Disseminating timely and relevant research findings to policy makers is a national priority to inform health policy decisions. Social media is a novel tool to bridge the communication gap.
Objectives: Although health policy research should inform policy making, the communication gap between researchers and policy makers limits successful translation. Social media represents a new opportunity to connect researchers and policy makers. Our objective was to assess who Congressional health policy staff follow on a major social media platform.
Study Design: Cross-sectional study.
Methods: Our study measured Congressional health policy staff’s use of Twitter and the types of individuals and organizations they follow. To focus on more influential Twitter accounts, we restricted our sample to those followed by at least 3 individual Congressional staff members.
Results: Of the 30,843 accounts followed by the 115 Congressional health policy staff, 1273 were potentially policy-related and followed by 3 or more staff. Of these, few were academically affiliated (2.4%) or explicitly health-related (5.6%) sites; many were general news media sources (50.9%) and political and governmental sources (36.4%). Health-focused accounts were frequently connected to the news media or government rather than academia. Top accounts followed (ie, highest quintile) were most likely to be national news organizations (odds ratio [OR], 5.88; 95% confidence interval [CI], 1.75-19.7) and elected officials (OR, 8.22; 95% CI, 1.75-38.6) compared with advocacy and interest groups.
Conclusions: Health-related and academic sources are largely absent from the Twitter conversations with US Congressional health policy staff. Even within social media, traditional and political news media are important information intermediaries that researchers and journals should target to disseminate health policy evidence.
In recent years, researchers, international policy bodies, health funders, and other commentators have called for new efforts to improve the translation of research into health policy.1,2 Yet, there are significant challenges to translating research, particularly to policy-maker audiences.1,3 Researchers often lack the skills, support, and time to effectively translate their work.4,5 Policy makers have very different incentives, values, timeframes, and competing priorities that challenge their efficient use of research evidence to set agendas and make decisions.6-9 Given that these barriers mean that research will not always be used in policy making, one necessary step in translation is effective communication of the research itself.
Social media offers opportunities to rapidly convey public health and health policy—relevant research to target audiences. For instance, researchers, journals, and institutions can use tools like Twitter to communicate findings and provide links to content.10,11 Blogs can “curate” policy-relevant research so that even older research findings can be made available to policy makers when windows of opportunity to use that research become apparent, and social networks can be used to disseminate these research findings.12,13 In 2013, 14% of health policy researchers reported using Twitter to disseminate research, but it is unknown whether they were connected via social media to policy makers—the target users of evidence.14
Congressional staff are responsible for bringing analyses to their legislators and, as drafters of legislation, are direct users of policy evidence.15,16 Research suggests that staffers perceive Twitter as influential17; however, to our knowledge, no research is available about Congressional staffers’ use of Twitter and the types of individuals and organizations they follow as potential sources of information. Rather, prior studies of social media in the US political system have generally focused on its use by elected officials to communicate with constituents, or the manner in which political information spreads within social networks of constituents.18-22 This study was designed to fill this gap in the literature, with a focus on Congressional staff. The primary objective was to describe the Twitter accounts followed by Congressional health staff and to inform potential communication opportunities for researchers.
Social media is emerging as a tool used to communicate research evidence. In this study, we were interested in who a key audience of health policy research—Congressional staff—followed on social media. We focused on a widely used form of social media, specifically Twitter, a micro-blogging tool, and identified 3 key findings.
We obtained a proprietary list of Congressional staff members with responsibilities in health from Legistorm,23 a subscription service for government affairs professionals. They collect this individual-level data on Congressional staff from publicly available sources, including government reports and traditional and social media. We purchased a list of 558 staff members with responsibilities in health as determined by Legistorm in April 2014. Legistorm provided us with the Twitter account names (“handles”) of 84 staff members. We then conducted a search for the remaining 474 Congressional staff using Google and Twitter search engines and demographic characteristics provided by Legistorm to determine if they had an active or identifiable account. Because Twitter users can make their account private, all analyses described concerned the subset of staff with public accounts (n = 115).
