图书情报工作

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2025 , Vol. 69 >Issue 16: 116 - 127

DOI: https://doi.org/10.13266/j.issn.0252-3116.2025.16.010

研究论文

解释水平理论视角下失真健康信息可信度甄别的个体异质性研究

  • 宋士杰 ,
  • 宋小康 ,
  • 赵宇翔 ,
  • 朱庆华
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  • 1 河海大学商学院 南京 211100;
    2 武汉大学信息管理学院 武汉 430072;
    3 徐州医科大学管理学院 徐州 221004;
    4 南京大学信息管理学院 南京 210023
宋士杰，副教授，博士;宋小康，副教授，博士;赵宇翔，教授，博士，通信作者，E-mail:yxzhao@vip.163.com;朱庆华，教授，博士。

收稿日期: 2024-09-02

  修回日期: 2025-02-02

  网络出版日期: 2025-08-01

基金资助

本文系国家自然科学基金青年项目“社交媒体失真健康信息的特征识别与协同纠偏机制研究”（项目编号： 72204076）、国家自然科学基金面上项目“社交媒体环境下失真健康信息的传播机制与协同治理研究”（项目编号： 72174083）和江苏省社会科学基金青年项目“人智交互体验中AI生成内容的可信度评价研究”（项目编号： 23TQC005）研究成果之一。

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Construal Level Theory-Guided Investigation of Individual Heterogeneity in Credibility Judgment of Health Misinformation

  • Song Shijie ,
  • Song Xiaokang ,
  • Zhao Yuxiang ,
  • Zhu Qinghua
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  • 1 Business School, Hohai University, Nanjing 211100;
    2 School of Information Management, Wuhan University, Wuhan 430072;
    3 School of Management, Xuzhou Medical University, Xuzhou 221004;
    4 School of Information Management, Nanjing University, Nanjing 210023
Song Shijie, associate professor, PhD; Song Xiaokang, associate professor, PhD; Zhao Yuxiang, professor, PhD, corresponding author, E-mail: yxzhao@vip.163.com; Zhu Qinghua, professor, PhD.

Received date: 2024-09-02

  Revised date: 2025-02-02

  Online published: 2025-08-01

Supported by

This work is supported by the National Natural Science Foundation of China project titled “Features Detection and Collaborative Correction of Health Misinformation on Social Media” (Grant No. 72204076), the National Natural Science Foundation of China project titled “Research on the Diffusion Mechanism and Collaborative Governance of Health Misinformation in Social Media” (Grant No. 72174083), and the Social Science Foundation of Jiangsu Province project titled “Credibility Assessment of AI-generated Content in Human-AI Interactions” (Grant No.23TQC005).

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摘要

[目的/意义] 互联网失真健康信息泛滥引发信息可信度危机。失真健康信息误导用户的健康决策并引致不良健康后果，而有效降低真健康信息的危害需首先厘清为何用户会轻信失真健康信息之问题。研究基于解释水平理论及健康与科学素养视角探究失真健康信息可信度甄别的个体异质性。[方法/过程] 采用网络实验收集样本数据，397名被试分别完成10项失真健康信息可信度甄别任务，共生成3 970条有效数据。数据分析方面，使用多层混合效应Logistic模型估计个体异质性对失真健康信息可信度甄别的影响效果。[结果/结论] 人们甄别失真健康信息可信度时存在普遍的障碍，用户在可信度甄别上存在十分显著的个体差异。其中，用户与失真健康信息的心理距离与可信度甄别成功概率呈显著负相关；用户的科学信念、科学推理能力与失真健康信息可信度甄别呈显著正相关；而用户对替代医学的态度与可信度甄别成功概率呈显著负相关。

关键词： 失真健康信息; 解释水平理论; 心理距离; 可信度; 个体异质性; 多层混合效应模型

本文引用格式

宋士杰 , 宋小康 , 赵宇翔 , 朱庆华 . 解释水平理论视角下失真健康信息可信度甄别的个体异质性研究[J]. 图书情报工作, 2025 , 69(16) : 116 -127 . DOI: 10.13266/j.issn.0252-3116.2025.16.010

