et al., 2016; Merelle et al., 2017), one study found a negative association (Strizek et al., 2020) and one study found that non-gamers were significantly more likely to have used cannabis in their lifetime than non-disordered and disordered gamers (Sucha et al., 2024). As for VG use, two studies found a positive association between time spent VG and cannabis use (Doggett et al., 2019; Horvath et al., 2021) and three studies found no association (Kaur et al., 2020; Nagata et al., 2025; Ohannessian, 2015). The other study found that, when using a 21 h/week cutoff, heavy gamers were not more likely to use cannabis 5 years later than normal gamers, however when using a 35 and 42 h/week cut off, they found that heavy gamers were less likely to use cannabis 5 years later than normal gamers (Liu, 2014). All studies focused on cannabis use, except for one study that looked at problem cannabis use and found that problem cannabis use was not associated with problem VG but was positively associated with VG use (Coeffec et al., 2015).
VG and cannabis use in young adults (18–30 years old)
Four studies were conducted focusing on VG and cannabis use within a young adult population. All studies recruited student populations except for one study, which recruited students alongside other recruitment strategies to capture non-students (Mills et al., 2020). Three studies focused on problem VG (Kotyuk et al., 2020; Mills et al., 2020; Perales et al., 2021), with one study also looking at participation in video games (i.e. gamers vs non-gamers; Mills et al., 2020). One study compared problem VG to problem cannabis use and found a positive relationship between problem VG and problem cannabis use (Perales et al., 2021). Two studies compared problem VG to cannabis use, where one study found a positive association between problem VG and cannabis use in the past 30 days (Kotyuk et al., 2020), and the other study found that a significantly greater proportion of those who play video games reported using cannabis compared to those who don't, however no significant difference was found within problem VG groups (Mills et al., 2020). Finally, one study qualitatively explored accounts regarding leisure time among cannabis users, which found that many participants (18/47) could be characterized as gamers, and several spoke about using cannabis while gaming to enhance experience and/or to moderate emotional arousal (Liebregts et al., 2015).
VG and cannabis use in adults (18+ years old)
Four studies were conducted looking at the relationship between VG and cannabis use among adult populations (18+). One study looked at the relationship between problem VG and problem cannabis use and found that among those reporting at least one problem behavior (i.e. alcohol, tobacco, cannabis, cocaine, gambling, shopping, VG, eating, sex, and work), 13.5% had a VG problem and a self-perceived cannabis use problem (Konkoly Thege et al., 2016). Hozman (2020) conducted a longitudinal study and found that wave 3 weekly VG hours did not predict past year cannabis use at wave 4, but at wave 4 more weekly VG hours did predict past year cannabis use at wave 4. Ream et al. (2011a) found a positive relationship between problem VG and problem cannabis use, however no significant relationship between problem VG and days of cannabis use, and between problem VG and concurrent use of cannabis while VG. Furthermore, the authors also found that concurrent use of cannabis while VG was associated with cannabis use problems but not associated with problem VG. Finally, the last study found that problem cannabis use and number of days using cannabis were both positively associated with the number of concurrent days using cannabis while playing VG (Ream et al., 2011b).
VG and cannabis use in other age brackets
Three studies were conducted with a mix of adolescent and adult samples. One study was conducted among adolescents and young adults (12–25 years old) and found that problem VG was positively associated with using cannabis in the past year (Walther et al., 2012). Munoz-Miralles et al. (2016) also looked at adolescents and young adults (12–20 years old) and found that problem VG was not associated with lifetime cannabis use. Finally, Skarupova et al. (2018) conducted their study among adolescents and adults (range: 11–57 years old) and found that concurrent users of cannabis while VG did not significantly differ in problem VG and in VG hours per week than non-concurrent users. There was one additional study that could not provide information on age bracket as they evaluated posts on an online community (Le et al., 2024). This study found that cannabis use related posts were not associated to IGD related posts.
Discussion
The present scoping review examines the current state of the literature on the relationship between VG and cannabis use. The literature demonstrates a rich diversity in the topics being explored, though with the existing lack of consistency in the way both VG and cannabis use have been operationalized, and the use of convenience samples, there is not enough existing evidence that clearly demonstrates the type of relationship that exists between VG and cannabis use. The results of this review suggest that a relationship between VG and cannabis use does exist, however there is still much that remains to be explored before we can draw specific conclusions about what kind of relationship exists. However, as the field remains in its infancy, a lack of clear conclusions should not discourage future research, especially given the World Health Organization's (WHO) recent decision to recognize GD as a mental health disorder (WHO, 2019).
