Healthcare experiences of patients with Down syndrome who are Black, African American, of African descent, or of mixed race
Bibliographic record
Abstract
Scant research has explored the healthcare experiences of people with Down syndrome (DS) in the United States who are Black, African American, of African descent, or of mixed race. The purpose of this study was to identify and describe the barriers and facilitators that such patients and their caregivers face when accessing healthcare. We gathered data in three ways: focus groups with caregivers, a national survey completed by caregivers, and in-depth interviews with primary care providers. Many caregivers and primary care physicians felt that patients with DS who are Black, African American, of African descent, or of mixed race receive a lower quality of medical care than their white counterparts with DS. Caregivers mentioned feeling tired of being reminded by the medical community about their race and wanting acknowledgment that raising a child with DS can be hard at times. Many felt that the medical community's conscious and unconscious racial biases do negatively impact the care of their loved ones with DS. Caregivers desired more race concordant medical providers or, when not possible, medical providers who are willing to learn more about DS and build trusted, longitudinal relationships. Primary care providers discussed the need for funded resources and support services to effectively care for their patients with DS.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".