Evidence map›Paper›PMID 42404952›Full record

ArticleFrontiers in public health2026

Online health information seeking preferences among pregnant women: a discrete choice experiment.

Jing Xu, Liyan Xie, Qingqing Wang, Yanxia Zhu, Yuhong Li

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.

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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

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

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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.

Jing XuSchool of Nursing, Anhui Medical University, Hefei, Anhui, China.
Liyan XieSchool of Nursing, Anhui Medical University, Hefei, Anhui, China.
Qingqing WangSchool of Nursing, Anhui Medical University, Hefei, Anhui, China.
Yanxia ZhuDepartment of Nursing, Anhui Women and Children's Medical Center, Hefei, Anhui, China.
Yuhong LiSchool of Nursing, Anhui Medical University, Hefei, Anhui, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: This study aims to investigate the online health information seeking preferences of pregnant women to provide guidance for optimizing prenatal care information services. Methods: From August to September 2025, a discrete choice experiment was conducted among 342 pregnant women recruited by convenience sampling from two tertiary hospitals in Anhui Province, China. All attributes and levels were identified through literature review, qualitative interviews and expert consultations. A D-efficient design was employed to create 18 choice sets, which were randomly divided into two blocks. A mixed logit model was used to analyze choice preferences, based on which we calculated relative importance (RI), willingness to pay (WTP) and performed scenario simulation. Results: The attribute that participants valued most was the information interaction function (RI = 29.80%), followed by information content (RI = 27.01%), cost per payment (RI = 26.56%), information access method (RI = 8.73%), and information format (RI = 7.89%). Pregnant women preferred online consultation ( Conclusion: Tailoring the provision of prenatal care information services to the actual preferences of pregnant women can improve their satisfaction with online prenatal care services and their adherence to health advice.

Indexed as

Choice BehaviorInformation Seeking BehaviorInternetPatient PreferencePregnant PeoplePrenatal CareAdultChinaDigital HealthDigital MediaFemaleHumansPregnancyYoung Adultconsumer health informationdiscrete choice experimentinternetpreferencespregnant women

Identifiers

PMID42404952
PMCPMC13328091

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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.