Burgess Romana, Boyd Andy, Davis Oliver Sp, Millard Louise Ac, Mumme Mark, Robertson Sarah, Skinner Andy, Xiao Zhuoni, Skatova Anya
Population Health Sciences, Bristol Medical School, University of Bristol, UK.
The MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK.
Int J Popul Data Sci. 2025 Jun 3;10(1):2946. doi: 10.23889/ijpds.v10i1.2946. eCollection 2025.
Linking digital footprint data into longitudinal population studies (LPS) presents an opportunity to enrich our understanding of how digitally captured behaviours relate to health traits and disease. However, this linkage introduces significant methodological challenges that require systematic exploration.
To develop a robust framework for successful digital footprint linkage into LPS, informed by discussions from a workshop from the Digital Footprints Conference 2024.
We propose a structured, four-stage framework to facilitate successful linkage of digital footprint data into LPS: (1) understand participant expectations and acceptability; (2) collect and link the data; (3) evaluate properties of the data; and (4) ensure secure and ethical access for research. This framework addresses the key methodological challenges identified at each stage, discussed through the lens of two LPS case studies: the Avon Longitudinal Study of Parents and Children and Generation Scotland.
Key methodological challenges identified include privacy and confidentiality concerns, reliance on third-party platforms, data quality issues like missing data and measurement error. We also emphasize the role of trusted research environments and synthetic datasets in enabling secure, privacy-sensitive data sharing for research.
While the linkage digital footprint data to LPS remains in early stages, our framework provides a methodological foundation for overcoming current challenges. Through iterative refinement of these methods there is significant potential to advance population-level insights into health and wellbeing.
将数字足迹数据纳入纵向人群研究（LPS）为深化我们对数字捕捉行为与健康特征及疾病之间关系的理解提供了契机。然而，这种关联带来了重大的方法学挑战，需要进行系统探索。
根据2024年数字足迹会议研讨会的讨论结果，制定一个将数字足迹成功关联到纵向人群研究的稳健框架。
我们提出一个结构化的四阶段框架，以促进数字足迹数据与纵向人群研究的成功关联：（1）了解参与者的期望和可接受性；（2）收集和关联数据；（3）评估数据属性；（4）确保研究的安全和道德访问。该框架通过两个纵向人群研究案例：雅芳亲子纵向研究和苏格兰世代研究，探讨了每个阶段所确定的关键方法学挑战。
确定的关键方法学挑战包括隐私和保密问题、对第三方平台的依赖、数据质量问题，如数据缺失和测量误差。我们还强调了可信研究环境和合成数据集在实现安全、对隐私敏感的数据共享用于研究方面的作用。
虽然将数字足迹数据与纵向人群研究的关联仍处于早期阶段，但我们的框架为克服当前挑战提供了方法学基础。通过对这些方法的迭代完善，有很大潜力推进对人群健康和福祉的洞察。
