解封网络疑病症:在线健康信息搜索、健康信息过载和健康误解的角色

IF 8.3 2区 管理学 Q1 INFORMATION SCIENCE & LIBRARY SCIENCE Telematics and Informatics Pub Date : 2025-02-01 Epub Date: 2024-12-09 DOI:10.1016/j.tele.2024.102225
Xiaoya Yang , Chen Luo , Yimeng Xu , Yifei He , Ruhan Zhao
{"title":"解封网络疑病症:在线健康信息搜索、健康信息过载和健康误解的角色","authors":"Xiaoya Yang ,&nbsp;Chen Luo ,&nbsp;Yimeng Xu ,&nbsp;Yifei He ,&nbsp;Ruhan Zhao","doi":"10.1016/j.tele.2024.102225","DOIUrl":null,"url":null,"abstract":"<div><div>Cyberchondria, the excessive search for health information online coupled with elevated health anxiety or concerns, has garnered growing scholarly attention recently. Anchored by the S-O-R (Stimulus-Organism-Response) model and information science literature, this study theorizes a pathway from online health information seeking via diverse sources (“S”) to cyberchondria (“R”) through health information overload and misperceptions (“O”). Structural equation modeling based on an online survey (<em>N</em> = 690) disclosed that health information overload was positively associated with searching for health information on online search engines and news media. Additionally, seeking health information from health-specific websites and online news media was positively tied to health misperceptions. Furthermore, increased health information overload was related to stronger health misperceptions, and they were both positively tied to cyberchondria. Theoretically, this study affords a more nuanced understanding of cyberchondria by zooming into the roles of seeking health information via different online sources. Besides, health misperceptions, as a relatively innovative predictor of cyberchondria, have been examined empirically. Practically, the findings furnish feasible strategies to optimize online platforms to mitigate the undesirable consequences of online health information consumption.</div></div>","PeriodicalId":48257,"journal":{"name":"Telematics and Informatics","volume":"97 ","pages":"Article 102225"},"PeriodicalIF":8.3000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Unpacking cyberchondria: The roles of online health information seeking, health information overload, and health misperceptions\",\"authors\":\"Xiaoya Yang ,&nbsp;Chen Luo ,&nbsp;Yimeng Xu ,&nbsp;Yifei He ,&nbsp;Ruhan Zhao\",\"doi\":\"10.1016/j.tele.2024.102225\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Cyberchondria, the excessive search for health information online coupled with elevated health anxiety or concerns, has garnered growing scholarly attention recently. Anchored by the S-O-R (Stimulus-Organism-Response) model and information science literature, this study theorizes a pathway from online health information seeking via diverse sources (“S”) to cyberchondria (“R”) through health information overload and misperceptions (“O”). Structural equation modeling based on an online survey (<em>N</em> = 690) disclosed that health information overload was positively associated with searching for health information on online search engines and news media. Additionally, seeking health information from health-specific websites and online news media was positively tied to health misperceptions. Furthermore, increased health information overload was related to stronger health misperceptions, and they were both positively tied to cyberchondria. Theoretically, this study affords a more nuanced understanding of cyberchondria by zooming into the roles of seeking health information via different online sources. Besides, health misperceptions, as a relatively innovative predictor of cyberchondria, have been examined empirically. Practically, the findings furnish feasible strategies to optimize online platforms to mitigate the undesirable consequences of online health information consumption.</div></div>\",\"PeriodicalId\":48257,\"journal\":{\"name\":\"Telematics and Informatics\",\"volume\":\"97 \",\"pages\":\"Article 102225\"},\"PeriodicalIF\":8.3000,\"publicationDate\":\"2025-02-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Telematics and Informatics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0736585324001291\",\"RegionNum\":2,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/12/9 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"INFORMATION SCIENCE & LIBRARY SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Telematics and Informatics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0736585324001291","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/9 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0

摘要

网络疑病症是指过度在网上搜索健康信息,同时伴有健康焦虑或担忧加剧的现象,最近引起了学术界越来越多的关注。本研究以S-O-R(刺激-有机体-反应)模型和信息科学文献为基础,从多种来源的在线健康信息搜索(“S”)到通过健康信息过载和误解(“O”)的网络疑病症(“R”)的途径进行了理论化。基于网络调查(N = 690)的结构方程模型显示,健康信息超载与在线搜索引擎和新闻媒体上的健康信息搜索呈正相关。此外,从健康网站和在线新闻媒体上寻求健康信息与健康误解呈正相关。此外,健康信息过载的增加与更强烈的健康误解有关,它们都与网络疑病症呈正相关。从理论上讲,这项研究通过放大到通过不同的在线资源寻求健康信息的角色,为网络疑病症提供了更细致入微的理解。此外,健康误解作为一种相对创新的网络疑病症预测因素,已经得到了实证检验。在实践中,研究结果为优化网络平台以减轻网络健康信息消费的不良后果提供了可行策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Unpacking cyberchondria: The roles of online health information seeking, health information overload, and health misperceptions
Cyberchondria, the excessive search for health information online coupled with elevated health anxiety or concerns, has garnered growing scholarly attention recently. Anchored by the S-O-R (Stimulus-Organism-Response) model and information science literature, this study theorizes a pathway from online health information seeking via diverse sources (“S”) to cyberchondria (“R”) through health information overload and misperceptions (“O”). Structural equation modeling based on an online survey (N = 690) disclosed that health information overload was positively associated with searching for health information on online search engines and news media. Additionally, seeking health information from health-specific websites and online news media was positively tied to health misperceptions. Furthermore, increased health information overload was related to stronger health misperceptions, and they were both positively tied to cyberchondria. Theoretically, this study affords a more nuanced understanding of cyberchondria by zooming into the roles of seeking health information via different online sources. Besides, health misperceptions, as a relatively innovative predictor of cyberchondria, have been examined empirically. Practically, the findings furnish feasible strategies to optimize online platforms to mitigate the undesirable consequences of online health information consumption.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Telematics and Informatics
Telematics and Informatics INFORMATION SCIENCE & LIBRARY SCIENCE-
CiteScore
17.00
自引率
4.70%
发文量
104
审稿时长
24 days
期刊介绍: Telematics and Informatics is an interdisciplinary journal that publishes cutting-edge theoretical and methodological research exploring the social, economic, geographic, political, and cultural impacts of digital technologies. It covers various application areas, such as smart cities, sensors, information fusion, digital society, IoT, cyber-physical technologies, privacy, knowledge management, distributed work, emergency response, mobile communications, health informatics, social media's psychosocial effects, ICT for sustainable development, blockchain, e-commerce, and e-government.
期刊最新文献
Assessing the impact of digital equity initiatives and government policies on university access, student achievement, and retention in low-income countries Unequal AI readiness: institutional and digital disparities in e-government across the European Union Three models of big data governance: A comparative analysis of privacy policies of contact tracing apps in China, Singapore, and Germany Development and application of the Masculinity Content Classification Framework Does hate attract likes? Offensive language and audience engagement in partisan YouTube videos
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1