Public Health Messaging during the COVID-19 Pandemic and Its Impact on Family Caregivers’ COVID-19 Knowledge
Bibliographic record
Abstract
BACKGROUND: Enabling accurate, accessible public health messaging is a critical role of public health officials during a pandemic, but family caregivers of people living with dementia (PLWD) have rarely been specifically addressed in public health messaging. OBJECTIVE: The objective of this study was to examine how family caregivers for people living with dementia access and evaluate public health messaging in Alberta. METHOD: An online survey was conducted with family caregivers for PLWD (n = 217). RESULTS: Most respondents rated public health messaging as good or excellent (63.9%), but specific information about how to access caregiving information (69.5%) and what to expect in the future (49.1%) was rated as less than good. Family caregivers also identified how to care for a PLWD during the pandemic (57.5%) as a key information need. Healthcare providers/workers were the least frequently used source of public health messaging. Almost all family caregivers (94.4%) rated their own COVID-19 knowledge as good or excellent. DISCUSSION: Tailored, context-driven public health messaging for family caregivers of PLWD is critically needed.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".