Barriers, frameworks, and mitigating strategies influencing the dissemination and implementation of health promotion interventions in indigenous communities: a scoping review
Bibliographic record
Abstract
BACKGROUND: Many Indigenous communities across the USA and Canada experience a disproportionate burden of health disparities. Effective programs and interventions are essential to build protective skills for different age groups to improve health outcomes. Understanding the relevant barriers and facilitators to the successful dissemination, implementation, and retention of evidence-based interventions and/or evidence-informed programs in Indigenous communities can help guide their dissemination. PURPOSE: To identify common barriers to dissemination and implementation (D&I) and effective mitigating frameworks and strategies used to successfully disseminate and implement evidence-based interventions and/or evidence-informed programs in American Indian/Alaska Native (AI/AN), Native Hawaiian/Pacific Islander (NH/PI), and Canadian Indigenous communities. METHODS: A scoping review, informed by the York methodology, comprised five steps: (1) identification of the research questions; (2) searching for relevant studies; (3) selection of studies relevant to the research questions; (4) data charting; and (5) collation, summarization, and reporting of results. The established D&I SISTER strategy taxonomy provided criteria for categorizing reported strategies. RESULTS: Candidate studies that met inclusion/exclusion criteria were extracted from PubMed (n = 19), Embase (n = 18), and Scopus (n = 1). Seventeen studies were excluded following full review resulting in 21 included studies. The most frequently cited category of barriers was "Social Determinants of Health in Communities." Forty-three percent of barriers were categorized in this community/society-policy level of the SEM and most studies (n = 12, 57%) cited this category. Sixteen studies (76%) used a D&I framework or model (mainly CBPR) to disseminate and implement health promotion evidence-based programs in Indigenous communities. Most highly ranked strategies (80%) corresponded with those previously identified as "important" and "feasible" for D&I The most commonly reported SISTER strategy was "Build partnerships (i.e., coalitions) to support implementation" (86%). CONCLUSION: D&I frameworks and strategies are increasingly cited as informing the adoption, implementation, and sustainability of evidence-based programs within Indigenous communities. This study contributes towards identifying barriers and effective D&I frameworks and strategies critical to improving reach and sustainability of evidence-based programs in Indigenous communities. REGISTRATION NUMBER: N/A (scoping review).
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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 | 0.081 | 0.231 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.005 | 0.007 |
| Bibliometrics | 0.028 | 0.026 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.012 | 0.010 |
| Open science | 0.004 | 0.006 |
| Research integrity | 0.004 | 0.004 |
| 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".