Accounts Followed on Twitter
Using the Twitter application program interface, we retrieved the list of the Twitter accounts followed by each Congressional staff member in our database. (The retrieval date was July 26, 2014.) We retrieved characteristics of these accounts, including their short biography/description, number of followers, and number of tweets. Because we were interested in potentially influential Twitter accounts, we restricted our sample to accounts followed by 3 or more staff.
We categorized accounts along the following domains: individual versus organization, health versus nonhealth, and type (academic, political/government, news media, or interest group/advocacy, which included think tanks). The coding categories were not mutually exclusive. We created subcategories for the political/government category (elected official, partisan political organization, and government agency) and news media category (national, local, and political). Coders used the Twitter bio to classify accounts; for example, any entity that cited a “.edu” address in the bio or offered a university affiliation was classified as academic and any entity that used health-related terms anywhere in their bio was classified as health-related. Accounts on Twitter that could not be categorized into this scheme were determined to be unlikely to be related to professional duties (eg, local restaurants, non—news-focused television programs) and excluded from our analysis. For the purposes of this study, we defined the remaining Twitter accounts as policy-related. We pilot tested the coding instrument with 2 trained coders. Each coder then classified all Twitter accounts. If a coding category had an inter-rater reliability below 0.61, a third coder and co-investigator (JS) adjudicated after discussing with the study team.
We calculated frequencies for each Twitter account followed to determine the number of Congressional staff following each, and limited our analyses to those accounts followed by 3 or more staff (n = 2203). We modeled the characteristics of the most-followed accounts (ie, those falling in the top quintile of sources) using multivariable logistic regression.
The study was reviewed and approved by the institutional review board at the University of Pennsylvania. Data collection and analyses were done in compliance with Twitter’s terms of service.
From a database of 558 Congressional staff, we identified 33% (184) with Twitter accounts. Of the 184 with Twitter accounts, 69 had private accounts and 115 had public accounts. The 115 Congressional staff with public accounts collectively followed 30,843 different individual or organization Twitter accounts. Three or more Congressional staff followed 2203 of these Twitter accounts.
Types of Accounts Followed on Twitter
Of the 2203 individuals and organizations followed by 3 or more Congressional staff, 1273 (57.8%) were policy related (Table 1). Of these 1273, just 71 (5.6%) were health related. Very few (30; 2.4%) of the Twitter accounts followed were affiliated with academic institutions. Congressional staff most commonly followed news media accounts; 648 (50.9%) were affiliated with news media organizations, primarily national news organizations and political news organizations (eg, Politico); local news organizations were less commonly followed. Political and governmental accounts were the second most common category, representing 464 (36.4%) of accounts followed.
Top Twitter Accounts Followed
The top accounts were followed by 40 to 67 Congressional staff (Table 2). These accounts also had a large number of followers, ranging from 62,876 to 44,129,382. The top 6 included political news organizations (Politico, The Hill), national news organizations (The New York Times), elected officials (The White House, Barack Obama), and a political satirist (Stephen Colbert). The other most frequently followed accounts were predominantly related to news media organizations.
In a multivariable logistic regression model, we modeled the association of the characteristics of Twitter accounts with their likelihood of being highly followed (top quintile). We restricted this analysis to the 1273 accounts followed that were coded as policy related. Although there were more Twitter accounts in our sample representing individuals, individual accounts were less likely to be frequently followed by Congressional staff than those representing organizations (odds ratio [OR], 0.30; 95% confidence interval [CI], 0.10-0.92; P = .035). Accounts representing national news organizations (OR, 5.88; 95% CI, 1.75-19.7; P = .004) and elected officials (OR, 8.22; 95% CI, 1.75-38.6; P = .008) were the most frequently followed by Congressional staff.
