Surveys have been a methodological cornerstone of epidemiology since the inception of the field. However, the manner in which epidemiologists conduct surveys has undergone several paradigm shifts in tandem with advances in mass communication and information dissemination [1]. Initially, data collection was limited to local in-person site visits [1,2]. Over time, new modes of communication, such as mailed questionnaires and random digital dialing [3], expanded epidemiologists’ methodological toolkit [1]. Once the internet began to function as a principal means of communication, it too was recognized for its potential utility as a data collection method [1,4,5]—particularly for substance use data [6]. Historically, collecting data on hidden and stigmatized populations such as substance users had been exceptionally difficult. Early pioneering work demonstrated that it was possible to use the internet to study these populations [7,8].

Today, approximately 3.5 billion people around the world have internet access [9], and 2.3 billion people own a smartphone [10], allowing them to access the internet at any time of day in almost any location. Approximately 2.5 billion people [11] now use social media and networking sites such as Facebook and Twitter, primarily on their smartphones [12,13], for an average of 1 to 2 hours per day [14,15]. In parallel with this increase in internet and social media use, researchers have devoted considerable attention to conducting Web-based studies of health behaviors. In doing so, they have developed various Web survey- and social media-based data collection methods [16-24]. Of the social media platforms now commonly used for health research purposes, Facebook, in particular, has emerged as a useful and low-cost means of recruiting participants [25] from hard-to-reach populations [16]. At present, researchers have used Facebook to disseminate Web surveys to study a range of diseases and health behaviors such as HIV [26]; vaccine uptake [27,28]; mammographies [29]; contraception [30]; several mental health disorders [31-33]; prescription medication misuse [34]; and use of alcohol [35], tobacco [36], e-cigarettes [37], and cannabis [38-42]. Such studies are part of a growing subdiscipline of epidemiology—often termed Infodemiology [43], Digital Epidemiology [44], or E-Epidemiology [45]—that is characterized by the overlap between traditional epidemiological research goals and the utilization of new digital infrastructures.

Facebook-based Web surveys are well suited for addressing questions that arise from sociocultural changes because they allow for the rapid study of behaviors on a population-level scale. One example of such a sociocultural change is the shifting legal landscape of cannabis in the United States. More recreational and medical legal cannabis laws (LCL) have been enacted since 2010 than were enacted from 1996 to 2009 (LCL is used here to differentiate such laws from those focused on criminalizing and prohibiting cannabis) [46], and several new concerns—including the expansion of cannabis product diversity [47-50]—have emerged as a result. Many of the questions brought about by cannabis legalization represent excellent scientific targets for Facebook-based sampling methods.

At the Center for Technology and Behavioral Health at Dartmouth College, we have been leveraging the Facebook Business advertising platform to conduct a series of Web surveys to study questions concerning patterns of use of new methods of cannabis administration (eg, vaping and edibles) and relationships between cannabis use and psychological constructs such as anxiety, pain, and readiness to reduce or stop cannabis use. In the process of conducting these surveys, we have learned several lessons about advertising procedures that minimize costs and maximize survey participation. In addition, given the need to determine strengths and limitations of social media-based data collection [51], we have aggregated and examined the data from several of our surveys to identify the unique characteristics of our sampling method.

This paper provides an overview of our procedures and lessons learned using Facebook advertisements and Web surveys as a method to study cannabis use, our findings regarding the unique characteristics of the cannabis use data produced by this method, and how the characteristics of the resulting data clarify the types of research questions best suited for study with this sampling method.

We have conducted a series of Web surveys using these methods, which have provided insights into patterns of cannabis use across the United States. Below we present data from 6 of those surveys, 3 of which have been published [57,59,60]. Table 1 provides an overview of the recruitment results for each of the surveys.

