图书情报工作

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2025 , Vol. 69 >Issue 19: 74 - 86

DOI: https://doi.org/10.13266/j.issn.0252-3116.2025.19.007

研究论文

失真健康信息纠正对大学生信任修复及搜寻意愿的影响研究

  • 赵泽瑞 ,
  • 徐孝娟 ,
  • 罗亚玲 ,
  • 赵悦言
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  • 1四川大学公共管理学院 成都 610065;
    2安徽大学管理学院 合肥 230039
赵泽瑞，博士研究生；徐孝娟，副教授，博士，通信作者，E-mail：xxjksks@126.com；罗亚玲，教授，博士生导师；赵悦言，博士研究生。

收稿日期: 2024-08-28

  修回日期: 2024-12-19

  网络出版日期: 2025-09-12

基金资助

本文系国家社会科学基金项目“数字社会背景下我国老年人信息失能治理研究”（项目编号：21BSH109）研究成果之一。

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Investigating the Influence of Correcting Health Misinformation on Trust Repair and Information-Seeking Intentions in College Students

  • Zhao Zerui ,
  • Xu Xiaojuan ,
  • Luo Yaling ,
  • Zhao Yueyan
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  • 1 School of Public Administration, Sichuan University, Chengdu 610065;
    2 School of Management, Anhui University, Hefei 230039
Zhao Zerui, Doctoral Candidate; Xu Xiaojuan, Associate Professor, PhD, Corresponding Author, E-mail: xxjksks@126.com; Luo Yaling, Professor, Doctoral Supervisor; Zhao Yueyan, Doctoral Candidate.

Received date: 2024-08-28

  Revised date: 2024-12-19

  Online published: 2025-09-12

Supported by

This work is supported by the project of National Social Science Fund of China, titled “Research on the Governance of Information Disability of the Elderly in China Under the Background of Digital Society” (Grant No. 21BSH109).

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摘要

[目的/意义] 社交媒体平台的开放性使大量失真健康信息滋生并迅速传播，探索失真健康信息纠正对大学生用户信任修复及搜寻意愿的影响机制，对降低失真健康信息负面影响、优化健康信息服务并重新赢得用户至关重要。[方法/过程] 以信任模型和自我验证理论为基础，分别针对社交性纠正和算法性纠正设计情景实验并收集数据，利用非参数检验、结构方程模型和Bootstrap检验变量间的主效应、中介效应和调节效应关系。[结果/结论] 信任修复正向影响健康信息搜寻意愿；社交性纠正与算法性纠正能有效修复大学生用户信任，认知验证与情感认证在其间发挥了不同的中介效应；社交性纠正强调情感认证的主导地位，算法性纠正强调认知验证的主导地位；数字健康素养负向调节了算法性纠正对认知验证的影响。研究能够丰富失真健康信息情境下大学生用户信任修复的理论基础，并为社交媒体平台失真健康治理提供新的见解。

关键词： 失真健康信息; 信任修复; 自我验证理论

本文引用格式

赵泽瑞 , 徐孝娟 , 罗亚玲 , 赵悦言 . 失真健康信息纠正对大学生信任修复及搜寻意愿的影响研究[J]. 图书情报工作, 2025 , 69(19) : 74 -86 . DOI: 10.13266/j.issn.0252-3116.2025.19.007

Abstract

[Purpose/Significance] The openness of social media platforms has facilitated the emergence and rapid spread of a large amount of health misinformation. Investigating the mechanisms by which the correction of health misinformation affects the trust repair and information-seeking intentions of college student users is essential for reducing the negative effects of such information, optimizing health information services, and regaining the trust of users. [Method/Process] Based on trust theory and self-validation theory, scenario experiments were designed for social corrections and algorithmic corrections, and data were collected through surveys. Non-parametric tests, structural equation modeling, and Bootstrap methods were employed to examine the relationships between main effects, mediating effects, and moderating effects among variables. [Result/Conclusion] Trust repair positively influences the willingness to seek health information. Social corrections and algorithmic corrections can effectively restore the trust of college students, with cognitive validation and affective validation playing distinct mediating roles. Social corrections emphasize the predominance of affective validation, while algorithmic corrections highlight the predominance of cognitive validation. Additionally, digital health literacy negatively moderates the influence of algorithmic correction on cognitive validation. This research enriches the theoretical foundation for trust repair of college students in the context of health misinformation and offers new insights into the management of health misinformation on social media platforms.