In terms of the operationalization of VG, there is a lot of variation in the literature, which has created substantial confusion and could be an important factor contributing to the discrepancies that have been found within the results of this scoping review. The definition of VG seems unclear, certain studies appear to be more inclusive of types of video games, including mobile games and/or arcade games (Castren et al., 2022; Coeffec et al., 2015; Horvath et al., 2021; Kaur et al., 2020; Merelle et al., 2017; Ream et al., 2011a, Ream et al., 2011b), as opposed to others that are more specific, including only console and computer video games (Konkoly Thege et al., 2016; Liu, 2014; Ohannessian, 2015; Skarupova et al., 2018; Walther et al., 2012) and/or only online games (Kotyuk et al., 2020; Skarupova et al., 2018; Strizek et al., 2020). Moreover, several studies did not specify their definition of VG (Doggett et al., 2019; Gallimberti et al., 2016; Mills et al., 2020; Munoz-Miralles et al., 2016; Perales et al., 2021), further contributing to challenges in comparing results across studies. This aligns with the fact that there remains widespread debate between experts in the field about the definition of VG and problem VG (Griffiths et al., 2016; Kuss & Griffiths, 2012). This debate continues to be showcased with the WHO preferring to employ the term “Gaming disorder” in the ICD-11, as opposed to the American Psychiatric Association using the term “Internet gaming disorder” in the DSM-5 (APA, 2013; WHO, 2019). Additionally, there also remains much debate surrounding the clinical validity and the criteria for (Internet) GD, with some experts expressing concern about the possibility of over-pathologizing VG (e.g. Ferguson & Colwell, 2020; Przybylski, Weinstein, & Murayama, 2017). As a result of this ongoing debate, there are few standardized measures, if any, that are considered to be valid and reliable to evaluate problem VG, which can explain why the vast majority of studies used a different measure for VG. The lack of valid measures is acknowledged in some studies within their limitations (Coeffec et al., 2015; Strizek et al., 2020) and could be a contributing factor for the inconsistency of the results in this scoping review.
Further complicating this issue is the fact that there is also considerable variation in the way cannabis use is operationalized, with some studies focusing on lifetime use of cannabis (Gallimberti et al., 2016; Horvath et al., 2021; Munoz-Miralles et al., 2016; Strizek et al., 2020), or use of cannabis at least once in the past year (Castren et al., 2022; Mills et al., 2020; Walther et al., 2012) or in the past month (Horvath et al., 2021; Kaur et al., 2020; Liu, 2014; Merelle et al., 2017; Van Rooij et al., 2014), in contrast to others that evaluated frequency in the past year, 6 months, or month (Doggett et al., 2019; Kotyuk et al., 2020; Ohannessian, 2015; Ream et al., 2011a, Ream et al., 2011b), or problem use (Coeffec et al., 2015; Konkoly Thege et al., 2016; Perales et al., 2021; Ream et al., 2011a, Ream et al., 2011b). Similar to VG, this may also contribute to the lack of consistency in the literature. A longstanding issue, the lack of uniformity in the way cannabis use is operationalized has been criticized in previous literature reviews surrounding substance use (e.g. Henkel, 2011; Roncero et al., 2015).
Thus far, the literature has been focused on specific populations (i.e. adolescents and young adult students) and has perhaps overlooked certain samples that would be considered more at risk, which could also contribute to the discrepancy in the literature. All studies that looked at young adults, except one (Mills et al., 2020), used a sample of students, particularly college and university students. These studies have a sample with a high level of education and typically a higher socioeconomic status, which overlooks more vulnerable populations. Studies have found that low-socioeconomic status and less educated individuals are at higher risk of developing a cannabis use problem (Grigsby et al., 2023). As for problem VG, it has been linked with poor academic achievement and lower educational attainment (e.g. Ropovik et al., 2023; Van Rooij et al., 2014). Mills et al. (2020) also found within their sample that participants recruited outside of colleges and universities were more likely to have at-risk problem VG. Therefore, the studies conducted thus far with young adults are not generalizable to the rest of the population, and the actual relationship between problem VG and problem cannabis use may be under-reported. This may explain the discrepancy in the results in studies that looked at young adults. It is also important to note that the young adult population constitutes a sub-population that is encompassed in the studies that focused on adult populations, which may be skewing the results of these studies. More studies exploring general young adult populations and older adult populations are important to be able to better identify more at-risk groups.
Additionally, this scoping review found no studies that were conducted within a full sample that derives from a political context where cannabis has been legalized. The legislation of cannabis within a region is important to consider as it impacts the accessibility and availability of cannabis, and it can also impact cultural views and stigma towards cannabis use (Grigsby et al., 2023). Indeed, a recent review of the literature found that the legalization of cannabis in Canada has led to more recreational cannabis users, and they also found evidence to suggest that there have been increases in Cannabis Use Disorders as well (Hall et al., 2023). Given these important changes, it is important to continue to explore the potential relationship between cannabis use and VG to understand how they may influence one another.
