Cultural Fit, Privacy Concerns, and GCC Women’s Openness to AI-Enabled Menstrual Tracking: A Cross-Sectional Study

Abstract

Artificial intelligence (AI) is increasingly embedded in menstrual and reproductive health applications, yet little is known about how women in conservative, rapidly digitizing regions evaluate AI-enabled menstrual tracking tools. This study investigates how perceived cultural fit and data privacy concerns are associated with women’s openness to AI-enabled menstrual tracking in Gulf Cooperation Council (GCC) countries. We conducted a survey of adult women residing in GCC countries (N = 273), measuring openness to AI menstrual tools, perceptions of cultural fit (e.g., respect for religious and cultural norms, endorsement by trusted institutions, Arabic language, GCC-specific design), privacy concerns (e.g., worries about who can access menstrual health data), and key sociodemographic characteristics and smartphone use. Multi-item constructs were evaluated for reliability and validity, and multivariable linear regression models were estimated to examine associations with openness. Higher perceived cultural-contextual fit was strongly and positively associated with openness to AI-enabled menstrual tracking, whereas composite privacy concerns showed no statistically significant association once cultural fit and sociodemographic factors were controlled. Item-level analyses indicated that beliefs about cultural sensitivity and GCC-specific design were the most robust predictors of openness, while concerns about data access, authority endorsement, and language accessibility played a limited role. Homemakers reported higher openness than employed women. Overall, the findings suggest that GCC women’s openness to AI-enabled menstrual tracking depends more on whether tools are perceived as culturally aligned and locally designed than on privacy concerns alone, highlighting the importance of culturally grounded, trust-building design and communication strategies for AI-based health applications.