Consolidated Principles for Equitable and Inclusive Digital Health and Virtual Care Co-Design
Bibliographic record
Abstract
Digital health and virtual care (DH/VC) interventions have been rapidly transforming healthcare systems, offering enormous potential to bridge gaps in healthcare access and deliver person-centred interventions to equity-deserving populations. Working in partnership with patients, caregivers and communities to meaningfully integrate lived experience perspectives into DH/VC interventions can help ensure that diverse needs are met. In this commentary, we propose a consolidated set of principles for co-designing equity-informed DH/VC interventions. We also identify how these principles can be leveraged through resources and opportunities offered by Healthcare Excellence Canada and others.
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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 | 0.198 | 0.177 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.010 | 0.064 |
| Scholarly communication | 0.027 | 0.012 |
| Open science | 0.008 | 0.022 |
| Research integrity | 0.021 | 0.030 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".