LGBTQ+ Structural Stigma and Health: Advancing the State of the Science Through New Meta-Analytic, Methodological, and Mechanistic Insights
4 - (SYM 16) Measuring Early-life LGBTQ+ Structural Stigma and Examining Its Life-course Effects Among Sexual Minority Women: A Natural Language Processing Approach
Friday, November 21, 2025
6:09 PM - 6:30 PM CST
Location: Imperial 12, Level 4
Keywords: LGBTQ+, Stigma, Mental Health Disparities Recommended Readings: Lattanner, M. R., et al. (2024). State of the science of structural stigma and LGBTQ+ health: Meta-analytic evidence, research gaps, and future directions. Annual Review of Public Health. https://doi.org/10.1146/annurev-publhealth-071723-013336, Hatzenbuehler, M. L., et al. (2024). Structural stigma and LGBTQ+ health: A narrative review of quantitative studies. The Lancet Public Health, 9(2), e109–e127. https://doi.org/10.1016/s2468-2667(23)00312-2, Ford, J. V., et al. (2024). (Re)conceptualizing structural stigma: Insights from a qualitative study of sexual minority men in a longitudinal, population-based cohort. Stigma and Health. https://doi.org/10.1037/sah0000571, Hollinsaid, N. L., et al. (2023). Incorporating macro-social contexts into emotion research: Longitudinal associations between structural stigma and emotion processes among gay and bisexual men. Emotion, 23(6), 1796–1801. https://doi.org/10.1037/emo0001198, Burger, J., & Pachankis, J. E. (2024). State of the science: LGBTQ-affirmative psychotherapy. Behavior Therapy,55(6), 1318–1334. https://doi.org/10.1016/j.beth.2024.02.011
Postdoctoral Fellow Columbia University Mailman School of Public Health New York, NY, United States
Abstract Body Structural stigma adversely impacts the health of LGBTQ+ people, including sexual minority women. These relationships are consistent across multiple health outcomes and across a variety of structural stigma measures (e.g., laws/policies, social attitudes). It is less well understood whether early-life exposure to LGBTQ+ structural stigma impacts health sequelae later into adulthood. A major barrier to explicating those relationships is that we have limited measures of LGBTQ+ structural stigma that reflect the childhood circumstances of sexual minorities who are middle and older ages today.
In this presentation, I will describe ongoing work using computational linguistics—specifically, natural language processing—to characterize the structural stigma environment surrounding sexual minorities in the US. Using a corpus of newspapers from the 1940s to the 1960s, this machine learning approach will extract information about the average structural stigma environment in each US state. This research uses a technique called sentiment analysis to discretely quantify how positively or negatively sexual minorities are represented in these historical newspaper texts.
In addition to discussing the creation and interpretation of this novel LGBTQ+ structural stigma measure, I will also present preliminary results testing how early-life exposure to LGBTQ+ structural stigma—measured using this approach—influences later life behavioral health among a sample of 7,335 sexual minority women from the US participating in the Nurses’ Health Study.
This approach lays the groundwork for utilizing alternative data structures to measure the structural stigma environment, which can facilitate scholarship examining the life-course effects of structural stigma not only for LGBTQ+ people but also for people with other stigmatized identities.
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