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

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.

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Publication Details

Journal
International Journal of Environmental Research and Public Health
Published
2026-08-28
DOI
https://doi.org/10.3390/ijerph23091121
Primary Topic
Mobile Health and mHealth Applications
Type
article
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article

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

Zeina Alkhalaf, Abdullah Alhauli
International Journal of Environmental Research and Public Health
Mobile Health and mHealth Applications
article

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

Zeina Alkhalaf, Abdullah Alhauli
article en

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.

International Journal of Environmental Research and Public HealthVol. 23(9)
Kuwait Institute for Scientific Research (KW), Kuwait University (KW), University of Maryland, College Park (US)
Gender equality
Openalex Percentile: Top 99%
Mobile Health and mHealth Applications
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