(MRC CASE DTP) Exploring the feasibility of using smartphone based augmented/ virtual reality to support primary falls awareness and prevention.

One in three older people over the age of 65 fall each year, leading to injury, death and health services costs. Supporting older adults to understand their falls risk and engage in healthy, active ageing is key to preventing falls and ideally needs to be done before engagement with health services. Although virtual reality has been used within primary falls prevention, it predominantly focuses on treadmill training/exercise rehabilitation.
Sentireal provide personalised healthcare guidance/training through virtual/augmented reality on smartphone applications. There is the potential to develop software which can provide broader support for self-management of falls risk to older people and be used as an engaging training tool for non-clinical staff (e.g. care staff).

Objectives

To establish whether it is feasible for smartphone based augmented reality to be used as a self-management tool for older adults/interactive training tool for care staff.

• Co-design a self-management and training smartphone application with both older adults and care staff (via AgeUK)
• Test the acceptability and feasibility of the application.


Methods

A mixed methods approach will be used to co-design and test a smartphone application with older adults and care staff. A mix of qualitative focus groups and interactive workshops will establish the design, functionality and interface of the smartphone application alongside the existing evidence base. A pilot study will then be carried out to test the acceptability and feasibility of the smartphone application with a cohort of older adults and care staff across two AgeUK organisations (Yorkshire and Manchester). Validated assessment tools will be used to assess the potential impact of the intervention and qualitative interviews will be carried out with older people and carers to establish experiences of using the technology and to inform further design of the interfaces/App functionality. Based on Medical Research Council guidance for development and evaluation of complex interventions (MRC, 2008) this work will inform the design of future trials. The student will work closely with Sentireal during the development phase of the prototype and will also link with mHealth Technologies (spin off company from the University of Bologna) to understand how movement detection and machine learning can inform the app development.

Impact

This project has the potential to create an app which can:

• assist older adults to self-manage their falls risk through bespoke personalised content
• Train care staff in a more effective, flexible, engaging and low cost way.
• Deliver on a population wide basis
• Develop new intellectual property