Learning From Our Strengths: Exploring Strategies to Support Heart Health in Indigenous Communities
Bibliographic record
Abstract
Indigenous populations have remained resilient in maintaining their unique culture and values, despite facing centuries of colonial oppression. With many discriminatory policies continuing to disempower Indigenous peoples, First Nations communities have been reported to experience a higher level of cardiovascular disease (CVD)-related mortality, compared to that in the general population. Many of the risk factors contributing to the burden of CVD have been attributed to the impact of colonization and the ongoing dismissal of Indigenous knowledge. Despite Indigenous peoples recognizing the value of addressing their mental, physical, spiritual, and emotional well-being in balanced totality, current health services focus predominantly on the promotion of Western biomedicine. To begin to move toward reconciliation, a better understanding of how Indigenous health is defined within different cultural worldviews is needed. The objective of this scoping review was to explore the various Western and/or Indigenous strategies used for the prevention of CVD and the management of heart health and wellness in Indigenous communities in Canada. In this review, a total of 3316 articles were identified, and only 21 articles met the eligibility criteria. Three major themes emerged, as follows: (i) valuing of the emotional domain of health through cultural safety; (ii) community is at the core of empowering health outcomes; and (iii) bridging of cultures through partnership and mutual learning. Most studies recognized the importance of community engagement to develop heart health strategies that integrate traditional languages and cultures. However, to move toward the delivery of culturally safe care, health systems need to rebuild their relationship with Indigenous peoples.
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 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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.007 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".