Only two studies in this review used a qualitative approach. Quantitative findings thus far show no clear conclusions on what type of relationship exists between VG and cannabis use. Qualitative findings have provided a unique insight into the lived experience of cannabis users, where several participants shared experiences of combining cannabis use while VG. They shared that they used cannabis while playing video games to enhance experience and/or to moderate emotional arousal (Liebregts et al., 2015). Qualitative accounts in this study deepen our understanding of the relationship between cannabis use and VG and showcase that, for some people, the two activities can be intertwined, and thus aggravation of one behavior could then lead to an exacerbation in the other. These findings are critical to consider in future research, as it is a testament to the existence of the co-occurrence of both activities, regardless of whether quantitative results are significant or not. They do support, however, quantitative findings by two studies that did find that problem cannabis use is positively associated with concurrent use of cannabis while playing video games (Ream et al., 2011a; Ream et al., 2011b). These findings have important clinical implications, and it is important for clinicians to consider that VG and cannabis use could be intertwined together when treating problem VG and/or cannabis use. These results are also important, as it seems that concurrent use is more indicative of problem cannabis use than problem VG, and thus prevention and treatment should perhaps prioritize cannabis use (Ream et al., 2011a; Ream et al., 2011b). More research, especially qualitative research, is needed to explore the concurrent use of cannabis while VG to deepen our understanding of this phenomenon.
Moreover, quantitative studies to date may also be looking for the wrong kind of relationship when it comes to VG and cannabis use. One study found no significant difference in cannabis use 5 years later between heavy gamers and normal gamers using a 21 h/week cutoff, but found that heavy gamers were less likely to use cannabis 5 years later when using a 35 and 42 h/week cutoff (Liu, 2014). These findings could be evidence to suggest that the relationship between cannabis use and VG may not be linear, as perhaps heavier gamers may avoid substances that hinder cognitive functions, like cannabis, as they could impede gaming performance (e.g. Brooks-Russell et al., 2024; Crean, Crane, & Mason, 2011). This could contribute to the mixed findings found in this review and is important to consider in future research. It is also important to note that many studies that found significant results, did not find strong associations between VG and cannabis use. This could also be a result of many studies looking at linear type relationships or it is possible that although there might be a statistically significant association, it is perhaps not clinically significant, which is why findings appear mixed in the literature. With the current state of the literature, it is not possible to draw any conclusions to this end, however. Moving forward, a unidimensional approach classifying individuals as either problem or non-problem may not grasp the complexity of the relationship between cannabis use and VG. Findings from the study by Liu (2014), although focused on time spent VG and not problem VG, indicate the importance of considering VG across a continuum with different typologies, as there may be important differences between problem, engaged and recreational gamers. Categorizing individuals as problem or non-problem video gamers may lead to the over-pathologization of individuals who should instead be considered as “engaged” gamers (Charlton & Danforth, 2010; Ferguson & Colwell, 2020). Engaged VG is defined as a high degree of positive involvement in VG, from which the person does not encounter negative consequences (Charlton & Danforth, 2010). This distinction is important, although most studies chose to employ a unidimensional approach that does not consider the relationship across a continuum, and thus perhaps are not allowing for an exploration of the full picture.
Strengths and limitations
A limitation of this scoping review is that there was not an extensive search of the grey literature, and thus some studies (i.e. government reports) may have been overlooked in this review. It is important to note that the scoping review spans 25 years, which encompasses major changes in VG, thus some findings may no longer be relevant. Additionally, this scoping review was limited to articles written in French or English. This scoping review also has several strengths. Several databases were consulted to capture as many articles as possible that explored the relationship between cannabis use and VG. Additionally, the inclusion of all literature on the subject, with a broad timeframe, allows for an accurate picture of the state of the literature on the matter to this date. The use of the PRISMA-SCR checklist, as well as a double-blind review of articles is also an important strength to increase scientific rigor.
Conclusion
This scoping review explores the intersection of VG and cannabis use. While the results demonstrate that a relationship between VG and cannabis use does seem to exist, there is currently not enough evidence to draw clear conclusions about the type of relationship that exists. There are important methodological issues that the field will need to address moving forward. Specifically, more consistency in the literature is needed in the way both cannabis use and VG are operationalized. In particular, VG needs to be defined more clearly by researchers in the field, so as to ensure uniformity in the literature. It is crucial to keep working on the definition and conceptualization of VG since well-defined concepts are the foundation of good research. Furthermore, future research should explore non-linear relationships between VG and cannabis use, as well as non-student young adult and older adult populations that are underrepresented in the literature thus far. More qualitative research is also needed in order to contextualize quantitative findings and provide unique insights into this phenomenon. Addressing these important issues in the literature will be critical for allowing the field to draw conclusions about the type of relationship that exists between VG and cannabis use.
Funding sources
This work was supported by the Jean Lapointe Foundation.
Authors' contribution
EJ: study concept and design, analysis and interpretation of data, and obtained funding, and writing of manuscript; AAL: study concept and design, analysis and interpretation of data, study supervision, and editing of manuscript. KL: analysis and interpretation of data and editing of manuscript. EM: study concept and design, analysis and interpretation of data, and study supervision and editing of manuscript.
Conflict of interest
Authors EJ, AAL, KL, and EM report no conflicts of interest. The authors alone are responsible for the content and writing of the article.
Acknowledgements
We would like to acknowledge Rebecca Scheurich for her work in the proofreading of this manuscript.
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Appendix
| List of databases consulted in scoping review |
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