Exploring Women's Perspectives on Receiving AI-Enabled Digital Support for Infant Feeding: Multimethods Cross-Sectional Study

作者：Stanley S, Jackson J, Brown AL, Lane C, Hudson N, Delaney T, Wolfenden L, Sutherland R · 发表于：JMIR formative research · 年份：2026 · DOI：10.2196/85102 · 研究领域：AI in health care、artificial intelligence、digital health interventions、digital technologies、infant feeding、mHealth、mobile health

BACKGROUND: Infant feeding practices, including breastfeeding, are known to benefit maternal and child health outcomes. Therefore, parent access to evidence-based infant feeding advice is critical. In recent years, there has been increased use of digital health technologies to support infant feeding. Despite its potential, using AI to complement existing health care and connect families to timely infant feeding support remains relatively unexplored. OBJECTIVE: This study aims to explore women's perceptions of using AI-enabled infant feeding support within mobile health (mHealth) interventions. The study investigates (A) openness to AI-enabled support, (B) experiences with existing AI-enabled support, (C) preferences for SMS text messages generated by AI versus "child and family health" nurses, and (D) opinions on infant feeding topics suitable for AI. METHODS: Two data collection activities were undertaken with women (primary caregivers) of infants aged 6-14 months, residing in the Hunter New England Local Health District (HNELHD) of New South Wales, Australia. Different women who received antenatal care in HNELHD were recruited for quantitative and qualitative data collection. Quantitative surveys assessed women's openness to receiving AI-enabled support (objective A). Descriptive and logistic regression analyses were conducted to explore associations between participant characteristics and openness to AI. Qualitative data collection involved focus groups to explore women'...