文献检索文档翻译深度研究
Suppr Zotero 插件Zotero 插件
邀请有礼套餐&价格历史记录

新学期,新优惠

限时优惠:9月1日-9月22日

30天高级会员仅需29元

1天体验卡首发特惠仅需5.99元

了解详情
不再提醒
插件&应用
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
高级版
套餐订阅购买积分包
AI 工具
文献检索文档翻译深度研究
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 @ 2025

有条件地为阳性:公众对使用健康数据进行人工智能研究的看法的定性研究。

Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research.

机构信息

Department of Bioethics, Hospital for Sick Children, Toronto, Ontario, Canada.

Health Team, Vector Institute, Toronto, Ontario, Canada.

出版信息

BMJ Open. 2020 Oct 28;10(10):e039798. doi: 10.1136/bmjopen-2020-039798.


DOI:10.1136/bmjopen-2020-039798
PMID:33115901
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7594363/
Abstract

OBJECTIVES: Given widespread interest in applying artificial intelligence (AI) to health data to improve patient care and health system efficiency, there is a need to understand the perspectives of the general public regarding the use of health data in AI research. DESIGN: A qualitative study involving six focus groups with members of the public. Participants discussed their views about AI in general, then were asked to share their thoughts about three realistic health AI research scenarios. Data were analysed using qualitative description thematic analysis. SETTINGS: Two cities in Ontario, Canada: Sudbury (400 km north of Toronto) and Mississauga (part of the Greater Toronto Area). PARTICIPANTS: Forty-one purposively sampled members of the public (21M:20F, 25-65 years, median age 40). RESULTS: Participants had low levels of prior knowledge of AI and mixed, mostly negative, perceptions of AI in general. Most endorsed using data for health AI research when there is strong potential for public benefit, providing that concerns about privacy, commercial motives and other risks were addressed. Inductive thematic analysis identified AI-specific hopes (eg, potential for faster and more accurate analyses, ability to use more data), fears (eg, loss of human touch, skill depreciation from over-reliance on machines) and conditions (eg, human verification of computer-aided decisions, transparency). There were mixed views about whether data subject consent is required for health AI research, with most participants wanting to know if, how and by whom their data were used. Though it was not an objective of the study, realistic health AI scenarios were found to have an educational effect. CONCLUSIONS: Notwithstanding concerns and limited knowledge about AI in general, most members of the general public in six focus groups in Ontario, Canada perceived benefits from health AI and conditionally supported the use of health data for AI research.

摘要

目的:鉴于人们普遍希望将人工智能(AI)应用于健康数据,以改善患者护理和提高医疗体系效率,因此有必要了解公众对在 AI 研究中使用健康数据的看法。

设计:一项涉及 6 个焦点小组的定性研究,参与者为公众成员。首先,参与者讨论了他们对 AI 的总体看法,然后被要求分享他们对三个现实的健康 AI 研究场景的想法。使用定性描述性主题分析对数据进行分析。

地点:加拿大安大略省的两个城市:萨德伯里(多伦多以北 400 公里)和密西沙加(大多伦多地区的一部分)。

参与者:41 名精心挑选的公众成员(21 名男性:20 名女性,25-65 岁,中位数年龄 40 岁)。

结果:参与者对 AI 的先前知识水平较低,对 AI 的总体看法褒贬不一。当健康 AI 研究具有很大的公共利益潜力时,大多数人赞成使用数据,但前提是要解决隐私、商业动机和其他风险问题。归纳主题分析确定了 AI 特有的希望(例如,更快、更准确分析的潜力,能够使用更多数据的能力)、恐惧(例如,失去人机交互,过度依赖机器导致技能贬值)和条件(例如,计算机辅助决策的人工验证,透明度)。对于健康 AI 研究是否需要数据主体同意,存在不同意见,大多数参与者希望知道他们的数据是如何以及由谁使用的。尽管这不是研究的目标,但发现现实的健康 AI 场景具有教育效果。

结论:尽管公众对 AI 普遍存在担忧和有限的了解,但在加拿大安大略省的六个焦点小组中,大多数普通公众认为健康 AI 有好处,并在一定条件下支持使用健康数据进行 AI 研究。

相似文献

[1]
Conditionally positive: a qualitative study of public perceptions about using health data for artificial intelligence research.

BMJ Open. 2020-10-28

[2]
Multi-stakeholder preferences for the use of artificial intelligence in healthcare: A systematic review and thematic analysis.

