The DOI matches its Crossref record, with a small difference in title or year; 46 of the 47 references it cites were found in a registry or an index.
Loneliness from young adulthood to old age: Explaining age differences in loneliness
Open accessAbstract
Prior research in non-U.S. samples has found a complex nonlinear relationship between loneliness and age. This research has shown that established predictors of loneliness - poor health, being unmarried, living alone, and having infrequent social interactions - help to explain age differences in loneliness. However, while some variables were found to be universal predictors of loneliness at all ages, others were relevant in specific age groups only. In this study, we describe age differences in frequency of loneliness from age 18 to 89+ years in the U.S., and examine age differences in predictors of loneliness from age-specificity and age-normative perspectives. We used cross-sectional nationally representative data from the General Social Survey (N = 2,477) and found a nonlinear relationship between age and loneliness that closely resembles prior research. However, we found no evidence for age-specific predictors of loneliness. Household income, household size, marital status, health, and frequency of socializing were "universal" predictors of loneliness; their associations with loneliness did not differ in strength with age. Our hypothesis that individuals who deviated from age-specific norms would experience more intense loneliness was not supported. Implications for research and loneliness interventions are discussed.
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“Age itself was not found to be significantly related to loneliness, but rather age differences in predictive factors (e.g., widowhood, poor health) seemed to explain the observed differences (Hawkley et al., 2022).”
From Feasibility, acceptability, and preliminary efficacy of an internet-based CBT intervention for loneliness in older adults: A pilot RCT (2024) · cites this paper as Hawkley et al., 2022
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Cites
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Buecker, S., Mund, M., Chwastek, S., Sostmann, M., & Luhmann, M. (2021) · Psychological Bulletin · doi:10.1037/bul0000332 · Cited by 347
Risk factors for loneliness: A literature review
Barjaková, M., Garnero, A., & d’Hombres, B. (2023) · Social Science & Medicine · doi:10.1016/j.socscimed.2023.116163 · Cited by 296
Loneliness across time and space
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Does unemployment lead to greater levels of loneliness? A systematic review
Morrish, N., & Medina‐Lara, A. (2021) · Social Science & Medicine · doi:10.1016/j.socscimed.2021.114339 · Cited by 149
“…employed; unemployed; student; inactive other I Growth mixture modelling, logistic regression (growth mixture modelling, logistic regression)b Hawkley et al. (2020) To consider the age distribution of loneliness, explanations for these differences, and evidence for age effects 2477 Range:…”
BackgroundMethodInfluential
Metadata
- Authors
- Hawkley, L. C., Buecker, S., Kaiser, T., & Luhmann, M.
- Affiliations
- University of Chicago (US)
- Ruhr University Bochum (DE)
- Corresponding author
- Hawkley, Louise C.
- Venue
- International Journal of Behavioral Development
- Publisher
- SAGE Publications
- Published
- 2020-11-15
- Volume
- 46
- Issue
- 1
- Pages
- 39-49
- ISSN
- 0165-0254 (ISSN-L)
- 1464-0651
- PMC
- PMC8734589
- OpenAlex
- W3106297590
- Cited by
- 281
- References
- 47
- Citations by year
- 2026: 55 · 2025: 73 · 2024: 62 · 2023: 51 · 2022: 29 · 2021: 10 · 2020: 1
- FWCI
- 12.58
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- International Journal of Behavioral Development (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Funders
- Deutsche Forschungsgemeinschaft (Grant LU 2053/2-1)
- Topics
- Social Sciences › Health › Health disparities and outcomes
- Social Sciences › Psychology › Developmental and Educational Psychology › Aging and Gerontology Research
- Social Sciences › Psychology › Social Psychology › Attachment and Relationship Dynamics
- Keywords
- loneliness, age differences, life course, predictors of loneliness, marital status, living alone, social interaction, household income, household size, older adults, young adults
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