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Loneliness Across Phylogeny and a Call for Comparative Studies and Animal Models
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Loneliness typically refers to the feelings of distress and dysphoria resulting from a discrepancy between a person’s desired and achieved levels of social relations, and there is now considerable evidence that loneliness is a risk factor for poor psychological and physical health. Loneliness has traditionally been conceptualized as a uniquely human phenomenon. However, over millions of years of evolution, efficient and manifold neural, hormonal, and molecular mechanisms have evolved for promoting companionship and mutual protection/assistance and for organizing adaptive responses when there is a significant discrepancy between the preferred and realized levels of social connection. We review evidence suggesting that loneliness is not a uniquely human phenomenon, but, instead, as a scientific construct, it represents a generally adaptive predisposition that can be found across phylogeny. Central to this argument is the premise that the brain is the key organ of social connections and processes. Comparative studies and animal models, particularly when integrated with human studies, have much to contribute to the understanding of loneliness and its underlying principles, mechanisms, consequences, and potential treatments.
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“Health behaviors and physiologic mechanisms are likely, in part, responsible for the negative health outcomes associated with social isolation and loneliness [31–34].”
From Examining social isolation and loneliness in combination in relation to social support and psychological distress using Canadian Longitudinal Study of Aging (CLSA) data (2020) · cites this paper as [31]
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“as well as physiologic responses, including increased blood pressure and heightened inflammatory reactivity to stress [30–34].”
From Examining social isolation and loneliness in combination in relation to social support and psychological distress using Canadian Longitudinal Study of Aging (CLSA) data (2020) · cites this paper as [31]
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“Therefore, an emerging social neuroscience model posits that evolutionarily conserved neurophysiological mechanisms underlie the adaptive, short-term, self-preservation mode triggered by a lack of social connections/mutual protection14,31.”
From Neural mechanisms of social homeostasis (2019) · cites this paper as [14]
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Loneliness is associated with more trust but worse trustworthiness expectations
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Metadata
- Authors
- Cacioppo, J. T., Cacioppo, S., Cole, S. W., Capitanio, J. P., Goossens, L., & Boomsma, D. I.
- Affiliations
- University of Chicago (US)
- David Geffen School of Medicine, University of California, Los Angeles
- University of California, Davis (US)
- KU Leuven (BE)
- Vrije Universiteit Amsterdam (NL)
- Venue
- Perspectives on Psychological Science
- Publisher
- SAGE Publications
- Published
- 2015-03
- Volume
- 10
- Issue
- 2
- Pages
- 202-212
- ISSN
- 1745-6916 (ISSN-L)
- 1745-6924
- PMC
- PMC5090712
- OpenAlex
- W2105989054
- Cited by
- 241
- References
- 96
- Citations by year
- 2026: 20 · 2025: 22 · 2024: 22 · 2023: 19 · 2022: 21 · 2021: 25 · 2020: 14 · 2019: 36 · 2018: 18 · 2017: 14 · 2016: 11 · 2015: 17
- FWCI
- 24.85
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Perspectives on Psychological Science (publishedVersion)
- PubMed (publishedVersion)
- VU Research Portal (publishedVersion)
- PubMed Central (acceptedVersion)
- Lirias (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Funders
- National Institutes of Health (P51OD011107)
- National Institute on Aging (R37AG033590)
- Topics
- Social Sciences › Health › Health disparities and outcomes
- Life Sciences › Neuroscience › Endocrine and Autonomic Systems › Neuroendocrine regulation and behavior
- Social Sciences › Psychology › Social Psychology › Death Anxiety and Social Exclusion
- Keywords
- loneliness, social connectedness, social behavior, brain and social behavior
- MeSH terms
- Animals, Humans, Loneliness
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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