用于精准公共卫生的社交媒体干预措施：前景与风险。
Social media interventions for precision public health: promises and risks.
作者信息
Dunn Adam G, Mandl Kenneth D, Coiera Enrico
机构信息
Centre for Health Informatics, Australian Institute of Health Innovation, Macquarie University, Sydney, NSW 2109, Australia.
Computational Health Informatics Program, Boston Children's Hospital, Boston, MA 02115, United States.
出版信息
NPJ Digit Med. 2018;1. doi: 10.1038/s41746-018-0054-0. Epub 2018 Sep 19.
Abstract
Social media data can be used with digital phenotyping tools to profile the attitudes, behaviours, and health outcomes of people. While there are a growing number of examples demonstrating the performance of digital phenotyping tools using social media data, little is known about their capacity to support the delivery of targeted and personalised behaviour change interventions to improve health. Similar tools are already used in marketing and politics, using individual profiling to manipulate purchasing and voting behaviours. The coupling of digital phenotyping tools and behaviour change interventions may play a more positive role in preventive medicine to improve health behaviours, but potential risks and unintended consequences may come from embedding behavioural interventions in social spaces.
摘要
社交媒体数据可与数字表型分析工具一起用于描绘人们的态度、行为和健康状况。虽然越来越多的例子展示了使用社交媒体数据的数字表型分析工具的性能，但对于它们支持提供有针对性的个性化行为改变干预措施以改善健康状况的能力却知之甚少。类似的工具已在市场营销和政治领域使用，通过个人画像来操纵购买和投票行为。数字表型分析工具与行为改变干预措施的结合在预防医学中可能会在改善健康行为方面发挥更积极的作用，但将行为干预措施嵌入社交空间可能会带来潜在风险和意外后果。
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