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HABIT Understanding the mechanisms of habit-forming and habit reliance ‘Provocations assignments’ for Day 1 of the NSF/EU/NIH Behavior Change Workshop.

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Presentation on theme: "HABIT Understanding the mechanisms of habit-forming and habit reliance ‘Provocations assignments’ for Day 1 of the NSF/EU/NIH Behavior Change Workshop."— Presentation transcript:

1 HABIT Understanding the mechanisms of habit-forming and habit reliance ‘Provocations assignments’ for Day 1 of the NSF/EU/NIH Behavior Change Workshop Daniel E. Rivera Katherina Martin Abello

2 Task How can we build on work of choice architectures and behavioral economics to develop computational models of “habit” and self-regulating mechanisms? How can we measure the power of simplicity and immediacy in decision making, how best can we uncover the (often unspoken) heuristics people may be following in many everyday interactions with the systems around them so we can figure out how to exploit it? Please think about this a way to rethink how people interact with their ‘inner’ and ‘outer’ environments, rather than an opportunity to review past research. In what way can the use of new technology help with the task of understanding the ‘hidden’ and ‘obvious’ pathways to habit formation and habit breaking? And what questions have we missed in this realm?

3 Keywords Social Media (Facebook) Semantic web & AI Intensive Longitudinal Data (ILD) Tailoring & optimizing interventions Persuasive Psychology Responsive design Responsive content

4 Semantic web search engine query data

5 Serious Games & Facebook A new Facebook application, HealthSeeker, wants to help people with diabetes become more informed about their disease, as well as make tangible lifestyle changes that might affect their health.

6 Dynamic Models, Tailoring & Optimizing Interventions Dynamic models which translate the data in decision making algorithms to tailor interventions Optimized Adaptive Behavioral Interventions Control Algorithms (e.g., Model Predictive Control) Intervention Performace Objectives & Clinical Constraints Computing and Mobile Technologies Dynamical Modeling Intensive Longitudinal Data (ILD) Experimentation

7 Next generation Behavior Change Modeling and Intervention

8 What about… Protecting user privacy People outside Social Media Mobile integration LOW-SES Methodological challenges/ “Dynamic Watson”


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