{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,24]],"date-time":"2026-10-24T01:16:21Z","timestamp":1792804581255,"version":"4.5.0"},"reference-count":42,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2020,3,31]],"date-time":"2020-03-31T00:00:00Z","timestamp":1585612800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/100007515","name":"National Science Foundation","doi-asserted-by":"publisher","award":["IIS-1702751"],"award-info":[{"award-number":["IIS-1702751"]}],"id":[{"id":"10.13039\/100007515","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Access. Comput."],"published-print":{"date-parts":[[2020,3,31]]},"abstract":"<jats:p>\n                    Accessibility barriers in mobile applications (apps) can make it challenging for people who have impairments or use assistive technology to use those apps. Ross et al.\u2019s epidemiology-inspired framework emphasizes that a wide variety of factors may influence an app's accessibility and presents large-scale analysis as a powerful tool for understanding the prevalence of accessibility barriers (i.e.,\n                    <jats:italic>inaccessibility diseases<\/jats:italic>\n                    ). Drawing on this framework, we performed a large-scale analysis of free Android apps, exploring the frequency of accessibility barriers and factors that may have contributed to barrier prevalence. We tested a population of 9,999 apps for seven accessibility barriers: few TalkBack-focusable elements, missing labels, duplicate labels, uninformative labels, editable TextViews with\n                    <jats:italic>contentDescription<\/jats:italic>\n                    , fully overlapping clickable elements, and undersized elements. We began by measuring the prevalence of each accessibility barrier across all relevant element classes and apps. Missing labels and undersized elements were the most prevalent barriers. As a measure of the spread of barriers across apps, we assessed the five most reused classes of elements for missing labels and undersized elements. The Image Button class was among the most barrier-prone of the high reuse element classes; 53% of Image Button elements were missing labels and 40% were undersized. We also investigated factors that may have contributed to the high barrier prevalence in certain classes of elements, selecting examples based on prior knowledge, our analyses, and metrics of reuse and barrier-proneness. These case studies explore: (1)\u00a0how the\n                    <jats:italic>few TalkBack-focusable elements<\/jats:italic>\n                    accessibility barrier relates to app category (e.g., Education, Entertainment) and the tools used to implement an app, (2) the prevalence of label-based barriers in image-based buttons, (3) design patterns that affect the labeling and size of Radio Buttons and Checkboxes, and (4) accessibility implications of the sizing of third-party plug-in elements. Our work characterizes the current state of Android accessibility, suggests improvements to the app ecosystem, and demonstrates analysis techniques that can be applied in further app accessibility assessments.\n                  <\/jats:p>","DOI":"10.1145\/3348797","type":"journal-article","created":{"date-parts":[[2020,5,4]],"date-time":"2020-05-04T06:43:15Z","timestamp":1588574595000},"page":"1-36","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":57,"title":["An Epidemiology-inspired Large-scale Analysis of Android App Accessibility"],"prefix":"10.1145","volume":"13","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8353-3176","authenticated-orcid":false,"given":"Anne Spencer","family":"Ross","sequence":"first","affiliation":[{"name":"Paul G. Allen School of Computer Science 8 Engineering, DUB Group, University of Washington, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyi","family":"Zhang","sequence":"additional","affiliation":[{"name":"Paul G. Allen School of Computer Science 8 Engineering, DUB Group, University of Washington, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"James","family":"Fogarty","sequence":"additional","affiliation":[{"name":"Paul G. Allen School of Computer Science 8 Engineering, DUB Group, University of Washington, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jacob O.","family":"Wobbrock","sequence":"additional","affiliation":[{"name":"The Information School, DUB Group, University of Washington, Seattle, WA, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2020,4,21]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"Retrieved on","author":"Adobe","year":"2019","unstructured":"Adobe. Adobe AIR. Retrieved on 17 April , 2019 from https:\/\/get.adobe.com\/air. Adobe. Adobe AIR. Retrieved on 17 April, 2019 from https:\/\/get.adobe.com\/air."},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/2901739.2903508"},{"key":"e_1_2_1_3_1","volume-title":"Making Applications Accessible. Retrieved on","author":"Source Android Open","year":"2019","unstructured":"Android Open Source . 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