“Those edibles hit hard”: Exploration of Twitter data on cannabis edibles in the U.S

Abstract

1. INTRODUCTION

In recent years, the legal status of cannabis has evolved rapidly in the U.S. with 23 states and the District of Columbia authorizing medical cannabis, including five that permit recreational use of cannabis (National Conference of State Legislatures, 2015). With these changes, new types of cannabis products have emerged (e.g., marijuana concentrates, THC syrup, e-cannabis), while others are becoming more readily available, such as leaf marijuana and cannabis edibles. The latter products can take several forms, most generally baked goods (e.g., cookies, brownies, muffins), candies (e.g., caramels, chocolates, hard candies, gums, “Rice Krispies,” lollipops), or infusions. With increased availability, these products have also raised health concerns after reports of acute intoxications (Bui et al., 2015; Wang et al., 2013), suicide attempts (Hancock-Allen et al., 2015), and other dangers posed by potential access by children, particularly in cases where packaging mimics candies and other marketed products (Wang et al., 2013). Despite the growing media reports about acute intoxications linked to edibles (CBS, 2014; CPR, 2015; Ghosh et al., 2015), epidemiologic surveys focusing on cannabis edibles remain scarce, mainly because classic surveillance systems do not specifically monitor the use of cannabis edibles apart from cannabis consumption (SAMHSA, 2014). Overall, little is known about the patterns of use and users’ perceptions of edible cannabis products.

In the last few years, there has been an increased interest in the use of large-scale web-based data as a timely source of information on evolving public health issues and trends (Butler et al., 2007; Daniulaityte et al., 2015; Eysenbach, 2011; Lazer et al., 2009; Miller and Sonderlund, 2010). Although there are a large variety of social media platforms, Twitter is of particular interest for public health research, because Twitter data are publicly accessible and reflect casual, unedited disclosures and communications from large numbers of people. Twitter is a micro-blogging platform enabling people to communicate via short posts (140 characters). With an average of 500 million tweets posted every day worldwide, Twitter represents a large and constantly updated source of information (Twitter, 2015). In the U.S., 19% of the entire population is comprised of active Twitter users, with 30% of these tweeting daily. Furthermore, the U.S. Twitter population is young (32% aged between 18 and 29 years), which makes it even more suitable for drug abuse surveillance since young adults display the highest rates of cannabis and most other drug use (SAMHSA, 2014). Twitter population in the U.S. is also ethnically diverse (e.g., 28% African-American, 28% Hispanic) and educated (50% with at least some college education; Pew Research, 2015). Because of the volume of data generated by Twitter users and also availability of geographic information, analysis of tweets can provide valuable population level metrics.

Several researchers have already illustrated the usefulness of Twitter in the field of drug abuse research. Hanson and colleagues (2013) analyzed geographic patterns of GPS-enabled tweets and found greater prevalence of Adderall-related tweets in the northeastern portion of the U.S. and also in some of the southern states. Cazavos-Rehg and colleagues (2015b) found that the prevalence of pro-alcohol tweets was significantly greater than anti-alcohol tweets and Twitter users’ opinions of marijuana were predominantly positive (Cavazos-Rehg et al., 2015a). West and colleagues (2012) found that alcohol-related tweets were predominatly sent during night time and over weekends, with higher rates during historically typical drinking time periods (e.g., Christmas, New Years Eve). Another study demonstrated that marijuana concentrate-related tweeting activity was significantly greater in U.S. states that allow recreational and/or medical cannabis use (Daniulaityte et al., 2015). By analyzing Twitter data, the present paper aims to: 1) compare tweeting activity related to cannabis edibles across U.S. states with different marijuana legalization policies, and 2) explore the content of tweets related to cannabis edibles.

2. METHODS

3. RESULTS

4. DISCUSSION

Our study indicates greater cannabis-edibles related tweeting activity in states where medical THC and/or recreational cannabis use have been legalized, and most tweets generally expressed positive attitudes about cannabis edibles. In Colorado and Washington, cannabis edibles can be obtained legally from licensed retailers. In addition, in several states across the country, such as California, Oregon, Arizona and others, qualified patients can obtain cannabis edibles at medical marijuana dispensaries. The highest adjusted percentages of Twitter users tweeting about edibles were in Colorado, Oregon and Washington, states where recreational cannabis consumption is legal. Although the legal market of Oregon was not in operation at the time our Twitter data were collected, Oregon has one of the oldest medical marijuana programs in the country (National Conference of State Legislatures, 2015), and among the highest rates of marijuana use in the general population. Moreover, Figure 1 reveals that a greater percentage of Twitter users tweeting about cannabis edibles are located in western states of the United States (such as California, Nevada, New Mexico, Oregon, or Washington), where medical cannabis programs were introduced earlier than in other parts of the country (National Conference of State Legislatures, 2015). Although epidemiological data on the prevalence of cannabis edibles use in the general population is lacking, one study conducted in Washington state a year before recreational cannabis use became legal found that almost 80% of cannabis users recruited for a web-based survey reported using cannabis edibles in the past year (Kilmer et al., 2013). Analysis of Twitter data on marijuana concentrates identified similar regional differences, with Oregon, Colorado and Washington showing the highest adjusted percentages of dabs-related tweets (Daniulaityte et al., 2015). As noted in other studies, high doses of THC can induce anxiety, panic attacks, cognitive impairments, and psychotic episodes (Di Forti et al., 2009; Hall and Degenhardt, 2015). The higher THC concentration of these two products, both marijuana concentrates and cannabis edibles, might lead to both short- (e.g., panic attacks, difficulty to focus, lack of memory, loss of attention) and long-term (e.g., cannabinoid hyperemesis syndrome, psychosis, schizophrenia) harmful consequences on a sub-population of cannabis users located in or visiting those states.

