Speaker
Description
Chronic loneliness is an urgent public health crisis associated with a range of mental and physical health consequences. Though treatments for loneliness exist, they are associated with only modest reductions in loneliness, and loneliness has continued to rise in recent decades. To more effectively treat and prevent loneliness, we need a clearer understanding of why loneliness develops and how it becomes chronic. There have been at least three key barriers to making more progress in loneliness research: (1) the lack of an integrated, interdisciplinary conceptualization of loneliness; (2) a reliance on imprecise verbal theories (i.e., theories that lay out the mechanisms hypothesized to drive loneliness in words only, without quantitatively specifying the relationships); and (3) the use of statistical approaches that cannot capture the complex, nonlinear interactions among variables likely driving loneliness. My dissertation aims to reduce these barriers by uniting interdisciplinary perspectives on loneliness via a systematic review, formalizing an integrated theory of loneliness using computational modeling tools (agent-based and differential equation modeling) that can represent complex systems, and precisely evaluating if and how well the formal theory can explain the development and maintenance of chronic loneliness over time via computational model simulations. Results will provide a systematic assessment of loneliness theories, help identify novel research questions, and pinpoint targets for intervention and prevention efforts. This presentation will focus on work completed for the systematic review and on our plans for developing and testing the computational model of loneliness.
