Abstract
Social media is increasingly being used as an information source and tool for individuals and organizations to share resources and engage in conversations about health topics. Because the public tends to learn about health topics and genetics from online social media sources, it is imperative to understand the amount, type, and quality of information being shared. We performed a retrospective analysis of tweets related to hereditary breast and ovarian cancer (HBOC) and Lynch syndrome (LS) between January 1, 2017 and December 31, 2017. A total of 63,770 tweets were included in our dataset. The majority were retweets (59.9%) and users came from 744 different cities. Most tweets were considered “informational” (51.4%) and were designed to provide resources to the public. Online communities (25%), organizations (20%), and providers or researchers (15%) were among the most common contributors. Our results demonstrated that conversations were primarily focused on information and resource sharing, along with individuals discussing their personal stories and testimonials about their experiences with these HBOC and LS. Future studies could consider ways to harness Twitter to help tailor and deliver health communication campaigns and education interventions to improve the public’s understanding of these complex topics.
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15 May 2020
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References
Cohen RA, Adams PF (2011) Use of the internet for health information: United States, 2009. NCHS Data Brief (66):1–8
Cline RJ, Haynes KM (2001) Consumer health information seeking on the internet: the state of the art. Health Educ Res 16(6):671–692
Bender JL, Jimenez-Marroquin MC, Jadad AR (2011) Seeking support on facebook: a content analysis of breast cancer groups. J Med Internet Res 13(1):e16
Logan AG (2014) Community hypertension programs in the age of mobile technology and social media. Am J Hypertens 27(8):1033–1035
Greene JA, Choudhry NK, Kilabuk E, Shrank WH (2011) Online social networking by patients with diabetes: a qualitative evaluation of communication with Facebook. J Gen Intern Med 26(3):287–292
Sugawara Y, Narimatsu H, Hozawa A, Shao L, Otani K, Fukao A (2012) Cancer patients on twitter: a novel patient community on social media. BMC Res Notes 5:699
Prochaska JJ, Coughlin SS, Lyons EJ (2017) Social media and Mobile Technology for Cancer Prevention and Treatment. Am Soc Clin Oncol Educ Book 37:128–137
Nastasi A, Bryant T, Canner JK, Dredze M, Camp MS, Nagarajan N (2018) Breast Cancer screening and social media: a content analysis of evidence use and guideline opinions on twitter. J Cancer Educ 33(3):695–702
Frank C, Fallah M, Sundquist J, Hemminki A, Hemminki K (2015) Population landscape of familial Cancer. Sci Rep 5:12891
Moyer VA, U.S. Preventive Services Task Force (2014) Risk assessment, genetic counseling, and genetic testing for BRCA-related cancer in women: U.S. Preventive Services Task Force recommendation statement. Ann Intern Med 160(4):271–281. https://www.ncbi.nlm.nih.gov/pubmed/24366376
Recommendations from the EGAPP Working Group (2009) Genetic testing strategies in newly diagnosed individuals with colorectal cancer aimed at reducing morbidity and mortality from lynch syndrome in relatives. Genet Med 11(1):35–41
Cragun DL, Couch SC, Prows CA, Warren NS (2005) Christianson CA. A success of a genetics educational intervention for nursing and dietetic students: a model for incorporating genetics into nursing and allied health curricula. J Allied Health 34(2):90–96
Hitlin P (2015) Methodology: how crimson hexagon works. Pew Research Center. http://www.journalism.org/2015/04/01/methodology-crimson-hexagon/. Accessed 15 March 2018
McKenna VB, Sixsmith J, Barry MM (2017) The relevance of context in understanding health literacy skills: findings from a qualitative study. Health Expect 20:1049–1060
Allen CG, Andersen B, Chambers DA, Groshek J, Roberts MC (2018) Twitter use at the 2016 conference on the science of dissemination and implementation in health: analyzing #DIScience16. Implement Sci 13(1):34
Himelboim I, Han JY (2014) Cancer talk on twitter: community structure and information sources in breast and prostate cancer social networks. J Health Commun 19(2):210–225
Hopkins DJ, King G (2010) A method of automated nonparametric content analysis for social science. Am J Polit Sci 54(1):229–247
DiscoverText. Scholarly mentions of Discover Text 2018. https://discovertext.com/publications/. Accessed 15 March 2018
DiscoverText (2018) Text and Twitter Data Analytics
Betton V, Borschmann R, Docherty M, Coleman S, Brown M, Henderson C (2015) The role of social media in reducing stigma and discrimination. Br J Psychiatry 206(6):443–444
Naslund JA, Aschbrenner KA, Marsch LA, Bartels SJ (2016) The future of mental health care: peer-to-peer support and social media. Epidemiol Psychiatr Sci 25(2):113–122
Hong Y, Pena-Purcell NC, Ory MG (2012) Outcomes of online support and resources for cancer survivors: a systematic literature review. Patient Educ Couns 86(3):288–296
Lepore SJ, Buzaglo JS, Lieberman MA, Golant M, Greener JR, Davey A (2014) Comparing standard versus prosocial internet support groups for patients with breast cancer: a randomized controlled trial of the helper therapy principle. J Clin Oncol 32(36):4081–4086
Xu S, Markson C, Costello KL, Xing CY, Demissie K, Llanos AA (2016) Leveraging social media to promote public health knowledge: example of Cancer awareness via twitter. JMIR Public Health Surveill 2(1):e17
Brownson RC, Jacobs JA, Tabak RG, Hoehner CM, Stamatakis KA (2013) Designing for dissemination among public health researchers: findings from a national survey in the United States. Am J Public Health 103(9):1693–1699
Wilson PM, Petticrew M, Calnan MW, Nazareth I (2010) Disseminating research findings: what should researchers do? A systematic scoping review of conceptual frameworks. Implement Sci 5(1):91
Keller B, Labrique A, Jain KM, Pekosz A, Levine O (2014) Mind the gap: social media engagement by public health researchers. J Med Internet Res 16(1):e8
Farmer AD, Bruckner Holt CE, Cook MJ, Hearing SD (2009) Social networking sites: a novel portal for communication. Postgrad Med J 85(1007):455–459
Jain SH (2009) Practicing medicine in the age of Facebook. N Engl J Med 361(7):649–651
Merchant RM, Elmer S, Lurie N (2011) Integrating social media into emergency-preparedness efforts. N Engl J Med 365(4):289–291
Brownstein JS, Freifeld CC, Madoff LC (2009) Digital disease detection--harnessing the web for public health surveillance. N Engl J Med 360(21):2153–2155, 2157
Bakal G, Kavuluru R. On quantifying diffusion of health information on twitter. IEEE-EMBS International Conference on Biomedical and Health Informatics IEEE-EMBS International Conference on Biomedical and Health Informatics 2017;2017:485–488
Strecher VJ, McClure JB, Alexander GL et al (2008) Web-based smoking-cessation programs: results of a randomized trial. Am J Prev Med 34(5):373–381
Gibbons MC, Fleisher L, Slamon RE, Bass S, Kandadai V, Beck JR (2011) Exploring the potential of web 2.0 to address health disparities. J Health Commun 16(Suppl 1):77–89
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Allen, C.G., Roberts, M., Andersen, B. et al. Communication About Hereditary Cancers on Social Media: A Content Analysis of Tweets About Hereditary Breast and Ovarian Cancer and Lynch Syndrome. J Canc Educ 35, 131–137 (2020). https://doi.org/10.1007/s13187-018-1451-4
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DOI: https://doi.org/10.1007/s13187-018-1451-4