Effective primary care management of type 2 diabetes for indigenous populations: A systematic review
Bibliographic record
Abstract
BACKGROUND: Indigenous peoples in high income countries are disproportionately affected by Type 2 Diabetes. Socioeconomic disadvantages and inadequate access to appropriate healthcare are important contributors. OBJECTIVES: This systematic review investigates effective designs of primary care management of Type 2 Diabetes for Indigenous adults in Australia, Canada, New Zealand, and the United States. Primary outcome was change in mean glycated haemoglobin. Secondary outcomes were diabetes-related hospital admission rates, treatment compliance, and change in weight or Body Mass Index. METHODS: Included studies were critically appraised using Joanna Briggs Institute appraisal checklists. A mixed-method systematic review was undertaken. Quantitative findings were compared by narrative synthesis, meta-aggregation of qualitative factors was performed. RESULTS: Seven studies were included. Three reported statistically significant reductions in means HbA1c following their intervention. Seven components of effective interventions were identified. These were: a need to reduce health system barriers to facilitate access to primary care (which the other six components work towards), an essential role for Indigenous community consultation in intervention planning and implementation, a need for primary care programs to account for and adapt to changes with time in barriers to primary care posed by the health system and community members, the key role of community-based health workers, Indigenous empowerment to facilitate community and self-management, benefit of short-intensive programs, and benefit of group-based programs. CONCLUSIONS: This study synthesises a decade of data from communities with a high burden of Type 2 Diabetes and limited research regarding health system approaches to improve diabetes-related outcomes. Policymakers should consider applying the seven identified components of effective primary care interventions when designing primary care approaches to mitigate the impact of Type 2 Diabetes in Indigenous populations. More robust and culturally appropriate studies of Type 2 Diabetes management in Indigenous groups are needed. TRAIL REGISTRATION: Registered with PROSPERO (02/04/2021: CRD42021240098).
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 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 | 0.011 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".