“Something is wrong!” A qualitative study of racial disparities in parental experiences of OSA detection in their child
Bibliographic record
Abstract
Introduction Approximately 3% of American children are affected by obstructive sleep apnea (OSA), yet Black children are 2–4 times more likely to experience OSA compared to White children. Little is known about parental experiences in detection, diagnosis, and treatment of OSA in their child, and how these experiences may differ by race. The study objective was to highlight convergent and divergent experiences between and across Black and White parents in the OSA detection process for their child. Methods We conducted 27 semi-structured interviews with mothers whose child was referred for a diagnostic overnight polysomnogram (PSG) to assess for OSA. Parents described how their child was referred for a PSG and their perceptions and feelings throughout the detection process. Data were analyzed using a thematic descriptive approach. Frequency of themes were examined by race. Themes that were unique to one racial group were categorized as divergent, whereas themes described by individuals from both groups were categorized as convergent. Within the convergent themes, we examined the prevalence within each racial group, noting those that were more prevalent (>10% difference in prevalence) in one race or the other. Results The sample included 19 Black and 8 White mothers, who were 36 years old on average. Qualitative analysis yielded 21 themes across 5 categories that captured divergent and convergent experiences across Black and White mothers during the OSA detection process for their child. Divergent themes that were unique to Black mothers included It Takes a Village—Teacher, Misplaced Blame, Missing the Day/night Connection, Trust in Provider, and the belief that Snoring is Normal. Only one divergent theme among White parents emerged, worries about Dying in Ones Sleep. Additional convergent themes were identified that were more prevalent in one race compared to the other. Discussion Black and White mothers experienced different paths to detection and diagnosis for their child's sleep disordered breathing, that are affected by individual awareness, education, patient-provider interactions, and experiences with the healthcare system. Divergent themes such as Misplaced Blame among Black mothers were a potential indication of racism and health disparities.
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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 | 0.011 | 0.019 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.010 | 0.007 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| 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".