Top Health-Related Twitter Accounts Followed
Among the 71 health-related accounts followed by Congressional staffers (top accounts shown in Table 2), the most popular account was that of Sarah Kliff, a journalist and blogger with a national media organization (Vox.com, formerly of the Washington Post). Health-related news media accounts (eg, NY Times Health) and governmental and political accounts (eg, HHS) were frequently represented among the top accounts. Health Affairs was the only health-related academic journal followed by 3 or more Congressional staff.
Using Twitter, we identified 3 key findings. First, many Congressional staff used Twitter and followed accounts that may be related to their professional roles. In our sample of health-related Congressional staff, we were able to successfully identify one-third of targeted individuals with Twitter accounts. This is likely an underestimate given that we were unable to search for individuals who preferred to obscure their identity on Twitter (eg, use of pseudonyms). Second, even among Congressional staff with a health focus, very few of the accounts followed were health or health-policy related (just 71 of 1273; 5.6%). The accounts that were explicitly health-focused were often associated with major news media outlets. Third, beyond health-focused accounts, Congressional staff were most likely to follow national and political news media organizations and second most likely to follow political and governmental individuals and agencies.
Academic sources were almost completely absent from Twitter accounts frequently followed by Congressional staff.24 The few academic accounts represented in the sample were typically individuals with faculty appointments who had once served in a political or governmental role. It has been well documented that traditional news media can shape policy-makers’ agendas25,26 and that information sources from government and interest groups are important to decision makers.27 However, social media does not appear to circumvent traditional pathways of information dissemination (ie, the news media), but rather serve as an alternative channel to connect entities with influence that predated social media.
Our study has several important implications. First, although policy makers’ staff were common users of social media, they did not appear to be using the technology in a way that directly connected researchers and policy makers. This suggests that academic researchers and institutions should not overlook traditional news media targets in their social media dissemination strategies. These findings may also point to the need for researchers and academic institutions to build relationships with trusted information intermediaries (eg, advocacy organizations/think tanks) that could curate new research findings and deliver information through social media that is timely and salient to policy makers. Second, although the pathways may be similar to traditional channels, the nature or influence of the information communicated may nonetheless be different. Future research should examine how the information communicated through social media differs from that provided by traditional news sources (eg, newspapers), and whether it produces alterations in terms of influence. News outlets increasingly have health-focused Twitter feeds that are narrow in focus. Future research should also examine how the information-seeking habits of various types of policy staff differ. For example, staff in Senate member offices, on Congressional committees, or in executive branch agencies have more specialized roles than staff in House member offices. Therefore, they may rely on different sources through social media.
Our study has several limitations. First, we obtained a list of health-related Congressional staff from a company that gathers this information and sells it to third parties. We were not able to validate that the database included all health-related Congressional staff or if those identified were actively working on health policy in a Congressional office. We also could not verify that the individuals used Twitter for work-related purposes. By restricting the search to accounts followed by 3 or more staff, we identified accounts that were more likely to be related to their professional roles. In addition, we were unable to extract the Twitter accounts followed by Congressional staff if their own account was private (n = 69). Another possibility is that some staff maintain 2 Twitter accounts—a private account (or public account with a pseudonym) for work-related use and a public account for personal use. If this were the case, our analysis may be missing some Twitter accounts followed by 3 or more staff. Given these limitations, our sample is unlikely to be representative of all health policy staff in the Congress, and may be missing some Twitter accounts followed by staff.
Second, we coded each Twitter account using the bio within the Twitter account. In some cases, the bio provided limited information and thus, there may be some misclassification of Twitter accounts that could not be classified within our coding scheme. Third, we did not attempt to characterize the content of information being communicated on Twitter or the relative contributions of different accounts. Fourth, Twitter users sometimes followed “lists” of Twitter accounts followed by others. This allowed a user to follow another user’s list of curated accounts, which could have been either public or private. Our analysis did not account for this. Finally, our study focused on Twitter and our results were only generalizable to this social media platform.
