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

Wendy Moncur, Ehud Reiter, Judith Masthoff, Alex Carmichael

    Research output: Contribution to journalArticle

    11 Citations (Scopus)

    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.

    Original languageEnglish
    Pages (from-to)319-325
    Number of pages7
    JournalIEEE Transactions on Information Technology in Biomedicine
    Volume14
    Issue number2
    DOIs
    Publication statusPublished - Mar 2010

    Keywords

    • Human factors
    • medical information systems
    • modeling
    • personal communication networks
    • SUPPORT
    • SIZE
    • CARE
    • STRESS
    • LIFE

    Cite this

    @article{f51332a25cb0406d8c2f9043336378ea,
    title = "Modeling the socially intelligent communication of health information to a patient's personal social network",
    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.",
    keywords = "Human factors, medical information systems, modeling, personal communication networks, SUPPORT, SIZE, CARE, STRESS, LIFE",
    author = "Wendy Moncur and Ehud Reiter and Judith Masthoff and Alex Carmichael",
    note = "Copyright 2010 Elsevier B.V., All rights reserved.",
    year = "2010",
    month = "3",
    doi = "10.1109/TITB.2009.2035361",
    language = "English",
    volume = "14",
    pages = "319--325",
    journal = "IEEE Transactions on Information Technology in Biomedicine",
    issn = "1089-7771",
    publisher = "Institute of Electrical and Electronics Engineers",
    number = "2",

    }

    Modeling the socially intelligent communication of health information to a patient's personal social network. / Moncur, Wendy; Reiter, Ehud; Masthoff, Judith; Carmichael, Alex.

    In: IEEE Transactions on Information Technology in Biomedicine, Vol. 14, No. 2, 03.2010, p. 319-325.

    Research output: Contribution to journalArticle

    TY - JOUR

    T1 - Modeling the socially intelligent communication of health information to a patient's personal social network

    AU - Moncur, Wendy

    AU - Reiter, Ehud

    AU - Masthoff, Judith

    AU - Carmichael, Alex

    N1 - Copyright 2010 Elsevier B.V., All rights reserved.

    PY - 2010/3

    Y1 - 2010/3

    N2 - 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.

    AB - 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.

    KW - Human factors

    KW - medical information systems

    KW - modeling

    KW - personal communication networks

    KW - SUPPORT

    KW - SIZE

    KW - CARE

    KW - STRESS

    KW - LIFE

    UR - http://www.scopus.com/inward/record.url?scp=77949674675&partnerID=8YFLogxK

    U2 - 10.1109/TITB.2009.2035361

    DO - 10.1109/TITB.2009.2035361

    M3 - Article

    C2 - 19887326

    VL - 14

    SP - 319

    EP - 325

    JO - IEEE Transactions on Information Technology in Biomedicine

    JF - IEEE Transactions on Information Technology in Biomedicine

    SN - 1089-7771

    IS - 2

    ER -