Stigmatizing Mothers: Qualitative Analysis of Language in Prenatal Records

Pregnant people experience moral judgment in healthcare settings that may be coded into clinical documentation. Stigmatizing language in medical records transmits bias between clinicians, potentially exacerbating disparities in maternal morbidity and mortality. We examined obstetrical records from 100 randomly selected patients who received prenatal and delivery care in an academic hospital system. Qualitative analysis sought to identify linguistic features conveying negative attitudes or moral judgment, revealing themes of epistemic injustice: (1) discrediting patient testimony as incompetent, unreliable, and hysterical; (2) unnecessary details that are objectifying, stigmatizing, or unprofessional; and (3) judgments of maternal fitness, where women are labeled "bad mothers" by emphasizing neglectful, selfish, and debauched characteristics. We conclude by advocating for further validation of our findings, revisiting medical education paradigms, and supporting the development of natural language processing (NLP) technologies to detect and intercept stigma.

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Publication Details

Journal
Narrative Inquiry in Bioethics
Published
2025-01-01
DOI
https://doi.org/10.1353/nib.2025.a974066
Primary Topic
Feminist Epistemology and Gender Studies
Type
article
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article

Stigmatizing Mothers: Qualitative Analysis of Language in Prenatal Records

Ananya Dewan, Mary Catherine Beach, Joie L. Zabec, Marielle S. Gross et al.
Narrative Inquiry in Bioethics
Feminist Epistemology and Gender Studies
article

Stigmatizing Mothers: Qualitative Analysis of Language in Prenatal Records

Ananya Dewan, Mary Catherine Beach, Joie L. Zabec, Marielle S. Gross, Diana Mendoza-Cervantes
article en

Abstract

Pregnant people experience moral judgment in healthcare settings that may be coded into clinical documentation. Stigmatizing language in medical records transmits bias between clinicians, potentially exacerbating disparities in maternal morbidity and mortality. We examined obstetrical records from 100 randomly selected patients who received prenatal and delivery care in an academic hospital system. Qualitative analysis sought to identify linguistic features conveying negative attitudes or moral judgment, revealing themes of epistemic injustice: (1) discrediting patient testimony as incompetent, unreliable, and hysterical; (2) unnecessary details that are objectifying, stigmatizing, or unprofessional; and (3) judgments of maternal fitness, where women are labeled "bad mothers" by emphasizing neglectful, selfish, and debauched characteristics. We conclude by advocating for further validation of our findings, revisiting medical education paradigms, and supporting the development of natural language processing (NLP) technologies to detect and intercept stigma.

Narrative Inquiry in BioethicsVol. 15(2)
Openalex Percentile: Top 58%
Feminist Epistemology and Gender Studies
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Stigmatizing Mothers: Qualitative Analysis of Language in Prenatal Records — Ananya Dewan, Mary Catherine Beach, et al. · Narrative Inquiry in Bioethics (2025) | TGRS Research Map | TGRS