554 Co-developing and mobilizing new Type 2 diabetes guidelines for immigrants and refugees
Bibliographic record
Abstract
Abstract PTH 4: Mental Health and Refugees 2, B307 (FCSH), September 4, 2025, 14:00 - 14:48 Aims: This knowledge mobilization project aimed to identify unique barriers and facilitators to new Type 2 Diabetes (DM) guidelines for immigrants and refugees. DM, along with related conditions such as cardiovascular disease (CVD) and obesity, is rising worldwide, disproportionately affecting marginalized communities, including many migrant groups. For example, disease rates are highest in populations coming from the Middle East, India and China. Our review considers recent studies on diabetes prevention and care, specifically lifestyle interventions and emerging therapies. Our review focused on new immigrants and refugees, primary care practices, emerging trends, and equity considerations. Methods: We conducted an evidence review on DM and drafted new guidelines for immigrants and refugees. We sought recent high-quality umbrella reviews and updated these reviews with the most recent systematic reviews. Our guidelines focused on diet, exercise and medical therapy for DM. Then, using an international refugee health preconference, we presented these new guidelines to patient advocates, international health graduates, and primary care practitioners. We used sequential, small group discussions considering the GRADE FACE Implementation approach, discussing feasibility, acceptability, equity and equity implications for newcomer populations and their primary care practitioners. Results: We presented our draft DM guidelines to 51 participants, representing 14 countries, and including nurses, dieticians, psychologists, pharmacists and family physicians. Most of our participants were somewhat aware of emerging diabetes guidelines, but none had thus far mobilized this knowledge to their communities. Discussions identified many barriers to culturally and linguistically isolated populations, including communication, travel, and financial and food security issues. Diet and exercise were recognized as an important starting point, an opportunity to begin discussing the lifestyles of newly arriving populations. Conclusion: Diabetes is a cardiometabolic chronic disease pandemic, and our guideline discussions clearly showed the importance of cultural safety and awareness, and informed equity considerations.
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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 | 0.029 | 0.070 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".