Abstract DPOC-005: #OVARIANCANCER: USING SOCIAL MEDIA TO FACILITATE HEALTH COMMUNICATION
Authors: Coffin Tara 
Published: June 2017

Abstract
PURPOSE: Current trends indicate an individual is likely to turn to their online social media accounts with questions about ovarian cancer, before talking to their physician. As access to the internet and social media continues to increase, so will this type of online health information seeking behavior, placing social media platforms like Twitter and Facebook in a unique position to facilitate health communication and improve access to health information. While improved access to health information has the capacity to benefit the individual, online health information is not without risk, with quality and accuracy often a point of concern. The dissemination of misinformation has the potential to do harm by misleading decision making or encouraging harmful health practices. With this risk–benefit balance in mind, this study seeks to gain a better understanding of what types of ovarian cancer information are exchanged over social media, while exploring how this information is shared. This knowledge may be used to inform health communication practices, providing insight into how social media can be used to disseminate quality, and timely, information about ovarian cancer prevention.
EXPERIMENTAL PROCEDURES: Using an infodemiological approach, we will collect tweets via a topic specific Twitter streaming Application Programming Interface (API), over a period of two to four weeks. Prior research suggests that this time frame will result in the collection of 500 to 2,000 tweets. Tweet selection will be based on a series of keywords related to ovarian cancer and ovarian cancer prevention. The resulting data will be compiled into a tweets corpus, and a random selection of tweets will be pulled from this corpus for further analysis. From there, we will perform a content analysis of the tweets, examining how ovarian cancer is mentioned, what, if any, information is being requested or provided via the tweet, while noting engagement (e.g. likes, shares, etc.). Finally, we will assess any use of imagery, graphics, videos, hashtags, calls to action, or external links. Publically available demographic information (including age, gender and ethnicity) will be noted, while maintaining user anonymity. We will use Pearson Chi–squared test to test for associations between the types of content, engagement, and demographic data.
SUMMARY OF DATA: Based on early data, we expect to see the public using Twitter frequently to share a variety of resources related to ovarian cancer prevention, including articles about health behaviors related to ovarian cancer risk, references to personal experience, and discussion of genetic test results. We anticipate that Tweets receiving high engagement will continue to feature graphics, trending hashtags, and a call to action, inviting user interaction. Early data also suggests that the quality and accuracy of health information shared over Twitter is inconsistent.
CONCLUSIONS: Early data reveals that Twitter is a fast, cost–effective, and customizable source for data collection, unveiling online health information seeking behaviors and associated health communication efforts. While there are lingering concerns regarding how keyword identification may impact data collection efforts, social media platforms like Twitter provide a novel opportunity to assess, and facilitate, the exchange of ovarian cancer information, particularly among Millennials. Given the potential reach of online health information via social media, alongside the suspect quality of many shared sources, further research is needed to learn more about guiding information consumption toward quality sources.
Citation Format: Tara Coffin, MEd. #OVARIANCANCER: USING SOCIAL MEDIA TO FACILITATE HEALTH COMMUNICATION [abstract]. In: Proceedings of the 11th Biennial Ovarian Cancer Research Symposium; Sep 12-13, 2016; Seattle, WA. Philadelphia (PA): AACR; Clin Cancer Res 2017;23(11 Suppl):Abstract nr DPOC-005.