Background: Capturing military sexual trauma (MST) exposure is critical for Veterans' health equity. For many, it improves access to VA services and allows for appropriate care.
Objective: Identify factors associated with nondisclosure of MST in VA screening among women.
Design: Cross-sectional telephone survey linked with VA electronic health record (EHR) data.
Participants: Women Veterans using primary care or women's health services at 12 VA facilities in nine states.
Main Measures: Survey self-reported MST (sexual assault and/or harassment during military service), socio-demographics and experiences with VA care, as well as EHR MST results. Responses were categorized as "no MST" (no survey or EHR MST), "MST captured by EHR and survey," and "MST not captured by EHR" (survey MST but no EHR MST). We used stepped multivariable logistic regression to examine "MST not captured by EHR" as a function of socio-demographics, patient experiences, and screening method (survey vs. EHR).
Key Results: Among 1287 women (mean age 50, SD 15), 35% were positive for MST by EHR and 61% were positive by survey. Approximately 38% had "no MST," 34% "MST captured by EHR and survey," and 26% "MST not captured by EHR". In fully adjusted models, odds of "MST not captured by EHR" were higher among Black and Latina women compared to white women (Black: OR = 1.6, 1.2-2.2; Latina: OR = 1.9, 1.0-3.6). Women who endorsed only sexual harassment in the survey (vs. sexual harassment and sexual assault) had fivefold higher odds of "MST not captured by EHR" (OR = 4.9, 3.2-7.3). Women who were screened for MST in the EHR more than once had lower odds of not being captured (OR = 0.3, 0.2-0.4).
Conclusions: VA screening for MST may disproportionately under capture patients from historically minoritized ethnic/racial groups, creating inequitable access to resources. Efforts to mitigate screening disparities could include re-screening and reinforcing that MST includes sexual harassment.
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http://dx.doi.org/10.1007/s11606-023-08257-6 | DOI Listing |
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Front Plant Sci
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College of Electronic Engineering (College of Artificial Intelligence), South China Agricultural University, Guangzhou, China.
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Aalborg University, Department of the Built Environment, Aalborg, Denmark. Electronic address:
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