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      The Volume and Tone of Twitter Posts About Cannabis Use During Pregnancy: Protocol for a Scoping Review

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          Abstract

          Background

          Cannabis use has increased in Canada since its legalization in 2018, including among pregnant women who may be motivated to use cannabis to reduce symptoms of nausea and vomiting. However, a growing body of research suggests that cannabis use during pregnancy may harm the developing fetus. As a result, patients increasingly seek medical advice from online sources, but these platforms may also spread anecdotal descriptions or misinformation. Given the possible disconnect between online messaging and evidence-based research about the effects of cannabis use during pregnancy, there is a potential for advice taken from social media to affect the health of mothers and their babies.

          Objective

          This study aims to quantify the volume and tone of English language posts related to cannabis use in pregnancy from January 2012 to December 2021.

          Methods

          Modeling published frameworks for scoping reviews, we will collect publicly available posts from Twitter that mention cannabis use during pregnancy and use the Twitter Application Programming Interface for Academic Research to extract data from tweets, including public metrics such as the number of likes, retweets, and quotes, as well as health effect mentions, sentiment, location, and users’ interests. These data will be used to quantify how cannabis use during pregnancy is discussed on Twitter and to build a qualitative profile of supportive and opposing posters.

          Results

          The CHEO Research Ethics Board reviewed our project and granted an exemption in May 2021. As of December 2021, we have gained approval to use the Twitter Application Programming Interface for Academic Research and have developed a preliminary search strategy that returns over 3 million unique tweets posted between 2012 and 2021.

          Conclusions

          Understanding how Twitter is being used to discuss cannabis use during pregnancy will help public health agencies and health care providers assess the messaging patients may be receiving and develop communication strategies to counter misinformation, especially in geographical regions where legalization is recent or imminent. Most importantly, we foresee that our findings will assist expecting families in making informed choices about where they choose to access advice about using cannabis during pregnancy.

          Trial Registration

          Open Science Framework 10.17605/OSF.IO/BW8DA; www.osf.io/6fb2e

          International Registered Report Identifier (IRRID)

          PRR1-10.2196/34421

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          Most cited references47

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          PRISMA Extension for Scoping Reviews (PRISMA-ScR): Checklist and Explanation

          Adrian Aldcroft, Chantelle Garritty, Simon Lewin … (2018)
          Scoping reviews, a type of knowledge synthesis, follow a systematic approach to map evidence on a topic and identify main concepts, theories, sources, and knowledge gaps. Although more scoping reviews are being done, their methodological and reporting quality need improvement. This document presents the PRISMA-ScR (Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews) checklist and explanation. The checklist was developed by a 24-member expert panel and 2 research leads following published guidance from the EQUATOR (Enhancing the QUAlity and Transparency Of health Research) Network. The final checklist contains 20 essential reporting items and 2 optional items. The authors provide a rationale and an example of good reporting for each item. The intent of the PRISMA-ScR is to help readers (including researchers, publishers, commissioners, policymakers, health care providers, guideline developers, and patients or consumers) develop a greater understanding of relevant terminology, core concepts, and key items to report for scoping reviews.
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            Scoping studies: towards a methodological framework

            Lisa O'Malley, Hilary Arksey (2005)
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              Twitter as a Tool for Health Research: A Systematic Review

