Co-Designing Together through Crisis: Development of a Virtual Care Guidance Document to Support Providers, Older Adults, and Caregivers
Bibliographic record
Abstract
COVID-19 has had a disproportionate and devastating impact on older adults. As health care resources suddenly shifted to emergency response planning, many health and community support services were cancelled, postponed, or shifted to virtual care. This rapid transformation of geriatric care resulted in an immediate need for practical guidance on decision making, planning and delivery of virtual care for older adults and caregivers. This article outlines the rapid co-design process that supported the development of a guidance document intended to support health and community support services providers. Data were collected through consultation sessions, surveys, and a rapid literature review, and analyzed using appropriate qualitative and quantitative methods. Although this work took place within the context of the COVID-19 pandemic, the resulting resources and lessons learned related to collective impact, co-design, population-based planning, and digital technologies can be applied more broadly.
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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 | 0.058 | 0.087 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.008 | 0.007 |
| Open science | 0.003 | 0.013 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".