Title: Frailty progression and maintaining independence to age in place: can routine data help?
During old age, people can struggle to remain independent and in their own homes, and this is often driven by social determinants of health.
This project will use mixed-methods and PPIE to explore social determinants of health, such as caring and housing, and how these support ageing in place. It will also explore how health data collected routinely by the NHS can help in frailty prevention, prediction, and clinical management. This would involve engaging with different stakeholders such as clinicians, community-dwelling older adults, persons with frailty, and possibly caregivers.
September 2022 - September 2025
Dunhill Medical trust / NiHR / University of Manchester PhD Studentship
The University of Manchester
My academic background is in biomedical science and global health. I worked in a digital health start-up based in India for two years where I created content on digital health, artificial intelligence, and preventive health behaviours. This included scientific journal articles, long-form blogs, microblogs, infographics, social media posts, and white papers. I look forward to widening my skills set by engaging in mixed-methods research during my PhD.
Dlima SD, Shevade S, Menezes SR, Ganju A. Digital Phenotyping in Health Using Machine Learning Approaches: Scoping Review. JMIR Bioinform Biotech 2022;3(1):e39618. doi: 10.2196/39618
Ganju A, Menezes SR, Dlima SD, Shevase S. Machine learning-driven recommender systems to improve engagement with health content in a low-resource setting: Poster. ACM SIGCAS Conference on Computing and Sustainable Societies (COMPASS) [Preprint]. Doi: 10.1145/3460112.3471976