The model goes beyond the state of the art due to it enables to create and personalize recommendations using contextual data from users in non-intrusive way.These recommendations consider information available from users (mobility level, desires, name, if pet or not) to personalize recommendations and adapt them to the capabilities, opportunities and preferences of the user. Also, they are not just focused on a specific aspect such as quit smoking, reduce alcohol intake, etc but they cover all areas around wellbeing and can be easily extensible to other areas such as behaviour change for sustainable, guidelines for e-learning platforms, etc.Finally, these recommendations are not just provided as notification, but they are offered by a coach that is also able to interact with the user if further information or motivation is required.