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"Koyi Sawaal Nahi Hai": Reimagining Maternal Health Chatbots for Collective, Culturally Grounded Care

Published: October 31, 2025 | arXiv ID: 2510.27401v1

By: Imaan Hameed , Huma Umar , Fozia Umber and more

Potential Business Impact:

Makes health helpers work for families, not just one person.

Business Areas:
mHealth Health Care, Mobile

In recent years, LLM-based maternal health chatbots have been widely deployed in low-resource settings, but they often ignore real-world contexts where women may not own phones, have limited literacy, and share decision-making within families. Through the deployment of a WhatsApp-based maternal health chatbot with 48 pregnant women in Lahore, Pakistan, we examine barriers to use in populations where phones are shared, decision-making is collective, and literacy varies. We complement this with focus group discussions with obstetric clinicians. Our findings reveal how adoption is shaped by proxy consent and family mediation, intermittent phone access, silence around asking questions, infrastructural breakdowns, and contested authority. We frame barriers to non-use as culturally conditioned rather than individual choices, and introduce the Relational Chatbot Design Grammar (RCDG): four commitments that enable mediated decision-making, recognize silence as engagement, support episodic use, and treat fragility as baseline to reorient maternal health chatbots toward culturally grounded, collective care.

Country of Origin
🇵🇰 Pakistan

Page Count
27 pages

Category
Computer Science:
Human-Computer Interaction