              Christina Mancheno, Lyle Ungar, Kevin Padrez … (2017)
              Background. Researchers have used traditional databases to study public health for decades. Less is known about the use of social media data sources, such as Twitter, for this purpose. Objectives. To systematically review the use of Twitter in health research, define a taxonomy to describe Twitter use, and characterize the current state of Twitter in health research. Search methods. We performed a literature search in PubMed, Embase, Web of Science, Google Scholar, and CINAHL through September 2015. Selection criteria. We searched for peer-reviewed original research studies that primarily used Twitter for health research. Data collection and analysis. Two authors independently screened studies and abstracted data related to the approach to analysis of Twitter data, methodology used to study Twitter, and current state of Twitter research by evaluating time of publication, research topic, discussion of ethical concerns, and study funding source. Main results. Of 1110 unique health-related articles mentioning Twitter, 137 met eligibility criteria. The primary approaches for using Twitter in health research that constitute a new taxonomy were content analysis (56%; n = 77), surveillance (26%; n = 36), engagement (14%; n = 19), recruitment (7%; n = 9), intervention (7%; n = 9), and network analysis (4%; n = 5). These studies collectively analyzed more than 5 billion tweets primarily by using the Twitter application program interface. Of 38 potential data features describing tweets and Twitter users, 23 were reported in fewer than 4% of the articles. The Twitter-based studies in this review focused on a small subset of data elements including content analysis, geotags, and language. Most studies were published recently (33% in 2015). Public health (23%; n = 31) and infectious disease (20%; n = 28) were the research fields most commonly represented in the included studies. Approximately one third of the studies mentioned ethical board approval in their articles. Primary funding sources included federal (63%), university (13%), and foundation (6%). Conclusions. We identified a new taxonomy to describe Twitter use in health research with 6 categories. Many data elements discernible from a user’s Twitter profile, especially demographics, have been underreported in the literature and can provide new opportunities to characterize the users whose data are analyzed in these studies. Twitter-based health research is a growing field funded by a diversity of organizations. Public health implications. Future work should develop standardized reporting guidelines for health researchers who use Twitter and policies that address privacy and ethical concerns in social media research.
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                Author and article information

                Contributors
                Daniel J Corsi:
                ORCID: https://orcid.org/0000-0001-7063-3354
                CHEO Research Institute501 Smyth RdCentre for Practice Changing Research, Room L1242, Box 241Ottawa, ON, K1H 8L6Canada1 613 737 8899dcorsi@ohri.ca
                Journal
                Journal ID (nlm-ta): JMIR Res Protoc
                Journal ID (iso-abbrev): JMIR Res Protoc
                Journal ID (publisher-id): ResProt
                Title: JMIR Research Protocols
                Publisher: JMIR Publications (Toronto, Canada )
                ISSN (Electronic): 1929-0748
                Publication date Collection: March 2022
                Publication date (Electronic): 29 March 2022
                Volume: 11
                Issue: 3
                Electronic Location Identifier: e34421
                Affiliations
                [1 ] Obstetrics & Maternal Newborn Investigations Research Group Clinical Epidemiology Program Ottawa Hospital Research Institute Ottawa, ON Canada
                [2 ] Faculty of Medicine University of Ottawa Ottawa, ON Canada
                [3 ] Department of Network and Data Science Central European University Vienna Austria
                [4 ] Department of Obstetrics and Gynecology Faculty of Medicine University of Ottawa Ottawa, ON Canada
                [5 ] School of Epidemiology and Public Health University of Ottawa Ottawa, ON Canada
                [6 ] Better Outcomes Registry & Network Ontario Ottawa, ON Canada
                [7 ] International and Global Health Office University of Ottawa Ottawa, ON Canada
                [8 ] CHEO Research Institute Ottawa, ON Canada
                Author notes
                Corresponding Author: Daniel J Corsi dcorsi@ 123456ohri.ca
                Author information
                https://orcid.org/0000-0003-4844-8122
                https://orcid.org/0000-0002-3945-2966
                https://orcid.org/0000-0002-4566-4957
                https://orcid.org/0000-0003-4356-9726
                https://orcid.org/0000-0001-8974-4548
                https://orcid.org/0000-0001-5382-8950
                https://orcid.org/0000-0001-7063-3354
                Article
                Publisher ID: v11i3e34421
                DOI: 10.2196/34421
                PMC ID: 9006132
                PubMed ID: 35348465
                SO-VID: 02938041-2114-4c42-ae9d-c122824cc4fd
                Copyright statement: ©Liam Cresswell, Lisette Espin-Noboa, Malia S Q Murphy, Serine Ramlawi, Mark C Walker, Márton Karsai, Daniel J Corsi. Originally published in JMIR Research Protocols (https://www.researchprotocols.org), 29.03.2022.
                License:

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Research Protocols, is properly cited. The complete bibliographic information, a link to the original publication on https://www.researchprotocols.org, as well as this copyright and license information must be included.

                History
                Date received : 22 October 2021
                Date revision requested : 17 December 2021
                Date revision received : 26 January 2022
                Date accepted : 8 February 2022
                Product
                Self URI: https://www.researchprotocols.org/2022/3/e34421
                Categories
                Subject: Protocol
                Subject: Protocol

                Keywords: cannabis,pregnancy,health information,social media,twitter
                Data availability:
                Keywords: cannabis, pregnancy, health information, social media, twitter

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