Social media discourse and internet search queries on cannabis as a medicine: A systematic scoping review
Authors: Hallinan Christine Mary , Habibabadi Sedigheh Khademi , Conway Mike , Bonomo Yvonne Ann 
Published: May 2022

AbstractThe use of cannabis for medicinal purposes has increased globally over the past decade since patient access to medicinal cannabis has been legislated. Yet, evidence of cannabis efficacy for a suite of conditions is only just emerging. Although there is considerable engagement from many stakeholders to add to the evidence base through randomized control trials, many gaps in the literature remain. Data from real-world and patient reported sources can provide opportunities to address this evidence deficit. This real-world data can be captured from a variety of sources such as found in routinely collected health care and health services records that include but are not limited to patient generated data from medical, administrative and claims data, patient reported data from surveys, wearable trackers, patient registries, and social media. In this systematic scoping review, we seek to understand the utility of online user generated text into the use of cannabis as a medicine. The objective of this scoping review is to synthesize primary research that uses social media discourse and internet search engine queries to answer the following questions: (i) Does online user-generated text provide a useful data source for studying cannabis as a medicine? (ii) What are the aims, data sources, and research themes of studies using online user-generated text to discuss the medicinal use of cannabis? For this scoping review we used a framework for systematic reviews and meta-analyses, the PRISMA guidelines to inform our methods. We conducted a manual search of primary research studies which used online user-generated text as a data source using the MEDLINE, Embase, Web of Science, and Scopus databases in October 2022. Editorials, letters, commentaries, surveys, protocols, and book chapters were excluded from the review. Forty-two studies were included in this review, 22 studies used manually labelled data, four studies used existing meta-data (Google trends/geo-location data), two studies used data that was manually coded using crowdsourcing services, and two used automated coding supplied by a social media analytics company, 15 used computational methods for annotating data. Our review reflects a growing interest in the use of user-generated content for public health surveillance. It also demonstrates the need for the development of a systematic approach for evaluating the quality of social media studies and highlights the utility of automatic processing and computational methods (machine learning technologies) for large social media datasets. This systematic scoping review has shown that user-generated content as a data source for studying cannabis as a medicine provides another means to understand how cannabis is perceived and used in the community. As such, it provides another potential ‘tool’ with which to engage in pharmacovigilance of, not only cannabis as a medicine, but also other novel therapeutics as they enter the market.