JOURNAL ARTICLE

Plotting the Past and Future of Hormonal Contraception: A Narrative Public Health Ethics Approach to Centering Patients' Voices in the Pharmacogenomic Era of Birth Control.

  • Published In: IJFAB: International Journal of Feminist Approaches to Bioethics, 2024, v. 17, n. 2. P. 1 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Towle, Sarah 3 of 3

Abstract

This article examines the emerging socio-ethical-legal challenges as hormonal contraception enters the pharmacogenomic era, where genetic testing (GT) could personalize birth control prescribing to improve safety and efficacy. Despite decades of evidence linking genetic variants—such as Factor V Leiden (FV) and BRCA mutations—to increased risks from hormonal contraceptives, North American clinical guidelines and regulations remain limited, while direct-to-consumer genetic testing (DTC-GT) for contraceptive users is expanding without comprehensive oversight. Using a narrative public health ethics framework, the article highlights the historical marginalization of patient voices, especially women and racialized groups, and argues for patient-centered research and policy development to address autonomy, justice, maleficence, and privacy concerns. It concludes that integrating diverse patient perspectives and improving education and regulation around pharmacogenomic testing are essential steps toward ethically informed contraceptive care in this evolving landscape.

Additional Information

  • Source:IJFAB: International Journal of Feminist Approaches to Bioethics. 2024/10, Vol. 17, Issue 2, p1
  • Document Type:Article
  • Subject Area:Consumer Health
  • Publication Date:2024
  • ISSN:1937-4585
  • DOI:10.3138/ijfab.17.2.01
  • Accession Number:180553363
  • Copyright Statement:Copyright of IJFAB: International Journal of Feminist Approaches to Bioethics is the property of University of Toronto Press and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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