Twitter data suggest predominantly positive attitudes toward cannabis edibles with 56.8% of tweets expressing positive opinion, compared to 13.2% of tweets denoting negative attitudes or describing detrimental experiences. Positive tweets describe the quality of the “high” experienced and how cannabis edibles facilitate falling asleep. Our data also indicate that several Twitter users consider cannabis edibles as healthier compared to smoking. These results are consistent with findings of Murphy and colleagues (Murphy et al., 2015), who suggested that among older cannabis users in California, edibles are considered a healthier alternative.

Despite the overall positive attitude about edibles, the analysis of negative tweets reveals that the unreliability of edibles’ THC dosage and delayed effects were linked to over-consumption of cannabis edibles which, in turn, could lead to potential harmful consequences. These adverse consequences seem to be linked to two main causes: unrealiable THC content labelling and user’s lack of practical knowledge concerning edibles. According to Vandrey and colleagues (2015), U.S. edible medical cannabis products display inaccurate ratios of THC and Cannabidiol (CBD). Of the 75 products tested, 23% were underlabeled by the producers, while 60% were overlabeled, increasing the risk of acute intoxication and/or overconsumption (Vandrey et al., 2015). In addition, the pharmacokinetic difference between inhaling and ingesting cannabis (Grotenhermen, 2003) leads some users who usually smoke marijuana to consume extra dose(s) of edibles before the initial one kicks in which, in turn, increases the risk of overdose (Monte et al., 2015; Murphy et al., 2015). As such, the population of regular cannabis smokers who are uneducated about edible consumption are at considerable risk of overdose, as New York Times columnist Maureen Dowd (Dowd, 2014) brought to national attention. Our findings reinforce and support the call of legislators and scientists to improve the labelling of edibles and testing the reliability of edibles’ THC dosage to reduce potential harms linked to overdosage as well as access by children (MacCoun and Mello, 2015). Furthermore, preventive harm-minimization efforts are needed to educate non-regular edibles users about consumption of these products (Global Drug Survey, 2015; The Cannabist, 2014).

This research has limitations, most of which are inherent to the field of Internet-based research. First, demographic characteristics of Twitter users were not available, and data collection was limited to tweets written in English. Second, individuals living in states with liberal cannabis policies might feel less restricted in publicly acknowledging their use and/or displaying their geolocation, which could partially affect regional differences in cannabis edibles-related tweeting activity. Furthermore, more work is required to increase the amount and accuracy of geolocated data, in particular for more-fine-grained analyses of regional trends. For example, Drezde and colleagues (2013) demonstrated that their automated geolocation information extraction approach achieved over 90% accuracy in identifying the country of a tweet, but dropped to 54.5% when the geolocation accuracy was measured to a resolution of 25 miles (Drezde et al., 2013). Third, these findings reflect the perception of a portion of Twitter users describing an experience of consumption or expressing their opinion about edibles and are not necesseraly correlated with actual use. For example, some Twitter users might have a positive perception of edibles but not be active edibles users, while others may be actual users but may not be willing to tweet about a negative experience. More research with community-recruited samples of active users are needed to better undestand trends and perceptions identified in Twitter-based research. Finally, as illustrated by the intercoder reliability assessment, the brevity, ambiguity, lack of context and pervasive use of slang terminology, turns content analysis of tweets into a difficult task even for human coders. Future work will include training a sentiment analysis algorithm to automatically categorize sentiments regarding cannabis edibles and other drugs. This sentiment analysis algorithm will be integrated into the eDrugTrends platform to strenghten its analysis capacities and extend our analysis to the total volume of tweets collected.

To the best of our knowledge, this is the first study attempting to describe and analyze Twitter data on cannabis edibles. In the constantly evolving legal context surrounding cannabis products in the U.S., our research demonstrates that Twitter data analysis offers the possibility to retrieve timely information concerning trends of emerging cannabis product use, and provide new insights into the overall perceptions of Twitter users about cannabis products. By providing an “insider” point-of-view, as well as timely and geolocated information, Twitter data could help policy makers to tackle and target specific aspects of a given phenomenon or trend. Furthermore, by using eDrugTrends as a tool to constantly collect Twitter data, we will be able to evaluate the performance and impact of newly implemented public health policies by monitoring changes in users experiences and opinions over time.

Acknowledgments

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