Tweets by People With Arthritis During the COVID-19 Pandemic : Content and Sentiment Analysis
©Danielle Berkovic, Ilana Ackerman, Andrew M Briggs, Darshini Ayton. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 03.12.2020..
BACKGROUND: Emerging evidence suggests that people with arthritis are reporting increased physical pain and psychological distress during the COVID-19 pandemic. At the same time, Twitter's daily usage has surged by 23% throughout the pandemic period, presenting a unique opportunity to assess the content and sentiment of tweets. Individuals with arthritis use Twitter to communicate with peers, and to receive up-to-date information from health professionals and services about novel therapies and management techniques.
OBJECTIVE: The aim of this research was to identify proxy topics of importance for individuals with arthritis during the COVID-19 pandemic, and to explore the emotional context of tweets by people with arthritis during the early phase of the pandemic.
METHODS: From March 20 to April 20, 2020, publicly available tweets posted in English and with hashtag combinations related to arthritis and COVID-19 were extracted retrospectively from Twitter. Content analysis was used to identify common themes within tweets, and sentiment analysis was used to examine positive and negative emotions in themes to understand the COVID-19 experiences of people with arthritis.
RESULTS: In total, 149 tweets were analyzed. The majority of tweeters were female and were from the United States. Tweeters reported a range of arthritis conditions, including rheumatoid arthritis, systemic lupus erythematosus, and psoriatic arthritis. Seven themes were identified: health care experiences, personal stories, links to relevant blogs, discussion of arthritis-related symptoms, advice sharing, messages of positivity, and stay-at-home messaging. Sentiment analysis demonstrated marked anxiety around medication shortages, increased physical symptom burden, and strong desire for trustworthy information and emotional connection.
CONCLUSIONS: Tweets by people with arthritis highlight the multitude of concurrent concerns during the COVID-19 pandemic. Understanding these concerns, which include heightened physical and psychological symptoms in the context of treatment misinformation, may assist clinicians to provide person-centered care during this time of great health uncertainty.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2020 |
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| Erschienen: |
2020 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:22 |
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| Enthalten in: |
Journal of medical Internet research - 22(2020), 12 vom: 03. Dez., Seite e24550 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Berkovic, Danielle [VerfasserIn] |
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| Links: |
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| Themen: |
Arthritis |
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| Anmerkungen: |
Date Completed 09.12.2020 Date Revised 30.03.2024 published: Electronic Citation Status MEDLINE |
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| doi: |
10.2196/24550 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
NLM317384708 |
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| 100 | 1 | |a Berkovic, Danielle |e verfasserin |4 aut | |
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| 500 | |a Date Revised 30.03.2024 | ||
| 500 | |a published: Electronic | ||
| 500 | |a Citation Status MEDLINE | ||
| 520 | |a ©Danielle Berkovic, Ilana Ackerman, Andrew M Briggs, Darshini Ayton. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 03.12.2020. | ||
| 520 | |a BACKGROUND: Emerging evidence suggests that people with arthritis are reporting increased physical pain and psychological distress during the COVID-19 pandemic. At the same time, Twitter's daily usage has surged by 23% throughout the pandemic period, presenting a unique opportunity to assess the content and sentiment of tweets. Individuals with arthritis use Twitter to communicate with peers, and to receive up-to-date information from health professionals and services about novel therapies and management techniques | ||
| 520 | |a OBJECTIVE: The aim of this research was to identify proxy topics of importance for individuals with arthritis during the COVID-19 pandemic, and to explore the emotional context of tweets by people with arthritis during the early phase of the pandemic | ||
| 520 | |a METHODS: From March 20 to April 20, 2020, publicly available tweets posted in English and with hashtag combinations related to arthritis and COVID-19 were extracted retrospectively from Twitter. Content analysis was used to identify common themes within tweets, and sentiment analysis was used to examine positive and negative emotions in themes to understand the COVID-19 experiences of people with arthritis | ||
| 520 | |a RESULTS: In total, 149 tweets were analyzed. The majority of tweeters were female and were from the United States. Tweeters reported a range of arthritis conditions, including rheumatoid arthritis, systemic lupus erythematosus, and psoriatic arthritis. Seven themes were identified: health care experiences, personal stories, links to relevant blogs, discussion of arthritis-related symptoms, advice sharing, messages of positivity, and stay-at-home messaging. Sentiment analysis demonstrated marked anxiety around medication shortages, increased physical symptom burden, and strong desire for trustworthy information and emotional connection | ||
| 520 | |a CONCLUSIONS: Tweets by people with arthritis highlight the multitude of concurrent concerns during the COVID-19 pandemic. Understanding these concerns, which include heightened physical and psychological symptoms in the context of treatment misinformation, may assist clinicians to provide person-centered care during this time of great health uncertainty | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a COVID-19 | |
| 650 | 4 | |a SARS-CoV-2 | |
| 650 | 4 | |a Twitter | |
| 650 | 4 | |a arthritis | |
| 650 | 4 | |a content analysis | |
| 650 | 4 | |a microblogging | |
| 650 | 4 | |a novel coronavirus | |
| 650 | 4 | |a sentiment analysis | |
| 650 | 4 | |a social media | |
| 700 | 1 | |a Ackerman, Ilana N |e verfasserin |4 aut | |
| 700 | 1 | |a Briggs, Andrew M |e verfasserin |4 aut | |
| 700 | 1 | |a Ayton, Darshini |e verfasserin |4 aut | |
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