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A Common Marmoset Model of Mother-Infant Intervention for Breastfeeding Disorders in the Presence of Paternal Inhibition and Maternal Neglect
Published on: September 22, 2023
In the Age of Artificial Intelligence: From Standardized Questions to Real-World Breastfeeding Concerns
Maria Kkirgia1, Elli-Panagiota Magklara1, Christiana Zoupa2
1Neonatal Department, Aretaieio Hospital, National and Kapodistrian University of Athens, 11528 Athens, Greece.
Abstract:
Background: Breastfeeding is the recommended source of infant nutrition, yet mothers may experience concerns and difficulties that require timely access to reliable information and professional support. As the use of digital health tools increases, AI-powered chatbots such as ChatGPT and Gemini are increasingly accessible sources of breastfeeding information and support. This study aimed to descriptively compare responses generated by ChatGPT and Gemini with established breastfeeding information and multidisciplinary clinical support provided in real-world practice, using both standardized breastfeeding questions and clinic-derived scenarios. Materials and Methods: A descriptive comparative content-analysis study was conducted at Aretaieio University Hospital. Ten breastfeeding-related questions were included: five standardized questions derived from educational materials of the Institute of Child Health in Greece and five clinic-derived scenarios originating from individualized consultations through the hospital's breastfeeding-support helpline. Identical prompts were submitted independently to ChatGPT and Gemini as single-turn interactions without supplementary information or follow-up. AI-generated responses to the five standardized questions were descriptively compared with the corresponding information provided by the Institute of Child Health, whereas responses to five clinic-derived scenarios were compared with the clinical guidance and management provided in real-world practice. Results: Both AI platforms provided relevant, detailed, and supportive responses, particularly to standardized questions. However, the clinic-derived scenarios highlighted dimensions of individualized lactation care that extended beyond the AI-generated responses, particularly direct clinical assessment, access to relevant clinical history, interpretation of emotional and contextual cues, continuity of care, and coordination of multidisciplinary care and practical support. Conclusions: As AI becomes increasingly integrated into everyday health information-seeking, its role in breastfeeding support needs to be clearly defined. AI platforms may complement professional care by providing accessible preliminary information and support, while individualized breastfeeding care remains rooted in direct assessment, continuity of professional care, and trusted human relationships.
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