“Just Because You Have Ears Doesn’t Mean You Can Hear”—Perception of Racial-Ethnic Discrimination During Childbirth
Bibliographic record
Abstract
Background: Black and Latina women in New York City are twice as likely to experience a potentially life-threatening morbidity during childbirth than White women. Health care quality is thought to play a role in this stark disparity, and patient-provider communication is one aspect of health care quality targeted for improvement. Perceived health care discrimination may influence patient-provider communication but has not been adequately explored during the birth hospitalization. Purpose: Our objective was to investigate the impact of perceived racial-ethnic discrimination on patient-provider communication among Black and Latina women giving birth in a hospital setting. Methods: We conducted four focus groups of Black and Latina women (n=27) who gave birth in the past year at a large hospital in New York City. Moderators of concordant race/ethnicity asked a series of questions on the women's experiences and interactions with health care providers during their birth hospitalizations. One group was conducted in Spanish. We used an integrative analytic approach. We used the behavioral model for vulnerable populations adapted for critical race theory as a starting conceptual model. Two analysts deductively coded transcripts for emergent themes, using constant comparison method to reconcile and refine code structure. Codes were categorized into themes and assigned to conceptual model categories. Results: Predisposing patient factors in our conceptual model were intersectional identities (eg, immigrant/Latina or Black/Medicaid recipient), race consciousness ("…as a woman of color, if I am not assertive, if I am not willing to ask, then they will not make an effort to answer"), and socially assigned race (eg, "what you look like, how you talk"). We classified themes of differential treatment as impeding factors, which included factors overlooked in previous research, such as perceived differential treatment due to the relationship with the infant's father and room assignment. Themes for differential treatment co-occurred with negative provider communication attributes (eg, impersonal, judgmental) or experience (eg, not listened to, given low priority, preferences not respected). Conclusions: Perceived racial-ethnic discrimination during childbirth influences patient-provider communication and is an important and potentially modifiable aspect of the patient experience. Interventions to reduce obstetric health care disparities should address perceived discrimination, both from the provider and patient perspectives.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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 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".