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Record W4412897855 · doi:10.2147/jmdh.s536732

Integrating Mental Health Services Into Perinatal Care: Challenges and Opportunities

2025· article· en· W4412897855 on OpenAlexfundno aff
Garumma Tolu Feyissa, Enrique R. Pouget, Sena Belina Kitila, Yonas Biratu Terfa, Tracy K. Y. Wong

Bibliographic record

VenueJournal of Multidisciplinary Healthcare · 2025
Typearticle
Languageen
FieldMedicine
TopicMaternal Mental Health During Pregnancy and Postpartum
Canadian institutionsnot available
FundersIndependent Electricity System OperatorTow FoundationCity University of New YorkWorld Health Organization
KeywordsMental healthMedicineData scienceMental health careHealth careComputer sciencePsychiatryPolitical science

Abstract

fetched live from OpenAlex

Introduction: In most low-income countries, including Ethiopia, mental healthcare has not been fully integrated into perinatal services. As a prerequisite for the integration, this project aimed to understand the facilitators and barriers to integrating mental health services into perinatal care. Methods: This exploratory qualitative research used in-depth interviews with 25 purposely selected participants representing diverse stakeholders (perinatal women, health service coordinators and providers, and community health workers and community volunteers). The transcribed interviews were coded and analyzed using Atlas ti Software. Results: The study found the following major impediments to providing and receiving perinatal mental health services: a) the lack of sense of ownership and accountability, b) constraints related to institutional resources and infrastructure; c) inequitable access to healthcare; d) the absence of supportive policy framework with focus on perinatal mental health; e) cultural beliefs and community perceptions; f) limited support from stakeholders; g) limited practice of compassionate and respectful care; and h) poor service planning and coordination. The opportunities for the integration of mental healthcare into perinatal services are a) the presence of maternal and child health (MCH) and mental health professionals, b) a conducive structure linking hospitals to the community and c) a convenient institutional infrastructure, d) higher level government support. Strategies suggested for the integration are awareness creation, capacity building, development of guidelines and checklists, and stakeholder engagement. Conclusion: The current Ethiopian primary healthcare system offers a conductive structure for the integration of mental healthcare into perinatal services. The existing bottlenecks against the service integration can be tackled by training health professionals, community sensitization, and advocacy and generating evidence that leads to the development of evidence-based implementation tools and health service delivery models tailored to local needs. The strategies outlined in this study may be used to design perinatal mental health services at multiple levels. Plain Language Summary: Why was this studyconducted? This study explored barriers and facilitators to integrate mental health into maternal and child health services. What did this study find? The absence of providers trained on perinatal mental health, absence of implementation tools, and limited focus on perinatal mental health deter the integration of mental health into MCH services.Cultural perceptions also deter seeking service for mental health problems during perinatal period.The existing primary healthcare structure of Ethiopia offers a favorable condition to integrate mental health into maternal and child health services. What do these results mean? The integration of mental health into MCH services requires community sensitization, engagement of stakeholders and training of providers at different levels. The service integration also requires the development of implementation guidelines and tools.The strategies outlined in this study might be used to design perinatal mental health services at multiple levels with the Ethiopian Healthcare System. Keywords: mental health, perinatal mental health, Ethiopia, service integration, maternal and child health

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.550
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.038
GPT teacher head0.362
Teacher spread0.324 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2025
Admission routes1
Has abstractyes

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