Evidence map›Paper›PMID 42442816›Full record

ArticleBMJ open2026

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.

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

Abstract readClinical Trial Protocol
In one paragraph

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

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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

6 authors.

Havva Sheikh AzamiStudent Research Committee, Babol University of Medical Sciences, Babol, Islamic Republic of Iran.
Fatemeh BakoueiInfertility and Reproductive Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Islamic Republic of Iran bakouei2004@yahoo.com.ORCID http://orcid.org/0000-0002-3653-4210
Mouloud Agajani DelavarInfertility and Reproductive Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Islamic Republic of Iran.ORCID http://orcid.org/0000-0001-6906-1440
Raheleh Aghababanataj JelodarSalamat Rayan Company, Babol, Islamic Republic of Iran.
Mir Taher Motahari TabariSalamat Rayan Company, Babol, Islamic Republic of Iran.
Hossein-Ali NikbakhtSocial Determinants of Health Research Center, Health Research Institute, Department of Epidemiology and Biostatistics, School of Public Health, Babol University of Medical Science, Babol, Islamic Republic of Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionUnderstanding 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.

Indexed as

Artificial IntelligenceCounselingMotivationReproductive BehaviorAdultFemaleHealth Knowledge, Attitudes, PracticeHumansIranRandomized Controlled Trials as TopicArtificial IntelligenceHealth EducationPopulation Dynamics

Identifiers

PMID42442816
PMCPMC13365750

What OpenQuestion holds

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LicenceCC BY-NC
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Registered trials

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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.