Exploring structural barriers to diabetes self-management in Alberta First Nations communities
Bibliographic record
Abstract
BACKGROUND: Type 2 diabetes is highly prevalent in Canadian First Nations (FN) communities. FN individuals with diabetes are less likely to receive guideline recommended care and access specialist care. They are also less likely to be able to engage in optimal self-management behaviours. While the systemic and racial contributors to this problem have been well described, individuals' experiences with structural barriers to care and self-management remain under-characterized. METHODS: We utilized qualitative methods to gain insight into the structural barriers to self-management experienced by FN individuals with diabetes. We conducted a qualitative descriptive analysis of a subcohort of patients with diabetes from FN communities (n = 5) from a larger qualitative study. Using detailed semi-structured telephone interviews, we inquired about participants' diabetes and barriers to diabetes self-management. Inductive thematic analysis was performed in duplicate using NVivo 10. RESULTS: The structural barriers faced by this population were substantial yet distinct from those described by non-FN individuals with diabetes. For example, medication costs, which are usually cited as a barrier to care, are covered for FN persons with status. The barriers to diabetes self-management that were commonly experienced in this cohort included transportation-related difficulties, financial barriers to uninsured health services, and lack of accessible diabetes education and resultant knowledge gaps. CONCLUSIONS: FN Albertans with diabetes face a myriad of barriers to self-management, which are distinct from the Non-FN population. In addition to the barriers introduced by colonialism and historical injustices, finances, geographic isolation, and lack of diabetes education each impede optimal management of diabetes. Programs targeted at addressing FN-specific barriers may improve aspects of diabetes self-management in this population.
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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.013 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 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".