Impact of older adult and health/social service provider partners on intervention research design, delivery, and translation
Bibliographic record
Abstract
Context: Partnering with older adults and communities in health research can improve health outcomes and enhance the health system. Though the practice of citizen and community engagement in research has rapidly expanded, little is known about the impact of engaged approaches. Rigor in evaluating the impact of participatory approaches in health research have been called for. This will ensure time and money invested in carrying out engaged health research is having its intended effect. EMBOLDEN is a co-designed, evidence-informed, novel community health intervention that aims to enhance mobility in older adults. A 26-person Strategic Guiding Council (SGC) composed of health/social service providers, older adults contributed to the co-design. Objective: To determine the impact of SGC engagement on stages of research- (preliminary, implementation phase, and translational). Study Design and Analysis: Developmental evaluation in partnership with four older adult members of EMBOLDEN’s SGC. Focus group data and meeting notes were analyzed thematically. Setting: Community, Hamilton, Ontario. Population Studied: Community-dwelling older adults; health/social service providers. Outcome Measures: Older adult SGC members set diversity, satisfaction, respect, and impact across stages of research as evaluation indicators. Data sources: survey, focus groups, and document analysis of meeting notes from >16 SGC meetings that took place between 2019-2023. Results: Five service providers and 4 older adults completed the evaluation survey. One service provider and four older adults participated in focus groups. The SGC designed how to work together, how to frame intervention components to best resonate with older adults, and identified how the SGC should be expanded to reflect more diverse perspectives. SGC input determined key competencies of interventionists, how intervention components were operationalized, and the delivery format. SGC members co-developed knowledge translation products including: infographics, manuscripts, program/training materials, research briefs, webinars, conference presentations, and the study website with EMBOLDEN researchers. Conclusions: Older adults and service providers can make important contributions to the design, delivery and knowledge mobilization of health research through their lived experience and connections to community.
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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 | 0.499 | 0.477 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.007 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.016 | 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".