Abstract

[Purpose/Significance] The prevalence of online health misinformation imposes crises of information credibility. Health misinformation misleads users’ health decisions and leads to negative health outcomes. To effectively address the harm caused by health misinformation, it is essential first to understand why users are susceptible to perceiving such misinformation as credible. This study aims to analyze the individual heterogeneity in users’ credibility judgment of health misinformation from the perspectives of construal level theory（CLT） and health and scientific literacy. [Method/Process] The study collected sample data through an online experiment. A total of 397 subjects each completed 10 credibility judgment tasks on health misinformation, generating 3,970 valid records. For data analysis, a multilevel mixed-effects logistic model was used to estimate the impact of individual heterogeneity on the ability to judge the credibility of health misinformation. [Result/Conclusion] There are common obstacles in distinguishing the credibility of health misinformation, with significant individual differences in credibility judgment. Specifically, the psychological distance between users and health misinformation is significantly negatively correlated with the probability of successfully judging credibility. Conversely, users’ scientific beliefs and scientific reasoning abilities are significantly positively correlated with the credibility judgment of health misinformation. Additionally, users’ attitudes towards alternative medicine negatively predict the probability of successfully judging health misinformation’s credibility.

Key words： health misinformation; construal level theory; psychological distance; credibility; individual heterogeneity; multilevel mixed-effects model

