Factors associated with healthcare professionals’ use of stigmatizing language in individuals with diabetes in pregnancy

Clinicians’ language can influence patient perception and engagement in care. Use of stigmatizing language, including terms such as “noncompliant”, “refused”, “failed”, and “unmotivated”, has been found to contribute to distress among individuals with diabetes in pregnancy. However, it is unclear how often healthcare professionals use stigmatizing language in the electronic health record (EHR) and the clinical factors associated with its use among birthing individuals with diabetes. A retrospective cohort study was conducted from 2018 to 2019, focusing on individuals with singleton, non-anomalous pregnancies diagnosed with pre-existing or gestational diabetes. We utilized an academic-community obstetric outcomes database, employing a Natural Language Processing (NLP) algorithm to identify stigmatizing terms in electronic health records, including variations of terms such as “failed,” “refused,” “unwilling,” “unmotivated,” “noncompliant,” and “non-adherent.” We then compared the clinical characteristics, outcomes, and glycemic markers of individuals with and without documented stigmatizing language. Unadjusted and adjusted logistic regression models assessed the association of clinical factors on the utilization of stigmatizing language. Out of 1,433 birthing individuals who met criteria, 128 (8.9%) exhibited stigmatizing language in their records. The most common terms were related to “noncompliant” (47%) and “refused” (42%), primarily used by physicians and nurses. Birthing individuals of color were about four times more likely to have stigmatizing language used in their EHR compared to White individuals (aOR 3.87, 95% CI 2.55–5.99, p < 0.001). Those speaking languages other than English and Spanish were three times more likely to have stigmatizing terms documented (aOR 3.18, 95% CI 1.98–5.01, p < 0.001). Finally, individuals using public insurance were nearly five times more likely to receive stigmatizing descriptions compared to those with private insurance (aOR 4.95, 95% CI 3.26–7.73, p < 0.001). No differences were seen in NICU admission after controlling for diabetes type, and few objective markers of glycemia were identified in the EHR. Birthing individuals of color, non-English/non-Spanish speakers, and those on public insurance diagnosed with diabetes in pregnancy were significantly more likely to have stigmatizing language documented within their medical records. Clinicians’ use of stigmatizing language appears disconnected from glycemic concerns.

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Publication Details

Journal
BMC Pregnancy and Childbirth
Published
2026-03-03
DOI
https://doi.org/10.1186/s12884-026-08891-y
Primary Topic
Health Literacy and Information Accessibility
Type
article
Field-Weighted Citation Impact
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article

Factors associated with healthcare professionals’ use of stigmatizing language in individuals with diabetes in pregnancy

Sarah A. Wernimont, Anwei Gwan, J’Mag Karbeah, Sereen K. Nashif et al.
BMC Pregnancy and Childbirth
Health Literacy and Information Accessibility
article

Factors associated with healthcare professionals’ use of stigmatizing language in individuals with diabetes in pregnancy

Sarah A. Wernimont, Anwei Gwan, J’Mag Karbeah, Sereen K. Nashif, Jessica Makori, Anna Ayers Looby, Katelyn Tessier, Isai Ortiz, Sanjana Molleti, Oluwabukola O. Akingbola, Alexander A. Boucher, Renee M. Mahr
article en

Abstract

Clinicians’ language can influence patient perception and engagement in care. Use of stigmatizing language, including terms such as “noncompliant”, “refused”, “failed”, and “unmotivated”, has been found to contribute to distress among individuals with diabetes in pregnancy. However, it is unclear how often healthcare professionals use stigmatizing language in the electronic health record (EHR) and the clinical factors associated with its use among birthing individuals with diabetes. A retrospective cohort study was conducted from 2018 to 2019, focusing on individuals with singleton, non-anomalous pregnancies diagnosed with pre-existing or gestational diabetes. We utilized an academic-community obstetric outcomes database, employing a Natural Language Processing (NLP) algorithm to identify stigmatizing terms in electronic health records, including variations of terms such as “failed,” “refused,” “unwilling,” “unmotivated,” “noncompliant,” and “non-adherent.” We then compared the clinical characteristics, outcomes, and glycemic markers of individuals with and without documented stigmatizing language. Unadjusted and adjusted logistic regression models assessed the association of clinical factors on the utilization of stigmatizing language. Out of 1,433 birthing individuals who met criteria, 128 (8.9%) exhibited stigmatizing language in their records. The most common terms were related to “noncompliant” (47%) and “refused” (42%), primarily used by physicians and nurses. Birthing individuals of color were about four times more likely to have stigmatizing language used in their EHR compared to White individuals (aOR 3.87, 95% CI 2.55–5.99, p < 0.001). Those speaking languages other than English and Spanish were three times more likely to have stigmatizing terms documented (aOR 3.18, 95% CI 1.98–5.01, p < 0.001). Finally, individuals using public insurance were nearly five times more likely to receive stigmatizing descriptions compared to those with private insurance (aOR 4.95, 95% CI 3.26–7.73, p < 0.001). No differences were seen in NICU admission after controlling for diabetes type, and few objective markers of glycemia were identified in the EHR. Birthing individuals of color, non-English/non-Spanish speakers, and those on public insurance diagnosed with diabetes in pregnancy were significantly more likely to have stigmatizing language documented within their medical records. Clinicians’ use of stigmatizing language appears disconnected from glycemic concerns.

BMC Pregnancy and Childbirth
University of Minnesota (US), University of Minnesota Medical Center (US), Minnesota Department of Health (US)
Gender equality
Openalex Percentile: Top 40%
Health Literacy and Information Accessibility
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