GRAIDs: a framework for closing the gap in the availability of health promotion programs and interventions for people with disabilities
Bibliographic record
Abstract
BACKGROUND: Evidence-based health promotion programs developed and tested in the general population typically exclude people with disabilities. To address this gap, a set of methods and criteria were created to adapt evidence-based health promotion programs for people with disabilities. In this first study, we describe a framework for adapting evidence-based obesity prevention strategies for people with disabilities. We illustrate how the framework has been used to adapt the U.S. Centers for Disease Control and Prevention's (CDC) obesity prevention strategies for individuals with physical and developmental disabilities. METHODS: The development of inclusion guidelines, recommendations and adaptations for obesity prevention (referred to as GRAIDs--Guidelines, Recommendations, Adaptations Including Disability) consists of five components: (i) a scoping review of the published and grey literature; (ii) an expert workgroup composed of nationally recognized leaders in disability and health promotion who review, discuss and modify the scoping review materials and develop the content into draft GRAIDs; (iii) focus groups with individuals with disabilities and their family members (conducted separately) who provide input on the potential applicability of the proposed GRAIDs in real world settings; (iv) a national consensus meeting with 21 expert panel members who review and vote on a final set of GRAIDs; and (v) an independent peer review of GRAIDs by national leaders from key disability organizations and professional groups through an online web portal. RESULTS: This is an ongoing project, and to date, the process has been used to develop 11 GRAIDs to coincide with 11 of the 24 CDC obesity prevention strategies. CONCLUSION: A set of methods and criteria have been developed to allow researchers, practitioners and government agencies to promote inclusive health promotion guidelines, strategies and practices for people with disabilities. Evidence-based programs developed for people without disabilities can now be adapted for people with disabilities using the GRAIDs framework.
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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 | 0.419 | 0.371 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.005 | 0.006 |
| Bibliometrics | 0.036 | 0.018 |
| Science and technology studies | 0.010 | 0.038 |
| Scholarly communication | 0.025 | 0.025 |
| Open science | 0.015 | 0.039 |
| Research integrity | 0.018 | 0.017 |
| Insufficient payload (model declined to judge) | 0.005 | 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".