What do you mean by engagement? – evaluating the use of community engagement in the design and implementation of chronic disease-based interventions for Indigenous populations – scoping review
Bibliographic record
Abstract
BACKGROUND: Indigenous populations have remained strong and resilient in maintaining their unique culture and values, despite centuries of colonial oppression. Unfortunately, a consequential result of facing years of adversity has led Indigenous populations to experience a disproportionate level of poorer health outcomes compared to non-Indigenous populations. Specifically, the rate of Indigenous chronic disease prevalence has significantly increased in the last decade. Many of the unique issues Indigenous populations experience are deeply rooted in their colonial history and the intergenerational traumas that has subsequently impacted their physical, mental, emotional and spiritual well-being. With this, to better improve Indigenous health outcomes, understanding the local context of their challenges is key. Studies have begun to use modes of community engagement to initiate Indigenous partnerships and design chronic disease-based interventions. However, with the lack of a methodological guideline regarding the appropriate level of community engagement to be used, there is concern that many interventions will continue to fall short in meeting community needs. OBJECTIVE: The objective of this study was to investigate the how various community engagement strategies have been used to design and/or implement interventions for Indigenous populations with chronic disease. METHODS: A scoping review guided by the methods outlined by Arksey and O'Malley was conducted. A comprehensive search was completed by two reviewers in five electronic databases using keywords related to community engagement, Indigenous health and chronic disease. Studies were reviewed using a descriptive-analytical narrative method and data was categorized into thematic groups reflective of the main findings. RESULTS: We identified 23 articles that met the criteria for this scoping review. The majority of the studies included the use a participatory research model and the procurement of study approval. However, despite the claimed use of participatory research methods, only 6 studies had involved community members to identify the area of priority and only five had utilized Indigenous interview styles to promote meaningful feedback. Adapting for the local cultural context and the inclusion of community outreach were identified as the key themes from this review. CONCLUSION: Many studies have begun to adopt community engagement strategies to better meet the needs of Indigenous Peoples. With the lack of a clear guideline to approach Indigenous-based participatory research, we recommend that researchers focus on 1) building partnerships, 2) obtaining study approval and 3) adapting interventions to the local context.
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 | 0.180 | 0.401 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.011 |
| Bibliometrics | 0.016 | 0.018 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.014 | 0.011 |
| Open science | 0.004 | 0.008 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 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".