Equitable inclusion of racialised communities in genomic research: a scoping review
Bibliographic record
Abstract
OBJECTIVES: Genome Canada has committed significant resources to ensure that racialised groups are included in its initiatives; however, specific equity considerations related to engaging these communities in human genomic research continue to require deeper attention and exploration. This scoping review aims to widen the frame of analysis concerning inclusive human genomics by undertaking a synthesis that includes perspectives from genomicists, decision and policymakers, legal experts in bioethics and leaders from racialised communities. DESIGN: We conducted a comprehensive scoping review using the Arksey and O'Malley framework to examine the equitable participation of racialised communities in human genomic research. ELIGIBILITY CRITERIA: Our goal was to identify the barriers preventing these populations from equally participating in human genomic research. The review focused on studies from five countries: Canada, the USA, the UK, Australia and New Zealand which have similar immigration patterns and have received racialised populations from from some of the same communities around the globe. These features makes studying these particular countries germane to studying the common challenges they face in human genomics research. DATA SOURCES: Our scoping review examined both academic and grey literature, including MEDLINE, EMBASE, PsycINFO (inception to 11 June 2025), CINAHL (to 12 June 2025) and Cochrane Central Register of Controlled Trials (CENTRAL) (to 19 June 2025), as well as Google Scholar and OAISter (October, 2023). DATA EXTRACTION AND SYNTHESIS: Data were analysed using Braun and Clarke's thematic synthesis guidelines. These included familiarisation with the relevant texts in the selected articles, generating initial codes using an inductive approach, reviewing potential themes and finalising the themes based on the consensus of the research team. RESULTS: The study identified key barriers and facilitators to participation in human genomic research among racialised communities. The first theme (exclusion) highlighted obstacles such as a lack of transportation, limited knowledge of genetics and distrust stemming from concerns of stigmatisation and health disparities. The second theme (diversity of positions) described varied perceptions influenced by cultural values and motivations, with preferences for transparency and autonomy in research participation. Finally, the third theme (equity in genetic research) outlined the limited use of community-based participatory models and biobanking, underscoring the need for more inclusive and equitable research practices to fully engage racialised communities. CONCLUSION: Future research should prioritise strategies of authentic engagement with racialised communities to enhance both inclusivity and equity in genetic, human genomic, precision medicine and precision health research.
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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 | 0.007 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.014 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".