Cargando…

Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter

BACKGROUND: The widespread use of social media has made it easier for patients to access cancer information. However, a large amount of misinformation and harmful information that could negatively impact patients’ decision-making is also disseminated on social media platforms. OBJECTIVE: We aimed to...

Descripción completa

Detalles Bibliográficos
Autores principales: Kureyama, Nari, Terada, Mitsuo, Kusudo, Maho, Nozawa, Kazuki, Wanifuchi-Endo, Yumi, Fujita, Takashi, Asano, Tomoko, Kato, Akiko, Mori, Makiko, Horisawa, Nanae, Toyama, Tatsuya
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10512120/
https://www.ncbi.nlm.nih.gov/pubmed/37672310
http://dx.doi.org/10.2196/49452
_version_ 1785108293540118528
author Kureyama, Nari
Terada, Mitsuo
Kusudo, Maho
Nozawa, Kazuki
Wanifuchi-Endo, Yumi
Fujita, Takashi
Asano, Tomoko
Kato, Akiko
Mori, Makiko
Horisawa, Nanae
Toyama, Tatsuya
author_facet Kureyama, Nari
Terada, Mitsuo
Kusudo, Maho
Nozawa, Kazuki
Wanifuchi-Endo, Yumi
Fujita, Takashi
Asano, Tomoko
Kato, Akiko
Mori, Makiko
Horisawa, Nanae
Toyama, Tatsuya
author_sort Kureyama, Nari
collection PubMed
description BACKGROUND: The widespread use of social media has made it easier for patients to access cancer information. However, a large amount of misinformation and harmful information that could negatively impact patients’ decision-making is also disseminated on social media platforms. OBJECTIVE: We aimed to determine the actual amount of misinformation and harmful information as well as trends in the dissemination of cancer-related information on Twitter, a representative social media platform. Our findings can support decision-making among Japanese patients with cancer. METHODS: Using the Twitter app programming interface, we extracted tweets containing the term “cancer” in Japanese that were posted between August and September of 2022. The eligibility criteria were the cancer-related tweets with the following information: (1) reference to the occurrence or prognosis of cancer, (2) recommendation or nonrecommendation of actions, (3) reference to the course of cancer treatment or adverse events, (4) results of cancer research, and (5) other cancer-related knowledge and information. Finally, we selected the top 100 tweets with the highest number of “likes.” For each tweet, 2 independent reviewers evaluated whether the information was factual or misinformation, and whether it was harmful or safe with the reasons for the decisions on the misinformation and harmful tweets. Additionally, we examined the frequency of information dissemination using the number of retweets for the top 100 tweets and investigated trends in the dissemination of information. RESULTS: The extracted tweets totaled 69,875. Of the top 100 cancer-related tweets with the most “likes” that met the eligibility criteria, 44 (44%) contained misinformation, 31 (31%) contained harmful information, and 30 (30%) contained both misinformation and harmful information. Misinformation was described as Unproven (29/94, 40.4%), Disproven (19/94, 20.2%), Inappropriate application (4/94, 4.3%), Strength of evidence mischaracterized (14/94, 14.9%), Misleading (18/94, 18%), and Other misinformation (1/94, 1.1%). Harmful action was described as Harmful action (9/59, 15.2%), Harmful inaction (43/59, 72.9%), Harmful interactions (3/59, 5.1%), Economic harm (3/59, 5.1%), and Other harmful information (1/59, 1.7%). Harmful information was liked more often than safe information (median 95, IQR 43-1919 vs 75.0 IQR 43-10,747; P=.04). The median number of retweets for the leading 100 tweets was 13.5 (IQR 0-2197). Misinformation was retweeted significantly more often than factual information (median 29.0, IQR 0-502 vs 7.5, IQR 0-2197; P=.01); harmful information was also retweeted significantly more often than safe information (median 35.0, IQR 0-502 vs 8.0, IQR 0-2197; P=.002). CONCLUSIONS: It is evident that there is a prevalence of misinformation and harmful information related to cancer on Twitter in Japan and it is crucial to increase health literacy and awareness regarding this issue. Furthermore, we believe that it is important for government agencies and health care professionals to continue providing accurate medical information to support patients and their families in making informed decisions.
format Online
Article
Text
id pubmed-10512120
institution National Center for Biotechnology Information
language English
publishDate 2023
publisher JMIR Publications
record_format MEDLINE/PubMed
