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. 2025 May 30;25(1):631.
doi: 10.1186/s12884-025-07753-3.

Artificial intelligence-assisted chatbot: impact on breastfeeding outcomes and maternal anxiety

Gizem Kerimoglu Yildiz  1 , Rukiye Turk Delibalta  2 , Zehra Coktay  3
Affiliations

Artificial intelligence-assisted chatbot: impact on breastfeeding outcomes and maternal anxiety

Gizem Kerimoglu Yildiz et al. BMC Pregnancy Childbirth. .

Abstract

Background: Artificial intelligence (AI) is increasingly used in healthcare interventions to provide accessible, continuous, and personalized patient support. This study investigates the impact of a mobile breastfeeding counseling application developed with artificial AI on mothers' breastfeeding self-efficacy, success, and anxiety levels.

Methods: A quasi-experimental design was employed, involving 60 mothers. Participants were divided into two groups: 30 mothers received AI-based counseling, and 30 mothers were provided a booklet. Data collection tools included a personal information form, Breastfeeding Charting System and Assessment Tool (LATCH), Postnatal Breastfeeding Self-Efficacy Scale, and Beck Anxiety Inventory. Data were collected from mothers who delivered at a state hospital's obstetrics and gynecology department and were followed for ten days postpartum (postpartum days 1, 3, 7, and 10).

Results: No significant differences were found in the demographic characteristics of the two groups (p > 0.05). Statistically significant improvements were observed in breastfeeding self-efficacy over time for both groups (AI group: f = 36.356, p = 0.000; booklet group: f = 43.349, p = 0.000). At day 10, the AI group scored significantly higher than the booklet group (Z=-2.216, p = 0.027). For breastfeeding success, as measured by the LATCH tool, significant differences were also noted over time for both groups (AI group: f = 68.466, p = 0.000; booklet group: f = 68.088, p = 0.000). At day seven, the AI group outperformed the booklet group (Z=-2.995, p = 0.003). Anxiety levels showed no significant differences between groups.

Conclusions: AI-based breastfeeding counseling positively impacts breastfeeding self-efficacy and success. The findings highlight the potential of AI applications in healthcare. AI-based chatbots can serve as effective tools for breastfeeding education, offering accessible, personalized, and continuous support. The significant improvements in breastfeeding outcomes indicate that innovative AI-assisted interventions can effectively support mothers during the critical early postpartum period. This research demonstrates the feasibility of integrating AI technology into maternal care and serves as a foundation for future studies.

Clinical trial number: Not applicable.

Keywords: Anxiety; Artificial intelligence; Breastfeeding counseling; Breastfeeding self-efficacy; Breastfeeding success.

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Conflict of interest statement

Declarations. Ethics approval and consent to participate: The study received ethical approval from a university’s non-interventional clinical research ethics committee on February 27, 2024 (approval no: 80576354-050-99/369). Written and verbal consent was obtained from the mothers. This study was conducted according to the Declaration of Helsinki. Consent for publication: Not applicable. Competing interests: The authors declare no competing interests.

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