American Indians’ Family Health Concern on a Northern Plains Reservation: “Diabetes Runs Rampant Here”
Bibliographic record
Abstract
OBJECTIVES: The objective was to identify significant family health concerns from the perspective of adult tribal members residing in a reservation setting on the Northern Plains of the United States. Findings were used to cocreate culturally appropriate strategies to address the most significant family health concern. DESIGN AND SAMPLE: A focused ethnography within a participatory framework was employed. An advisory council, comprised of seven tribal members, guided the research team. A purposive sampling technique with a snowball process was used. Twenty-one adult tribal members volunteered to participate. MEASURES: Face-to-face, audio-recorded, semi-structured interviews were conducted and transcribed verbatim. Other data sources included field notes of approximately 100 hours of field work, windshield surveys, and a focus group. Data were analyzed using Spradley's guidelines. RESULTS: The significant family health concern was "diabetes runs rampant here" with inter-related cognitive, emotional, and behavioral responses. These responses were compounded by accumulated emotional trauma from witnessing premature deaths and severe comorbidities associated with diabetes. Contextual factors shaping "diabetes runs rampant here" were identified. CONCLUSION: Holistic approaches are urgently needed in diabetes prevention and management programs. Implications for public health nurses are discussed and recommendations are provided for future research.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".