Optimizing the Meaningful Engagement of Older Adults With Multimorbidity and Their Caregivers as Research Partners: A Qualitative Study
Bibliographic record
Abstract
It is widely recognized that the engagement of older adults with multimorbidity and their caregivers as partners in health care research is important and invaluable. The objective of this study was to examine how researchers can best engage and support older adults with multimorbidity and informal friend or family caregivers of older adults with multimorbidity as research partners in health care research teams. The persona-scenario method was used for participants to create fictional stories. These stories were analyzed to shed light on specific strategies that can support older adults and caregivers as partners on health care research teams, such as a patient-centered approach, identifying and addressing barriers to engagement, and clarifying roles and responsibilities on the research team. The results from this study can be used to inform research, policy, and education on supporting older adults with multimorbidity and caregivers of older adults with multimorbidity as research partners.
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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 | 0.033 | 0.044 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.008 |
| Scholarly communication | 0.004 | 0.005 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".