RESEARCH PAPERS

Research on Social Media Users’ Correcting Health Misinformation Intention

  • Zhang Song ,
  • Chen Shudan ,
  • Chen Hao ,
  • Lü Tu
Expand
  • School of Business, Qingdao University, Qingdao 266071
Zhang Song,professor,PhD,postdoc,doctoral supervisor;Chen Shudan,master candidate;Chen Hao,professor,PhD,doctoral supervisor,corresponding author,E-mail:ch9569@qdu.edu.cn;Lü Tu,professor,PhD,master supervisor.

Received date: 2024-06-05

  Revised date: 2024-08-09

  Online published: 2025-03-24

Supported by

This work is supported by the National Social Science Fund of China project titled “Research on the Path and Countermeasures of Enhancing the Effectiveness of Digital Government Governance for Public Demand” (Grant No. 22CGL037).

Abstract

[Purpose/Significance] The rampant spread of false, inaccurate, or incomplete health information on social media can be detrimental to public health. As information recipients, the public promptly identifies and corrects such misinformation, which not only protects their well-being but also contributes to the construction of a healthy health information ecology. [Method/Process] Based on the situational theory of problem solving, this study integrated protection motivation theory and self-construal theory to develop a research model that explored the influence mechanisms of social media users’ intention to correct health misinformation from two aspects: self-correction and correcting others. By means of quasi-experimental method, four common health misinformation scenarios were meticulously designed for sports, first aid, disease and health care. A total of 677 online and offline questionnaires were collected on users’ cognition, appraisal and correction intention on health misinformation. The differences in correction intention among different scenarios and age groups were compared using one-way ANOVA. [Result/Conclusion] The results show that involvement recognition has significant positive effects on threat appraisal, situational motivation and coping appraisal, while problem cognition has significant positive effects on threat appraisal and situation motivation. Coping appraisal plays a mediating role between involvement recognition, constraint recognition, and situational motivation. Independent self-construal plays a positive role in moderating the relationship between situational motivation and self-correcting intention, while dependent self-construal plays a positive role in regulating the relationship between situational motivation and the intention to correct others. The results reveal the mechanism of correcting health misinformation of ordinary users, and provide suggestions for social media platforms to manage health misinformation according to different users’ psychological characteristics.

Cite this article

Zhang Song , Chen Shudan , Chen Hao , Lü Tu . Research on Social Media Users’ Correcting Health Misinformation Intention[J]. Library and Information Service, 2025 , 69(7) : 67 -79 . DOI: 10.13266/j.issn.0252-3116.2025.07.006

