Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/148953
Title: COVID-19 contact-tracing apps : analysis of the readability of privacy policies
Authors: Zhang, Melvyn
Chow, Aloysius
Smith, Helen
Keywords: Science::Medicine
Issue Date: 2020
Source: Zhang, M., Chow, A. & Smith, H. (2020). COVID-19 contact-tracing apps : analysis of the readability of privacy policies. Journal of Medical Internet Research, 22(12). https://dx.doi.org/10.2196/21572
Project: NMRC/Fellowship/0048/2017
Journal: Journal of Medical Internet Research
Abstract: Apps that enable contact-tracing are instrumental in mitigating the transmission of COVID-19, but there have been concerns among users about the data collected by these apps and their management. Contact tracing is of paramount importance when dealing with a pandemic, as it allows for rapid identification of cases based on the information collected from infected individuals about other individuals they may have had recent contact with. Advances in digital technology have enabled devices such as mobile phones to be used in the contract-tracing process. However, there is a potential risk of users’ personal information and sensitive data being stolen should hackers be in the near vicinity of these devices. Thus, there is a need to develop privacy-preserving apps. Meanwhile, privacy policies that outline the risk associated with the use of contact-tracing apps are needed, in formats that are easily readable and comprehensible by the public. To our knowledge, no previous study has examined the readability of privacy policies of contact-tracings apps. Therefore, we performed a readability analysis to evaluate the comprehensibility of privacy policies of 7 contact-tracing apps currently in use. The contents of the privacy policies of these apps were assessed for readability using Readability Test Tool, a free web-based reliability calculator, which computes scores based on a number of statistics (ie, word count and the number of complex words) and indices (ie, Flesch Reading Ease, Flesch-Kincaid Reading Grade Level, Gunning Fog Index, and Simplified Measure of Gobbledygook index). Our analysis revealed that explanations used in the privacy policies of these apps require a reading grade between 7 and 14, which is considerably higher than the reading ability of the average individual. We believe that improving the readability of privacy policies of apps could be potentially reassuring for users and may help facilitate the increased use of such apps.
URI: https://hdl.handle.net/10356/148953
ISSN: 1438-8871
DOI: 10.2196/21572
Rights: © 2020 Melvyn Zhang, Aloysius Chow, Helen Smith. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 03.12.2020. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:LKCMedicine Journal Articles

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