Older Adults and Social Isolation and Loneliness During the COVID-19 Pandemic: An Integrated Review of Patterns, Effects, and Interventions
Bibliographic record
Abstract
A scoping review was conducted to identify patterns, effects, and interventions to address social isolation and loneliness among community-dwelling older adult populations during the COVID-19 pandemic. We also integrated (1) data from the Canadian Longitudinal Study on Aging (CLSA) and (2) a scan of Canadian grey literature on pandemic interventions. CLSA data showed estimated relative increases in loneliness ranging between 33 and 67 per cent depending on age/gender group. International studies also reported increases in levels of loneliness, as well as strong associations between loneliness and depression during the pandemic. Literature has primarily emphasized the use of technology-based interventions to reduce social isolation and loneliness. Application of socio-ecological and resilience frameworks suggests that researchers should focus on exploring the wider array of potential pandemic age-friendly interventions (e.g., outdoor activities, intergenerational programs, and other outreach approaches) and strength-based approaches (e.g., building community and system-level capacity) that may be useful for reducing social isolation and loneliness.
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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 | 0.006 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.004 | 0.005 |
| Bibliometrics | 0.009 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".