References

[1] 朱庆华, 陈琼, 陆冬梅, 等. 互联网环境下失真健康信息研究 进展 [J]. 情报 学报, 2023, 42(9): 1125-1138. (ZHU Q H, CHEN Q, LU D M, et al. Research on health disinformation on the internet [J]. Journal of the China Society for Scientific and Technical Information, 2023, 42(9): 1125-1138.)
[2] BAUTISTA J R, ZHANG Y, GWIZDKA J. Predicting healthcare professionals’ intention to correct health misinformation on social media[J]. Telematics and informatics, 2022, 73: 101864.
[3] 朱宏淼, 莫雨桐, 齐佳音. 医联网失真健康信息的三维审视:内涵与成因· 特征与分类· 识别与治理[J]. 北京交通大学学报(社会科学版), 2023, 22(4): 100-110. (ZHU H M, MO Y T, QI J Y. Three-dimensional analysis of health disinformation in the internet of healthcare system: connotation and causes, characteristics and classification, identification and governance [J]. Journal of Beijing Jiaotong University (social sciences edition), 2023, 22(4): 100-110.)
[4] KHAN M L, IDRIS I K. Recognise misinformation and verify before sharing: a reasoned action and information literacy perspective[J]. Behaviour & information technology, 2019, 38(12): 1194-1212.
[5] VRAGA E K, BODE L. Using expert sources to correct health misinformation in social media[J]. Science communication, 2017, 39(5): 621-645.
[6] BAUTISTA J R, ZHANG Y, GWIZDKA J. Healthcare professionals’ acts of correcting health misinformation on social media[J]. International journal of medical informatics, 2021, 148: 104375.
[7] KOO A Z X, SU M H, LEE S, et al. What motivates people to correct misinformation? Examining the effects of third-person perceptions and perceived norms[J]. Journal of broadcasting & electronic media, 2021, 65(1): 111-134.
[8] CHEN L, FU L. Let's fight the infodemic: the third-person effect process of misinformation during public health emergencies[J]. Internet research, 2022, 32(4): 1357-1377.
[9] CHAO F, WANG X, YU G. Determinants of debunking information sharing behaviour in social media users: perspective of persuasive cues[J]. Internet research, 2024, 34(5): 1545-1576.
[10] SUN M, MA X. Combating health misinformation on social media through fact-checking: the effect of threat appraisal, coping appraisal, and empathy[J]. Telematics and informatics, 2023, 84: 102031.
[11] 王雪宁, 董庆兴, 宋志君, 等. 社交媒体上的错误信息防控研究述评[J]. 信息资源管理学报, 2022, 12(5): 102-113. (WANG X N, DONG Q X, SONG Z J, et al. Misinformation prevention and control on social media: a systematic review [J]. Journal of information resources management, 2022, 12(5): 102-113.)
[12] AI-JEFRI M M, EVANS R, GHEZZI P, et al. Using machine learning for automatic identification of evidence-based health information on the web[C]//Proceedings of the 2017 international conference on digital health. London: ACM, 2017: 167-174.
[13] 王雷, 宋士杰, 朱庆华. 基于微信公众号文章的失真健康信息识别方法比较与优化[J]. 情报学报, 2023, 42(2): 127-135. (WANG L, SONG S J, ZHU Q H. Comparison and improvement of health misinformation identification methods in WeChat official account articles [J]. Journal of the China Society for Scientific and Technical Information, 2023, 42(2): 127-135.)
[14] KUMARI R, ASHOK N, GHOSAL T, et al. What the fake? Probing misinformation detection standing on the shoulder of novelty and emotion[J]. Information processing & management, 2022, 59(1): 102740.
[15] SICILIA R, GIUDICE S L, PEI Y, et al. Twitter rumour detection in the health domain[J]. Expert systems with applications, 2018, 110: 33-40.
[16] LEWANDOWSKY S, ECKER U K H, SEIFERT C M, et al. Misinformation and its correction: continued influence and successful debiasing[J]. Psychological science in the public interest, 2012, 13(3): 106-131.
[17] 曹坡, 赵思莹, 刘蕤. 信息来源可信度调节下的纠正类健康信息逆火效应作用机制研究—— 基于受控实验的探索[J]. 图书情报工作, 2024, 68(6): 48-59. (CAO P, ZHAO S Y, LIU R. Research on the backfire effect of corrective health information under the information source credibility: a study of controlled experiments [J]. Library and information service, 2024, 68(6): 48-59.)
[18] PAL A, CHUA A Y K, GOH D H L. How do users respond to online rumor rebuttals?[J]. Computers in human behavior, 2020, 106: 106243.
[19] WALTER N, TUKACHINSKY R. A meta-analytic examination of the continued influence of misinformation in the face of correction: how powerful is it, why does it happen, and how to stop it?[J]. Communication research, 2020, 47(2): 155-177.
[20] 曹坡, 梁悦悦, 刘蕤. 信息疫情背景下公众的纠正类健康信息采纳意愿研究—— 基于SEM与fsQCA方法[J]. 现代情报, 2022, 42(12): 83-95. (CAO P, LIANG Y Y, LIU R. Exploring the cognitive factors of corrective health information adoption intention in infodemic using SEM and fsQCA [J]. Journal of modern information, 2022, 42(12): 83-95.)
[21] ZHANG Y, GUO B, DING Y, et al. Investigation of the determinants for misinformation correction effectiveness on social media during COVID-19 pandemic[J]. Information processing & management, 2022, 59(3): 102935.
