• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

相似文献

1
An Ethics Checklist for Digital Health Research in Psychiatry: Viewpoint.精神科数字健康研究的伦理学清单:观点。
J Med Internet Res. 2022 Feb 9;24(2):e31146. doi: 10.2196/31146.
2
Returning Individual Research Results from Digital Phenotyping in Psychiatry.精神医学中数字化表型研究的个体研究结果回报。
Am J Bioeth. 2024 Feb;24(2):69-90. doi: 10.1080/15265161.2023.2180109. Epub 2023 May 8.
3
Ethical Development of Digital Phenotyping Tools for Mental Health Applications: Delphi Study.数字表型工具在精神健康应用中的伦理发展:德尔菲研究。
JMIR Mhealth Uhealth. 2021 Jul 28;9(7):e27343. doi: 10.2196/27343.
4
[The origin of informed consent].[知情同意的起源]
Acta Otorhinolaryngol Ital. 2005 Oct;25(5):312-27.
5
Ethical, legal, and social implications of digital health: A needs assessment from the Society of Behavioral Medicine to inform capacity building for behavioral scientists.数字健康的伦理、法律和社会影响:来自行为医学学会的需求评估,以告知行为科学家的能力建设。
Transl Behav Med. 2024 Feb 23;14(3):189-196. doi: 10.1093/tbm/ibad076.
6
Developing a framework for the ethical design and conduct of pragmatic trials in healthcare: a mixed methods research protocol.制定医疗保健中实用临床试验的伦理设计和实施框架:混合方法研究方案。
Trials. 2018 Sep 27;19(1):525. doi: 10.1186/s13063-018-2895-x.
7
International Society of Psychiatric Genetics Ethics Committee: Issues facing us.国际精神遗传学协会伦理委员会:我们面临的问题。
Am J Med Genet B Neuropsychiatr Genet. 2019 Dec;180(8):543-554. doi: 10.1002/ajmg.b.32736. Epub 2019 May 23.
8
The future of Cochrane Neonatal.考克兰新生儿协作网的未来。
Early Hum Dev. 2020 Nov;150:105191. doi: 10.1016/j.earlhumdev.2020.105191. Epub 2020 Sep 12.
9
Prioritising African perspectives in psychiatric genomics research: Issues of translation and informed consent.在精神疾病基因组学研究中优先考虑非洲视角:翻译和知情同意问题。
Dev World Bioeth. 2020 Sep;20(3):139-149. doi: 10.1111/dewb.12248. Epub 2019 Nov 14.
10
Ethical, Legal and Social Issues of Digital Phenotyping as a Future Solution for Present-Day Challenges: A Scoping Review.数字表型作为解决当前挑战的未来解决方案的伦理、法律和社会问题:范围综述。
Sci Eng Ethics. 2021 Dec 20;28(1):1. doi: 10.1007/s11948-021-00354-1.

引用本文的文献

1
Addressing the Ethical, Legal, and Social Issues of Healthtech in Education: Insights From Japan.探讨健康科技在教育领域的伦理、法律和社会问题:来自日本的见解。
JMIR Form Res. 2025 Jul 18;9:e72781. doi: 10.2196/72781.
2
Digital health technologies in the accelerating medicines Partnership® Schizophrenia Program.加速药物合作组织精神分裂症项目中的数字健康技术
Schizophrenia (Heidelb). 2025 Jun 3;11(1):83. doi: 10.1038/s41537-025-00599-w.
3
Transforming Digital Phenotyping Raw Data Into Actionable Biomarkers, Quality Metrics, and Data Visualizations Using Cortex Software Package: Tutorial.使用 Cortex 软件包将数字表型原始数据转化为可操作的生物标志物、质量指标和数据可视化:教程。
J Med Internet Res. 2024 Aug 23;26:e58502. doi: 10.2196/58502.
4
Expanding a Behavioral View on Digital Health Access: Drivers and Strategies to Promote Equity.拓展数字健康获取的行为视角:促进公平的驱动因素与策略
J Med Internet Res. 2024 Aug 1;26:e51355. doi: 10.2196/51355.
5
Reporting guidelines in medical artificial intelligence: a systematic review and meta-analysis.医学人工智能报告指南:系统评价与荟萃分析
Commun Med (Lond). 2024 Apr 11;4(1):71. doi: 10.1038/s43856-024-00492-0.
6
Navigating ethical challenges in psychological research involving digital remote technologies and people who use alcohol or drugs.探索涉及使用酒精或毒品的人群和数字远程技术的心理研究中的伦理挑战。
Am Psychol. 2024 Jan;79(1):24-38. doi: 10.1037/amp0001193.
7
Development, Reliability, and Structural Validity of the Scale for Knowledge, Attitude, and Practice in Ethics Implementation Among AI Researchers: Cross-Sectional Study.人工智能研究人员伦理实践知识、态度与行为量表的编制、信效度研究:横断面研究
JMIR Form Res. 2023 Oct 26;7:e42202. doi: 10.2196/42202.
8
Ethics of artificial intelligence in prenatal and pediatric genomic medicine.产前和儿科基因组医学中的人工智能伦理
J Community Genet. 2024 Feb;15(1):13-24. doi: 10.1007/s12687-023-00678-4. Epub 2023 Oct 5.
9
Selecting and describing control conditions in mobile health randomized controlled trials: a proposed typology.移动健康随机对照试验中对照条件的选择与描述:一种拟议的类型学
NPJ Digit Med. 2023 Sep 30;6(1):181. doi: 10.1038/s41746-023-00923-7.
10
The Use of Mobile Assessments for Monitoring Mental Health in Youth: Umbrella Review.移动评估在青少年心理健康监测中的应用:伞式综述。
J Med Internet Res. 2023 Sep 19;25:e45540. doi: 10.2196/45540.

