[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"detail-sidebar-cat-0-en-105":3,"doc-seo-625574-105":59,"doc-detail-625574-en":130},{"code":4,"msg":5,"data":6},0,"success",[7,13,18,23,28,33,38,43,48,51,55],{"id":8,"doc_module":4,"doc_module_name":9,"category_name":10,"show_sort_weight":11,"slug":12},1,"Document","Story & Novel",90,"story-novel",{"id":14,"doc_module":4,"doc_module_name":9,"category_name":15,"show_sort_weight":16,"slug":17},2,"Literature",80,"literature",{"id":19,"doc_module":4,"doc_module_name":9,"category_name":20,"show_sort_weight":21,"slug":22},4,"Exam",70,"exam",{"id":24,"doc_module":4,"doc_module_name":9,"category_name":25,"show_sort_weight":26,"slug":27},5,"Comic",60,"comic",{"id":29,"doc_module":4,"doc_module_name":9,"category_name":30,"show_sort_weight":31,"slug":32},6,"Technology",50,"technology",{"id":34,"doc_module":4,"doc_module_name":9,"category_name":35,"show_sort_weight":36,"slug":37},7,"Healthcare",40,"healthcare",{"id":39,"doc_module":4,"doc_module_name":9,"category_name":40,"show_sort_weight":41,"slug":42},8,"Research & Report",30,"research-report",{"id":44,"doc_module":4,"doc_module_name":9,"category_name":45,"show_sort_weight":46,"slug":47},9,"Religion & Spirituality",20,"religion-spirituality",{"id":46,"doc_module":4,"doc_module_name":9,"category_name":49,"show_sort_weight":46,"slug":50},"World Cup","world-cup",{"id":52,"doc_module":4,"doc_module_name":9,"category_name":53,"show_sort_weight":52,"slug":54},10,"Lifestyle","lifestyle",{"id":56,"doc_module":4,"doc_module_name":9,"category_name":57,"show_sort_weight":24,"slug":58},19,"General","general",{"code":4,"msg":60,"data":61},"ok",{"site_id":62,"language":63,"slug":64,"title":65,"keywords":66,"description":67,"schema_data":68,"social_meta":123,"head_meta":125,"extra_data":127,"updated_unix":129},105,"en","a-systematic-literature-review-on-digital-health-continuance-intention-applying-the-expectation-confimation-model-ecm","A Systematic Literature Review on Digital Health Continuance Intention - Applying the Expectation Confimation Model (ECM)","","Rapid digitalization has driven widespread adoption of digital health services such as telemedicine, e-health, and m-health, yet long-term viability depends on users’ continuance use intention (CUI). This study performs a systematic literature review to examine how the Expectation Confirmation Model (ECM) is applied to CUI in digital health contexts. Seventeen peer-reviewed studies from 2019 to 2024 are analyzed, highlighting confirmation of expectations, perceived usefulness, and user satisfaction as key determinants. Results show ECM as the dominant framework, often extended with TAM, UTAUT, and trust-based theories, while future work should test contextual moderators like digital literacy, technology trust, health condition types, self-efficacy, and service quality to strengthen sustainability of digital platforms.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/a-systematic-literature-review-on-digital-health-continuance-intention-applying-the-expectation-confimation-model-ecm/625574/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/a-systematic-literature-review-on-digital-health-continuance-intention-applying-the-expectation-confimation-model-ecm/625574.png","ImageObject",300,407,{"name":92,"@type":93},"Aria","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-31","2026-10-20",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What does the study investigate about digital health services?","Question",{"text":112,"@type":113},"It investigates how the Expectation Confirmation Model (ECM) explains users’ continuance use intention (CUI) in digital health contexts.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"How was the evidence collected in this review?",{"text":117,"@type":113},"The study uses a systematic literature review approach and examines 17 peer-reviewed studies published between 2019 and 2024.",{"name":119,"@type":110,"acceptedAnswer":120},"Which factors are identified as influencing continuance use intention?",{"text":121,"@type":113},"Key factors include confirmation of initial expectations, perceived usefulness, and user satisfaction.