Asthma care is commonly reactive, with treatment intensified only after symptoms have been detected by the individual and have worsened. Wearable devices may allow physiological and behavioural changes to be detected earlier, enabling patients to take preventive action through their personalised asthma action plans.
The primary aim of this PhD project will be to determine whether a smartwatch-based asthma prediction algorithm can improve asthma care and clinical outcomes compared with standard care. First, the PhD student will conduct a prospective UK validation study of the published asthma prediction algorithm with Apple devices, building on its initial development using Fitbit devices (DIGIPREDICT: https://doi.org/10.1136/bmjresp-2023-002275). Second, the student will conduct a UK randomised controlled trial evaluating whether smartwatch-based asthma risk alerts improve asthma management and clinical outcomes compared with standard care. Across the project, the student will be responsible for developing the UK study protocols, identifying appropriate UK recruitment routes and potential data sources, obtaining relevant regulatory and ethics approvals, recruiting and following up participants, managing study delivery, and undertaking data collection, cleaning, management, and analysis. The PhD may also include complementary literature reviews or methodological work where appropriate.
The project will provide interdisciplinary training in digital health, prospective observational research, pharmacoepidemiology, health data science, predictive modelling, participant recruitment, and study management. The student will join ACEPOP’s wider research environment and benefit from the expertise of the supervisory team and its research networks.
Dr Adrienne Chan has expertise in pharmacoepidemiology, international healthcare data research, and studies using large-scale longitudinal health records. She will supervise the UK study design, data-source assessment, recruitment strategy, epidemiological methods, and validation framework.
Professor Ian Wong has expertise in pharmacoepidemiology, big data analytics, and the translation of healthcare research into clinical and policy applications. He will provide strategic oversight and support the project within ACEPOP’s wider research programme.
Professor Maia Angelova has expertise in artificial intelligence, mathematical modelling, and complex health data. She will supervise the predictive-modelling and computational components of the project.
Associate Professor Amy Chan, Head of the School of Pharmacy at the University of Auckland, leads the research programme that developed the published asthma prediction algorithm. As external supervisor, she will provide specialist advice on asthma, digital health, wearable technologies, and the original development of the algorithm.
In their application, applicants should explain their interest in asthma, digital health, wearable technologies, healthcare data, or predictive modelling, and describe how their experience has prepared them to undertake the project.
Project supervisors
Dr Adrienne Chan
Dr Adrienne Chan's profile is coming soon
