Ford Elizabeth, Shepherd Scarlett, Jones Kerina, Hassan Lamiece
Department of Primary Care and Public Health, Brighton and Sussex Medical School, Brighton, United Kingdom.
Population Data Science, Medical School, Swansea University, Swansea, United Kingdom.
Front Digit Health. 2021 Jan 26;2:592237. doi: 10.3389/fdgth.2020.592237. eCollection 2020.
Text-mining techniques are advancing all the time and vast corpora of social media text can be analyzed for users' views and experiences related to their health. There is great promise for new insights into health issues such as drug side effects and spread of disease, as well as patient experiences of health conditions and health care. However, this emerging field lacks ethical consensus and guidance. We aimed to bring together a comprehensive body of opinion, views, and recommendations in this area so that academic researchers new to the field can understand relevant ethical issues. After registration of a protocol in PROSPERO, three parallel systematic searches were conducted, to identify academic articles comprising commentaries, opinion, and recommendations on ethical practice in social media text mining for health research and gray literature guidelines and recommendations. These were integrated with social media users' views from qualitative studies. Papers and reports that met the inclusion criteria were analyzed thematically to identify key themes, and an overarching set of themes was deduced. A total of 47 reports and articles were reviewed, and eight themes were identified. Commentators suggested that publicly posted social media data could be used without consent and formal research ethics approval, provided that the anonymity of users is ensured, although we note that privacy settings are difficult for users to navigate on some sites. Even without the need for formal approvals, we note ethical issues: to actively identify and minimize possible harms, to conduct research for public benefit rather than private gain, to ensure transparency and quality of data access and analysis methods, and to abide by the law and terms and conditions of social media sites. Although social media text mining can often legally and reasonably proceed without formal ethics approvals, we recommend improving ethical standards in health-related research by increasing transparency of the purpose of research, data access, and analysis methods; consultation with social media users and target groups to identify and mitigate against potential harms that could arise; and ensuring the anonymity of social media users.
文本挖掘技术一直在进步,大量社交媒体文本语料库可用于分析用户与健康相关的观点和经历。这为深入了解药物副作用和疾病传播等健康问题以及患者的健康状况和医疗保健体验带来了巨大希望。然而,这个新兴领域缺乏伦理共识和指导。我们旨在汇集该领域全面的意见、观点和建议,以便该领域的新学术研究人员能够理解相关伦理问题。在PROSPERO中注册了一项方案后,进行了三项并行的系统检索,以识别包含关于社交媒体文本挖掘用于健康研究的伦理实践的评论、意见和建议以及灰色文献指南和建议的学术文章。这些与定性研究中社交媒体用户的观点相结合。对符合纳入标准的论文和报告进行主题分析以确定关键主题,并推导出一组总体主题。共审查了47份报告和文章,确定了八个主题。评论者建议,在确保用户匿名的情况下,无需征得同意和获得正式的研究伦理批准即可使用公开发布的社交媒体数据,不过我们注意到在某些网站上用户难以操作隐私设置。即使无需正式批准,我们也注意到存在伦理问题:积极识别并尽量减少可能的危害,进行公益而非私利的研究,确保数据获取和分析方法的透明度和质量,并遵守法律以及社交媒体网站的条款和条件。尽管社交媒体文本挖掘通常无需正式的伦理批准即可合法且合理地进行,但我们建议通过提高研究目的、数据获取和分析方法的透明度;与社交媒体用户和目标群体协商以识别和减轻可能出现的潜在危害;以及确保社交媒体用户的匿名性来提高健康相关研究的伦理标准。