Co-development of a Post-Acute Care Intervention for Frailty using Information and Communication technology (PACIFIC): a development process protocol
Bibliographic record
Abstract
INTRODUCTION: Hospitalisation is one of the most stressful life events for older adults, particularly for those who are pre-frail or frail. Multi-component community-based interventions have the potential to address the complex needs of older adults post-acute care admission. While some available interventions have been developed with end-user engagement, fully involving older people who are pre-frail or frail in the design of interventions has been less common. Multi-component community-based interventions that address the needs of older adults and their care partners with potential implementation barriers informed by healthcare providers, community partners and health system decision makers are needed. This protocol paper describes the planned process of co-designing for older patients discharged into the community, a Post-Acute Care Intervention for Frailty using Information and Communication technology. METHODS AND ANALYSIS: The development of a complex multi-component frailty intervention which meets older people's needs involves several concurrent tasks and methodologies, each informed by co-design and conducted with consideration to eventual implementation. These tasks include: (1) establishing a Research Advisory Board, (2) assessing the feasibility and validity of using hospital administrative data to identify frail or pre-frail older adults and their needs, (3) conducting a needs assessment of patients returning to the community, (4) mapping community assets to identify existing programmes and services to help tailor the intervention, (5) co-designing a multicomponent frailty intervention, (6) selecting study outcome measures and (7) selecting and tailoring a digital health patient portal to support intervention delivery, data capture and communication. ETHICS AND DISSEMINATION: Each task requiring ethics approval will be submitted to the Hamilton Integrated Research Ethics Board at McMaster University. Results will be disseminated through peer-reviewed journal articles, conferences and networks of relevant knowledge users who have the capacity to promote dissemination of the results. A toolkit will be developed to help researchers and healthcare providers replicate the methodology for other populations.
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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 | 0.086 | 0.083 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.035 | 0.007 |
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".