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Ethical dilemmas posed by mobile health and machine learning in psychiatry research

机译:精神病学研究中移动健康和机器学习带来的伦理困境

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摘要

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.
机译:数字技术在精神病学研究中的应用正在迅速导致移动医疗领域的新发现和新功能。但是,被动地收集有关研究参与者的大量详细信息的机会的增加,以及使机器学习模型能够处理此类信息的统计技术的进步,都引起了有关研究人员在以下方面的职责的新的伦理困境:(i)监测不良事件和相应地干预; (ii)获得充分知情的自愿同意; (iii)保护参与者的隐私; (iv)增强强大的机器学习模型的透明度,以确保它们可以在道德上公平地应用于精神病治疗。这篇评论重点介绍了流动健康研究中出现的道德挑战和尚未解决的伦理问题,并就流动健康研究人员如何在实践中解决这些问题提供了建议。最终,希望是这次审查将有助于继续讨论如何在精神病学领域实现移动医疗研究的最佳实践。

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