本文引用的文献

1
GENETIC DUTIES.遗传职责。
William Mary Law Rev. 2020 Oct;62(1):143-211.
2
Seeing through health information technology: the need for transparency in software, algorithms, data privacy, and regulation.看穿健康信息技术:软件、算法、数据隐私及监管方面的透明度需求。
J Law Biosci. 2020 Oct 9;7(1):lsaa062. doi: 10.1093/jlb/lsaa062. eCollection 2020 Jan-Dec.
3
A FAUSTIAN BARGAIN THAT UNDERMINES RESEARCH PARTICIPANTS' PRIVACY RIGHTS AND RETURN OF RESULTS.一项破坏研究参与者隐私权和结果反馈的浮士德式交易。
Fla Law Rev. 2019 Sep;71(5):1281-1345.
4
The Urgency of Justice in Research: Beyond COVID-19.研究中的正义紧迫性:超越 COVID-19。
Trends Mol Med. 2021 Feb;27(2):97-100. doi: 10.1016/j.molmed.2020.11.004. Epub 2020 Nov 17.
5
REVISITING HEALTH INFORMATION TECHNOLOGY ETHICAL, LEGAL, and SOCIAL ISSUES and EVALUATION: TELEHEALTH/TELEMEDICINE and COVID-19.重新审视健康信息技术的伦理、法律和社会问题及评估:远程医疗/远程医学和 COVID-19。
Int J Med Inform. 2020 Nov;143:104239. doi: 10.1016/j.ijmedinf.2020.104239. Epub 2020 Jul 31.
6
Mobile Research Applications and State Research Laws.移动研究应用与州研究法规。
J Law Med Ethics. 2020 Mar;48(1_suppl):82-86. doi: 10.1177/1073110520917032.
7
Assessing Real-Time Moderation for Developing Adaptive Mobile Health Interventions for Medical Interns: Micro-Randomized Trial.评估为医学实习生开发适应性移动健康干预措施的实时审核:微型随机试验
J Med Internet Res. 2020 Mar 31;22(3):e15033. doi: 10.2196/15033.
8
The case for implementing sustainable routine, population-level genomic reanalysis.实施可持续的常规、人群水平基因组重新分析的理由。
Genet Med. 2020 Apr;22(4):815-816. doi: 10.1038/s41436-019-0719-3. Epub 2019 Dec 12.
9
Actionable digital phenotyping: a framework for the delivery of just-in-time and longitudinal interventions in clinical healthcare.可操作的数字表型分析:临床医疗中即时和纵向干预的交付框架。
Mhealth. 2019 Aug 12;5:25. doi: 10.21037/mhealth.2019.07.04. eCollection 2019.
10
Why include the humanities in medical studies?为什么要将人文学科纳入医学研究?
Intern Emerg Med. 2019 Oct;14(7):1013-1017. doi: 10.1007/s11739-019-02131-2. Epub 2019 Jun 20.

精神科数字健康研究的伦理学清单:观点。

An Ethics Checklist for Digital Health Research in Psychiatry: Viewpoint.

机构信息

Harvard Medical School, Boston, MA, United States.

Law School, University of Minnesota, Minneapolis, MN, United States.

出版信息

J Med Internet Res. 2022 Feb 9;24(2):e31146. doi: 10.2196/31146.

