The association of pre-COVID-19 social isolation and functional social support with loneliness during COVID-19: a longitudinal analysis of the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
OBJECTIVES: We evaluated the association between two measures of social connection prior to COVID-19-social isolation and functional social support-and loneliness during the pandemic. METHOD: The study was a retrospective longitudinal analysis of 20,129 middle-aged and older adults enrolled in the Canadian Longitudinal Study on Aging (CLSA). We drew upon two waves of CLSA data spanning three years and the supplemental COVID-19 Questionnaire Study of eight months to conduct our analysis. RESULTS: Social isolation prior to COVID-19 was associated with loneliness during COVID-19 only among persons who were lonely before the pandemic (adjusted odds ratio [aOR]: 1.17; 95% confidence interval [CI]: 1.02, 1.35). Higher functional social support prior to COVID-19 was inversely associated with loneliness during the pandemic, when adjusting for pre-COVID-19 loneliness (aOR: 0.37; 95%CI: 0.34, 0.41) and when assessing incident loneliness during the pandemic (adjusted relative risk: 0.59; 95% CI: 0.55, 0.63). CONCLUSION: Policies are needed to identify people who are both socially isolated and lonely, and provide them with functional social support, to prevent worsening loneliness during public health crises.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".