Resources and Services for Family Caregivers in the Time of COVID-19
Bibliographic record
Abstract
Abstract COVID-19 has led to increased burden on family caregivers (FCGs) for people living with dementia (PLWD), while simultaneously limiting the resources available to them. Our study surveyed Alberta, Canada FCGs to assess their needs and generate recommendations to inform policies about care access, resources, and agency supports. We conducted a mixed methods study using a sequential triangulation design (QUANTITATIVE + qualitative). Our Community Advisory Committee was involved in all stages of study planning, execution, and dissemination. Survey results informed the qualitative data collected from focus groups with FCGs. A total of 230 FCGs participated in the survey, with an average age of 59. The average age of PLWD was 75. The majority were women (77%), 46% were spouses and 41% were adult children. Respondents reported feeling more isolated (69%), more strain (66%) and decreased quality of life (55%) compared to pre-pandemic. Resource use by FCGs decreased from an average of 5 resources pre-pandemic to 1.6 during COVID-19. Services including day programs and home care were no longer available or reconfigured, leading to greater strain and heightened need for respite, which was also unavailable. Focus groups highlighted that system navigation and accessing services during COVID-19 was overly burdensome, leaving FCGs feeling abandoned by the system. FCGs reported an increase in caregiving responsibility and less access to services resulting in PLWD experiencing a decline in wellness and function. As such: 1) resources should be consistently available for FCGs and 2) FCGs require clear, correct, and concise information about COVID-19.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".