Feedback in problematic life-domains may motivate change and goal-achievement over time. Intel investigate "tools for personalized, longitudinal self-investigation that help end users learn about the conditions and variables that impact their social, cognitive, and physical health".
Here is the lifetrack inteface which enables you to track changes in important life areas over time:http://architecture.mit.edu/house_n/data/tracking/lifetrack.html
Here is the life-domain and goal-selection questionnaire: http://architecture.mit.edu/house_n/data/tracking/sortingexercise.html
Including lay-descriptions of behaviour change techniques such as those recently described by Abraham & Michie (In press) or even framing feedback in ways to promote regret or to use social norms in a web community to motivate behaviour may all help the person achieve their aims. A personalized non-invaseive ubiquitious computing approach with integrated tailored health promotion services to provide a sustainable business model may be the way to go with this. Research, technology, and consumer driven feedback are synthesized to refine the system enhancing effectiveness and user-experience. This makes large-scale panel data collection possible through providing a useful service to those interested in proactive health technologies.
User reactions to this service are documented here
Interestingly, the researchers also include a page which details which kind of personal information they would like to have tracked over time. The number one aspect is heart rate followed by time of going to sleep, short term memory span, muscle tone, and use of space. TV watching, drinking, and smoking feature at the bottom of the list surprisingly.
We track heart rate in our recent Day Reconstruction Study and many of the participants were very interested in their heart rate over the course of the day. Producing this data in a readily accessible and useful format is something which would be of great interest to people. Going one better intel aim to produce a device which infers mood from heart data and provides feedback via mobile phone to those need a stress intervention (for more see: Technologies for Heart and Mind). Again user generated content is fed back into the online system to refine algorithms for identifying mood and providing feedback.
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