The ELDERS Research Team conducts research on cognitive impairment in older adults, with a particular focus on early identification, risk stratification, intervention optimisation, and real-world translation. Our work examines the dynamic interplay between social networks, health behaviours, and individual cognitive and physiological processes across the trajectory of cognitive decline. By integrating these perspectives, we aim to develop evidence-based approaches that support screening, management, intervention delivery, and decision-making in both community and healthcare settings. A central mission of the team is to translate rigorous research into practical, scalable solutions that can be implemented in real-world systems.
Our research spans three closely integrated areas. First, early identification and digital marker development, with an emphasis on identifying risk for cognitive impairment in older adults through behavioural and digital signal extraction, predictive stratification, and the development of scalable early screening tools. This work supports the identification of high-risk populations, cohort management, and pre-clinical or community-based screening. Second, patient–family collaborative intervention models, addressing real-world challenges such as suboptimal adherence, difficulties in long-term management, and variable intervention effectiveness in community settings. We design and evaluate intervention strategies that actively engage patients, families, and community resources to improve participation and sustain long-term outcomes. Third, strategy modelling and value-based evaluation, in which we leverage real-world data to conduct modelling, simulation, implementation science research, and health economic analyses, providing quantitative evidence to inform clinical practice optimisation, resource allocation efficiency, and health policy decision-making.
The team is interdisciplinary, bringing together expertise from public health, clinical medicine, biostatistics, computer science, and nursing, and is well positioned to conduct both methodological and applied research on complex real-world problems. Core collaborators include faculty and researchers from Sun Yat-sen University, Jinan University, and University College London. We also maintain long-term collaborations with Centres for Disease Control, mental health centres, healthcare providers, and health administration agencies. These partnerships enable close alignment of research with population-level needs and support the implementation of large-scale studies and real-world projects at the intersection of clinical care and public health practice.
We welcome collaboration with hospitals, academic institutions, public health agencies, industry partners, and other stakeholders interested in cognitive health and ageing. Priority areas for collaboration include early screening and risk stratification of cognitive impairment; optimisation of patient- and caregiver-involved intervention strategies; evaluation of real-world effectiveness and the value and efficiency of resource use; digital health programmes integrated across community and healthcare settings; and methodological support grounded in implementation science and health economic evaluation. Building on our existing research platforms, the team can provide integrated support across study design, data analysis, and implementation evaluation to facilitate the translation of research findings into real-world practice. Collaborations may begin with pilot studies and, based on shared objectives and emerging evidence, expand into multi-centre studies, regional programmes, or longer-term strategic partnerships.
For further information or collaboration inquiries, please contact ruinisunn@163.com.
Additional information about the team is available at: https://elderslab.github.io
ELDERS研究团队聚焦面向真实世界的老年认知障碍早期识别、风险分层、干预优化与应用转化，关注老年患者从社区筛查、临床评估到长期治疗与管理全过程中的实际需求，致力于将高质量研究转化为可落地、可持续且可规模化的筛查、管理、干预和决策支持方案。
团队具备三类核心能力。第一，早期识别与数字标志物开发。围绕老年认知障碍风险识别、行为与数字信号提取、分层预测和早筛工具开发，团队致力于构建可规模化应用的数字化识别方案，服务于高风险人群发现、队列管理和临床前置筛查及后续诊疗路径衔接。第二，患者—家庭协同干预与长期管理。围绕依从性不足、长期管理困难和社区场景下干预效果不稳定等现实问题，团队开发并评估患者、家庭、社区和医疗服务多方参与的支持模式，改善认知与日常生活功能，关注干预效果在真实世界中的维持。第三，策略模拟与价值评估。团队具备基于真实世界数据开展模型构建、实施科学研究和卫生经济学评价的能力，综合评估干预或治疗方案的实际效果、实施可行性、资源利用与成本效益，为服务流程优化、资源配置和卫生政策制定提供量化支持。
团队成员来自公共卫生、临床医学、医学统计、计算机科学、护理学等多个学科，具有跨学科协同开展复杂研究的基础。团队欢迎与医院、药企、科研机构、公共卫生部门及产业合作伙伴围绕以下方向开展合作：老年认知障碍的社区早筛与风险分层，患者与照护者参与的治疗支持及依从性优化，真实世界治疗效果与患者功能结局评价，社区与医疗场景衔接的长期管理和数字健康项目，及基于实施科学和卫生经济学的可及性、资源利用与成本效益研究。
如希望进一步了解团队研究基础、代表性成果和合作模式，欢迎联系团队沟通：ruinisunn@163.com。
团队介绍详见：https://elderslab.github.io