Exploring the potential of AI to support self-care in menopause for all
Lead Participant:
CHANGEXTRA LIMITED
Abstract
Pausetrack is a health tracking app for women who might be experiencing symptoms of peri-menopause and want to understand their health and learn how to best self-care. Pausetrack was created by Dr Claire Mann based on her own (horrible) experiences of peri-menopause. The app aims to help women to track their symptoms and the interventions they try to help themselves.
Pausetrack will be an 'end-to-end' solution for women, offering education about the menopause and suggestions of how to self-care, as well as health tracking. There is a big lack of data about this issue and Pausetrack will capture big data about what works for women in menopause.
We want the benefits of Pausetrack to be accessible to all so we will work with community groups representing minority groups of women to make sure we understand diverse user experiences. We will work with these groups to understand users response to the app, digital health and AI and to co-produce education and self-care resources.
In this project we are exploring whether we can use AI as part of our data analysis to predict what self-care works best for individuals. We recognise that what works might be different for different women and we want to make personalised suggestions for women based on evidence and big data. We will work with experts to look at the data we hold and how we can best use it to benefit our users.
We will also use the data we collect to inform research, policy and practice.
When using AI there is a risk of bias so it is very important that we represent diverse users to ensure equality in our data analysis approaches. This is an important reason why it is important that we are developing a diverse user base when we are thinking about using complex data analysis and in particular AI.
This project will help to improve Pausetrack from a basic health tracking app into an 'end-to-end' solution that can help all women through peri-menopause with personalised self-care support.
Pausetrack will be an 'end-to-end' solution for women, offering education about the menopause and suggestions of how to self-care, as well as health tracking. There is a big lack of data about this issue and Pausetrack will capture big data about what works for women in menopause.
We want the benefits of Pausetrack to be accessible to all so we will work with community groups representing minority groups of women to make sure we understand diverse user experiences. We will work with these groups to understand users response to the app, digital health and AI and to co-produce education and self-care resources.
In this project we are exploring whether we can use AI as part of our data analysis to predict what self-care works best for individuals. We recognise that what works might be different for different women and we want to make personalised suggestions for women based on evidence and big data. We will work with experts to look at the data we hold and how we can best use it to benefit our users.
We will also use the data we collect to inform research, policy and practice.
When using AI there is a risk of bias so it is very important that we represent diverse users to ensure equality in our data analysis approaches. This is an important reason why it is important that we are developing a diverse user base when we are thinking about using complex data analysis and in particular AI.
This project will help to improve Pausetrack from a basic health tracking app into an 'end-to-end' solution that can help all women through peri-menopause with personalised self-care support.
Lead Participant | Project Cost | Grant Offer |
|---|---|---|
| CHANGEXTRA LIMITED | £50,000 | £ 50,000 |
People |
ORCID iD |
| Claire Mann (Project Manager) |