Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study.
Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study.
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DOI：
10.2196/27343
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发表时间：
2021-07-28
影响因子：
5
通讯作者：
Cho MK
中科院分区：
文献类型：
--
作者：
Martinez-Martin N;Greely HT;Cho MK
数字表型分析（也称为个人感测、智能感测或身体计算）涉及从数字设备（如智能手机、可穿戴设备或社交媒体）原位收集生物特征和个人数据，以测量行为或其他健康指标。分析收集的数据以生成人的精神状态的每时每刻的量化，并可能预测未来的精神状态。数字表型项目整合了来自多个来源的数据，如电子健康记录、生物特征扫描或基因检测。由于数字表型分析工具可用于研究和预测行为，因此它们对一系列消费者、政府和医疗保健应用越来越感兴趣。在临床护理中，数字表型分析有望改善心理健康诊断和治疗。与此同时，数字表型的心理健康应用提出了伦理问题的重要领域，特别是在隐私和数据保护，同意，偏见和问责制方面。本研究旨在就美国数字表型分析在精神卫生领域应用的关键伦理指导领域达成共识。我们使用了修改后的德尔菲技术，以确定新出现的伦理挑战所带来的数字表型的精神卫生应用，并制定指导，以解决这些挑战。数字表型、数据科学、心理健康、法律和伦理学方面的专家作为小组成员参加了这项研究。该小组通过一个涉及访谈和调查的反复过程达成了协商一致的建议。小组成员主要关注精神健康数字表型的临床应用，但也包括有关透明度和数据保护的建议，以解决医疗保健领域以外滥用数字表型数据的潜在领域。这项研究的结果表明，在开发数字表型的心理健康应用中，与这些伦理问题相关的强烈一致性：隐私，透明度，同意，问责制和公平性。当指导意见的表述足够宽泛，能够容纳一系列潜在的应用时，关于建议声明的共识最为强烈。德尔菲参与者认为，隐私和数据保护问题尤其需要解决，这些问题涉及到保护敏感个人信息的现行法规和框架的不足之处，以及在卫生系统之外销售和分析个人数据的可能性。德尔菲的研究发现，在精神健康应用的数字表型开发中，对一些伦理问题的优先考虑达成了一致。德尔菲共识声明确定了关于数字表型在精神健康中的伦理应用的一般建议和原则。随着精神健康的数字表型在临床护理中的实施，仍然需要与相关利益相关者进行实证研究和咨询，以进一步了解和解决相关的伦理问题。
Digital phenotyping (also known as personal sensing, intelligent sensing, or body computing) involves the collection of biometric and personal data in situ from digital devices, such as smartphones, wearables, or social media, to measure behavior or other health indicators. The collected data are analyzed to generate moment-by-moment quantification of a person’s mental state and potentially predict future mental states. Digital phenotyping projects incorporate data from multiple sources, such as electronic health records, biometric scans, or genetic testing. As digital phenotyping tools can be used to study and predict behavior, they are of increasing interest for a range of consumer, government, and health care applications. In clinical care, digital phenotyping is expected to improve mental health diagnoses and treatment. At the same time, mental health applications of digital phenotyping present significant areas of ethical concern, particularly in terms of privacy and data protection, consent, bias, and accountability. This study aims to develop consensus statements regarding key areas of ethical guidance for mental health applications of digital phenotyping in the United States. We used a modified Delphi technique to identify the emerging ethical challenges posed by digital phenotyping for mental health applications and to formulate guidance for addressing these challenges. Experts in digital phenotyping, data science, mental health, law, and ethics participated as panelists in the study. The panel arrived at consensus recommendations through an iterative process involving interviews and surveys. The panelists focused primarily on clinical applications for digital phenotyping for mental health but also included recommendations regarding transparency and data protection to address potential areas of misuse of digital phenotyping data outside of the health care domain. The findings of this study showed strong agreement related to these ethical issues in the development of mental health applications of digital phenotyping: privacy, transparency, consent, accountability, and fairness. Consensus regarding the recommendation statements was strongest when the guidance was stated broadly enough to accommodate a range of potential applications. The privacy and data protection issues that the Delphi participants found particularly critical to address related to the perceived inadequacies of current regulations and frameworks for protecting sensitive personal information and the potential for sale and analysis of personal data outside of health systems. The Delphi study found agreement on a number of ethical issues to prioritize in the development of digital phenotyping for mental health applications. The Delphi consensus statements identified general recommendations and principles regarding the ethical application of digital phenotyping to mental health. As digital phenotyping for mental health is implemented in clinical care, there remains a need for empirical research and consultation with relevant stakeholders to further understand and address relevant ethical issues.
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