Evidence map›Paper›PMID 40958656›Full record

ArticleGlobal health action2025

Transitioning to midwifery models of care: lessons from case studies in India.

Paridhi Jha, Bharati Sharma, Alison McFadden, Sowmya Thota, Joyce Marshall, Neha Singh, Sowmya Ramesh, Jitender Nagpal, Andrew Symon

Abstract read
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Article in Global health action, 2025. 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

9 authors.

Paridhi JhaFoundation for Research in Health Systems, Indian Society for Health Administrators Building, Bengaluru, India.ORCID 0000-0002-1285-7138
Bharati SharmaIndian Institute of Public Health, Gandhinagar, Gujarat, India.ORCID 0000-0003-0793-1249
Alison McFaddenMother and Infant Research Unit, School of Health Sciences, University of Dundee, Dundee, UK.ORCID 0000-0002-5164-2025
Sowmya ThotaFernandez Hospital Educational and Research Foundation, Hyderabad, Telangana, India.ORCID 0000-0002-2580-7789
Joyce MarshallUniversity of Huddersfield, Huddersfield, UK.ORCID 0000-0002-2784-1817
Neha SinghQuicksand Design Studio Pvt. Ltd, New Delhi, India.
Sowmya RameshNorth Bristol NHS Trust, Department of Infection, Bristol, UK.ORCID 0000-0002-4880-3350
Jitender NagpalSitaram Bhartia Institute of Science and Research, New Delhi, India.ORCID 0000-0003-4752-5843
Andrew SymonMother and Infant Research Unit, School of Health Sciences, University of Dundee, Dundee, UK.ORCID 0000-0001-9269-940X

Funding

Medical Research Council MR/T039469/1
6 · The paper itself

Abstract

backgroundLimited evidence exists on how midwives, other healthcare providers, and their local communities in low- and middle-income countries experience the transition to a midwifery model of care.

objectivesThis study aimed to identify opportunities, enablers, and barriers to integrating midwifery into existing public health systems, from the perspectives of key stakeholders representing health systems and communities.

methodWe conducted two case studies - community-based and public health facility-based - in Gujarat and Telangana, comprising 63 in-depth interviews and five focus group discussions with 40 participants, including midwives, obstetricians, nurse-midwives, hospital administrators, local women, family members, and community influencers. The ecological systems theory and the quality maternal and newborn care framework guided the framework analysis.

resultsFive themes were developed, each aligning with one level of ecological systems theory: 1) Becoming a midwife; 2) Negotiating the full scope of autonomous midwifery practice; 3) Midwives' integration into existing maternity care teams; 4) Building social recognition of midwifery in communities; and 5) Balancing the care context and policy directives. Midwives had to demonstrate professional competence, confidence, and assertiveness to overcome professional challenges and conflicts and gain acceptance.

conclusionIntegrating midwifery into existing health systems depends on midwives' acceptance and perceived trustworthiness by existing health teams/communities and can be facilitated by ongoing support and mentoring of midwives, preparatory sensitisation of other healthcare providers, and building social recognition of midwives in communities. Further research is needed to develop and test interventions that support midwives in fulfilling their potential to improve the care quality for mothers and infants.

Indexed as

Maternal Health ServicesMidwiferyFemaleFocus GroupsHumansIndiaInterviews as TopicNurse MidwivesOrganizational Case StudiesPregnancyQualitative Researchecological systems theoryframework analysishealth systems researchMidwife-led care unitsQMNC frameworkquality of maternity services

Identifiers

PMID40958656
PMCPMC12444964

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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.