参考文献

[1] 李月琳, 张秀, 王姗姗.社交媒体健康信息质量研究:基于真伪健康信息特征的分析[J]. 情报学报, 2018, 37(3):294-304.(LI Y L, ZHANG X, WANG S S. Health information quality in social media:an analysis based on the features of real and fake health information[J]. Journal of the China Society for Scientific and Technical Information, 2018, 37(3):294-304.)
[2] 邓胜利, 顾一飞.网络虚假健康信息研究综述:认知、行为与治理[J]. 图书馆杂志, 2022, 41(5):14-22.(DENG S L, GU Y F. A review of online health misinformation:recognition, action and governance[J]. Library journal, 2022, 41(5):14-22.)
[3] 付少雄, 陈晓宇, 郑汉, 等.错误信息的成因、负面影响及管控:基于国外研究的综述[J]. 图书馆杂志, 2023, 42(5):33-43, 54.(FU S X, CHEN X Y, ZHENG H, et al. Causes, negative impacts and control on misinformation:a systematic review of research abroad[J]. Library journal, 2023, 42(5):33-43, 54.)
[4] 宋士杰, 赵宇翔, 朱庆华. iField视域下的信息可信度研究:概念溯源、主题演化与未来展望[J]. 中国图书馆学报, 2022, 48(1):107-126.(SONG S J, ZHAO Y X, ZHU Q H. Information credibility research in the iField:conceptual development, topic evolution, and future direction[J]. Journal of library science in China, 2022, 48(1):107-126.)
[5] NAN X, WANG Y, THIER K. Why do people believe health misinformation and who is at risk? A systematic review of individual differences in susceptibility to health misinformation[J]. Social science & medicine, 2022, 314:115398.
[6] SOUTHWELL B G, OTERO MACHUCA J, CHERRY S T, et al. Health misinformation exposure and health disparities:observations and opportunities[J]. Annual review of public health, 2023, 44(1):113-130.
[7] LI J, YANG X. Does exposure necessarily lead to misbelief?A meta-analysis of susceptibility to health misinformation[J]. Public understanding of science, 2024, 34(2):222-242.
[8] 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, et al. Investigating the influential factors of consumer’s credibility judgment on health misinformation[J]. Journal of library science in China, 2019, 45(4):72-85.)
[9] SEO H, BLOMBERG M, ALTSCHWAGER D, et al. Vulnerable populations and misinformation:a mixed-methods approach to underserved older adults’ online information assessment[J]. New media & society, 2021, 23(7):2012-2033.
[10] TROPE Y, LIBERMAN N.Construal-level theory of psychological distance[J]. Psychological review, 2010, 117(2):440-463.
[11] 王军, 丁丹丹.在线评论有用性与时间距离和社会距离关系的研究[J]. 情报理论与实践, 2016, 39(2):73-77, 81.(WANG J, DING D D. Research on the relationship between the usefulness of online review and the time and social distance[J]. Information studies:theory & application, 2016, 39(2):73-77, 81.)
[12] AERTS G, SMITS T, VERLEGH P W. How online consumer reviews are influenced by the language and valence of prior reviews:a construal level perspective[J]. Computers in human behavior, 2017, 75:855-864.
[13] 王翠翠, 陈雪, 朱万里, 等.带图片评论与纯文字评论对消费者有用性感知影响的眼动研究[J]. 情报理论与实践, 2020, 43(6):135-141.(WANG C C, CHEN X, ZHU W L, et al. Eyetracking study on the impact of photographic reviews and verbal reviews on consumers’ perceived usefulness[J]. Information studies:theory & application, 2020, 43(6):135-141.)
[14] ZHANG Z, WANG X, WU R. Is the devil in the details?Construal-level effects on perceived usefulness of online reviews for experience services[J]. Electronic commerce research and applications, 2021, 46:101033.
[15] 李贺, 余璐, 许一明, 等.解释水平理论视角下的社交网络隐私悖论研究[J]. 情报学报, 2018, 37(1):1-13.(LI H, YU L, XU Y M, et al. Research on privacy paradox in social network sites under the perspective of construal level theory[J]. Journal of the China Society for Scientific and Technical Information, 2018, 37(1):1-13.)
[16] 张敏, 马臻, 张艳.在线健康社区中用户主观知识隐藏行为的形成路径[J]. 情报理论与实践, 2018, 41(10):111-117, 153.(ZHANG M, MA Z, ZHANG Y. The formation path of users’ intentional knowledge hiding behavior in online health community[J]. Information studies:theory & application, 2018, 41(10):111-117, 153.)
[17] HANSEN J, WäNKE M. Truth from language and truth from fit:the impact of linguistic concreteness and level of construal on subjective truth[J]. Personality and social psychology bulletin, 2010, 36(11):1576-1588.
[18] KIRKPATRICK A W. The spread of fake science:lexical concreteness, proximity, misinformation sharing, and the moderating role of subjective knowledge[J]. Public understanding of science, 2021, 30(1):55-74.
[19] KINDIG D A, PANZER A M, NIELSEN-BOHLMAN L. Health literacy:a prescription to end confusion[M]. Washington, DC:National Academies Press, 2004.
[20] NUTBEAM D. Health literacy as a public health goal:a challenge for contemporary health education and communication strategies into the 21st century[J]. Health promotion international, 2000, 15(3):259-267.
[21] NORMAN C D, SKINNER H A. eHealth literacy:essential skills for consumer health in a networked world[J]. Journal of medical Internet research, 2006, 8(2):e9.
[22] ZHANG Y, SONG S. Older adults’ evaluation of the credibility of online health information[C] //Proceedings of the 2020conference on human information interaction and retrieval.Vancouver:Association for Computing Machinery, 2020:358-362.
[23] SANTIROCCHI A, SPATARO P, ALESSI F, et al. Trust in science and belief in misinformation mediate the effects of political orientation on vaccine hesitancy and intention to be vaccinated[J]. Acta psychologica, 2023, 237:103945.
[24] AGLEY J, XIAO Y. Misinformation about COVID-19:evidence for differential latent profiles and a strong association with trust in science[J]. BMC public health, 2021, 21:1-12.
[25] 宋士杰, 赵宇翔, 朱庆华.社交媒体中失真健康信息的传播、识别与纠偏研究[J]. 情报杂志, 2023, 42(6):162-169.(SONG S J, ZHAO Y X, ZHU Q H. A comprehensive review on health misinformation dissemination, identification and correction in social media[J]. Journal of intelligence, 2023, 42(6):162-169.)
