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Modeling the Socially Intelligent Communication of Health Information to a Patient's Personal Social Network

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4 Author(s)
Wendy Moncur ; Department of Computer Science, University of Aberdeen, Aberdeen, U.K. ; Ehud Reiter ; Judith Masthoff ; Alex Carmichael

This study examined how emotional proximity and gender affect people's information requirements when someone that they know is chronically or critically ill. In an online study, participants were asked what information they would want to receive about members of their social network in three categories: someone who was very close, someone who was not so close, and someone who was not close at all. Our results show that the information that people want can be predicted from their gender and emotional proximity to the network member. The closer the relationship with the patient, the more information people want. Women want more information than men. We propose a model for the socially intelligent communication of health information across the social network, and discuss areas for its application.

Published in:

IEEE Transactions on Information Technology in Biomedicine  (Volume:14 ,  Issue: 2 )