In our initial study, we used Facebook advertising to recruit adults (N=2910) for a survey on cannabis vaping and edible use. We found that over half (61.27%, 1783/2910) of the users had tried vaping, but only 12.44% (362/2910) of the sample preferred vaping over other methods [61], and the likelihood of vaping and edible use was positively associated with the number of within-state cannabis dispensaries per capita [59]. A second study replicated these findings with cannabis users (N=933). Again, the majority (55.2%, 515/933) had tried vaping, and of those, 27.2% (140/515) had vaped while driving, 34.2% (176/515) had vaped in public, and 14.2% (73/515) had vaped at work (A J Budney, unpublished data, July 2016). In a third study, we collected cannabis use survey data from younger cannabis users (aged 14-18 years; N=2630) and replicated our previous adult findings. We observed the same relationship between dispensaries and vaping and edible use. We also found that home cultivation provisions of legal cannabis laws were uniquely related to a greater likelihood of having used edibles [60]. In a follow-up survey of adults, we collected responses (N=1813) to explore the relationship between provisions of legal cannabis laws (home cultivation and dispensaries) and cannabis edible procurement behaviors. We determined that those who live in states that permit home cultivation tend to make their own cannabis edibles, whereas those who live in states with cannabis dispensaries primarily purchase their edibles [57]. In another study, cannabis users (N=1212) participated in a survey assessing the frequency of cannabis use and thoughts about decreasing their use. A sizeable portion (19.39%, 235/1212) reported having “been concerned about their cannabis use,” and, among these individuals, 75.32% (177/235) had recently thought about reducing their use (A J Budney, unpublished data, February 2017). In another study, cannabis users (n=3561) participated in a survey on frequency of cannabis use and selected psychological processes. Indirect effects of anxiety sensitivity on past 30-day heavy cannabis use were mediated by coping-related motives for cannabis use (A A Knapp, unpublished data, November 2016).

This Facebook-based Web survey approach can be particularly useful for expeditiously conducting studies that help clarify observations and questions that arise from prior survey studies. For example, the primary analyses of the youth survey discussed previously revealed that state-level permission of cannabis home cultivation was statistically related only to an elevated likelihood of edible use, whereas state-level permission of cannabis dispensaries was related to elevated likelihoods of both lifetime vaping and edible use. After developing a hypothesis to explain this observation, we conducted a new survey 3 months later to better understand these relationships. These data replicated the results from the prior study and further demonstrated that those who grow cannabis were more likely to make edibles at home by economizing low-tetrahydrocannabinol (THC) leftover parts of the cannabis plant. However, those who lived in states with dispensaries were more likely to purchase cannabis edibles [57].

As this line of research expands, it is crucial to understand both the strengths and limitations of this Facebook survey sampling method. Epidemiologists use a variety of sampling methods to answer different types of research questions [62-65]. For example, accurately estimating the prevalence of lifetime cannabis use in the United States requires probability-based methods, but understanding the unique cannabis use disorder treatment needs of various population subgroups requires nonprobability-based sampling methods [66]. The unique properties of Facebook sampling for studying cannabis use are largely unclear at this point — making it difficult to determine which types of research questions are most effectively addressed with this method. To begin to fill this gap, we have conducted several secondary analyses of our Facebook-based data. On the basis of our understanding that Facebook advertising was originally designed to help businesses contact their specific niche audience, we hypothesized that Facebook advertisements would produce data similar to traditional nonrandom epidemiological sampling methods, thus producing data on a relatively homogenous subpopulation.

The utilization of social media–based recruitment for conducting cannabis epidemiology research has only begun to scratch the surface of its potential. Our experiences in conducting this research have revealed several insights about this method and the resulting data. First, it would appear prudent to operate under the assumption that Facebook advertising algorithms require a sufficient amount of time to learn about a target population to effectively disseminate advertisements. Thus, we have found it useful to wait at least 48 to 72 hours before evaluating the effectiveness of a Facebook advertising campaign. Second, Facebook advertising methods that recruit for Web-based surveys on cannabis use can quickly and inexpensively generate samples of current, regular cannabis users across the United States. Given the speed of data collection, we have also found that this sampling method is useful for timely clarification of hypotheses, via the expeditious conduct of follow-up surveys. Overall, we encourage the conceptualization of Web survey dissemination via Facebook advertising as a new type of nonprobability-based targeted sampling method. Cannabis researchers can include Facebook as part of their armamentarium of sampling methods. It can be considered as an alternative or adjunct to traditional survey methods, perhaps most valuable when trying to study cannabis behaviors not captured by traditional methods. In addition, in light of the difficulties in developing data infrastructures for evaluating the effects of cannabis legalization [73] and literature suggesting that changes to the legal status of cannabis may disproportionately impact the behavior of regular cannabis users [74], Facebook recruitment methods appear to be valuable for collecting policy-relevant data.

