Evidence map›Paper›PMID 42745938›Full record

ArticleFrontiers in public health2026

Health education needs of pregnant women regarding newborn inborn errors of metabolism based on a social ecological model: a qualitative study.

Hao Yang, Fenghua He, Dan Xia, Xihong Wang, Yujia Guan, Hongqian Liu

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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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Hao Yang *Department of Center for Medical Genetics, West China Second University Hospital, Sichuan University, Chengdu, China.
Fenghua He *Department of Center for Medical Genetics, West China Second University Hospital, Sichuan University, Chengdu, China.
Dan XiaDepartment of Center for Medical Genetics, West China Second University Hospital, Sichuan University, Chengdu, China.
Xihong WangWest China School of Public Health and West China Fourth Hospital, Sichuan University, Chengdu, Sichuan, China.
Yujia GuanDepartment of Pediatric Urinary Disease Center Nursing, West China Second University Hospital, Sichuan University, Chengdu, Sichuan, China.
Hongqian LiuDepartment of Center for Medical Genetics, West China Second University Hospital, Sichuan University, Chengdu, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study explored pregnant women's perceptions, experiences, and health education needs regarding newborn inborn errors of metabolism (IEM) and newborn screening, and examined how these needs operate across individual, interpersonal/healthcare-organizational, and community/policy-environment levels. Methods: A descriptive phenomenological qualitative design was used. Fifteen pregnant women (N1-N15) were purposively recruited from one national regional medical center between October 2025 and January 2026 for one-to-one, face-to-face, semi-structured interviews lasting 30-45 min. Two trained researchers conducted the interviews. Recordings were transcribed verbatim and managed in Results: Three overarching analytic levels and 16 subthemes were identified. Individual-level needs concerned conceptual boundaries, screening value, personalized risk information, graded management of abnormal results, uncertainty-related psychological support, and probability communication. Interpersonal and healthcare-organization needs concerned time-linked flowcharts, result notification, operational checklists, repeat-testing/referral navigation, and family communication with privacy protection. Community and policy-environment needs concerned post-diagnosis support, affordability and assistance, authoritative information access, staged reminders, and understandable multimodal delivery. Participants' accounts showed that their needs extended beyond knowledge acquisition to actionable, time-sensitive pathways linking antenatal education with postnatal screening and follow-up. Conclusions: Pregnant women's health education needs regarding newborn IEM are multi-level, time-sensitive, and action oriented. Interventions should combine plain-language risk communication and coping support at the individual level, family-inclusive communication and closed-loop service processes at the interpersonal/organizational level, and authoritative information, financial navigation, and accessible multimodal support at the community/policy level.

Indexed as

Health EducationMetabolism, Inborn ErrorsNeeds AssessmentPregnant PeopleAdultFemaleHealth Knowledge, Attitudes, PracticeHumansInfant, NewbornInterviews as TopicNeonatal ScreeningPregnancyQualitative Researchhealth education needsinborn errors of metabolismnewborn screeningpregnant womenqualitative researchsocial ecological model

Identifiers

PMID42745938
PMCPMC13574986

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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.