Evaluating an Indigenous health curriculum for diabetes prevention: engaging the community through talking circles and knowledge translation of results
Bibliographic record
Abstract
Background: Kahnawà:ke is a Kanien'kehá:ka (Mohawk) community in Quebec, Canada. In 1997, the community-controlled Kateri Memorial Hospital Centre in partnership with the Kahnawake Education Center, and the Kahnawake Schools Diabetes Prevention Project (KSDPP) developed an elementary school diabetes prevention health education program, aimed to increase knowledge of Type 2 diabetes, healthy eating and active lifestyles. Long-term goals for KSDPP community and school interventions are to decrease obesity and diabetes. Objectives: To evaluate the Kateri Memorial Hospital Centre Health Education Program for Diabetes Prevention (HEP) and use key principles of knowledge translation to promote understanding of results to upgrade HEP content and improve delivery. Methods: A KSDPP community-based participatory research team used mixed methods for evaluation, combining a cross-sectional survey for 23 teachers with interviews of two elementary school principals and three culturally appropriate Indigenous talking circles with HEP authors, teachers and parents. Questionnaire results were presented as descriptive statistics. The thematic textual analysis identified emerging themes from talking circles and interviews. Results: Facilitators of HEP delivery were an acknowledgement of its importance; appreciation of prepared lesson plans for teachers; and KSDPP's strong community presence. Barriers included reduced administrative support and instructional time due to competing academic demands; the need for increased Kanien'kehá:ka cultural content; and outdated resource materials. Recommendations included increasing teacher training, Kanien'kehá:ka cultural content and administrative support. Conclusion: Community researchers undertook detailed knowledge translation activities of facilitators, barriers and recommendations with hospital and education centre administrators and Kahnawà:ke community to maximize uptake of findings before external dissemination of results.
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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 | 0.036 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".