Modeling the socially intelligent communication of health information to a patient's personal social network

Authors:
Wendy Moncur;Ehud Reiter;Judith Masthoff;Alex Carmichael
Affiliations:
Department of Computer Science, University of Aberdeen, Aberdeen, U.K. and School of Applied Computing, University of Dundee, Dundee, U.K.;Department of Computer Science, University of Aberdeen, Aberdeen, U.K.;Department of Computer Science, University of Aberdeen, Aberdeen, U.K.;School of Applied Computing, University of Dundee, Dundee, U.K.
Venue:
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Year:
2010

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Abstract

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.