Conversations and misconceptions about chemotherapy in Arabic tweets: Content analysis

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Abstract

Background: Although chemotherapy was first introduced for the treatment of cancer more than 60 years ago, the public understanding and acceptance of chemotherapy is still debatable. To the best of our knowledge, no study has assessed the conversations and misconceptions about chemotherapy as a treatment for cancer on social media platforms among the Arabic-speaking populations. Objective: The aim of this study was to assess the types of conversations and misconceptions that were shared on Twitter regarding chemotherapy as a treatment for cancer among the Arabic-speaking populations. Methods: All Arabic tweets containing any of the representative set of keywords related to chemotherapy and written between May 1, 2017 and October 31, 2017 were retrieved. A manual content analysis was performed to identify the categories of the users, general themes of the tweets, and the common misconceptions about chemotherapy. A chi-square test for independence with adjusted residuals was used to assess the significant associations between the categories of the users and the themes of the tweets. Results: A total of 402,157 tweets were retrieved, of which, we excluded 309,602 retweets and 62,651 irrelevant tweets. Therefore, 29,904 tweets were included in the final analysis. The majority of the tweets were posted by general users (25,774/29,904, 86.2%), followed by the relatives and friends of patients with cancer (1913/29,904, 6.4%). The tweets were classified into 9 themes; prayers and wishes for the well-being of patients undergoing chemotherapy was the most common theme (20,288/29,904, 67.8%), followed by misconceptions about chemotherapy (2084/29,904, 7.0%). There was a highly significant association between the category of the users and the themes of the tweets (χ240= 16904.4, P

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Alghamdi, A., Abumelha, K., Allarakia, J., & Al-Shehri, A. (2020). Conversations and misconceptions about chemotherapy in Arabic tweets: Content analysis. Journal of Medical Internet Research, 22(7). https://doi.org/10.2196/13979

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