Impact of a multidisciplinary diabetes care programme on glycaemic and metabolic outcomes in regional and First Nations communities: a retrospective observational study
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes mellitus (T2DM) poses a significant public health challenge in Australia, particularly among underserved populations such as First Nations people and rural communities. In response, the Together Strong Connected Care (TSCC) programme was developed to address these disparities by offering a culturally appropriate, multidisciplinary approach to diabetes management in a regional hospital setting. AIMS: The aim of the study was to assess the impact of the TSCC programme on glycaemic and metabolic control in people living with diabetes. METHODS: This was a retrospective observational study. Baseline characteristics, including age, gender, ethnicity and clinical measures, were collected. The primary outcome was the change in HbA1c over 12 months. Statistical analysis included descriptive analysis, univariate comparative analysis, paired t-tests for change in outcomes and multivariate linear regression analysis. RESULTS: The study included 119 patients, divided into those who participated in the TSCC programme (n = 68) and those who declined participation (n = 51). The study participants had a mean age of 55.71 years, with 58.82% identifying as female. The mean baseline HbA1c was 8.25% (SD = 2.60) and mean baseline weight was 97.38 kg (SD = 28.81). People in the TSCC group had significantly greater reductions in HbA1c (-1.65%, P < 0.001) compared to the no-TSCC group (+0.02%, P < 0.001). After adjusting for confounders, TSCC participation remained independently associated with improved glycaemic control (β = -0.78, P < 0.001), particularly in patients with T2DM. CONCLUSIONS: The TSCC programme significantly improved glycaemic control in regional First Nations patients, supporting the effectiveness of culturally appropriate, multidisciplinary care models in managing diabetes in underserved communities. Further research is warranted to evaluate long-term outcomes of similar interventions.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".