[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83832-en":3,"doc-seo-83832-105":29,"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":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":13,"seo_description":14,"update_tm":27,"read_time":28},83832,2336464648322,"Aria","https://ap-avatar.wpscdn.com/avatar/2200025388227c56fec?_k=1778556882303663488",8,"Research & Report","Identifying Deceptive Patterns Across Three Age Groups: A Heuristic-Based Cognitive Walkthrough Study of Mobile Apps","Deceptive patterns manipulate users into unintended actions, and mobile apps increasingly tailor these tactics across age groups. This paper uses a heuristic-based cognitive walkthrough to examine how deceptive patterns vary for teens (12–17), adults (18–49), and older adults (50+) across multiple app categories. Analysis of 30 apps in 6 categories shows 93% use the nagging pattern. Entertainment apps contain more deceptive patterns than other categories, and older-adult entertainment apps use sneaking more frequently, motivating ethical, age-specific design guidance.","Identifying Deceptive Patterns Across Three Age Groups: A Heuristic-Based Cognitive Walkthrough  \nStudy of Mobile Apps  \nNasra Hassan Carleton University Ottawa, Canada  \nNasrahassan3@cmail.carleton.ca  \nHala Assal  \nCarleton University Ottawa, Canada HalaAssal@cunet.carleton.ca  \narXiv :2607 .04573v 1 [ cs .HC] 6 Jul 2026  \nI. ABSTRACT  \nDeceptive patterns are tactics used to manipulate users into performing unintended actions. Today, many of these deceptive patterns are implemented in mobile apps targeting diverse age groups. In this paper, we employ a heuristic-based cognitive walkthrough to explore how deceptive patterns are tailored to three age groups, specifically teens (12-17), adults (18-49), and older adults (50+), across different app categories. By analyzing 30 apps spanning 6 categories, we found that 93% of these apps use the nagging pattern. Furthermore, our findings reveal that entertainment apps contain significantly more deceptive patterns than other app categories, such as music/books. Our data also shows that entertainment apps for older adults use sneaking patterns more frequently than entertainment apps for teens or adults. These findings call for the development of more ethical, age-specific design guidelines to protect users from targeted digital manipulation attempts.  \nII. INTRODUCTION  \nDeceptive patterns (also referred to as dark patterns) have become a major concern for users of various ages. With today’s modern technology, it has become easier for designers to implement these patterns through mobile apps more than ever. Many apps across various categories intentionally steer their users into performing actions that are not in their favour. Mathur et al. [1] investigated ∼ 11K shopping websites that apply deceptive patterns to nudge users into making additional purchases or simply prompt them to share more information. Similarly, Luguri and Strahilevitz [2] demonstrated that deceptive patterns exploit customers’ cognitive biases to manipulate their decision-making. This leaves users in a state of confusion or regret, specifically when encountering patterns such as hidden information, trick questions, and obstruction.  \nHowever, much of this previous work laid the foundations for studying deceptive patterns by creating taxonomies (such as Gray et al. [3]) . Furthermore, Di Geronimo et al. [4] implemented a different approach by heavily relying on analyzing popular mobile apps and recording examples of identified patterns broadly, finding that most apps contain one or more forms of deceptive patterns. Despite these efforts, there is a  \ncurrent gap in the literature regarding how apps vary their use of deceptive patterns across different target age groups, and whether the implementation of these patterns differs by app category. To address this, we conducted a heuristic-based cognitive walkthrough study [5] analyzing 30 apps tailored to different age groups across 6 categories, including shopping, gaming, and health & fitness. In our study, we address the following research question: How do deceptive patterns vary across different app categories and target age groups? By understanding how such patterns are used across multiple apps and categories, our objective is to contribute to a more comprehensive understanding of deceptive pattern practices across different age groups.  \nIII. BACKGROUND AND RELATED WORK  \nEarly work in deceptive patterns introduced by Brignull [6] established the field’s core concepts, with standardized taxonomies later developed [3], [7] . With such foundational work, subsequent research has studied deceptive patterns from various lenses, such as examining how they are used in gaming apps [8] or in specific social media platforms like Instagram [9], and the impacts of these patterns on users [10] . Users encounter deceptive patterns more frequently—often with limited understanding or recognition abilities; therefore, these tactics are widely considered malicious design practice","cbCaihuDrZleLEWm","https://ap.wps.com/l/cbCaihuDrZleLEWm","pdf",2203630,1,13,"English","en",105,"# Abstract\n# Introduction\n# Background and Related Work\n# Taxonomies and Approaches to Deceptive Patterns\n## Deceptive","[{\"question\":\"What are deceptive patterns in mobile apps according to the study?\",\"answer\":\"Deceptive patterns are interface tactics designed to manipulate users into actions they do not intend to take. They rely on steering users toward outcomes that are not in their favor.\"},{\"question\":\"Which age groups are compared in the research and how are apps analyzed?\",\"answer\":\"The study compares teens (12–17), adults (18–49), and older adults (50+). It analyzes 30 mobile apps across six categories using a heuristic-based cognitive walkthrough approach.\"},{\"question\":\"What key results does the study report about deceptive patterns across app categories?\",\"answer\":\"93% of the examined apps use the nagging pattern. Entertainment apps contain significantly more deceptive patterns than other categories, and entertainment apps for older adults use sneaking patterns more often than those for teens or adults.\"}]",1784190813,33,{"code":4,"msg":30,"data":31},"ok",{"site_id":24,"language":23,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":27},"identifying-deceptive-patterns-across-three-age-groups-a-heuristic-based-cognitive-walkthrough-study-of-mobile-apps","",{"@graph":35,"@context":85},[36,53,68],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/identifying-deceptive-patterns-across-three-age-groups-a-heuristic-based-cognitive-walkthrough-study-of-mobile-apps/83832/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":23,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-17","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 are deceptive patterns in mobile apps according to the study?","Question",{"text":75,"@type":76},"Deceptive patterns are interface tactics designed to manipulate users into actions they do not intend to take. They rely on steering users toward outcomes that are not in their favor.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Which age groups are compared in the research and how are apps analyzed?",{"text":80,"@type":76},"The study compares teens (12–17), adults (18–49), and older adults (50+). It analyzes 30 mobile apps across six categories using a heuristic-based cognitive walkthrough approach.",{"name":82,"@type":73,"acceptedAnswer":83},"What key results does the study report about deceptive patterns across app categories?",{"text":84,"@type":76},"93% of the examined apps use the nagging pattern. Entertainment apps contain significantly more deceptive patterns than other categories, and entertainment apps for older adults use sneaking patterns more often than those for teens or adults.","https://schema.org",{"og:url":51,"og:type":87,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":89,"canonical":51},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,128,131,135],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":45,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":45,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":45,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":124,"doc_module":4,"doc_module_name":45,"category_name":125,"show_sort_weight":126,"slug":127},9,"Religion & Spirituality",20,"religion-spirituality",{"id":126,"doc_module":4,"doc_module_name":45,"category_name":129,"show_sort_weight":126,"slug":130},"World Cup","world-cup",{"id":132,"doc_module":4,"doc_module_name":45,"category_name":133,"show_sort_weight":132,"slug":134},10,"Lifestyle","lifestyle",{"id":136,"doc_module":4,"doc_module_name":45,"category_name":137,"show_sort_weight":106,"slug":138},19,"General","general"]