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社交媒体平台上关于抗生素耐药性的讨论:文本挖掘与混合方法内容分析研究

Discussions of Antibiotic Resistance on Social Media Platforms: Text Mining and Mixed Methods Content Analysis Study.

作者信息

Arquembourg Jocelyne, Glaser Philippe, Roblot France, Metzler Isabelle, Gallant-Dewavrin Mélanie, Nanguem Hugues Feutze, Mebarki Adel, Voillot Paméla, Schück Stéphane

机构信息

Laboratoire l3, Telecom Paris, Telecom Paris, Palaiseau, France.

Unité EERA Institut Pasteur, CNRS UMR3525, Université de Paris, Paris, France.

出版信息

JMIR Form Res. 2025 Apr 25;9:e37160. doi: 10.2196/37160.

DOI:10.2196/37160
PMID:40289322
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC12047853/
Abstract

BACKGROUND

With the increasing popularity of web 2.0 apps, social media has made it possible for individuals to post messages on antibiotic ineffectiveness. In such online conversations, patients discuss their quality of life (QoL). Social media have become key tools for finding and disseminating medical information.

OBJECTIVE

To identify the main themes of discussion, the difficulties encountered by patients with respect to antibiotic ineffectiveness and the impact on their QoL (physical, psychological, social, or financial).

METHODS

A noninterventional retrospective study was carried out by collecting social media posts in French language written by internet users mentioning their experience with antibiotics, and the impact of their ineffectiveness on their QoL. Messages posted between January 2014 and July 2020 were extracted from French-speaking publicly available online forums.

RESULTS

A total of 3773 messages were included in the analysis corpus after extraction and filtering. These messages were posted by 2335 individual web users, most of them being women around 35 years of age. Inefficacy of treatment options and the lack of information regarding the use of antibiotics were among the most discussed topics. QoL was discussed in 63% of the 3773 messages posted. The most common is the physical impact (78%). Patients discussed the persistence of symptoms and adverse effects. The second kind of impact is psychological (65%), characterized by feelings of anxiety or despair about the situation.

CONCLUSIONS

This social media analysis allowed us to identify a strong impact of the perceived ineffectiveness of antibiotic therapy on patients' daily life particularly in terms of physical and psychological consequences. These results provide health care experts information directly generated by patients regarding their own experiences. Social media studies constitute a complementary source of evidence that could be used to optimize messages to the public about appropriate use of antibiotics.

摘要

背景

随着网络2.0应用程序越来越受欢迎,社交媒体使个人能够发布关于抗生素无效的信息。在这类在线对话中,患者会讨论他们的生活质量(QoL)。社交媒体已成为查找和传播医学信息的关键工具。

目的

确定讨论的主要主题、患者在抗生素无效方面遇到的困难以及对其生活质量(身体、心理、社会或经济方面)的影响。

方法

通过收集互联网用户用法语撰写的社交媒体帖子开展一项非干预性回顾性研究,这些帖子提及了他们使用抗生素的经历以及抗生素无效对其生活质量的影响。从讲法语的公开在线论坛中提取了2014年1月至2020年7月期间发布的信息。

结果

经过提取和筛选,分析语料库共纳入3773条信息。这些信息由2335名个人网络用户发布,其中大多数是35岁左右的女性。治疗方案无效以及缺乏抗生素使用信息是讨论最多的话题。在3773条发布的信息中,63%讨论了生活质量。最常见的是身体影响(78%)。患者讨论了症状的持续和不良反应。第二种影响是心理方面的(65%),其特征是对这种情况感到焦虑或绝望。

结论

这项社交媒体分析使我们能够确定抗生素治疗效果不佳对患者日常生活有很大影响,尤其是在身体和心理方面。这些结果为医疗保健专家提供了患者直接提供的关于其自身经历的信息。社交媒体研究构成了一个补充证据来源,可用于优化向公众传达的关于合理使用抗生素的信息。

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本文引用的文献

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A New Method to Extract Health-Related Quality of Life Data From Social Media Testimonies: Algorithm Development and Validation.一种从社交媒体证词中提取健康相关生活质量数据的新方法:算法的开发和验证。
J Med Internet Res. 2022 Jan 28;24(1):e31528. doi: 10.2196/31528.
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Health intelligence: how artificial intelligence transforms population and personalized health.健康智能:人工智能如何改变群体与个性化健康。
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Web-Based Signal Detection Using Medical Forums Data in France: Comparative Analysis.
法国利用医学论坛数据进行的基于网络的信号检测:比较分析
J Med Internet Res. 2018 Nov 20;20(11):e10466. doi: 10.2196/10466.
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Filtering Entities to Optimize Identification of Adverse Drug Reaction From Social Media: How Can the Number of Words Between Entities in the Messages Help?筛选实体以优化从社交媒体中识别药物不良反应:消息中实体之间的单词数量有何帮助?
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