[22] BODE L, VRAGA E K. See something, say something: correction of global health misinformation on social media[J]. Health communication, 2018, 33(9): 1131-1140.
[23] VRAGA E K, KIM S C, COOK J, et al. Testing the effectiveness of correction placement and type on Instagram[J]. The international journal of press/politics, 2020, 25(4): 632-652.
[24] SWIRE B, ECKER U K H, LEWANDOWSKY S. The role of familiarity in correcting inaccurate information[J]. Journal of experimental psychology: learning, memory, and cognition, 2017, 43(12): 1948-1961.
[25] CONNOR DESAI S, REIMERS S. Comparing the use of open and closed questions for Web-based measures of the continuedinfluence effect[J]. Behavior research methods, 2019, 51: 1426-1440.
[26] OKTAVIANUS J, BAUTISTA J R. Motivating healthcare professionals to correct online health misinformation: the roles of subjective norm, third-person perception, and channel differences[J]. Computers in human behavior, 2023, 147: 107839.
[27] DAVISON W P. The third-person effect in communication[J]. Public opinion quarterly, 1983, 47(1): 1-15.
[28] KIM J N, GRUNIG J E. Problem solving and communicative action: a situational theory of problem solving[J]. Journal of communication, 2011, 61(1): 120-149.
[29] 郭路生, 廖丽芳, 胡佳琪. 社交媒体用户健康信息传播行为的影响机制研究——基于风险认知与问题解决情境理论[J]. 现代情报, 2020, 40(3): 148-156. (GUO L S, LIAO L F, HU J Q. Research on the influence mechanism of health information communication behavior of social media users: based on risk perception theory and the problem solving situation theory [J]. Journal of modern information, 2010, 40(3): 148-156.)
[30] TAO W, LI J Y, LEE Y, et al. Individual and collective coping with racial discrimination: what drives social media activism among Asian Americans during the COVID-19 outbreak[J]. New media & society, 2024, 26(6): 3168-3187.
[31] LEE Y, TAO W, LI J Y Q. Motivations of online and offline activism against racism and xenophobia among Asian-American publics during the COVID-19 pandemic[J]. Telematics and informatics, 2022, 67: 101751.
[32] WANG J, LIU-LASTRES B, RITCHIE B W, et al. Travellers' self-protections against health risks: an application of the full Protection Motivation Theory[J]. Annals of tourism research, 2019, 78: 102743.
[33] ROGERS R W. A protection motivation theory of fear appeals and attitude change1[J]. The journal of psychology, 1975, 91(1): 93-114.
[34] FLOYD D L, PRENTICE-DUNN S, ROGERS R W. A metaanalysis of research on protection motivation theory[J]. Journal of applied social psychology, 2000, 30(2): 407-429.
[35] CHEN H, YUAN Y. The impact of ignorance and bias on information security protection motivation: a case of e-waste handling[J]. Internet research, 2022, 33(6): 2244-2275.
[36] AGRAWAL N, MAHESWARAN D. The effects of self-construal and commitment on persuasion[J]. Journal of consumer research, 2005, 31(4): 841-849.
[37] WANG Y, MA S S, LI D. Customer participation in virtual brand communities: The self-construal perspective[J]. Information & management, 2015, 52(5): 577-587.
[38] LUAN J, FILIERI R, XIAO J, et al. Product information and green consumption: an integrated perspective of regulatory focus, self-construal, and temporal distance[J]. Information & management, 2023, 60(2): 103746.
[39] 宋士杰, 齐云飞, 赵宇翔, 等. 冲突性健康信息对用户健康信息搜寻的影响:基于不确定性视角的探究[J]. 图书情报工作, 2021, 65(11): 24-32. (SONG S J, QI Y F, ZHAO Y X, et al. The impact of conflicting health information in consumers’ health information seeking: an investigation of uncertainty[J]. Library and information service, 2021, 65(11): 24-32.)
[40] DOOTSON P, KULIGOWSKI E, GREER D A, et al. Consistent and conflicting information in floods and bushfires impact risk information seeking, risk perceptions, and protective action intentions[J]. International journal of disaster risk reduction, 2022, 70: 102774.
[41] DE AVILA BATISTA G, JÚNIOR P D M. (Mis) Perception of environmental laws: modeling challenges based on information source preferences[J]. Environmental impact assessment review, 2023, 103: 107244.
[42] LIANG X, GUO G, LI S, et al. COVID-19-related information seeking and individual's rumor refuting: a multi-informationsource perspective[J]. Computers in human behavior, 2022, 134: 107342.
[43] S U N Y. Verification up on exposure to COVID-19 misinformation: predictors, outcomes, and the mediating role of verification[J]. Science communication, 2022, 44(3): 261-291.
[44] MURRAY G, WILLER C J, ARNER T, et al. Contextualized knowledge reduces misconceived COVID-19 health decisions[J]. Journal of applied research in memory and cognition, 2021, 10(3): 381-391.
