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
- Journal
- BMJ open (Q1)
- Published
- 13 July 2026
- Study design
- Study protocol (planned trial, no results yet)
- Evidence level
- Level 5, Expert Opinion (CEBM 5)
- Authors
- Havva Sheikh Azami, Fatemeh Bakouei, Mouloud Agajani Delavar, Raheleh Aghababanataj Jelodar, Mir Taher Motahari Tabari, Hossein-Ali Nikbakht
- PMID
- 42442816
- DOI
- 10.1136/bmjopen-2025-114653
Why clinicians should know about it
- Picked for Reproductive Medicine (top studies of the week, 19 July 2026).
Abstract
INTRODUCTION: 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. METHODS AND ANALYSIS: 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. ETHICS AND DISSEMINATION: 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. TRIAL REGISTRATION NUMBER: IRCT20221109056451N7.
Abstract as published, via PubMed.
For healthcare professionals. The summary is generated by AI from the published abstract, and the evidence level is assigned automatically from the study design on the Oxford CEBM hierarchy. Neither is medical advice. Read the full paper before changing practice.