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. 2019 Jul 8;21(7):e13664.
doi: 10.2196/13664.

Reducing Patient Loneliness With Artificial Agents: Design Insights From Evolutionary Neuropsychiatry

Kate Loveys  1 , Gregory Fricchione  2   3 , Kavitha Kolappa  2 , Mark Sagar  4 , Elizabeth Broadbent  1
Affiliations

Reducing Patient Loneliness With Artificial Agents: Design Insights From Evolutionary Neuropsychiatry

Kate Loveys et al. J Med Internet Res. .

Abstract

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.

Keywords: artificial intelligence; biological evolution; eHealth; interpersonal relations; loneliness; neuropsychiatry; psychological bonding; social support.

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Conflict of interest statement

Conflicts of Interest: MS is the CEO of Soul Machines (an artificial intelligence company), which supports KL with a PhD stipend, and contracts EB for consultancy work.

Figures

Figure 1
Figure 1
Model of behavior that may increase patient engagement with artificial agents according to evolutionary neuropsychiatry.
See this image and copyright information in PMC

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