[26] IRVING D, CLARK R W, LEWANDOWSKY S, et al. Correcting statistical misinformation about scientific findings in the media:causation versus correlation[J]. Journal of experimental psychology:applied, 2022, 28(1):1-9.
[27] PAL S K. Complementary and alternative medicine:an overview[J]. Current science, 2002, 82(5):518-524.
[28] LEE E L, RICHARDS N, HARRISON J, et al. Prevalence of use of traditional, complementary and alternative medicine by the general population:a systematic review of national studies published from 2010 to 2019[J]. Drug safety, 2022, 45(7):713-735.
[29] ASTIN J A. Why patients use alternative medicine:results of a national study[J]. JAMA, 1998, 279(19):1548-1553.
[30] COMAN C, BULARCA M C, REPANOVICI A, et al.Misinformation about medication during the COVID-19pandemic:a perspective of medical staff[J]. Plos one, 2022, 17(10):e0276693.
[31] DARKE P R, BRADY M K, BENEDICKTUS R L, et al. Feeling close from afar:the role of psychological distance in offsetting distrust in unfamiliar online retailers[J]. Journal of retailing, 2016, 92(3):287-299.
[32] PAIGE S R, STELLEFSON M, KRIEGER J L, etal. Transactional eHealth literacy:developing and testing a multidimensional instrument[J]. Journal of health communication, 2019, 24(10):737-748.
[33] FARIAS M, NEWHEISER A-K, KAHANE G, et al. Scientific faith:belief in science increases in the face of stress and existential anxiety[J]. Journal of experimental social psychology, 2013, 49(6):1210-1213.
[34] DRUMMOND C, FISCHHOFF B. Development and validation of the scientific reasoning scale[J]. Journal of behavioral decision making, 2017, 30(1):26-38.
[35] HYLAND M, LEWITH G, WESTOBY C. Developing a measure of attitudes:the holistic complementary and alternative medicine questionnaire[J]. Complementary therapies in medicine, 2003, 11(1):33-38.
[36] HEGGESTAD E D, SCHEAF D J, BANKS G C, et al. Scale adaptation in organizational science research:a review and bestpractice recommendations[J]. Journal of management, 2019, 45(6):2596-2627.
[37] COSTE J, GUILLEMIN F, POUCHOT J, et al. Methodological approaches to shortening composite measurement scales[J]. Journal of clinical epidemiology, 1997, 50(3):247-252.
[38] GJERSING L, CAPLEHORN J R M, CLAUSEN T. Crosscultural adaptation of research instruments:language, setting, time and statistical considerations[J]. BMC medical research methodology, 2010, 10:13.
[39] VERMUNT J K. Mixed-effects logistic regression models for indirectly observed discrete outcome variables[J]. Multivariate behavioral research, 2005, 40(3):281-301.
[40] 李月琳, 张秀.大学生社交媒体健康信息甄别能力研究[J]. 图书情报知识, 2018(1):66-77, 43.(LI Y L, ZHANG X. College students’ capability of screening health information in social media[J]. Document, information & knowledge, 2018(1):66-77, 43.)
[41] YEO S K, MCKASY M. Emotion and humor as misinformation antidotes[J]. Proceedings of the national academy of sciences, 2021, 118(15):e2002484118.
[42] 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.)
[43] WESTERWICK A. Effects of sponsorship, web site design, and Google ranking on the credibility of online information[J]. Journal of computer-mediated communication, 2013, 18(2):194-211.
[44] LUCASSEN T, SCHRAAGEN J M. The influence of source cues and topic familiarity on credibility evaluation[J]. Computers in human behavior, 2013, 29(4):1387-1392.
[45] LEE S J. The role of construal level in message effects research:a review and future directions[J]. Communication theory, 2019, 29(3):319-338.
[46] LEE J, LEE E H, CHAE D. eHealth literacy instruments:systematic review of measurement properties[J]. Journal of medical Internet research, 2021, 23(11):e30644.
[47] CHANG Y S, ZHANG Y, GWIZDKA J. The effects of information source and eHealth literacy on consumer health information credibility evaluation behavior[J]. Computers in human behavior, 2021, 115:106629.
[48] SONG S, LI X, SUN J, et al. Credibility judgment against online health misinformation among older adults:integrated view of psychological distance and health literacy[C] //Proceedings of the human aspects of IT for the aged population. Cham:Springer, 2023.
[49] SCHERER L D, MCPHETRES J, PENNYCOOK G, et al. Who is susceptible to online health misinformation? a test of four psychosocial hypotheses[J]. Health psychology, 2021, 40(4):274-284.
[50] FONTANAROSA P B, LUNDBERG G D. Alternative medicine meets science[J]. JAMA, 1998, 280(18):1618-1619.
[51] SONG S, ZHANG Y, YU B. Interventions to support consumer evaluation of online health information credibility:a scoping review[J]. International journal of medical informatics, 2021, 145:104321.
[52] XIE B. Effects of an eHealth literacy intervention for older adults[J]. Journal of medical Internet research, 2011, 13(4):e1880.
[53] ARMSTRONG-HEIMSOTH A, JOHNSON M L, MCCULLEY A, et al. Good Googling:a consumer health literacy program empowering parents to find quality health information online[J]. Journal of consumer health on the Internet, 2017, 21(2):111-124.
[54] MITSUHASHI T. Effects of two-week e-learning on eHealth literacy:a randomized controlled trial of Japanese Internet users[J]. PeerJ, 2018, 6:e5251.
[55] 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.)
[56] ZHANG Y, LIU J, SONG S. The design and evaluation of a nudge-based interface to facilitate consumers’ evaluation of online health information credibility[J]. Journal of the Association for Information Science and Technology, 2023, 74(7):828-845.
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