%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 21
%N 7
%P e13664
%T Reducing Patient Loneliness With Artificial Agents: Design Insights From Evolutionary Neuropsychiatry
%A Loveys,Kate
%A Fricchione,Gregory
%A Kolappa,Kavitha
%A Sagar,Mark
%A Broadbent,Elizabeth
%+ Department of Psychological Medicine, The University of Auckland, Auckland City Hospital, Level 12 Support Building, 85 Park Road, Grafton, Auckland, 1023, New Zealand, 64 9 373 7599 ext 84340, k.loveys@auckland.ac.nz
%K loneliness
%K neuropsychiatry
%K biological evolution
%K psychological bonding
%K interpersonal relations
%K artificial intelligence
%K social support
%K eHealth
%D 2019
%7 08.07.2019
%9 Viewpoint
%J J Med Internet Res
%G English
%X Loneliness is a growing public health issue that substantially increases the risk of morbidity and mortality. Artificial agents, such as robots, embodied conversational agents, and chatbots, present an innovation in care delivery and have been shown to reduce patient loneliness by providing social support. However, similar to doctor and patient relationships, the quality of a patient’s relationship with an artificial agent can impact support effectiveness as well as care engagement. Incorporating mammalian attachment-building behavior in neural network processing as part of an agent’s capabilities may improve relationship quality and engagement between patients and artificial agents. We encourage developers of artificial agents intended to relieve patient loneliness to incorporate design insights from evolutionary neuropsychiatry.
%M 31287067
%R 10.2196/13664
%U https://www.jmir.org/2019/7/e13664/
%U https://doi.org/10.2196/13664
%U http://www.ncbi.nlm.nih.gov/pubmed/31287067