基于《通用数据保护条例》的强效验证加权量表建议,用于评估移动健康应用的隐私政策质量:一项 eDelphi 研究。

IF 1.3 4区 医学 Q3 COMPUTER SCIENCE, INFORMATION SYSTEMS Methods of Information in Medicine Pub Date : 2023-12-01 Epub Date: 2023-08-17 DOI:10.1055/a-2155-2021
Jaime Benjumea, Jorge Ropero, Enrique Dorronzoro-Zubiete, Octavio Rivera-Romero, Alejandro Carrasco
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引用次数: 0

摘要

背景:医疗保健服务正在经历数字化转型,其中参与式健康信息学领域扮演着重要角色。在这一领域,开展了旨在评估数字工具(包括移动医疗应用程序)质量的研究。隐私是移动医疗应用程序质量的一个维度。隐私由几个部分组成,包括组织、技术和法律保障。在法律保障措施中,向用户提供有关如何处理其数据的透明信息至关重要。这些信息通常通过隐私政策文件向用户披露。评估隐私政策的质量是一项复杂的任务,文献中提出了若干支持这一过程的量表。然而,这些量表各不相同,甚至不是很客观。在之前的研究中,我们根据《通用数据保护条例》,提出了一份移动医疗应用程序隐私政策质量评估指导项目清单:目的:完善我们基于《一般数据保护条例》的隐私量表的稳健性,以评估移动医疗应用程序隐私政策的质量,确定新的项目,并为量表中的每个项目分配权重:方法:由隐私专家小组进行两轮修改后的德尔菲研究:结果:经过德尔菲程序后,大多数专家认为量表中的所有项目都 "重要 "或 "非常重要"(在 5 分制李克特量表中分别为 4 分和 5 分)。其中一个原始项目被建议重新措辞,同时提出了八个暂定项目。第二轮之后,最终只增加了其中两个项目。本量表的 16 个项目中有 11 个被认为 "非常重要"(权重为 1),另外 5 个被认为 "重要"(权重为 0.5):Benjumea隐私量表是评估移动医疗应用程序隐私政策质量的一种新的稳健工具,可对其他量表进行更深入的补充分析。此外,该量表还为制定高质量的移动医疗应用程序隐私政策提供了指导。
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A Proposal for a Robust Validated Weighted General Data Protection Regulation-Based Scale to Assess the Quality of Privacy Policies of Mobile Health Applications: An eDelphi Study.

Background: Health care services are undergoing a digital transformation in which the Participatory Health Informatics field has a key role. Within this field, studies aimed to assess the quality of digital tools, including mHealth apps, are conducted. Privacy is one dimension of the quality of an mHealth app. Privacy consists of several components, including organizational, technical, and legal safeguards. Within legal safeguards, giving transparent information to the users on how their data are handled is crucial. This information is usually disclosed to users through the privacy policy document. Assessing the quality of a privacy policy is a complex task and several scales supporting this process have been proposed in the literature. However, these scales are heterogeneous and even not very objective. In our previous study, we proposed a checklist of items guiding the assessment of the quality of an mHealth app privacy policy, based on the General Data Protection Regulation.

Objective: To refine the robustness of our General Data Protection Regulation-based privacy scale to assess the quality of an mHealth app privacy policy, to identify new items, and to assign weights for every item in the scale.

Methods: A two-round modified eDelphi study was conducted involving a privacy expert panel.

Results: After the Delphi process, all the items in the scale were considered "important" or "very important" (4 and 5 in a 5-point Likert scale, respectively) by most of the experts. One of the original items was suggested to be reworded, while eight tentative items were suggested. Only two of them were finally added after Round 2. Eleven of the 16 items in the scale were considered "very important" (weight of 1), while the other 5 were considered "important" (weight of 0.5).

Conclusion: The Benjumea privacy scale is a new robust tool to assess the quality of an mHealth app privacy policy, providing a deeper and complementary analysis to other scales. Also, this robust scale provides a guideline for the development of high-quality privacy policies of mHealth apps.

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来源期刊
Methods of Information in Medicine
Methods of Information in Medicine 医学-计算机:信息系统
CiteScore
3.70
自引率
11.80%
发文量
33
审稿时长
6-12 weeks
期刊介绍: Good medicine and good healthcare demand good information. Since the journal''s founding in 1962, Methods of Information in Medicine has stressed the methodology and scientific fundamentals of organizing, representing and analyzing data, information and knowledge in biomedicine and health care. Covering publications in the fields of biomedical and health informatics, medical biometry, and epidemiology, the journal publishes original papers, reviews, reports, opinion papers, editorials, and letters to the editor. From time to time, the journal publishes articles on particular focus themes as part of a journal''s issue.
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