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Disruptions in the Cystic Fibrosis Community’s Experiences and Concerns During the COVID-19 Pandemic: Topic Modeling and Time Series Analysis of Reddit Comments
http://hdl.handle.net/10061/0002000422
http://hdl.handle.net/10061/0002000422da1a8487-b8d0-470d-9539-3946a562c187
| アイテムタイプ | 学術雑誌論文 / Journal Article(1) | |||||||||||
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| 公開日 | 2024-05-23 | |||||||||||
| タイトル | ||||||||||||
| タイトル | Disruptions in the Cystic Fibrosis Community’s Experiences and Concerns During the COVID-19 Pandemic: Topic Modeling and Time Series Analysis of Reddit Comments | |||||||||||
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| 言語 | eng | |||||||||||
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| 主題Scheme | Other | |||||||||||
| 主題 | COVID-19 | |||||||||||
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| 主題Scheme | Other | |||||||||||
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| 主題Scheme | Other | |||||||||||
| 主題 | time series analysis | |||||||||||
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| 主題Scheme | Other | |||||||||||
| 主題 | BERTopic | |||||||||||
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| 主題Scheme | Other | |||||||||||
| 主題 | topic modeling | |||||||||||
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| 主題Scheme | Other | |||||||||||
| 主題 | cystic fibrosis | |||||||||||
| 資源タイプ | ||||||||||||
| 資源タイプ | journal article | |||||||||||
| アクセス権 | ||||||||||||
| アクセス権 | open access | |||||||||||
| 著者 |
Yao, Lean Franzl
× Yao, Lean Franzl
× Ferawati, Kiki
× Liew, Kongmeng
× 若宮, 翔子× 荒牧, 英治 |
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| 抄録 | ||||||||||||
| 内容記述タイプ | Abstract | |||||||||||
| 内容記述 | Background: The COVID-19 pandemic disrupted the needs and concerns of the cystic fibrosis community. Patients with cystic fibrosis were particularly vulnerable during the pandemic due to overlapping symptoms in addition to the challenges patients with rare diseases face, such as the need for constant medical aid and limited information regarding their disease or treatments. Even before the pandemic, patients vocalized these concerns on social media platforms like Reddit and formed communities and networks to share insight and information. This data can be used as a quick and efficient source of information about the experiences and concerns of patients with cystic fibrosis in contrast to traditional survey- or clinical-based methods. Objective: This study applies topic modeling and time series analysis to identify the disruption caused by the COVID-19 pandemic and its impact on the cystic fibrosis community’s experiences and concerns. This study illustrates the utility of social media data in gaining insight into the experiences and concerns of patients with rare diseases. Methods: We collected comments from the subreddit r/CysticFibrosis to represent the experiences and concerns of the cystic fibrosis community. The comments were preprocessed before being used to train the BERTopic model to assign each comment to a topic. The number of comments and active users for each data set was aggregated monthly per topic and then fitted with an autoregressive integrated moving average (ARIMA) model to study the trends in activity. To verify the disruption in trends during the COVID-19 pandemic, we assigned a dummy variable in the model where a value of “1” was assigned to months in 2020 and “0” otherwise and tested for its statistical significance. Results: A total of 120,738 comments from 5827 users were collected from March 24, 2011, until August 31, 2022. We found 22 topics representing the cystic fibrosis community’s experiences and concerns. Our time series analysis showed that for 9 topics, the COVID-19 pandemic was a statistically significant event that disrupted the trends in user activity. Of the 9 topics, only 1 showed significantly increased activity during this period, while the other 8 showed decreased activity. This mixture of increased and decreased activity for these topics indicates a shift in attention or focus on discussion topics during this period. Conclusions: There was a disruption in the experiences and concerns the cystic fibrosis community faced during the COVID-19 pandemic. By studying social media data, we were able to quickly and efficiently study the impact on the lived experiences and daily struggles of patients with cystic fibrosis. This study shows how social media data can be used as an alternative source of information to gain insight into the needs of patients with rare diseases and how external factors disrupt them. |
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| 書誌情報 |
en : Journal of Medical Internet Research 巻 25, 発行日 2023-04-20 |
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| 出版者 | JMIR Publications | |||||||||||
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| 収録物識別子タイプ | EISSN | |||||||||||
| 収録物識別子 | 1438-8871 | |||||||||||
| 出版者版DOI | ||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||
| 識別子タイプ | DOI | |||||||||||
| 関連識別子 | https://doi.org/10.2196/45249 | |||||||||||
| 出版者版URI | ||||||||||||
| 関連タイプ | isReplacedBy | |||||||||||
| 識別子タイプ | URI | |||||||||||
| 関連識別子 | https://www.jmir.org/2023/1/e45249/ | |||||||||||
| 権利 | ||||||||||||
| 権利情報Resource | https://creativecommons.org/licenses/by/4.0/ | |||||||||||
| 権利情報 | $00A9Lean Franzl Yao, Kiki Ferawati, Kongmeng Liew, Shoko Wakamiya, Eiji Aramaki. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 20.04.2023. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included. | |||||||||||
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| 出版タイプ | NA | |||||||||||