Soc Sci Med. 2023-12

[3]
Artificial intelligence in primary care practice: Qualitative study to understand perspectives on using AI to derive patient social data.

Can Fam Physician. 2024

[4]
Perceptions of Artificial Intelligence Use in Primary Care: A Qualitative Study with Providers and Staff of Ontario Community Health Centres.

J Am Board Fam Med. 2023-4-3

[5]
Ethical concerns around use of artificial intelligence in health care research from the perspective of patients with meningioma, caregivers and health care providers: a qualitative study.

CMAJ Open. 2020

[6]
Surveying Public Perceptions of Artificial Intelligence in Health Care in the United States: Systematic Review.

J Med Internet Res. 2023-4-4

[7]
Centering Public Perceptions on Translating AI Into Clinical Practice: Patient and Public Involvement and Engagement Consultation Focus Group Study.

J Med Internet Res. 2023-9-26

[8]
Patient Perceptions on Data Sharing and Applying Artificial Intelligence to Health Care Data: Cross-sectional Survey.

J Med Internet Res. 2021-8-26

[9]
Physical therapists' perceptions and attitudes towards artificial intelligence in healthcare and rehabilitation: A qualitative study.

Musculoskelet Sci Pract. 2024-10

[10]
Singapore radiographers' perceptions and expectations of artificial intelligence - A qualitative study.

J Med Imaging Radiat Sci. 2022-12

引用本文的文献

[1]
Value of using artificial intelligence derived clusters by health and social care need in primary care: A qualitative interview study with patients living with multiple long-term conditions, carers and health care professionals.

J Multimorb Comorb. 2025-6-24

[2]
Patients' Perceptions of Artificial Intelligence Acceptance, Challenges, and Use in Medical Care: Qualitative Study.

J Med Internet Res. 2025-5-15

[3]
Public Awareness of and Attitudes Toward the Use of AI in Pathology Research and Practice: Mixed Methods Study.

J Med Internet Res. 2025-4-2

[4]
Health data social licence: An inclusive process to learn more about the perspectives of experienced public and patient advisors.

Int J Popul Data Sci. 2024-4-17

[5]
Understanding Public Judgements on Artificial Intelligence in Healthcare: Dialogue Group Findings From Australia.

Health Expect. 2025-4

[6]
Artificial Intelligence in Medical Care - Patients' Perceptions on Caregiving Relationships and Ethics: A Qualitative Study.

Health Expect. 2025-4

[7]
Acceptability of artificial intelligence in breast screening: focus groups with the screening-eligible population in England.

BMJ Public Health. 2024-12-12

[8]
Attitudes toward artificial intelligence and robots in healthcare in the general population: a qualitative study.

Front Digit Health. 2025-1-27

[9]
Analysis of public perceptions on the use of artificial intelligence in genomic medicine.

Hum Genomics. 2024-11-18

[10]
Trustworthy and ethical AI-enabled cardiovascular care: a rapid review.

BMC Med Inform Decis Mak. 2024-9-4

本文引用的文献

[1]
Sharing linked data sets for research: results from a deliberative public engagement event in British Columbia, Canada.

Int J Popul Data Sci. 2019-5-7

[2]
Consensus Statement on Public Involvement and Engagement with Data Intensive Health Research.

Int J Popul Data Sci. 2019-2-12

[3]
Notches on the dial: a call to action to develop plain language communication with the public about users and uses of health data.

Int J Popul Data Sci. 2019-8-5

[4]
A Review of Challenges and Opportunities in Machine Learning for Health.

AMIA Jt Summits Transl Sci Proc. 2020-5-30

[5]
Patient trust must come at the top of researchers' priority list.

Nat Med. 2020-3

[6]
Patient Perspectives on the Use of Artificial Intelligence for Skin Cancer Screening: A Qualitative Study.

JAMA Dermatol. 2020-5-1

[7]
Patient Perspectives on the Use of Artificial Intelligence.

JAMA Dermatol. 2020-5-1

[8]
Ethical concerns around use of artificial intelligence in health care research from the perspective of patients with meningioma, caregivers and health care providers: a qualitative study.

CMAJ Open. 2020

[9]
Patients' views on the implementation of artificial intelligence in radiology: development and validation of a standardized questionnaire.

Eur Radiol. 2019-11-8

[10]
Estimating the success of re-identifications in incomplete datasets using generative models.

Nat Commun. 2019-7-23

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

推荐工具

医学文档翻译智能文献检索