Satisfaction with and perceived cultural competency of healthcare providers: the minority experience.
Bibliographic record
Abstract
It is well known that nonwhite minority participation in clinical research is lower than their representation in the community. The goal of this study was to assess satisfaction of minority community members in Omaha with the care received and cultural competency of healthcare providers. We sought input from Omaha minority communities on how to improve the care they received and asked why they did not participate in healthcare research. Seventy-two minority members representing African Americans, Hispanic Americans, Native Americans, Sudanese, and Vietnamese; and eight whites were surveyed. The results of this study indicated that the majority of our respondents were satisfied with the care they received, but for a small percentage, language, communication and/or culture contributed to dissatisfaction. In addition, some respondents did not think the provider was culturally competent, i.e., not sufficiently knowledgeable about their racial, ethnic and/or cultural background. Some participants indicated that they preferred a provider of similar racial, ethnic and/or cultural background, and/or thought some diseases were better treated by a provider of the same racial, ethnic and/or cultural background. Regardless of the cultural competency of the provider, the overwhelming majority of our respondents (with the exception of African Americans) indicated a willingness to participate in healthcare research. In conclusion, this study found that satisfaction with healthcare providers was not associated with perceived cultural competency and that the cultural competency of the provider did not affect patient willingness to participate in healthcare research; however, we acknowledge that the Hawthorne effect may be in operation.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".