Diverse experts' perspectives on ethical issues of using machine learning to predict HIV/AIDS risk in sub-Saharan Africa: a modified Delphi study.
Diverse experts' perspectives on ethical issues of using machine learning to predict HIV/AIDS risk in sub-Saharan Africa: a modified Delphi study.
复制标题
DOI：
10.1136/bmjopen-2021-052287
复制
发表时间：
2021-07-28
期刊：
影响因子：
2.9
通讯作者：
Cho MK
中科院分区：
文献类型：
--
作者：
Nichol AA;Bendavid E;Mutenherwa F;Patel C;Cho MK
为了更好地了解不同专家对美国国立卫生研究院资助的正在进行的研究的伦理影响的看法，该研究利用机器学习根据公开的人口统计和健康调查数据预测撒哈拉以南非洲 (SSA) 的艾滋病毒/艾滋病风险。使用修改后的德尔菲方法在在线专家小组中进行三轮半结构化调查。信息学、非洲公共卫生、艾滋病毒/艾滋病和生物伦理学领域的专家应邀参加。在 5 点单极李克特量表上对道德问题的相关性的感知重要性或一致意见。定性数据分析确定了与道德问题相关的新兴主题，并制定了道德框架和针对开放式问题的建议。 35位受邀专家中，有22位参加了在线专家小组（63%）。新兴主题是将非洲研究人员纳入研究设计、分析和传播的各个方面，以识别和解决当地背景问题以及社区的参与。专家们重点关注与健康和科学专业人士的合作，以解决风险、收益和研究结果的交流。受访者优先考虑减轻研究参与者的耻辱感，但也认识到隐私与传播研究结果以实现公共健康效益之间的权衡。建议采取负责任的结果沟通策略，包括在介绍结果时仔细选择词语，以及有限地向公共卫生规划者等需要了解的利益相关者传播。专家们确定了非洲特有的道德问题，并对敏感的公开数据和解决这些问题的策略进行了研究。这些发现可用于为伦理实施框架提供信息，并提供针对特定研究阶段的建议，说明如何使用公开数据进行基于机器学习的预测分析，以预测 SSA 中的艾滋病毒/艾滋病风险。
To better understand diverse experts’ views about the ethical implications of ongoing research funded by the National Institutes of Health that uses machine learning to predict HIV/AIDS risk in sub-Saharan Africa (SSA) based on publicly available Demographic and Health Surveys data. Three rounds of semi-structured surveys in an online expert panel using a modified Delphi approach. Experts in informatics, African public health and HIV/AIDS and bioethics were invited to participate. Perceived importance of or agreement about relevance of ethical issues on 5-point unipolar Likert scales. Qualitative data analysis identified emergent themes related to ethical issues and development of an ethical framework and recommendations for open-ended questions. Of the 35 invited experts, 22 participated in the online expert panel (63%). Emergent themes were the inclusion of African researchers in all aspects of study design, analysis and dissemination to identify and address local contextual issues, as well as engagement of communities. Experts focused on engagement with health and science professionals to address risks, benefits and communication of findings. Respondents prioritised the mitigation of stigma to research participants but recognised trade-offs between privacy and the need to disseminate findings to realise public health benefits. Strategies for responsible communication of results were suggested, including careful word choice in presentation of results and limited dissemination to need-to-know stakeholders such as public health planners. Experts identified ethical issues specific to the African context and to research on sensitive, publicly available data and strategies for addressing these issues. These findings can be used to inform an ethical implementation framework with research stage-specific recommendations on how to use publicly available data for machine learning-based predictive analytics to predict HIV/AIDS risk in SSA.
登录
查看更多内容
DOI：
10.1017/gheg.2017.9
发表时间：
2017
期刊：
Global health, epidemiology and genomics
影响因子：
--
作者：
Tindana P;Campbell M;Marshall P;Littler K;Vincent R;Seeley J;de Vries J;Kamuya D;H3Africa Community Engagement Working Group
通讯作者：
H3Africa Community Engagement Working Group
影响因子：
1.9
作者：
Virani, Alice Hawkins;Longstaff, Holly
通讯作者：
Longstaff, Holly
影响因子：
2.7
作者：
Nyirenda D;Sariola S;Kingori P;Squire B;Bandawe C;Parker M;Desmond N
通讯作者：
Desmond N
DOI：
10.1080/11287462.2019.1703504
发表时间：
2020-01-01
期刊：
Global bioethics = Problemi di bioetica
影响因子：
--
作者：
Adhikari, Bipin;Pell, Christopher;Cheah, Phaik Yeong
通讯作者：
Cheah, Phaik Yeong
影响因子：
3.8
作者：
Patel, Chirag J.;Bhattacharya, Jay;Bendavid, Eran
通讯作者：
Bendavid, Eran