Impact of COVID-19 on mobility and participation of older adults living in Hamilton, Ontario, Canada: a multimethod cohort design protocol
Bibliographic record
Abstract
INTRODUCTION: The novel COVID-19 required many countries to impose public health measures that likely impacted the participation and mobility of community-dwelling older adults. This protocol details a multimethod cohort design undertaken to describe short-term and medium-term changes to the mobility and participation of older Canadians living in the community rather than retirement facilities during the COVID-19 pandemic. METHODS AND ANALYSIS: A longitudinal telephone (or online)-administered survey is being conducted with a random sample of older adults living within 20 km of McMaster University, Hamilton, Ontario, Canada, identified from census dissemination areas. Baseline data collection of community-dwelling older adults aged 65 years and over began in May 2020 with follow-ups at 3, 6, 9 and 12 months. The Late-Life Function and Disability Instrument and global rating of change anchors are the primary outcomes of interest. A subsample of respondents will participate in open-ended, semistructured interviews conducted over the telephone or through video-conference, to explore participants' lived experiences with respect to their mobility and participation during the pandemic. Descriptive statistics and quantitative approaches will be used to determine changes in mobility and social and personal participation, and associated personal and environmental factors. For the interviews, qualitative data will be analysed using descriptive phenomenology. ETHICS AND DISSEMINATION: Approval was obtained from the Hamilton Integrated Research Ethics Board of McMaster University (2020-10814-GRA). This study may inform the design of programmes that can support community-dwelling older adults during and after the COVID-19 pandemic. Findings will be disseminated through peer-reviewed publications and conferences focused on ageing.
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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 | 0.039 | 0.024 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.010 | 0.003 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.006 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.035 | 0.006 |
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".