EMBOLDEN: CATALYZING RESEARCH FOR OLDER ADULTS THROUGH CO-DESIGNED MOBILITY-PROMOTING INTERVENTION RESEARCH
Bibliographic record
Abstract
Abstract Mobility and social participation are requisites for optimizing health, independence, and quality of life in older populations. Most mobility-enhancing interventions for older adults have been designed by researchers alone, which often experience implementation challenges and limited effectiveness when translated to real-world contexts. The EMBOLDEN research program aims to i) partner with older adults and service providers to co-design, implement, and evaluate a mobility-promoting intervention and ii) enhance physical and mental health, foster social connections, and support system navigation among older adults living in neighbourhoods with health inequities. EMBOLDEN has completed two phases: (1) intervention co-design based on evidence reviews, environmental scan, qualitative study, and strategic guiding council expertise; (2) a mixed-methods pilot randomized controlled trial. Twenty-seven local older adults (≥55y) and 34 service providers contributed to Phase 1, co-designing an integrated health and social care intervention delivered through collaboration with primary care, public health, and recreation. The three-month community-based program includes a weekly interactive group program of physical activity, healthy eating, socialization, and individual system navigation support. The co-design determined priority intervention features (e.g., addressing social determinants of health, assets-based approaches) and implementation strategies. The pilot study evaluated quantitative and qualitative participant outcomes and experiences and intervention team experiences. The pilot study demonstrated intervention feasibility and acceptability to participants and interventionists, informing a larger pragmatic hybrid implementation-effectiveness trial that is currently underway. EMBOLDEN’s partnership engagement was critical to successfully co-designing intervention research to address identified health, mobility, and social needs of older adults living in neighbourhoods with significant health inequities.
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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 | 0.141 | 0.119 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.013 | 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".