ArticleJMIR cancer2022
Twitter Conversations About Pancreatic Cancer by Health Care Providers and the General Public: Thematic Analysis.
Article in JMIR cancer, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed, 6 citations in OpenAlex.
- What are IBD Patients Talking About on Twitter? Using Natural Language Understanding to Investigate Patients' Tweets.SN computer science · 2023Article
- Scandinavian Nurses' Use of Social Media during the COVID-19 Pandemic-A Berger and Luckman Inspired Analysis of a Qualitative Interview Study.Healthcare (Basel, Switzerland) · 2022Article
Corrections and comments
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Authors and funding
8 authors at 8 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThere is a growing interest in the pattern of consumption of health-related information on social media platforms.
objectiveWe evaluated the content of discussions around pancreatic cancer on Twitter to identify subtopics of greatest interest to health care providers and the general public.
methodsWe used an online analytical tool (Creation Pinpoint) to quantify Twitter mentions (tweets and retweets) related to pancreatic cancer between January 2018 and December 2019. Keywords, hashtags, word combinations, and phrases were used to identify mentions. Health care provider profiles were identified using machine learning and then verified by a human analyst. Remaining user profiles were classified as belonging to the general public. Data from conversations were stratified qualitatively into 5 domains: (1) prevention, (2) survivorship, (3) treatment, (4) research, and (5) policy. We compared the themes of conversations initiated by health care providers and the general public and analyzed the impact of the Pancreatic Cancer Awareness Month and announcements by public figures of pancreatic cancer diagnoses on the overall volume of conversations.
resultsOut of 1,258,028 mentions of pancreatic cancer, 313,668 unique mentions were classified into the 5 domains. We found that health care providers most commonly discussed pancreatic cancer research (10,640/27,031 mentions, 39.4%), while the general public most commonly discussed treatment (154,484/307,449 mentions, 50.2%). Health care providers were found to be more likely to initiate conversations related to research (odds ratio [OR] 1.75, 95% CI 1.70-1.79, P<.001) and prevention (OR 1.49, 95% CI 1.41-1.57, P<.001) whereas the general public took the lead in the domains of treatment (OR 1.63, 95% CI 1.58-1.69, P<.001) and survivorship (OR 1.17, 95% CI 1.13-1.21, P<.001). Pancreatic Cancer Awareness Month did not increase the number of mentions by health care providers in any of the 5 domains, but general public mentions increased temporarily in all domains except prevention and policy. Health care provider mentions did not increase with announcements by public figures of pancreatic cancer diagnoses. After Alex Trebek, host of the television show Jeopardy, received his diagnosis, general public mentions of survivorship increased, while Justice Ruth Bader Ginsburg's diagnosis increased conversations on treatment.
conclusionsHealth care provider conversations on Twitter are not aligned with the general public. Pancreatic Cancer Awareness Month temporarily increased general public conversations about treatment, research, and survivorship, but not prevention or policy. Future studies are needed to understand how conversations on social media platforms can be leveraged to increase health care awareness among the general public.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.