The representation of Indigenous peoples in chronic disease clinical trials in Australia, Canada, New Zealand, and the United States
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Indigenous peoples are overrepresented with chronic health conditions and experience suboptimal outcomes compared with non-Indigenous peoples. Genetic variations influence therapeutic responses, thus there are potential risks and harm when extrapolating evidence from the general population to Indigenous peoples. Indigenous population-specific clinical studies, and inclusion of Indigenous peoples in general population clinical trials, are perceived to be rare. Our study (1) identified and characterized Indigenous population-specific chronic disease trials and (2) identified the representation of Indigenous peoples in general population chronic disease trials conducted in Australia, Canada, New Zealand, and the United States. METHODS: For Objective 1, publicly available clinical trial registries were searched from May 2010 to May 2020 using Indigenous population-specific terms and included for data extraction if in pre-specified chronic disease. For identified trials, we extracted Indigenous population group identity and characteristics, type of intervention, and funding type. For Objective 2, a random selection of 10% of registered clinical trials was performed and the proportion of Indigenous population participants enrolled extracted. RESULTS: In total, 170 Indigenous population-specific chronic disease trials were identified. The clinical trials were predominantly behavioral interventions (n = 95). Among general population studies, 830 studies were randomly selected. When race was reported in studies (n = 526), Indigenous individuals were enrolled in 172 studies and constituted 5.6% of the total population enrolled in those studies. CONCLUSION: Clinical trials addressing chronic disease conditions in Indigenous populations are limited. It is crucial to ensure adequate representation of Indigenous peoples in clinical trials to ensure trial data are applicable to their clinical care.
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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 | 0.144 | 0.021 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it