Ethical dilemmas posed by mobile health and machine learning in psychiatry research
Ethical dilemmas posed by mobile health and machine learning in psychiatry research
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DOI：
10.2471/blt.19.237107
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发表时间：
2020-04-01
影响因子：
11.1
通讯作者：
Coppersmith, Daniel D. L.
中科院分区：
文献类型：
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作者：
Jacobson, Nicholas C.;Bentley, Kate H.;Coppersmith, Daniel D. L.
数字技术在精神病学研究中的应用正在迅速导致移动的健康领域的新发现和新能力。然而，被动收集研究参与者大量详细信息的机会增加，加上统计技术的进步，使机器学习模型能够处理这些信息，这给研究人员的职责带来了新的伦理困境：（i）监测不良事件并进行相应干预;（ii）获得完全知情的自愿同意;（iii）保护参与者的隐私;（iv）保护参与者的隐私。以及（iv）增加强大的机器学习模型的透明度，以确保它们可以在道德和公平的情况下应用于精神病护理。这篇综述强调了移动的健康研究中出现的伦理挑战和未解决的伦理问题，并就移动的健康研究人员如何在实践中解决这些问题提出了建议。最终，希望这篇综述将有助于继续讨论如何在精神病学中实现移动的健康研究的最佳实践。
The application of digital technology to psychiatry research is rapidly leading to new discoveries and capabilities in the field of mobile health. However, the increase in opportunities to passively collect vast amounts of detailed information on study participants coupled with advances in statistical techniques that enable machine learning models to process such information has raised novel ethical dilemmas regarding researchers' duties to: (i) monitor adverse events and intervene accordingly; (ii) obtain fully informed, voluntary consent; (iii) protect the privacy of participants; and (iv) increase the transparency of powerful, machine learning models to ensure they can be applied ethically and fairly in psychiatric care. This review highlights emerging ethical challenges and unresolved ethical questions in mobile health research and provides recommendations on how mobile health researchers can address these issues in practice. Ultimately, the hope is that this review will facilitate continued discussion on how to achieve best practice in mobile health research within psychiatry.