mobile peer support in diabetes
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Mobile Peer Support in Diabetes Taridzo CHOMUTARE a,b,c , Eirik RSAND - PowerPoint PPT Presentation

Mobile Peer Support in Diabetes Taridzo CHOMUTARE a,b,c , Eirik RSAND a,b , Gunnar HARTVIGSEN a,b a Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway b Department of Computer Science, University of Troms,


  1. Mobile Peer Support in Diabetes Taridzo CHOMUTARE a,b,c , Eirik ÅRSAND a,b , Gunnar HARTVIGSEN a,b a Norwegian Centre for Integrated Care and Telemedicine, University Hospital of North Norway b Department of Computer Science, University of Tromsø, Norway c Presenter Oral Presentation Oslo, Norway – 30 August 2011 1 of 7

  2. Introduction n Main motivators ¨ mobile devices have become more user-friendly ¨ leverage social media success in healthcare ¨ counter Internet health info explosion by tailoring MIE2011, Taridzo Chomutare 2 of 7

  3. Research Goals n Goals for a peer support framework ¨ find peers based on health status++ ¨ filter relevant user-generated content ¨ deploy on (ubiquitous) mobile devices ¨ measure effect of patient-to-patient dialogue on: ¨ health outcomes ¨ self-efficacy MIE2011, Taridzo Chomutare 3 of 7

  4. Research Goals n Some challenges ¨ forming a good representation of the user [patient] ¨ persuading users to consent to data acquisition ¨ maintaining motivation to participate in a longitudinal trial ¨ sustaining relationships during a trial MIE2011, Taridzo Chomutare 4 of 7

  5. Methods n Patient data acquisition & modeling ¨ daily blood glucose values ¨ daily food habits ¨ daily physical activity and weight ¨ learning user data and modeling health status n Fostering mentor-protégé relationships ¨ extending Morris et al. (2009) ideas for fostering social engagement MIE2011, Taridzo Chomutare 5 of 7

  6. ETSI extension MIE2011, Taridzo Chomutare 6 of 7

  7. Discussion Thats all folks!! n Early results confirm the feasibility of: ¨ adding health status to the user model to filter peers ¨ learning user data from (near) real-time health data ¨ adapting recommender systems to eHealth requirements ¨ managing relationships using mentor models Taridzo Chomutare taridzo.chomutare@telemed.no n Conclusion and future work ¨ personalizing health social media is feasible using personal health data +47 47 68 00 32 ¨ Need for evaluating healthcare recommender algorithms (e.g., relevancy and performance) ¨ Need to elaborate social/psychology theories - relationship dynamics MIE2011, Taridzo Chomutare 7 of 7

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