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arXiv:2611.15580 · v1

Making Doula Coordination Breakdowns Visible: A Participatory Case Study

首次提交 2026-11-11 23:02
版本更新 2026-11-11 23:02
雷达观测 2026-11-13 14:16
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摘要

Doulas are trained, non-medical professionals who provide emotional, physical, and informational support to pregnant individuals before, during, and after childbirth. Doulas provide extensive relational and coordination labor for pregnant and postpartum patients, spending far more time with clients than traditional providers do, yet they operate with almost no doula-specific digital infrastructure. This gap is especially acute in rural communities, where postpartum depression affects about 25% of women, well above the national average, and where geographic isolation and provider shortages leave many without access to behavioral health care. DoulaConnect began as a 12-week evidence-based postpartum texting curriculum, piloted separately in a randomized controlled trial in rural New England. Building on that work, we present DoulaConnect's development into an AI-enabled platform co-designed with doulas and rural mothers through participatory human-centered design, as a case for surfacing where coordination breaks down in doula practice and who currently absorbs the resulting burden. Our community-based participatory study, conducted across the platform's Discover and Define phases, combines qualitative sessions with doulas and mothers to identify these breakdowns. We close with tensions this approach surfaces and open questions for the workshop about how these findings will inform future participatory AI infrastructure for doula care in rural and other under-resourced communities.

作者备注:Presented at the CSCW 2026 Workshop on Women's Health as Cooperative Work: Participatory AI Across Care, Community, and Policy (arXiv:2611.03776)

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v1 · 2026-11-11 23:02 · 最新观测版本

Making Doula Coordination Breakdowns Visible: A Participatory Case Study

Doulas are trained, non-medical professionals who provide emotional, physical, and informational support to pregnant individuals before, during, and after childbirth. Doulas provide extensive relational and coordination labor for pregnant and postpartum patients, spending far more time with clients than traditional providers do, yet they operate with almost no doula-specific digital infrastructure. This gap is especially acute in rural communities, where postpartum depression affects about 25% of women, well above the national average, and where geographic isolation and provider shortages leave many without access to behavioral health care. DoulaConnect began as a 12-week evidence-based postpartum texting curriculum, piloted separately in a randomized controlled trial in rural New England. Building on that work, we present DoulaConnect's development into an AI-enabled platform co-designed with doulas and rural mothers through participatory human-centered design, as a case for surfacing where coordination breaks down in doula practice and who currently absorbs the resulting burden. Our community-based participatory study, conducted across the platform's Discover and Define phases, combines qualitative sessions with doulas and mothers to identify these breakdowns. We close with tensions this approach surfaces and open questions for the workshop about how these findings will inform future participatory AI infrastructure for doula care in rural and other under-resourced communities.

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