{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,7]],"date-time":"2026-08-07T14:37:19Z","timestamp":1786113439898,"version":"build-2736575974"},"reference-count":43,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Form Res"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>This study aims to explore women\u2019s 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 \u201cchild and family health\u201d nurses, and (D) opinions on infant feeding topics suitable for AI.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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\u2019s 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\u2019s perceptions and preferences on infant feeding topics suitable for AI (objectives B, C, and D). Thematic analysis was used to analyze focus group transcripts.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>A total of 164 women completed the quantitative survey. Approximately 53% (87\/164) of participants were open to receiving AI recommendations to see a health professional for infant feeding support, 34% (56\/164) were open to AI assessing their breastfeeding experiences, and 41% (67\/163) were open to AI providing advice to prevent or address breastfeeding challenges. Fewer Aboriginal and Torres Strait Islander participants were open to receiving AI-generated support (adjusted odds ratio 0.41, 95% CI 0.19-0.92) or advice to see a health professional (adjusted odds ratio 0.29, 95% CI 0.13-0.64). Twelve women participated in 3 online focus groups. Thematic analysis resulted in three overarching themes: (1) opportunities to fill gaps in support, (2) variable confidence engaging with AI for information and advice, and (3) potential convenience of AI and mHealth to offer timely support.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>The study highlights the potential of AI and barriers to women\u2019s acceptability and engagement. While women recognized the potential for AI to fill health care gaps in infant feeding support, including after business hours, there was less interest in AI replacing \u201cin-person\u201d support or information easily located via online search. Women\u2019s concerns regarding the credibility and trustworthiness of AI-enabled support should be addressed to maximize their use of emerging AI-enabled tools, embedded within digital technologies and mHealth. There is potential for AI to complement rather than replace usual care.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2196\/85102","type":"journal-article","created":{"date-parts":[[2026,5,14]],"date-time":"2026-05-14T15:32:03Z","timestamp":1778772723000},"page":"e85102","source":"Crossref","is-referenced-by-count":0,"title":["Exploring Women\u2019s Perspectives on Receiving AI-Enabled Digital Support for Infant Feeding: Multimethods Cross-Sectional 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