spelling pubmed-105121202023-09-22 Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter Kureyama, Nari Terada, Mitsuo Kusudo, Maho Nozawa, Kazuki Wanifuchi-Endo, Yumi Fujita, Takashi Asano, Tomoko Kato, Akiko Mori, Makiko Horisawa, Nanae Toyama, Tatsuya JMIR Form Res Original Paper BACKGROUND: The widespread use of social media has made it easier for patients to access cancer information. However, a large amount of misinformation and harmful information that could negatively impact patients’ decision-making is also disseminated on social media platforms. OBJECTIVE: We aimed to determine the actual amount of misinformation and harmful information as well as trends in the dissemination of cancer-related information on Twitter, a representative social media platform. Our findings can support decision-making among Japanese patients with cancer. METHODS: Using the Twitter app programming interface, we extracted tweets containing the term “cancer” in Japanese that were posted between August and September of 2022. The eligibility criteria were the cancer-related tweets with the following information: (1) reference to the occurrence or prognosis of cancer, (2) recommendation or nonrecommendation of actions, (3) reference to the course of cancer treatment or adverse events, (4) results of cancer research, and (5) other cancer-related knowledge and information. Finally, we selected the top 100 tweets with the highest number of “likes.” For each tweet, 2 independent reviewers evaluated whether the information was factual or misinformation, and whether it was harmful or safe with the reasons for the decisions on the misinformation and harmful tweets. Additionally, we examined the frequency of information dissemination using the number of retweets for the top 100 tweets and investigated trends in the dissemination of information. RESULTS: The extracted tweets totaled 69,875. Of the top 100 cancer-related tweets with the most “likes” that met the eligibility criteria, 44 (44%) contained misinformation, 31 (31%) contained harmful information, and 30 (30%) contained both misinformation and harmful information. Misinformation was described as Unproven (29/94, 40.4%), Disproven (19/94, 20.2%), Inappropriate application (4/94, 4.3%), Strength of evidence mischaracterized (14/94, 14.9%), Misleading (18/94, 18%), and Other misinformation (1/94, 1.1%). Harmful action was described as Harmful action (9/59, 15.2%), Harmful inaction (43/59, 72.9%), Harmful interactions (3/59, 5.1%), Economic harm (3/59, 5.1%), and Other harmful information (1/59, 1.7%). Harmful information was liked more often than safe information (median 95, IQR 43-1919 vs 75.0 IQR 43-10,747; P=.04). The median number of retweets for the leading 100 tweets was 13.5 (IQR 0-2197). Misinformation was retweeted significantly more often than factual information (median 29.0, IQR 0-502 vs 7.5, IQR 0-2197; P=.01); harmful information was also retweeted significantly more often than safe information (median 35.0, IQR 0-502 vs 8.0, IQR 0-2197; P=.002). CONCLUSIONS: It is evident that there is a prevalence of misinformation and harmful information related to cancer on Twitter in Japan and it is crucial to increase health literacy and awareness regarding this issue. Furthermore, we believe that it is important for government agencies and health care professionals to continue providing accurate medical information to support patients and their families in making informed decisions. JMIR Publications 2023-09-06 /pmc/articles/PMC10512120/ /pubmed/37672310 http://dx.doi.org/10.2196/49452 Text en ©Nari Kureyama, Mitsuo Terada, Maho Kusudo, Kazuki Nozawa, Yumi Wanifuchi-Endo, Takashi Fujita, Tomoko Asano, Akiko Kato, Makiko Mori, Nanae Horisawa, Tatsuya Toyama. Originally published in JMIR Formative Research (https://formative.jmir.org), 06.09.2023. https://creativecommons.org/licenses/by/4.0/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 JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Kureyama, Nari
Terada, Mitsuo
Kusudo, Maho
Nozawa, Kazuki
Wanifuchi-Endo, Yumi
Fujita, Takashi
Asano, Tomoko
Kato, Akiko
Mori, Makiko
Horisawa, Nanae
Toyama, Tatsuya
Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter
title Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter
title_full Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter
title_fullStr Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter
title_full_unstemmed Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter
title_short Fact-Checking Cancer Information on Social Media in Japan: Retrospective Study Using Twitter
title_sort fact-checking cancer information on social media in japan: retrospective study using twitter
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10512120/
https://www.ncbi.nlm.nih.gov/pubmed/37672310
http://dx.doi.org/10.2196/49452
work_keys_str_mv AT kureyamanari factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT teradamitsuo factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT kusudomaho factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT nozawakazuki factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT wanifuchiendoyumi factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT fujitatakashi factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT asanotomoko factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT katoakiko factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT morimakiko factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT horisawananae factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter
AT toyamatatsuya factcheckingcancerinformationonsocialmediainjapanretrospectivestudyusingtwitter