Evidence map›Paper›PMID 42517659›Full record

ArticleMaternal & child nutrition2026

Experiences of Primiparous Mothers Using ChatGPTfor Breastfeeding and Infant Care.

Eyşan Hanzade Savaş, Maide Nur Tümkaya, Ezgi Hasret Kozan Çıkırıkçı, Pelin Gökoğlu Gürer, Nevra Didem Kılınç

Abstract read
In one paragraph

Article in Maternal & child nutrition, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Eyşan Hanzade SavaşPediatric Oncology Department, Regina Margherita Children's Hospital, Turin, Italy.ORCID 0000-0002-0083-7754
Maide Nur TümkayaDepartment of Nursing, İstanbul Atlas University, Istanbul, Türkiye.ORCID 0000-0002-8361-2955
Ezgi Hasret Kozan ÇıkırıkçıKoç University School of Nursing, Istanbul, Türkiye.ORCID 0000-0002-7840-1635
Pelin Gökoğlu GürerDepartment of Child Development, Haliç University, Istanbul, Türkiye.ORCID 0000-0003-1627-2652
Nevra Didem KılınçPediatric Oncology Department, Regina Margherita Children's Hospital, Turin, Italy.ORCID 0000-0002-9540-9225

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Artificial intelligence-based conversational tools such as ChatGPT are increasingly used by mothers to obtain health-related information during early motherhood. This study aimed to explore and describe the experiences and perceptions of primiparous mothers using ChatGPT as a source of information for breastfeeding and early infant care. A qualitative descriptive study was conducted. Fifteen primiparous mothers in Türkiye were recruited using purposive sampling from a pediatric outpatient clinic. Data were collected through semi-structured, in-depth online interviews and analyzed using Braun and Clarke's reflexive thematic analysis. The study followed the COREQ checklist to enhance methodological transparency. A total of 15 primiparous mothers participated in the study (28.7 ± 2.5 years). The mean age of infants was 4.2 ± 1.6 months, and most were female (73.3%). All participants reported regular internet access and used smartphones to access ChatGPT, with use ranging from daily to a few times per month. Three main themes emerged: (1) ChatGPT as an accessible alternative information source in early motherhood; (2) the role of ChatGPT in reducing uncertainty in early motherhood, characterized by support in unfamiliar situations, reassurance during moments of concern, and strengthening decision-making skills and maternal confidence; and (3) rare use of ChatGPT, reflecting mothers' deliberate avoidance of the tool in serious or complex infant health situations and their preference for personalized professional support. ChatGPT may serve as a complementary information resource during early motherhood, offering reassurance and confidence for everyday care; however, it cannot replace individualized professional healthcare support.

Indexed as

Breast FeedingInfant CareMothersAdultFemaleGenerative Artificial IntelligenceHumansInfantInfant, NewbornInternetParityQualitative ResearchTurkeyartificial intelligencebreastfeedinginfant carepostpartum periodprimiparous mothers

Identifiers

PMID42517659
PMCPMC13410945

What OpenQuestion holds

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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.