Compensatory Connections? Living Alone, Loneliness, and the Buffering Role of Social Connection Among Older American and European Adults
Bibliographic record
Abstract
OBJECTIVES: The growth of solo living has important implications for the rising "loneliness epidemic" among older adults. This study considered whether 2 forms of social connectedness-extra-household core discussion networks and social participation-buffer the loneliness associated with living alone. METHOD: Our study used data from 2 surveys (National Social Life, Health, and Aging Project; Survey of Health, Ageing and Retirement in Europe) encompassing 20 developed Western countries in 2009/2010 and 2015/2016 (n = 110,817). Harmonizing measures across data sets, we estimated survey-specific and pooled longitudinal regression models with interaction terms. RESULTS: High levels of social connectedness only moderately buffered the loneliness associated with living alone in later life. Findings were largely consistent across regions of Europe and the United States, though the buffering patterns were most robustly identified for widowed solo dwellers. DISCUSSION: Extra-household connections are partial compensators, but do not seem to fully replace the ready companionship afforded by residential copresence in later life. Future research is needed to understand whether the efficacy of compensatory connections differs by gender, race/ethnicity, and across more diverse global regions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".