DOI:10.2196/31146
PMID:35138261
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8867294/
Abstract

BACKGROUND

Psychiatry has long needed a better and more scalable way to capture the dynamics of behavior and its disturbances, quantitatively across multiple data channels, at high temporal resolution in real time. By combining 24/7 data-on location, movement, email and text communications, and social media-with brain scans, genetics, genomics, neuropsychological batteries, and clinical interviews, researchers will have an unprecedented amount of objective, individual-level data. Analyzing these data with ever-evolving artificial intelligence could one day include bringing interventions to patients where they are in the real world in a convenient, efficient, effective, and timely way. Yet, the road to this innovative future is fraught with ethical dilemmas as well as ethical, legal, and social implications (ELSI).

OBJECTIVE

The goal of the Ethics Checklist is to promote careful design and execution of research. It is not meant to mandate particular research designs; indeed, at this early stage and without consensus guidance, there are a range of reasonable choices researchers may make. However, the checklist is meant to make those ethical choices explicit, and to require researchers to give reasons for their decisions related to ELSI issues. The Ethics Checklist is primarily focused on procedural safeguards, such as consulting with experts outside the research group and documenting standard operating procedures for clearly actionable data (eg, expressed suicidality) within written research protocols.

METHODS

We explored the ELSI of digital health research in psychiatry, with a particular focus on what we label "deep phenotyping" psychiatric research, which combines the potential for virtually boundless data collection and increasingly sophisticated techniques to analyze those data. We convened an interdisciplinary expert stakeholder workshop in May 2020, and this checklist emerges out of that dialogue.

RESULTS

Consistent with recent ELSI analyses, we find that existing ethical guidance and legal regulations are not sufficient for deep phenotyping research in psychiatry. At present, there are regulatory gaps, inconsistencies across research teams in ethics protocols, and a lack of consensus among institutional review boards on when and how deep phenotyping research should proceed. We thus developed a new instrument, an Ethics Checklist for Digital Health Research in Psychiatry ("the Ethics Checklist"). The Ethics Checklist is composed of 20 key questions, subdivided into 6 interrelated domains: (1) informed consent; (2) equity, diversity, and access; (3) privacy and partnerships; (4) regulation and law; (5) return of results; and (6) duty to warn and duty to report.

CONCLUSIONS

Deep phenotyping research offers a vision for vastly more effective care for people with, or at risk for, psychiatric disease. The potential perils en route to realizing this vision are significant; however, and researchers must be willing to address the questions in the Ethics Checklist before embarking on each leg of the journey.

摘要

背景

精神病学长期以来一直需要一种更好、更具可扩展性的方法来捕捉行为及其障碍的动态,在实时的情况下以高时间分辨率跨多个数据通道进行定量分析。通过将 24/7 的位置、运动、电子邮件和文本通信以及社交媒体数据与大脑扫描、遗传学、基因组学、神经心理学测试和临床访谈相结合,研究人员将拥有前所未有的大量客观的个体水平数据。通过不断发展的人工智能对这些数据进行分析,有朝一日可以将干预措施直接带到患者所在的现实世界,以方便、高效、有效和及时的方式。然而,这条通往创新未来的道路充满了伦理困境,以及伦理、法律和社会影响(ELSI)。

目的

该伦理检查表的目标是促进研究的精心设计和执行。它并不是要强制规定特定的研究设计;实际上,在这个早期阶段,没有共识指导,研究人员可能会做出一系列合理的选择。但是,检查表旨在明确这些伦理选择,并要求研究人员就与 ELSI 问题相关的决策给出理由。该伦理检查表主要侧重于程序保障,例如咨询研究小组以外的专家,并在书面研究方案中记录明确可操作数据(例如,表达自杀意念)的标准操作程序。

方法

我们探讨了精神病学中数字健康研究的 ELSI,特别关注我们称之为“深度表型”精神病学研究的问题,这种研究结合了几乎无限的数据收集潜力和越来越复杂的分析这些数据的技术。我们于 2020 年 5 月召开了一次跨学科专家利益相关者研讨会,本检查表就是这次对话的成果。

结果

与最近的 ELSI 分析一致,我们发现现有的伦理指导和法律法规不足以满足精神病学中深度表型研究的需要。目前,在监管方面存在差距,研究团队之间的伦理协议不一致,机构审查委员会在何时以及如何进行深度表型研究方面也缺乏共识。因此,我们开发了一种新工具,即《精神病学中数字健康研究的伦理检查表》(“伦理检查表”)。该伦理检查表由 20 个关键问题组成,分为 6 个相互关联的领域:(1)知情同意;(2)公平、多样性和可及性;(3)隐私和伙伴关系;(4)监管和法律;(5)结果回报;(6)警告和报告义务。

结论

深度表型研究为患有或有患精神病风险的人群提供了更有效的治疗方案。实现这一愿景的潜在风险巨大,然而,研究人员在开始旅程的每一步之前,都必须愿意回答伦理检查表中的问题。