[45] LI Y, FAN Z, YUAN X, ZHANG X. Recognizing fake information through a developed feature scheme: a user study of health misinformation on social media in China[J]. Information processing & management, 2022, 59(1): 102769.
[46] JOHNSTON A C, WARKENTIN M, SIPONEN M. An enhanced fear appeal rhetorical framework[J]. MIS quarterly, 2015, 39(1): 113-134.
[47] HUANG X, DAI S, XU H. Predicting tourists' health risk preventative behaviour and travelling satisfaction in Tibet: combining the theory of planned behaviour and health belief model[J]. Tourism management perspectives, 2020, 33: 100589.
[48] SO J, KUANG K, CHO H. Information seeking upon exposure to risk messages: predictors, outcomes, and mediating roles of health information seeking[J]. Communication research, 2019, 46(5): 663-687.
[49] CHEN A, LU Y. Protective behavior in ride-sharing through the lens of protection motivation theory and usage situation theory[J]. International journal of information management, 2021, 61: 102402.
[50] SCHUETZ S W, SYKES T A, VENKATESH V. Combating COVID-19 fake news on social media through fact checking: antecedents and consequences[J]. European journal of information systems, 2021, 30(4): 376-388.
[51] CHENG Y, LUO Y. The presumed influence of digital misinformation: examining US public’s support for governmental restrictions versus corrective action in the COVID-19 pandemic[J]. Online information review, 2020, 45(4): 834-852.
[52] CAO X, LUO Z, QIU J, et al. Does ostracism impede Chinese tourist self-disclosure on WeChat? the perspective of social anxiety and self-construal[J]. Journal of hospitality and tourism management, 2022, 50: 178-187.
[53] JEBARAJAKIRTHY C, DAS M. How self-construal drives intention for status consumption: a moderated mediated mechanism[J]. Journal of retailing and consumer services, 2020, 55: 102065.
[54] KIM J, PARK E H, PARK Y S, et al. Prosocial rule breaking on health information security at healthcareorganisations in South Korea[J]. Information systems journal, 2022, 32(1): 164-191.
[55] LUAN J, FILIERI R, XIAO J, et al. Product information and green consumption: an integrated perspective of regulatory focus, self-construal, and temporal distance[J]. Information & management, 2023, 60(2): 103746.
[56] PAL A, CHUA A Y, GOH D H L. How do users respond to online rumor rebuttals?[J]. Computers in human behavior, 2020, 106: 106243.
[57] LUAN J, FILIERI R, XIAO J, et al. Product information and green consumption: an integrated perspective of regulatory focus, self-construal, and temporal distance[J]. Information & management, 2023, 60(2): 103746.
[58] JACOBSON J A, JI L J, DITTO P H, et al. The effects of culture and self-construal on responses to threatening health information[J]. Psychology & health, 2012, 27(10): 1194-1210.
[59] HAIR J F, RISHER J J, SARSTEDT M, et al. When to use and how to report the results of PLS-SEM[J]. European business review, 2019, 31(1): 2-24.
[60] HENSELER J, RINGLE C M, SARSTEDT M. A new criterion for assessing discriminant validity in variance-based structural equation modeling[J]. Journal of the academy of marketing science, 2015, 43: 115-135.
[61] MASON C H, PERREAULT JR W D. Collinearity, power, and interpretation of multiple regression analysis[J]. Journal of marketing research, 1991, 28(3): 268-280.
[62] TALWAR S, DHIR A, SINGH D, et al. Sharing of fake news on social media: application of the honeycomb framework and the third-person effect hypothesis[J]. Journal of retailing and consumer services, 2020, 57: 102197.
[63] 王烨娣, 席悦, 蒋玉石. 隐私显著性与互联网定向广告规避行为的非线性关系研究—— 基于感知威胁的中介作用[J]. 南开管理评论, 2023, 26(3): 135-147. (WANG Y D, XI Y, JIANG Y S. Research on the non-linear relationship between privacy salience and internet targeted advertising avoidance behavior: based on the mediating effect of perceived threat [J]. Nankai business review, 2023, 26(3): 135-147.)
[64] BHALLA A, DURHAM R L, Al-TABAA N, et al. The development and initial psychometric validation of the eHealth readiness scale[J]. Computers in human behavior, 2016, 65: 460-467.
[65] 宋士杰, 赵宇翔, 宋小康,等. 互联网环境下失真健康信息可信度判断的影响因素研究[J]. 中国图书馆学报, 2019, 45(4): 72-85. (SONG S J, ZHAO Y X, SONG X K, ZHU Q H, Investigating the influential factors of consumer's credibility judgment on health misinformation [J]. Journal of library science in China, 2019, 45(4): 72-85.)
[66] HAYES A F. Partial, conditional, and moderated mediation: quantification, inference, and interpretation[J]. Communication monographs, 2018, 85(1): 4-40.
[67] ZHANG L, SHAO Z, LI X, et al. Gamification and online impulse buying: the moderating effect of gender and age[J]. International journal of information management, 2021, 61: 102267.
Outlines

/

〈 〉