Web surveying via Facebook is only one of many emerging epidemiological methods for studying cannabis use. A growing body of literature has demonstrated that digital trace data [44] (ie, records of naturalistic digital behavior and communication) can be used to study cannabis use. For example, Twitter has been used to study new forms of cannabis administration such as dabbing [75,76], vaping [77], and edibles [78,79]; perceptions, attitudes, and normalization of cannabis use [80-82]; and unique communities of cannabis user subgroups and network structures of cannabis dispensaries [83,84]. Data from other Web-based platforms such as Reddit [85], Instagram [86], YouTube [87], and search engines such as Google [88] or Bing [89] are all other potential sources of digital trace data that have been used to study patterns of cannabis use.

Given the sensitive nature of substance use data, the concept of IP address tracking warrants discussion. When designing a survey, researchers must consider the balance between the need to prevent multiple responses and the need for anonymity to obtain valid responses. Without being able to determine who has already taken a survey, researchers run the risk of having single individuals complete a survey multiple times—especially if monetary incentives are used to encourage survey participation [90]. However, failure to provide respondents with anonymity may result in fewer responses or invalid data. In our surveys to date, we have used the prevent ballot box stuffing feature of Qualtrics as a middle ground. This feature uses cookies rather than IP addresses to prevent multiple responses, which allows us to maintain participant anonymity. Even so, the promise of anonymity may not convince individuals involved in illicit behavior to participate [91]. Finally, note that the use of IP addresses for preventing multiple responses can inadvertently prevent individuals who share the same IP address (eg, college dorm, shared house) from completing the survey.

The landscape of social media will continue to evolve in the coming years, and specific social media platforms such as Facebook may not remain as popular as they are today. However, all indications are that digital social networking and mass communication platforms are here to stay and will continue to grow as advertising tools. In 2017, businesses spent approximately 13.5 billion dollars using social media marketing to sell their products and services [92]. Thus, it seems likely that providing an advertising service within digital social networking platforms will remain a staple means of generating revenue for the companies that create such platforms. In addition, as the machine learning techniques used to disseminate digital marketing advertisements continue to become more sophisticated and effective, researchers can leverage such advances to even more efficiently reach and collect data on clinical subpopulations of interest.

There remain many unanswered questions related to this sampling method. Here, we mention just 3, each of which could provide exciting additional research opportunities. First, can these methods be used effectively to study the use of other substances? It is likely that the degree of stigma surrounding a particular substance of interest will affect the utility of the methodology presented here. For example, there are nationally distributed magazines and well-recognized political activist groups devoted specifically to the promotion of cannabis use and cannabis culture. These aspects of cannabis culture are available as specific targeted interests on the Facebook Business advertising platform. In contrast, to our knowledge, there are no regularly published national magazines or political activist groups that promote crystal methamphetamine use and culture. Thus, the targeting strategies for more stigmatized drugs such as crystal methamphetamine may need to be different and will likely require the use of monetary incentives. One suggestion to overcome this issue is to conduct an in-person pilot focus group with regular users of the substance of interest and collect digital or self-report data concerning their Web-based behavior. The resulting data could then be used to generate a more effective Facebook advertising campaign.

Second, will participants provide identifying contact information in a survey to facilitate longitudinal survey follow-up (ie, repeated sampling from the same individual over time)? Previous work by Harris et al has demonstrated that survey respondents recruited via Facebook are willing to provide contact information to facilitate follow-up for longitudinal studies. However, their study aimed to understand patterns of contraception use among young Australian women [30]. It remains to be seen whether something similar can be accomplished with a US-based sample of heavy cannabis users.

Finally, is it possible to use alternative advertising strategies (eg, not using cannabis-related targeted interests) to obtain samples of less experienced or less frequent cannabis users? Preliminary data currently being collected by our team suggest that this can be readily accomplished using different targeting strategies, but that data collection may be somewhat slower and more expensive.

Sampling issues are a primary concern of any epidemiological investigation because they dictate the conclusions that can be drawn from the data [63,64]. Additional methodological evaluations of social media–based sampling will fill essential gaps in our knowledge of how to use the data effectively. Presently, we believe that social media–based Web surveys have tremendous utility for members of the research community and will continue to facilitate our understanding of the evolving nature of cannabis use behaviors.