The Challenges of Being a Family Caregiver During the COVID-19 Pandemic in Canada
Bibliographic record
Abstract
Abstract The COVID-19 pandemic has impacted all of our lives, but the population most at risk are older adults. Canadians over the age of 60 account for 36% of all COVID-19 cases but 95% of the deaths, and over two-thirds of ICU admissions. Older adults with chronic health conditions are especially at risk. Prior to COVID-19, family caregivers (FCGs) for older adults were managing their caregiving duties at the limits of their emotional, physical and financial capacity. As such, FCGs need special consideration during these times of uncertainty to support them in their role and enable the continuation of care for their older adult family members. This symposium will report on independently conducted studies from across Canada that have examined how the pandemic and associated public health measures have influenced resource utilization by FCGs and the older adults for whom they provide care. McAiney et al’s study examines the deleterious effect of reduced services on community dwelling FCGs and the wellbeing of their family member with dementia. Parmar & Anderson examined the effect of pandemic restrictions on FCGs of frail older adults and found they were experiencing increased distress and decreased wellbeing. Flemons et al report on the experiences of FCGs managing caregiving without critical services and the effect of restrictive visiting policies and the well-being of the caregiving dyad (FCGs and family member with dementia). Finally, McGhan et al will share how FCGs evaluated the efficacy of public health measures and the public health messaging about the pandemic.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.027 | 0.003 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".