{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T05:14:00Z","timestamp":1783401240979,"version":"3.54.6"},"reference-count":49,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T00:00:00Z","timestamp":1782432000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["MTI"],"abstract":"<jats:p>Smartphone applications routinely collect and share personal data, yet users often struggle to understand these practices, particularly when third-party data sharing is involved. Existing mechanisms such as privacy policies and notices provide limited support for user understanding. To address this gap, we investigated how explainability concepts can enhance contextual privacy policies for mobile apps. We designed two interface prototypes integrating explanation strategies: contrastive explanations, which clarify data-sharing boundaries, and example-based explanations, which illustrate counterfactual scenarios. In an exploratory between-subjects user study (N = 30), we evaluated their impact on comprehensibility, simplicity, cognitive load, and experience. Statistical analysis revealed no significant differences between the two types. Hence, the findings should be read as descriptive trends rather than confirmatory effects. These trends suggested example-based explanations better supported users mental models, while contrastive explanations better supported decision-making. Our findings contribute design recommendations on applying explanation strategies in privacy interfaces, offering guidance for developers and researchers seeking to improve user understanding and trust in digital systems.<\/jats:p>","DOI":"10.3390\/mti10070071","type":"journal-article","created":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T05:58:04Z","timestamp":1782799084000},"page":"71","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Contrastive vs. Example-Based Explanations: Designing for Better User Comprehension in Smartphone Privacy Interfaces"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0009-0002-7616-2674","authenticated-orcid":false,"given":"Ananya","family":"Bhadauria","sequence":"first","affiliation":[{"name":"Independent Researcher, 68789 Sankt Leon-Rot, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9174-8895","authenticated-orcid":false,"given":"Andreas","family":"Riener","sequence":"additional","affiliation":[{"name":"Human-Computer Interaction Group, Technische Hochschule Ingolstadt, Esplanade 10, 85049 Ingolstadt, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,6,26]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Magoulas, G.S., and Polykalas, S.E. 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