• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
Social media for early characterization of pandemic symptoms: A qualitative analysis of patient-reported COVID-19 experiences.社交媒体在大流行病症状早期特征描述中的作用:一项基于患者报告的 COVID-19 体验的定性分析。
Pharmacoepidemiol Drug Saf. 2023 Mar;32(3):341-351. doi: 10.1002/pds.5564. Epub 2022 Nov 11.
2
Reddit Users' Experiences of Suicidal Thoughts During the COVID-19 Pandemic: A Qualitative Analysis of r/Covid19_support Posts.Reddit 用户在 COVID-19 大流行期间经历自杀念头:r/Covid19_support 帖子的定性分析。
Front Public Health. 2021 Aug 12;9:693153. doi: 10.3389/fpubh.2021.693153. eCollection 2021.
3
Sexually Transmitted Disease-Related Reddit Posts During the COVID-19 Pandemic: Latent Dirichlet Allocation Analysis.COVID-19 大流行期间与性传播疾病相关的 Reddit 帖子:潜在狄利克雷分配分析。
J Med Internet Res. 2022 Oct 31;24(10):e37258. doi: 10.2196/37258.
4
Disruptions in the Cystic Fibrosis Community's Experiences and Concerns During the COVID-19 Pandemic: Topic Modeling and Time Series Analysis of Reddit Comments.囊性纤维化社区在 COVID-19 大流行期间的经历和关注点的中断:Reddit 评论的主题建模和时间序列分析。
J Med Internet Res. 2023 Apr 20;25:e45249. doi: 10.2196/45249.
5
Tracking Self-reported Symptoms and Medical Conditions on Social Media During the COVID-19 Pandemic: Infodemiological Study.在 COVID-19 大流行期间在社交媒体上跟踪自我报告的症状和医疗状况:信息流行病学研究。
JMIR Public Health Surveill. 2021 Sep 28;7(9):e29413. doi: 10.2196/29413.
6
A qualitative content analysis of cannabis-related discussions on Reddit during the COVID-19 pandemic.对新冠疫情大流行期间 Reddit 上与大麻相关讨论的定性内容分析。
PLoS One. 2024 Jun 6;19(6):e0304336. doi: 10.1371/journal.pone.0304336. eCollection 2024.
7
Harnessing the Power of Social Media to Understand the Impact of COVID-19 on People Who Use Drugs During Lockdown and Social Distancing.利用社交媒体了解封锁和社交隔离期间吸毒者受 COVID-19 影响的情况。
J Addict Med. 2022;16(2):e123-e132. doi: 10.1097/ADM.0000000000000883.
8
Identifying Reddit Users at a High Risk of Suicide and Their Linguistic Features During the COVID-19 Pandemic: Growth-Based Trajectory Model.识别新冠疫情期间有高自杀风险的Reddit用户及其语言特征:基于增长的轨迹模型
J Med Internet Res. 2024 Aug 8;26:e48907. doi: 10.2196/48907.
9
Characterizing Social Media Messages Related to Underage JUUL E-Cigarette Buying and Selling: Cross-Sectional Analysis of Reddit Subreddits.描述与未成年人购买和销售JUUL电子烟相关的社交媒体信息:Reddit子版块的横断面分析
J Med Internet Res. 2020 Jul 20;22(7):e16962. doi: 10.2196/16962.
10
Using Social Media to Help Understand Patient-Reported Health Outcomes of Post-COVID-19 Condition: Natural Language Processing Approach.利用社交媒体帮助了解新冠后症状患者报告的健康结果:自然语言处理方法。
J Med Internet Res. 2023 Sep 19;25:e45767. doi: 10.2196/45767.

引用本文的文献

1
Evaluation of the Content Validity of the COVID-19 Symptoms Daily Diary.新型冠状病毒肺炎症状每日日记的内容效度评估
Patient Relat Outcome Meas. 2025 Jan 17;16:37-53. doi: 10.2147/PROM.S488914. eCollection 2025.
2
Identifying COVID-19 cases and extracting patient reported symptoms from Reddit using natural language processing.利用自然语言处理技术从 Reddit 上识别 COVID-19 病例并提取患者自述症状。
Sci Rep. 2023 Aug 22;13(1):13721. doi: 10.1038/s41598-023-39986-7.

