Media exposure to maternal health trauma: A qualitative study on its effects on Black women's mental health
Bibliographic record
Abstract
Black women experience disproportionately higher rates of death, illness, and mental health issues during and after pregnancy. The recent surge in avoidable maternal deaths in the U.S. has alarmed national and local media. Despite the media’s responsibility to inform, its coverage of traumatic events may negatively affect people’s mental health. This research examined if and how exposure to media narratives regarding maternal healthcare experiences affected the mental health of Black women. Between June and September 2020, we interviewed thirty Black women who had given birth within the prior 18 months. The data were analyzed using thematic analysis. The main themes were: 1) sources of and experiences with traumatic maternal health narratives, 2) the stressful effects of media, and 3) the media’s role in fostering positive communication. We found that traumatic maternal health narratives in the media affect the mental health of Black women. However, such narratives also facilitated valuable discussions between the women, their partners, family, and healthcare providers. Thus, despite being a potential source of stress, media exposure can cultivate positive communication patterns.
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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 | 0.010 | 0.014 |
| 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 | 0.008 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| 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".