Enhancing Physical and Community MoBility in OLDEr Adults with Health Inequities Using CommuNity Co-Design (EMBOLDEN): Results of an Environmental Scan
Bibliographic record
Abstract
Background: Using the comparatively new environmental scan methodology, a protocol was developed and conducted to inform the co-design and implementation of a novel intervention to promote mobility among older adults in Hamilton, Ontario, Canada. The EMBOLDEN program seeks to promote physical and community mobility in adults 55 years and older who face barriers accessing community programs and who reside in areas of high inequity in Hamilton, and to address the following areas of focus: physical activity, nutrition, social participation, and system navigation supports. Methods: The environmental scan protocol was developed using existing models and drew insights from census data, a review of existing services, organizational representative interviews, windshield surveys of selected high-priority neighbourhoods, and Geographic Information System (GIS) mapping. Results: A total of 98 programs for older adults from 50 different organizations were identified, with the majority (92) supporting mobility, physical activity, nutrition, social participation, and system navigation. The analysis of census tract data identified eight high-priority neighbourhoods characterized by large shares of older adults, high material deprivation, low income, and high proportion of immigrants. These populations can be hard to reach and face multiple barriers to participation in community-based activities. The scan also revealed the nature and types of services geared toward older adults in each neighbourhood, with each priority neighbourhood having at least one school and park. Most areas had a range of services and supports (i.e., health care, housing, stores, religious options), although there was a lack of diverse ethnic community centres and income-diverse activities specific to older adults in most neighbourhoods. Neighbourhoods also differed in the geographic distribution number of services, along with the number of recreational services specific to older adults. Barriers included financial and physical accessibility, lack of ethnically diverse community centres, and food deserts. Conclusions: Scan results will inform the co-design and implementation of the Enhancing physical and community MoBility in OLDEr adults with health inequities using commuNity co-design intervention-EMBOLDEN.
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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 | 0.017 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.000 |
| 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".