Abstract: TH-OR47
#AskRenal: Use of an Automated Twitter Account to Crowdsource Nephrology Queries
Session Information
- Technology-Based Approaches in Nephrology
November 03, 2022 | Location: W308, Orange County Convention Center‚ West Building
Abstract Time: 05:51 PM - 06:00 PM
Category: Educational Research
- 900 Educational Research
Authors
- Teakell, Jade M., The University of Texas Health Science Center at Houston John P and Katherine G McGovern Medical School, Houston, Texas, United States
- Rosolowska, Alicja, Uniwersytet Medyczny w Bialymstoku, Bialystok, Poland
- Hiremath, Swapnil, University of Ottawa Faculty of Medicine, Ottawa, Ontario, Canada
- Sparks, Matthew A., Duke University, Durham, North Carolina, United States
- Lerma, Edgar V., University of Illinois Chicago, Chicago, Illinois, United States
- Topf, Joel M., Oakland University William Beaumont School of Medicine, Rochester, Michigan, United States
- Shah, Nikhil A., University of Alberta Faculty of Medicine & Dentistry, Edmonton, Alberta, Canada
Group or Team Name
- #NephJC
Background
Social media platforms are used in contemporary crowdsourcing, and Twitter is apt for reaching a large number of people with a common interest. Users, especially those with a small follower count may find it challenging to reach a large audience. #AskRenal was developed as a Twitter crowdsourcing tool to help users get answers to nephrology questions. We hypothesized that the #AskRenal hashtag could be used by anyone to receive helpful and timely responses to simple or complex nephrology questions posed on the social media platform.
Methods
A Twitter account @AskRenal, and an online Twitter bot that automatically retweeted any new tweets containing the hashtag #AskRenal were created. Using the Symplur Healthcare Hashtag tool, we extracted and analyzed public Twitter content containing the hashtag #AskRenal posted between Dec 2016 to Aug 2020. Tweets were excluded if they were duplicates, retweets, or if the tweet content was not the form of an original question. A group of 15 medical professionals reviewed #AskRenal tweets individually and a 10-question survey was completed for each one.
Results
During the study period, there were 17,704 tweets containing the hashtag #AskRenal and 3099 were included in the survey analysis. We found that 40% (1228/3099) of #AskRenal questions were posed by users with < 1000 followers and 9% (270/3099) were from students and trainees. The questions were spread across a wide range of nephrology topics. Over 75% (2386/3099) of the #AskRenal questions garnered a response, and answers came quickly with 69% (1644/2386) receiving a reply within 6 hours of posting. The reviewers found these responses to be helpful in answering the original questions 83% (1978/2386) of the time. The inclusion of hyperlinks and images in the reply was associated with a helpful answer (p < 0.001) and a higher follower count was not significantly associated with the probability of obtaining a helpful answer.
Conclusion
We demonstrated that a targeted hashtag and a dedicated Twitter account that retweets the hashtag automatically can be used to garner timely and helpful responses by a wide range of individuals, irrespective of follower count, seeking answers to nephrology questions.