Cancer patients may struggle with mental wellbeing issues such as distress and depression. As a part of the CAPABLE project, we aim to develop a digital behaviour-change intervention that helps them build positive health habits and improve their wellbeing. The main challenge to the evaluation of the system is the lack of access to real data prior to intervention start. Therefore, first, we created a simulator that mimics patient responses to activity suggestions based on Fogg's behaviour model. Later we used supervised and reinforcement learning methods to learn the best time of sending the patient prompts. We found that the reinforcement learning methods learn quickly not to over-notify patients and find prompt policies that are more effective in facilitating users in performing target activity than a random notification strategy, but are less effective than adaptive supervised learning method trained to predict patient responsiveness.
|Number of pages||12|
|Journal||CEUR Workshop Proceedings|
|State||Published - 2021|
|Event||2021 Workshop on Towards Smarter Health Care: Can Artificial Intelligence Help?, SMARTERCARE 2021 - Virtual, Online|
Duration: 29 Nov 2021 → …
Bibliographical noteFunding Information:
The CAPABLE project has received funding from the European Union's Horizon 2020 research and innovation programme under grant agreement No 875052.
The CAPABLE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 875052.
© 2021 Copyright for this paper by its authors.
- Digital behaviour change intervention
- Fogg behaviour model
- Reinforcement learning
ASJC Scopus subject areas
- Computer Science (all)