社交媒体在大流行病症状早期特征描述中的作用:一项基于患者报告的 COVID-19 体验的定性分析。

Social media for early characterization of pandemic symptoms: A qualitative analysis of patient-reported COVID-19 experiences.

机构信息

Office of Medical Policy, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.

Office of Surveillance and Epidemiology, Center for Drug Evaluation and Research, Food and Drug Administration, Silver Spring, Maryland, USA.

出版信息

Pharmacoepidemiol Drug Saf. 2023 Mar;32(3):341-351. doi: 10.1002/pds.5564. Epub 2022 Nov 11.

DOI:10.1002/pds.5564
PMID:36333979
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9877633/
Abstract

BACKGROUND

Patients use social media forums to discuss their medical history and healthcare experiences, providing early insight into real-world patient experiences. We analyzed COVID-19 patient experiences from Reddit social media posts.

METHODS

We extracted Reddit Application Programming Interface data for the subreddit/COVID-19 positive from March to August 2020 and selected users tagged as "Tested Positive" or "Tested Positive- Me" flair and who posted at least thirty times in any calendar month, excluding users who explicitly stated location outside of the U.S. For tested-positive patients (users), we created and reviewed individual case profiles summarizing their COVID-19 symptoms, testing, and medications or treatments. Data were imported to Nvivo qualitative analysis software and qualitative coding was conducted.

FINDING

There were 31 759 posts and comments from 720 users in March to May 2020 (Q1) and 40 446 posts and comments from 1649 users from June to August 2020 (Q2). Final count of "Tested Positive" was 1296 users (280 in Q1 and 1016 in Q2). Across both quarters, frequently reported symptoms included sore throat, headaches, fevers, or chills. Loss of sense of smell or taste were reported by users in early March, prior to the inclusion of this symptom to the CDC list in April and GI-related symptoms and fatigue were reported in the March to May data, before they were added as a COVID-19 associated symptom in July 2020. Users also reported in-depth descriptions of their symptoms, motivations for testing, and long-term impacts such as post-viral fatigue.

INTERPRETATION

Social media data can potentially serve as an early surveillance data source in a pandemic and offer preliminary insights into patient disease experiences.

摘要

背景

患者在社交媒体论坛上讨论他们的病史和医疗保健经验,从而提供对现实世界患者体验的早期洞察。我们分析了 Reddit 社交媒体上与 COVID-19 相关的患者体验。

方法

我们从 2020 年 3 月至 8 月提取了 Reddit 应用程序接口数据,针对 subreddit/COVID-19 positive 选择标记为“Tested Positive”或“Tested Positive-Me”的用户,并选择至少在任何日历月内发布三十次以上的用户,不包括明确表示位置不在美国的用户。对于测试呈阳性的患者(用户),我们创建并审查了个人案例简介,总结了他们的 COVID-19 症状、检测结果以及药物或治疗方法。数据被导入到 Nvivo 定性分析软件中,并进行了定性编码。

发现

在 2020 年 3 月至 5 月(第 1 季度),有 31759 个帖子和评论来自 720 名用户,而在 2020 年 6 月至 8 月(第 2 季度),有 40446 个帖子和评论来自 1649 名用户。最终的“Tested Positive”用户数为 1296 名(第 1 季度 280 名,第 2 季度 1016 名)。在两个季度中,经常报告的症状包括喉咙痛、头痛、发烧或发冷。嗅觉或味觉丧失在 3 月初被用户报告,早于该症状在 4 月被纳入 CDC 清单,而与 GI 相关的症状和疲劳在 3 月至 5 月的数据中被报告,早于该症状在 2020 年 7 月被添加为 COVID-19 相关症状。用户还报告了他们症状的详细描述、检测的动机以及病毒后疲劳等长期影响。

解释

社交媒体数据有可能成为大流行期间的早期监测数据源,并提供对患者疾病体验的初步见解。