Shared medical appointments for Innu patients with well-controlled diabetes in a Northern First Nation Community
Bibliographic record
Abstract
INTRODUCTION: The prevalence of diabetes and its complications in the Innu community of Sheshatshiu is high. We wanted to determine if shared medical appointments (SMAs) could provide culturally appropriate, effective treatment to Innu patients with relatively well-controlled diabetes, as an alternative to standard, 'one-on-one' care. METHODS: We conducted a mixed-method study including a randomised controlled trial comparing standard care versus SMAs for patients aged 18-65 years with haemoglobin A1C (HbA1C) of ≤7.5%, followed by a qualitative study using semi-structured interviews with patients who attended SMAs. RESULTS: Among 23 patients, 13 received the intervention. There were no significant differences of HbA1C level or HbA1C percentage of change between intervention and control groups at baseline, 6 months or 12 months. There were no statistical differences between standard care and SMA groups, concerning mortality or the need for haemodialysis. The qualitative analysis found that patients generally enjoyed the SMA model and the peer support and learning benefits of the SMAs. Patients did not believe that the SMA model was more or less culturally appropriate than standard care, but the majority said they felt that the SMAs were good for the community and could be a good venue for incorporating Innu healthy-lifestyle knowledge into medical diabetes care. CONCLUSIONS: SMAs may be an efficient way to manage well-controlled diabetic patients in the Innu community of Sheshatshiu and to provide peer support and opportunities for learning and incorporating community-specific knowledge into care.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".