Improving the translation and dissemination of health policy and health service research is essential to achieving evidence-influenced policy making. Social media represents a highly touted opportunity to communicate research evidence. However, it does not appear to circumvent the traditional news media as an important intermediary that provides information to policy makers.28 As academic researchers and institutions use social media to disseminate research, our findings suggest that they should focus their communication strategies on news media targets if the goal is to reach networks policy makers already use.
The authors thank Maarten Sap for his technical assistance on this project. This study was supported by the Robert Wood Johnson Foundation Health & Society Scholars Program at the University of Pennsylvania. The funder had no role in the study design; collection, analysis and interpretation of data; writing of the manuscript; and the decision to submit the article for publication.
Author Affiliations: Division of General Internal Medicine (DG), Leonard Davis Institute of Health Economics (DG, ZFM, RMM), and Department of Emergency Medicine (ZFM, RMM), University of Pennsylvania, Philadelphia, PA; School of Public Health, Boston University (JS), (Boston, MA); School of Public Health, University of Minnesota (SEG), (Minneapolis, MN).
Source of Funding: Robert Wood Johnson Foundation Health & Society Scholars Program at the University of Pennsylvania.
Author Disclosures: The authors report no relationship or financial interest with any entity that would pose a conflict of interest with the subject matter of this article.
Authorship Information: Concept and design (DG, ZFM, RMM, SEG); acquisition of data (DG, ZFM, RMM); analysis and interpretation of data (DG, ZFM, RMM, JS, SEG); drafting of the manuscript (DG, RMM, JS, SEG); critical revision of the manuscript for important intellectual content (DG, ZFM, RMM, SEG); statistical analysis (DG); obtaining funding (DG); administrative, technical, or logistic support (ZFM, JS).
Address Correspondence to: David Grande, MD, MPA, University of Pennsylvania, 3641 Locust Walk ­— 407, Philadelphia, PA 19104. E-mail: email@example.com.
1. Prewitt K, Schwandt TA, Straf ML; National Research Council. Using science as evidence in public policy. The National Academies Press website. https://www.nap.edu/catalog/13460/using-science-as-evidence-in-public-policy. Published 2012. Accessed July 12, 2017.
2. World report on knowledge for better health: strengthening health systems. World Health Organization website. http://www.who.int/rpc/meetings/en/world_report_on_knowledge_for_better_health2.pdf. Published 2004. Accessed July 12, 2017).
3. Bogenschneider K, Corbett TJ. Evidence-Based Policymaking: Insights From Policy-Minded Researchers and Research-Minded Policymakers. New York: Routledge; 2011.
4. Brownson RC, Jacobs JA, Tabak RG, Hoehner CM, Stamatakis KA. Designing for dissemination among public health researchers: findings from a national survey in the United States. Am J Public Health. 2013;103(9):1693-1699. doi: 10.2105/AJPH.2012.301165.
5. Otten JJ, Dodson EA, Fleischhacker S, Siddiqi S, Quinn EL. Getting research to the policy table: a qualitative study with public health researchers on engaging with policy makers. Prev Chron Dis. 2015;12:E56. doi: 10.5888/pcd12.140546.
6. Caplan N. The two-communities theory and knowledge utilization. Am Behav Sci. 1979;22(3):459-470.
7. Brownson RC, Royer C, Ewing R, McBride TD. Researchers and policymakers: travelers in parallel universes. Am J Prev Med. 2006;30(2):164-172.
8. Mitton C, Adair CE, McKenzie E, Patten SB, Waye Perry B. Knowledge transfer and exchange: review and synthesis of the literature. Milbank Q. 2007;85(4):729-768.
9. Jewell CJ, Bero LA. “Developing good taste in evidence”: facilitators of and hindrances to evidence-informed health policymaking in state government. Milbank Q. 2008;86(2):177-208. doi: 10.1111/j.1468-0009.2008.00519.x.
10. Harris JK, Moreland-Russell S, Tabak RG, Ruhr LR, Maier RC. Communication about childhood obesity on Twitter. Am J Public Health. 2014;104(7):e62-e69. doi: 10.2105/AJPH.2013.301860.
