Artificial Intelligence Analysis of Cultural Narratives Shaping Emotional Responses to Infertility

Infertility is a global health concern often linked to emotional distress shaped by cultural narratives. While medical aspects are well studied, the cultural emotional dimension remains less explored, especially using computational methods. This study examines how cultural norms influence emotional responses to infertility. AI-driven Natural Language Processing (NLP) techniques, such as sentiment analysis, thematic coding, and topic modelling, were applied to qualitative data from interviews, social media, and cultural texts across Southeast Asia, Sub-Saharan Africa, Western Europe, and North America. Findings show clear cultural patterns: collectivist societies report higher shame and stigma, while individualist cultures exhibit greater resilience but more isolation. Religious contexts often rely on spiritual guidance, whereas medicalized societies prioritize fertility treatments. These results underscore the strong influence of cultural norms on emotional expression, social support, and healthcare access. By combining computational analysis with sociocultural perspectives, this study offers actionable insights for designing culturally sensitive interventions. The approach demonstrates the value of integrating AI and cultural analysis in addressing infertility’s emotional and social impacts.