Key words： health misinformation; trust repair; self-validation theory

参考文献

[1] BASCH C H, HILLYER G C, FRIEDMAN A, et al. Health information seeking behavior among college students[J]. Journal of community health, 2018, 43(6):1094-1099.
[2] ZHANG S Y, ZHOU H, ZHU Y M. Have we found a solution for health misinformation?A ten-year systematic review of health misinformation literature 2013-2022[J]. International journal of medical informatics, 2024, 188(8):105478.
[3] PALVIA P. The role of trust in e-commerce relational exchange:a unified model[J]. Information & management, 2009, 46(4):213-220.
[4] EWICKI R J, BUNKER B B. Developing and maintaining trust in work relationships[C]//KRAMER R M, TYLER T R. Trust in organizations:frontiers of theory and research. Thousand Oaks:Sage, 1996:114-139.
[5] 韩平,宁吉.基于两种信任违背类型的信任修复策略研究[J].管理学报, 2013, 10(3):390-396.(HAN P, NING J. Trust repair strategy based on two types of trust violation[J]. Chinese journal of management, 2013, 10(3):390-396.)
[6] CHEN Y H, WU J J, CHANG H T. Examining the mediating effect of positive moods on trust repair in e‐commerce[J]. Internet research, 2013, 23(3):355-371.
[7] HUANG Y, WANG W R. When a story contradicts:correcting health misinformation on social media through different message formats and mechanisms[J]. Information, communication & society, 2022, 25(8):1192-1209.
[8] FERILING I, MATTHES J. Correcting climate change misinformation on social media:reciprocal relationships between correcting others, anger, and environmental activism[J]. Computers in human behavior, 2023, 145(4):107769.
[9] MARTEL C, RAND D G. Misinformation warning labels are widely effective:a review of warning effects and their moderating features[J]. Current opinion in psychology, 2023, 54(6):101710.
[10] 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.
[11] 段秋婷,张大伟,谢兴政.社交媒体隐私侵犯情境下的用户信任修复策略效果研究[J].图书馆学研究, 2022(3):75-86, 68.(DUAN Q T, ZHANG D W, XIE X Z. Research on the effect of user trust repair strategies in the context of social media privacy violation[J]. Research on library science, 2022(3):75-86, 68.)
[12] ESTERWOOD C, ROBERT JR L P. Three strikes and you are out!The impacts of multiple human-robot trust violations and repairs on robot trustworthiness[J]. Computers in human behavior, 2023, 142(3):107658.
[13] ZHANG N, GUO X, ZHANG L, et al. How to repair public trust effectively:research on enterprise online public opinion crisis response[J]. Electronic commerce research and applications, 2021, 49(5):101077.
[14] DE VISSER EJ, PAK R, SHAW T H. From'automation'to'autonomy':the importance of trust repair in human-machine interaction[J]. Ergonomics, 2018, 61(10):1409-1427.
[15] LONGONI C, BONEZZI A, MOREWEDGE C K. Resistance to medical artificial intelligence[J]. Journal of consumer research, 2019, 46(4):629-650.
[16] LIN T H, CHANG M C, CHANG C C. Government-sponsored disinformation and the severity of respiratory infection epidemics including COVID-19:a global analysis, 2001-2020[J]. Social science & medicine, 2022, 296(6):114744.
[17] 薛翔,马海云,赵宇翔,等.失真健康信息特征对社交媒体用户分享意愿影响机制研究[J].图书情报工作, 2024, 68(4):70-82.(XUE X, MA H Y, ZHAO Y X, et al. Investigating the influence of health misinformation features on users'sharing willingness in social media[J]. Library and information service, 2024, 68(4):70-82.)
[18] YANG J, TIAN Y. "Others are more vulnerable to fake news than I am" :third-person effect of COVID-19 fake news on social media users[J]. Computers in human behavior, 2021, 125(6):106950.
[19] 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.)
[20] 李新月,宋士杰,韩文婷,等.失真健康信息预先干预对个体感知与行为意愿影响的实证研究[J].信息资源管理学报, 2024, 14(1):44-54.(LI X Y, SONG S J, HAN W T, et al. An empirical study of the effects of a prebunking of health misinformation on individuals'perceptions and behavioral intentions[J]. Journal of information resources management, 2024, 14(1):44-54.)
[21] 喻梅,余诗雅,刘蕤.医护人员的社交媒体虚假健康信息纠正意图研究——基于SEM与fsQCA方法[J].信息资源管理学报, 2024, 14(3):104-120.(YU M, YU S Y, LIU R. Exploring the cognitive factors of healthcare professionals'health misinformation correcting intention on social media:using SEM and fsQCA[J]. Journal of information resources management, 2024, 14(3):104-120.)
[22] 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.)
[23] 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.)
[24] DEWULF A, GRAY B, PUTNAM L, et al. Disentangling approaches to framing in conflict and negotiation research:a meta-paradigmatic perspective[J]. Human relations, 2009, 62(2):155-193.
[25] 谢娟,王铮.命令性社会规范对社交媒体虚假信息纠正效果的影响研究[J].图书情报工作, 2024, 68(7):102-112.(XIE J, WANG Z. The influence of injunctive norm on the effect of misinformation correction[J]. Library and information service, 2024, 68(7):102-112.)
[26] JACOBS W, AMUTA A O, JEON K C. Health information seeking in the digital age:an analysis of health information seeking behavior among US adults[J]. Cogent social sciences, 2017, 3(1):1302785.
