[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-81656-en":3,"doc-seo-81656-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},81656,16904993612988,"Olivia Brown","https://ap-avatar.wpscdn.com/davatar_a8503ba1806abce46bf441b54a3ca4cd",8,"Research & Report","Building Resilience to Misinformation: The Digital Media and Information Literacy Scale (DMILS)","Growing concerns about information quality and credibility in digital media highlight a lack of a concise, comprehensive, and psychometrically robust instrument for assessing competencies that help people navigate misinformation. This article develops the Digital Media and Information Literacy Scale (DMILS), a multidimensional measure distinguishing domain (digital vs. information/news) and competency type (knowledge vs. skill), using both subjective and objective items. Across two studies with three matched national samples from the United States and Singapore (N=1,498), DMILS demonstrates strong validity and offers both a full 18-item battery and an 8-item short form to support cross-national evaluation of media literacy interventions.","Building Resilience to Misinformation: A Cross-National Development of the Digital Media and Information Literacy Scale (DMILS)  \nSijia Qian (Corresponding Author) 1, Cuihua Shen2, Huiyi Wang3, Hichang Cho4  \n1 Assistant Professor, School of Data Science, University of North Carolina at Charlotte; Email: [sqian@charlotte.edu](sqian@charlotte.edu)  \n2 Professor, Department of Communication, University of California, Davis; Email: [shencuihua@gmail.com](shencuihua@gmail.com)  \n3 Assistant Professor, Research Center of Journalism and Social Development, School of  \nJournalism and Communication, Renmin University of China; [Email: ](Email: wanghuiyi314@ruc.edu.cn)[wanghuiyi314@ruc.edu.cn](Email: wanghuiyi314@ruc.edu.cn)  \n4 Associate Professor, Department of Communications and New Media, National University of Singapore; [Email: ](Email: hichang_cho@nus.edu.sg)[hichang_cho@nus.edu.sg](Email: hichang_cho@nus.edu.sg)  \nCitation: Qian, S., Shen, C., Wang, H., & Cho, H. (2026). Building resilience to misinformation: A cross-national development of the Digital Media and Information Literacy Scale  \n(DMILS) . new media & society, 14614448261448549. [link]  \nAbstract  \nAmid growing concern about information quality and credibility in digital media environments, researchers and educators still lack a concise, comprehensive yet psychometrically sound instrument for tracking the competencies that help people navigate this landscape. This article develops the Digital Media and Information Literacy Scale (DMILS)—a robust and multidimensional measure that distinguishes domain (digital vs. information/news), competency type (knowledge vs. skill), and is measured through both subjective and objective items. Through two empirical studies with three nationally matched samples in the United States and Singapore (N = 1,498), we developed an 18-item self-report battery and 16-item objective knowledge questions, showing strong structural, convergent, and predictive validity, along with a short form (8 self-report and 8 objective items). By offering a parsimonious yet multidimensional yardstick, DMILS enables rigorous evaluation of media literacy interventions and supplies a common metric for cross-national research, critical for building an information ecosystem resilient to misand disinformation.  \nKey words: Digital media literacy, information literacy, scale development, media literacy measurement, validity  \nBuilding Resilience to Misinformation: A Cross-National Development of the Digital Media and Information Literacy Scale (DMILS)  \nIn an increasingly complex media landscape, where misinformation spreads rapidly, media literacy has emerged as an essential competency for democratic deliberation and individual well-being (Mihailidis & Thevenin, 2013; Potter, 2019) . Although the urgency of media literacy has been widely acknowledged by educators, policymakers, and scholars alike, the field remains conceptually fragmented and empirically inconsistent. Multiple literacies—digital literacy, information literacy, news literacy, algorithm literacy, and AI literacy—have evolved to address specific features of the digital ecosystem, yet they often operate in parallel rather than in concert (Martens, 2010) . Similarly, while a growing body of research highlights the promise of media literacy as a tool to reduce misinformation susceptibility (e.g., Guess et al., 2020; Qian et al., 2023), the empirical evaluation of such efforts has been hampered by the absence of a unified, multidimensional measurement framework. Existing scales are often fragmented, outdated, or narrowly focused, failing to capture the full spectrum of relevant competencies or to adapt to rapidly changing technological affordances (e.g., Hargittai & Hsieh, 2012). Although different components of media and information literacy (e.g., news literacy, digital literacy) may play distinct roles depending on the type of content or task, a more unified and parsimonious measure would address thes","cbCaivBx0xea8gfC","https://ap.wps.com/l/cbCaivBx0xea8gfC","pdf",682168,3,1,40,"English","en",105,"# Building Resilience to Misinformation: DMILS\n## The Need for an Integrated Literacy Framework\n## DMILS Framework and Development\n## Validation Outcomes and Use Cases","[{\"question\":\"What problem does the DMILS study address?\",\"answer\":\"It addresses the lack of a unified, psychometrically sound measurement tool to assess competencies for navigating misinformation in digital media environments.\"},{\"question\":\"How is DMILS structured in terms of literacy domains and competence types?\",\"answer\":\"DMILS distinguishes literacy domains (digital vs. information/news) and competence types (knowledge vs. skill), measured with both subjective self-report and objective performance-based items.\"},{\"question\":\"What evidence supports DMILS validity and usability?\",\"answer\":\"Two empirical studies using matched samples from the United States and Singapore (N=1,498) support structural, convergent, and predictive validity, and provide both a full 18-item instrument and a short 8-item form for comparison across contexts.\"}]",1784175203,101,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"building-resilience-to-misinformation-the-digital-media-and-information-literacy-scale-dmils","",{"@graph":36,"@context":85},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,50],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":20},"https://docshare.wps.com/document/research-report/",{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/building-resilience-to-misinformation-the-digital-media-and-information-literacy-scale-dmils/81656/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-23","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What problem does the DMILS study address?","Question",{"text":75,"@type":76},"It addresses the lack of a unified, psychometrically sound measurement tool to assess competencies for navigating misinformation in digital media environments.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How is DMILS structured in terms of literacy domains and competence types?",{"text":80,"@type":76},"DMILS distinguishes literacy domains (digital vs. information/news) and competence types (knowledge vs. skill), measured with both subjective self-report and objective performance-based items.",{"name":82,"@type":73,"acceptedAnswer":83},"What evidence supports DMILS validity and usability?",{"text":84,"@type":76},"Two empirical studies using matched samples from the United States and Singapore (N=1,498) support structural, convergent, and predictive validity, and provide both a full 18-item instrument and a short 8-item form for comparison across 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