The negative impact of loneliness on health has been receiving more attention in the published literature. A recent study in Social Psychiatry and Psychiatric Epidemiology suggests that over 17% of 1,839 US-based study participants classify themselves as lonely, digging deeper into the data the authors show that rather than loneliness being a one-dimensional construct; there are four subtypes of loneliness each with their potential health consequences. The dimensions include low, social, emotional, and social and emotional subtypes of loneliness that are quantitatively and qualitatively different. The most prevalent subtype was low (52.8%), which is a combination of social and emotional loneliness, followed by social loneliness (8.2%). Emotional loneliness made up over 25% of the sample- these participants experienced high emotional loneliness but low levels of social loneliness. The findings indicated a predictable gradient of psychological distress, those with low levels of loneliness reported lower levels of distress compared to those with high levels of loneliness and relationship quality was more important than relationship quantity. Those demonstrating high levels of social and emotional loneliness experienced the highest levels of psychological distress and were more likely to be younger and female.
Can Technology Assist?
We often think about loneliness and isolation in older populations, but clearly, no generation is immune, and loneliness and isolation are having profound impacts on health- this begs the question about the role of technology in helping to improve some of these issues. A new paper by Kate Loveys from the University of Auckland, New Zealand published in the Journal of Medical Internet Research examines the role of artificial agents, chatbots, robots, and AI-assisted devices in reducing loneliness. The authors encourage technology companies to leverage the science-base on human attachment to amplify support as opposed to displacing social support, which has been a significant concern for those who care for older adults.
The authors propose leveraging the behavioral triad, an evolutionary series of complex loops that help us form attachments and separations in social situations that are deeply embedded in brain structures. These loops support our ability to generate genuine attachment, often via the use of empathic language, reading facial expressions, and leveraging reciprocal gestures during human communication often seen as attentiveness.
Learning more about the user during each interaction; just as you would in developing new friendships and being proactive in conversations about the person’s life circumstance is also an essential component of the behavioral triad. Many of the more modern robots can mimic facial expressions during interactions which can reinforce attachment and build bonds over time due to this reciprocal process, which can increase patient engagement.
Artificial agents are still nascent, and it will be essential to develop them as additive supports as humans will always need human connection. Looking for ways to integrate technology versus have it displace critical aspects of the human experience will remain a crucial consideration in all ages.
Thanks for reading – Trina
(Opinions are my own)
References
Quality not quantity: loneliness subtypes, psychological trauma, and mental health in the US adult population
https://link.springer.com/article/10.1007/s00127-018-1597-8
Loveys K, Fricchione G, Kolappa K, Sagar M, Broadbent E
Reducing Patient Loneliness With Artificial Agents: Design Insights From Evolutionary NeuropsychiatryJ Med Internet Res 2019;21(7):e13664
DOI: 10.2196/13664PMID: 31287067