11. Darling ES, Shiffman D, Côté IM, Drew JA. The role of Twitter in the life cycle of a scientific publication. PeerJ Preprints website. http://www.peerj.com/preprints/16/. Published May 6, 2013. Accessed June 11, 2017.
12. Batts SA, Anthis NJ, Smith TC. Advancing science through conversations: bridging the gap between blogs and the academy. PLoS Biol. 2008;6(9):e240. doi: 10.1371/journal.pbio.0060240.
13. Frakt A. Blogging: is it good or bad for journal article readership? The Incidental Economist website. http://www.theincidentaleconomist.com/wordpress/blogging-is-it-good-or-bad-for-journal-article-readership/. Published June 18, 2014. Accessed July 11, 2017.
14. Grande D, Gollust SE, Pany M, et al. Translating research for health policy: researchers’ perceptions and use of social media. Health Aff (Millwood). 2014;33(7):1278-1285. doi: 10.1377/hlthaff.2014.0300.
15. Weiss CH. Congressional committees as users of analysis. J Policy Anal Manage. 1989;8(3):411-431. doi: 10.2307/3324932.
16. Romzek BS, Utter JA. Congressional legislative staff: political professionals or clerks? Am J Poli Sci. 1997;41(4):1251-1279. doi: 10.2307/2960489.
17. Nehls C. Just a handful of social media comments can grab the attention of Congress, study shows. Connectivity website. http://connectivity.cqrollcall.com/just-a-handful-of-social-media-comments-can-grab-attention-of-congress-study-shows/. Published October 27, 2014. Accessed July 11, 2017.
18. Lassen DS, Brown AR. Twitter: the electoral connection? Soc Sci Comput Rev. 2011;29(4):419-436. doi: 10.1177/0894439310382749.
19. Bode L, Dalrymple KE. Politics in 140 characters or less: campaign communication, network interaction, and political participation on Twitter. J Polit Market. 2014:1-22. doi: 10.1080/15377857.2014.959686.
20. Bode L, Hanna A, Yang J, Shah DV. Candidate networks, citizen clusters, and political expression: strategic hashtag use in the 2010 midterms. Ann Am Acad Polit SS. 2015;659(1):149-165. doi: 10.1177/0002716214563923.
21. Glassman ME, Straus JR, Shogan C. Social networking and constituent communications: members’ use of Twitter and Facebook during a two-month period in the 112th Congress. Congressional Research Service website. https://fas.org/sgp/crs/misc/R43018.pdf. Published March 22, 2013. Accessed July 11, 2017.
22. Kapp JM, Hensel B, Schnoring KT. Is Twitter a forum for disseminating research to health policy makers? Ann Epidemiol. 2015;25(12):883-887. doi: 10.1016/j.annepidem.2015.09.002.
23. Paek HM, Swiatek-Kelley J, O’Connell R, Brandt C. Qualitative study of patients’ perceptions of safety and risk related to electronic health records in a hospital. AMIA Annu Symp Proc. 2006:1054.
24. Kristof N. Smart minds, slim impact. The New York Times website. https://www.nytimes.com/2014/02/16/opinion/sunday/kristof-professors-we-need-you.html. Published February 16, 2014. Accessed July 11, 2017.
25. Edwards GC, Wood BD. Who influences whom? the president, Congress, and the media. Am Polit Sci Rev. 1999;93(2):327-344. doi: 10.2307/2585399.
26. Yanovitzky I. Effects of news coverage on policy attention and actions: a closer look into the media-policy connection. Communic Res. 2002;29(4):422-451.
27. Baumgartner FR, Jones BD. The Politics of Information: Problem Definition and the Course of Public Policy in America. Chicago, IL: University of Chicago Press; 2014.
28. Gold M. Pathways to the use of health services research in policy. Health Serv Res. 2009;44(4):1111-1136. doi: 10.1111/j.1475-6773.2009.00958.x.