MDU mHealth independent research
We’re excited to announce that we are currently undertaking our own independent research project.
With the prominence of mHealth (mobile health) playing an ever-larger role in patient care and an increasing number of mHealth devices having companion apps, we wanted to explore in-depth a problem that affects all developers of mobile apps. User retention and high drop off rates.
Whether an app is designed to help improve a patient’s adherence to their treatment plan or to aid them in tracking their side effects while giving advice and recommendations. We would like all the users of our devices to use them for the entire duration of their treatment by fully taking advantage of all the features that have been specifically designed for them. This is not however the case for a large proportion of users, as retention rates can be very poor.
Users can therefore be divided into one of two groups, those who continue to use mobile apps and those who stop after a short period of time.
Medical Device Usability and Patient Powered Medicine (PPM) are working together on a research project to provide insight if there are any distinct characteristics within the two user groups that can be identified. We’ll do this by speaking to a diverse sample of users from a diverse variety of backgrounds and a wide range of different medical conditions such as R.A (Rheumatoid Arthritis), Cancer and Asthma / COPD (Chronic Obstructive Pulmonary Disease).
From the research output we aim to understand;
- Why do some users continue to use mobile health apps for a long period of time?
- Why do some users stop using mobile health apps after a short period of time?
- Can trends be found among these two user groups?
- Are there individual characteristics or traits that can be identified within individuals or groups that lead to them belonging to one of the two groups?
- From the findings, can any design principles be made to reduce drop off rates, improve user satisfaction and user experience.
After we analyse the feedback PPM will take the data and use their expertise in drawing out hidden insights and present them in a visual interactive graph, displaying a wide and varied cross section of ideas, individual characteristics and emotions.
We aim to publish our findings in the early autumn. To keep up with progress about this project, sign up to our blog!