The Ubhave Project (Part 1/2)
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The Ubhave Project (Part 1/2)

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Invited talk at the 2nd ACM Conference on Mobile Systems for Computational Social Science #ubicom13

Invited talk at the 2nd ACM Conference on Mobile Systems for Computational Social Science #ubicom13

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  • 1. Ubiquitous and Social Computing for Positive Behaviour Change
  • 2. UBHave's ...aim is to investigate the power and challenges of using mobile phones and social networking for Digital Behaviour Change Interventions (DBCIs), and to contribute to creating a scientifc foundation for digitally supported behaviour change.
  • 3. Digital Behaviour Change Interventions ...focus on delivering relevant information via digital means (e.g., a web site) in order to support intents to change behaviour
  • 4. Monitor Learn Deliver Mobile Intervention “Smartphones for Large-Scale Behaviour Change Interventions”. IEEE Pervasive 2013.
  • 5. “ Study fndings suggested that young, currently healthy adults have some interest in apps that attempt to support health-related behaviour change [...] The ability to record and track behaviour and goals and the ability to acquire advice and information “on the go” were valued. Context-sensing capabilities and social media features tended to be considered unnecessary and off-putting.” “Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study” Dennison et. al
  • 6. “...They predicted that context-triggered advice and suggestions would produce counterproductive effects by drawing attention towards unhealthy but attractive behaviour choices.” “Opportunities and Challenges for Smartphone Applications in Supporting Health Behavior Change: Qualitative Study” Dennison et. al
  • 7. Monitor Learn Deliver Mobile Intervention Design
  • 8. ● User Interface and interaction: – Diaries – Menus – Information – Questionnaires – Feedback ● Sensor data collection ● Context triggering Towards a framework... Generic components for mobile apps:
  • 9. { “intervention_id”:”my_intervention”, “questions”: [ … ] “diary”: [ …] “sensors”: [ …], “trigger”:[ {“accelerometer”:”moving”, “survey”:”physical_activity”} ] } ...that can be 'authored' Using well-known mobile app design patterns Native app's benefts, web apps' benefts:
  • 10. ● Questionnaires ● Feedback ● Sensor data collection & management – “Open Source Smartphone Libraries for Computational Social Science” MCSS 2013. Part of the path so far... Mostly measurement. (experience sampling) Building from a subset of the functionality:
  • 11. Emotion Sense
  • 12. ● How can we keep users engaged in a seemingly repetitive task? – Diversify and sample from the questions as a “journey” of unlocking feedback – User needs vs. research needs ● How can we effciently collect sensor data? – First deployment took a naïve approach – Current implementation focuses on CPU time rather than sensor strategy Design Challenges
  • 13. “sensor duty cycling”
  • 14. Sensor & Emotion Data
  • 15. “Can I run an ESM study like Emotion Sense?” Generalise sensor- enhanced experience sampling tool. Currently in alpha testing.
  • 16. Smartphone Libraries: Sensing, Triggers, Data Management Emotion Sense Easy M Sensing Apps & ESM Research towards ubhave's intervention framework Research