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},625574,1792877300,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":29,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144},2336464648322,"https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488","2025 13th International Conference on Cyber and IT Service Management (CITSM) ©2025 IEEE DOI: 10.1109/CITSM67730.2025.11291545| 979-8-3315-7585-4/25/$31.00 |   \nA Systematic Literature Review on Digital Health Continuance Intention: Applying the Expectation Confimation Model (ECM)  \n1st Yusuf Durachman  \nDepartment of Science and Technology UINSyarif Hidayatullah Jakarta Tangerang, Indonesia [yusuf_durachman@uinjkt.ac.id](yusuf_durachman@uinjkt.ac.id)  \n4th Muhammad Qomarul Huda  \nDepartment of Science and Technology UINSyarif Hidayatullah Jakarta Tangerang, Indonesia [mqomarul@uinjkt.ac.id](mqomarul@uinjkt.ac.id)  \n2nd Nurbojatmiko  \nDepartment of Science and Technology UINSyarif Hidayatullah Jakarta Tangerang, Indonesia[nurbojatmiko@uinjkt.ac.id](nurbojatmiko@uinjkt.ac.id)  \n5th Nuryasin  \nDepartment of Science and Technology UINSyarif Hidayatullah Jakarta Tangerang, Indonesia[nuryasin@uinjkt.ac.id](nuryasin@uinjkt.ac.id)  \n3rd Alvin Aryan  \nDepartment of Science and Technology UINSyarif Hidayatullah Jakarta Tangerang, Indonesia [alvin.aryan20@mhs.uinjkt.ac.id](alvin.aryan20@mhs.uinjkt.ac.id)  \nAbstract—The rapid evolution of digital technologies has led to the widespread adoption of digital health services, including telemedicine, e-health, and m-health. However, the sustainability of these services relies heavily on users' intention to continue using them over time—known as Continuance Use Intention (CUI). This study aims to systematically review the application of the Expectation Confirmation Model (ECM) in analyzing CUI within digital health contexts. Using a Systematic Literature Review (SLR) approach, 17 peer-reviewed studies published between 2019 and 2024 were examined. The review identifies key factors influencing CUI, including confirmation of initial expectations, perceived usefulness, and user satisfaction. Findings reveal that ECM is the most widely used theoretical framework to explain continuance behavior in digital health, often extended with models such as TAM, UTAUT, and trustbased theories to provide a more holistic analysis. Future research is encouraged to further explore contextual factors such as digital literacy, trust in technology, and types of health conditions, which may moderate the relationships among ECM variables, including self-efficacy and service quality. The results of this review offer both theoretical and practical implications for enhancing the sustainability of digital health platforms.  \nKeywords—digital health, continuance use intention, expectation confirmation model, systematic literature review, telemedicine  \nI. INTRODUCTION  \nCurrent technological advancements are progressing rapidly and have permeated nearly every aspect of human life. Broadly speaking, technology serves as a tool that aids humans in expanding knowledge, applying skills, and solving diverse challenges. One tangible impact of technological progress is the emergence of innovative procedures that enhance utility across various sectors. Digital transformation has significantly contributed to advancements in communication, transportation, industry, education, and particularly healthcare [1] . In the healthcare sector, technological progress has given rise to telemedicine—a digital-based healthcare system enabling remote interactions between patients and medical professionals [2] . This service has grown increasingly popular, especially since the COVID- 19 pandemic [3], as it provides quick, efficient, and safe access to healthcare while minimizing transmission risks. Although early adoption of digital health shows a positive  \ntrend, it remains crucial to assess whether users will sustain long-term usage. The concept of continuance use intention—or the intention to continue using a service—has become a key topic in evaluating system sustainability. To understand this behavior, many researchers employ the Expectation Confirmation Model (ECM), a theoretical framework originally derived from consumer behavior studies a","cbCaiiNg5Ip6Jb7E","https://ap.wps.com/l/cbCaiiNg5Ip6Jb7E","pdf",231234,"English","# Introduction\n# Theory Review","[{\"question\":\"What does the study investigate about digital health services?\",\"answer\":\"It investigates how the Expectation Confirmation Model (ECM) explains users’ continuance use intention (CUI) in digital health contexts.\"},{\"question\":\"How was the evidence collected in this review?\",\"answer\":\"The study uses a systematic literature review approach and examines 17 peer-reviewed studies published between 2019 and 2024.\"},{\"question\":\"Which factors are identified as influencing continuance use intention?\",\"answer\":\"Key factors include confirmation of initial expectations, perceived usefulness, and user satisfaction.\"}]","A Systematic Literature Review on Digital Health Continuance Intention - Applying the Expectation Confimation Model (ECM) | PDF",1792531623,15]