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Record W2148975886 · doi:10.1093/heapro/dak003

Development of an integrated diabetes prevention program with First Nations in Canada

2006· article· en· W2148975886 on OpenAlexaboutno aff
Lara S. Ho

Bibliographic record

VenueHealth Promotion International · 2006
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsnot available
Fundersnot available
KeywordsFormative assessmentPsychological interventionHealth promotionPromotion (chess)MedicineIntervention (counseling)Environmental healthBusinessGerontologyPublic relationsMedical educationNursingPsychologyPolitical sciencePublic health

Abstract

fetched live from OpenAlex

Type 2 diabetes mellitus is a major cause of morbidity and mortality among First Nations in Canada. We used multiple research methods to develop an integrated multi-institutional diabetes prevention program based on the successful Sandy Lake Health and Diabetes Project and Apache Healthy Stores programs. In-depth interviews, a structured survey, demonstration and feedback sessions, group activities, and meetings with key stakeholders were used to generate knowledge about the needs and resources for each community, and to obtain feedback on SLHDP interventions. First Nations communities were eager to address the increasing epidemic of diabetes. Educating children through a school prevention program was the most popular proposed intervention. Remote communities had poorer access to healthy foods and more on-reserve media and services than the smaller semi-remote reserves. While the reserves shared similar risk factors for diabetes, variations in health beliefs and attitudes and environmental conditions required tailoring of programs to each reserve. In addition, it was necessary to balance community input with proven health promotion strategies. This study demonstrates the importance of formative research in developing integrated health promotion programs for multiple communities based on previously evaluated studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.821
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.329
Teacher spread0.310 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations69
Published2006
Admission routes1
Has abstractyes

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