Impact of an artificial intelligence automated chatbot-driven educational-counselling intervention on childbearing attitudes and motivations among childless married women: study protocol for a parallel randomised controlled trial.

Authors

Havva Sheikh Azami, Fatemeh Bakouei, Mouloud Agajani Delavar, Raheleh Aghababanataj Jelodar, Mir Taher Motahari Tabari, Hossein-Ali Nikbakht

Published in

BMJ open. Volume 16. Issue 7. Pages e114653. Jul 13, 2026. Epub Jul 13, 2026.

Abstract

Understanding population dynamics is essential for achieving the Sustainable Development Goals. Global population growth has slowed, and Iran has experienced a marked fertility decline. Given the decline in fertility rates and shifts in women's attitudes and motivations regarding childbearing, this study aims to explore whether an artificial intelligence (AI)-based chatbot can improve attitudes and increase positive motivation towards childbearing among married women of reproductive age.
This parallel randomised controlled trial will be conducted on 80 childless married women who need fertility counselling according to national guidelines. Participants will be randomly allocated using permuted-block randomisation (four blocks) to either an intervention or control arm. The intervention consists of a systematic educational and counselling programme delivered via an AI-powered chatbot across 4 weekly sessions. The control arm will receive standard in-person childbearing counselling per national guidelines. Primary outcomes are attitudes and motivation towards fertility and childbearing, measured by validated questionnaires at baseline and 1-month postintervention. Analysis will use analysis of covariance (ANCOVA) with group as a fixed factor and baseline scores as covariates; effect size will be reported as mean difference with 95% CIs.
The Ethics Committee of Babol University of Medical Sciences (IR.MUBABOL.HRI.REC.1404.172). The study findings will be disseminated through publication in peer-reviewed journals and presentation at scientific conferences.
IRCT20221109056451N7.

PMID:
42442816
Bibliographic data and abstract were imported from PubMed on 14 Jul 2026.

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