Impact of the COVID-19 Pandemic on Participation in Community-Dwelling Older Adults: A Cross-Sectional Analysis
Bibliographic record
Abstract
Abstract Public health guidelines to prevent spreading COVID-19 place older adults at risk of loneliness and social isolation. Evidence suggests that participation protects older adults from such detrimental outcomes, therefore we aimed to identify the factors associated with participation in life roles among older adults living in the community during the COVID-19 pandemic. We conducted a telesurvey on a random sample of community-dwelling older adults living in Hamilton, Ontario, Canada, between May and July 2020. Outcome measures included participation in life roles, physical function, physical activity, mobility, mental health, nutrition, and demographics. We conducted two multivariate regression analyses with the Late Life Disability Instrument’s (LLDI) frequency and limitations scales as the dependent variables. Candidate factors were organized by International Classification of Functioning, Disability, and Health (ICF) framework domains; personal factors, body functions and structures, activities, and environmental factors. A total of 272 older adults completed the telesurvey (mean age 78 ±7.3 yrs, 70% female). Age, using walking aids, driving status, household income, education, mental health, nutrition, physical function, and dwelling type explained 47.1% (p<0.001) of the variance observed in LLDI frequency scores. Using walking aids, driving status, receiving health assistance, mental health, and physical function explained 33.9% (p<0.001) of the variance observed in LLDI limitation scores. These findings highlight factors from multiple ICF domains that are associated with participation limitation and frequency among older adults during the pandemic. Our findings have implications for developing public health initiatives to mitigate the effects of the pandemic on the participation of older adults.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| 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".