Community Input for Addressing Dementia Health Disparities: Richmond Brain Health Initiative
Bibliographic record
Abstract
BACKGROUND: The development of the Richmond Brain Health Initiative (RBHI) was guided by the need to address local brain health service gaps to improve Alzheimer's/Dementia health disparities in racially diverse communities. This paper describes the establishment of RBHI through 1) community and provider stakeholder input and 2) community brain health screening/intake development and testing. METHODS: Phase 1 involved provider and community stakeholder questionnaires to gather feedback as part of the Plan-Do-Study-Act cycle. Subsequently, stakeholder findings directed the RBHI structure and screening/intake registration testing in the community. RESULTS: Based on the stakeholder responses from fifteen providers and twenty community members, there was strong consensus in the need for local brain health services. The most highly recommended screening needs were for caregiving, cognitive status, and lifestyle risks. Thereafter the RBHI screening/intake was developed and completed by 45 community participants. Participants showed hypertension (62%) as the most prevalent brain health risk factor, followed by depression/anxiety (56%), and loneliness (44%). The intake also indicated cognitive and functional deficits, with the Montreal Cognitive mean equaling 18.4 and the Functional Activities mean equaling 14.9. Additionally, 73% of participants reported experiencing subjective cognitive decline. CONCLUSIONS: This study showcases a model for promoting brain health in racially diverse communities to improve access to Alzheimer's disease and related dementia resources and services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.004 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".