The Effects of Loneliness on Depressive Symptoms Among Older Adults During COVID-19: Longitudinal Analyses of the Canadian Longitudinal Study on Aging
Bibliographic record
Abstract
Objectives This paper examines the longitudinal effects of changes in the association between loneliness and depressive symptoms during the pandemic among older adults (65+). Methods Baseline (2011–2015) and Follow-up 1 (2015–2018) from the Canadian Longitudinal Study on Aging (CLSA), and the Baseline and Exit waves of the CLSA COVID-19 study (April–December, 2020) ( n = 12,469) were used. Loneliness was measured using the 3-item UCLA Loneliness Scale and depression using the CES_D- 9. Results Loneliness is associated with depressive symptoms pre-pandemic; and changes in level of loneliness between FUP1 and the COVID Exit survey, adjusting for covariates. No interaction between loneliness and caregiving, and with multimorbidity, on depressive symptoms were observed, and several covariates exhibited associations with depressive symptoms. Discussion Strong support is found for an association between loneliness on depressive symptoms among older adults during the pandemic. Public health approaches addressing loneliness could reduce the burden of depression on older populations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".