Development of risk profiling matrix for chronic diseases and preventive smartphone application

Vera Buss supervised by Margo Barr, Mark Harris and Marlien Varnfield


Non-communicable diseases are posing the greatest burden – in terms of morbidity and mortality as well as costs – on the worldwide healthcare systems. The number of people developing chronic diseases is still rising; therefore, it is time to increase efforts aiming at chronic disease prevention. These interventions should target prevention or at least delay the onset of the diseases. Since the current strategies seem to be insufficient, new ways need to be explored that can reach large proportions of the population. 


  1. Which of the existing prognostic risk models for cardiovascular disease (CVD) and type 2 diabetes mellitus (T2DM) are suited for use by Australians aged 45 years and older to determine their risk of developing any one of these two conditions?
  2. How well does a risk prediction matrix, which was developed based on individual risk prediction models for CVD and T2DM, perform in an Australian cohort aged 45 years and older?
  3. What is the current evidence for CVD and T2DM prevention through mobile health interventions?
  4. Is it feasible to deliver a preventative intervention for CVD and T2DM through a smartphone application to people aged 45 years and older?

Design and Method

A risk prediction matrix for the onset of CVD and T2DM will be developed and validated using the 45 and Up Study cohort and linked datasets. In a user-centred design, a smartphone application for the primary prevention of CVD and T2DM will be developed which will incorporate the risk prediction matrix. The feasibility of the smartphone application will be assessed in a single-arm interventional study with three months follow-up. Recruitment will be via purposeful sampling with the aim of getting a sample of 40 participants that includes both males and females, and people aged 45-64 years and 65 years and over. The results of the feasibility study will be used to improve the app design and develop implementation strategies to achieve a maximum uptake and overall benefit of the app. In the future, it is envisaged to conduct an effectiveness study in which participants will be followed-up over several years to measure long-term effects.