COMMUNITY MOBILITY PATTERNS OF OLDER ADULTS DURING THE COVID-19 PANDEMIC
Bibliographic record
Abstract
Abstract The COVID-19 pandemic has had appreciative impacts on the lives of older adults. At various times during the pandemic, Canadian provinces put in place public health measures to prevent the spread of the virus, including closures of non-essential businesses and services. The Candrive Driving Cessation sub-study is a 12-year, mixed methods, longitudinal study. During the COVID-19 pandemic, participants from four sites (n=124, mean age=85.5 years) were asked to report how their community mobility patterns during the pandemic compared with before the pandemic. They also completed the COVID-19 Anxiety Syndrome Scale and the Assessment of Readiness for Mobility Transition (ARMT) tool. The results indicated that during the pandemic, participants were less likely to drive (χ2=7.11, p=.004) or ride a public bus (χ2=20.05, p<.001) when leaving their home. During the pandemic, they reported fewer trips to the supermarket (χ2=99.00, p<.001) and fewer visits with family (χ2=68.00, p=.001). We observed a statistically significant relationship between COVID-19 Anxiety Syndrome Scale scores and ARMT (Anticipatory Anxiety subscale; r= .810, p<.001), such that higher COVID-19-related anxiety was associated with greater anxiety related to anticipating changes in mobility. These results emphasize the impacts of the COVID-19 pandemic on the mobility patterns of older adults. Promoting community mobility for older adults alongside preventative public health measures is essential.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".