ANS International Section

The current ANS International Section article is titled “Intersectionality in Maternal Health: Gender, Labor, and Structural Barriers With “a Focus on Korea,” This article is authored by Jeung-Im Kim, PhD of the School of Nursing, Soonchunhyang University, Asan, Chungnam, South Korea; and Mi Yu, PhD of the College of Nursing, Sustainable Health Research Institute, Gyeongsang National University, Jinju, Gyeongnam, South Korea.

Article abstract

Drawing on intersectional feminist theory, this review interrogates maternal health disparities through lenses of gender, labor, and structural inequality, with a particular focus on South Korea. It integrates global trends with local realities to examine how socioeconomic status, digital divides, and algorithmic bias in artificial intelligence systems could compound maternal vulnerability. By critically evaluating gender gaps in nursing research and leadership, this paper advocates for the adoption of intersectionality as a foundational framework in nursing science to redress inequities and promote inclusive health care innovation.

Statements of Significance

What is known or assumed to be true about this topic?

• Maternal health is shaped by intersecting factors such as gender, socioeconomic status, and employment. In Korea and other countries, women face structural barriers such as workplace discrimination, financial strain, and stress during pregnancy. Although technological innovations such as artificial intelligence (AI) offer new possibilities for care delivery, their effectiveness is limited when gender biases in data and design are unaddressed. Despite increasing global focus on health equity, Korean nursing research often relies on gender-neutral frameworks that overlook lived experiences of marginalized women.

What this article adds:

• This review introduces an intersectional perspective to the examination of maternal health disparities in Korea, placing local issues within broader international frameworks. It shows how gender, economic inequality, and digital access can combine with each other to affect health outcomes, highlighting risks related to algorithmic bias and digital exclusion in AI-based care. The article calls for gender-responsive, inclusive nursing research and recommends strategies such as diversifying health data, expanding community-based care, and ethically integrating digital technologies. It argues that structural change in nursing is essential to advance equity in maternal health.