Evidence map›Paper›PMID 42639093›Full record

ArticleFrontiers in public health2026

Associations between pregnant women's attitudes toward, and literacy in, artificial intelligence, and their association with perceived influence of internet-based information on decision-making.

Esra Cevik

Abstract read
In one paragraph

Article in Frontiers in public health, 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
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1 · What the graph read from it

What it found

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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

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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

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5 · Who and what money

Authors and funding

1 author.

Esra CevikDepartment of Midwifery, Faculty of Health Sciences, Balikesir University, Balikesir, Türkiye.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aimed to determine the level of perceived influence of internet-based information on decision-making among pregnant women and to examine its associations with artificial intelligence (AI) literacy and attitudes toward AI. Methods: This cross-sectional study was conducted among 423 pregnant women attending a university hospital in Balikesir, Türkiye, between March and December 2025. Data were collected using a Personal Information Form, the Decision-Making Scale via Internet on Pregnancy (DMSIP), the Artificial Intelligence Literacy Scale (AILS), and the General Attitudes toward Artificial Intelligence Scale (GAAIS). Descriptive statistics, group comparisons, correlation analyses, hierarchical multiple linear regression, structural equation modeling (SEM), and mediation analysis within the SEM framework were performed. Results: The mean DMSIP score was 34.39 ± 7.73. The hierarchical regression model explained 59.0% of the variance, with positive attitudes toward AI emerging as the strongest associated factor. In the structural equation model, the contextual latent composite construct representing selected sociodemographic and obstetric characteristics (SDS) showed the strongest direct association with DMSIP, followed by attitudes toward AI. AI literacy was not significantly associated with DMSIP in the structural model. Mediation analysis showed that attitudes toward AI mediated the association between AI literacy and DMSIP. Conclusion: The role of AI should also be considered when examining the perceived influence of internet-based information on pregnancy-related decision-making. As AI becomes increasingly integrated into pregnancy-related information environments, the development and validation of pregnancy-specific instruments to assess AI literacy and attitudes toward AI may strengthen future research in this field.

Indexed as

Artificial IntelligenceDecision MakingHealth Knowledge, Attitudes, PracticeInternetPregnant PeopleAdultCross-Sectional StudiesFemaleHumansPregnancySurveys and QuestionnairesYoung AdultAI literacyartificial intelligencedecision-makinginternetpregnancy

Identifiers

PMID42639093
PMCPMC13500754

What OpenQuestion holds

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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.