[27] LEWICKI R J, BRINSFIELD C. Trust repair[J]. Annual review of organizational psychology and organizational behavior, 2017, 4(1):287-313.
[28] LEWIS J D, WEIGERT A. Trust as a social reality[J]. Social forces, 1985, 63(4):967-985.
[29] SHAREEF M A, KUMAR V, KUMAR U, et al. Application of behavioral theory in predicting consumers adoption behavior[J]. Journal of information technology research, 2013, 6(4):36-54.
[30] BRINOL P, PETTY R E. Self-validation theory:an integrative framework for understanding when thoughts become consequential[J]. Psychological review, 2022, 129(22):340-367.
[31] JI H, DONG J, PAN W, et al. Associations between digital literacy, health literacy, and digital health behaviors among rural residents:evidence from Zhejiang, China[J]. International journal for equity in health, 2024, 23(1):68.
[32] VAN DER VAART R, DROSSAERT C. Development of the digital health literacy instrument:measuring a broad spectrum of health 1.0 and health 2.0 skills[J]. Journal of medical Internet research, 2017, 19(1):e27.
[33] STELLEFSON M, HANIK B, CHANEY B, et al. eHealth literacy among college students:a systematic review with implications for eHealth education[J]. Journal of medical Internet research, 2011, 13(4):e102.
[34] HANCOCK P A, BILLINGS D R, SCHAEFER K E, et al. A meta-analysis of factors affecting trust in human-robot interaction[J]. Human factors, 2011, 53(5):517-527.
[35] DIRKS K T, KIM P H, FERRIN D L, et al. Understanding the effects of substantive responses on trust following a transgression[J]. Organizational behavior and human decision processes, 2011, 114(2):87-103.
[36] VÁRÓN SANDOVAL A, GONZÁLEZ CALIXTO M B, RAMÍREZ SALAZAR M D. Colombia:innovation, trust and emotions during the COVID-19 pandemic[J]. Management research:journal of the Iberoamerican Academy of Management, 2021, 19(1):1-21.
[37] MCALLISTER D J. Affect-and cognition-based trust as foundations for interpersonal cooperation in organizations[J]. Academy of management journal, 1995, 38(1):24-59.
[38] GEFEN D, KARAHANNA E, STRAUB D W. Trust and tam in online shopping:an integrated model[J]. MIS quarterly, 2003, 27(1):51-90.
[39] XIAO N, SHARMA R, RAO H R, et al. Factors influencing online health information search:an empirical analysis of a national cancer-related survey[J]. Decision support systems, 2014, 57(1):417-427.
[40] LI Y B, WANG X Q. Seeking health information on social media:a perspective of trust, self-determination, and social support[J]. Journal of Organizational and End User Computing, 2018, 30(1):1-22.
[41] WANG X, WUJI S J, LIU Y, et al. Study on the impact of recommendation algorithms on user perceived stress and health management behaviour in short video platforms[J]. Information processing & management, 2024, 61(3):103674.
[42] LI H, LI L, GAN C, et al. Disentangling the factors driving users'continuance intention towards social media:a configurational perspective[J]. Computers in human behavior, 2018, 85(4):175-182.
[43] HADLEY M, PATIL U, COLVIN K F, et al. Exploring the impact of digital health literacy on COVID-19 behaviors in New York state college students during the COVID-19 pandemic[J]. Computer methods and programs in biomedicine update, 2023, 4(1):100126.
[44] ABDOH E. Online health information seeking and digital health literacy among information and learning resources undergraduate students[J]. The journal of academic librarianship, 2022, 48(6):102603.
[45] ALI A, QAZI I A. Countering misinformation on social media through educational interventions:evidence from a randomized experiment in Pakistan[J]. Journal of development economics, 2023, 163(6):103108.
[46] BEAK T H, KIM M. Is ChatGPT scary good?How user motivations affect creepiness and trust in generative artificial intelligence[J]. Telematics and informatics, 2023, 83(3):102030.
[47] 宋士杰,赵宇翔,宋小康,等.信息源对数字原住民健康信息可信度判断的启发式实验研究[J].情报学报, 2020, 39(4):399-408.(SONG S J, ZHAO Y X, SONG X K, et al. Impact of source selection on health information credibility judgment:a heuristic information processing experiment among digital natives[J]. Journal of the China Society for Scientific and Technical Information, 2020, 39(4):399-408.)
[48] WANG J, SHAHZAD F, ASHRAF S F. Elements of information ecosystems stimulating the online consumer behavior:a mediating role of cognitive and affective trust[J]. Telematics and informatics, 2023, 80(2):101970.
[49] 张蓓,吴宝姝,文晓巍.网络谣言社会共治对消费者信任的影响——以食品伤害为例[J].经济管理, 2019, 41(5):136-155.(ZHANG B, WU B S, WEN X W. Research the effects of the social co-governance of the internet rumors on consumer's trust:taking food harm as an example[J]. Business and management journal, 2019, 41(5):136-155.)
[50] ZHAO Y X, ZHAO M Y, SONG S J. Online health information seeking among patients with chronic conditions:integrating the health belief model and social support theory[J]. Journal of medical internet research, 2022, 24(11):e42447.
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