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Record W3022953960 · doi:10.1186/s12884-020-02955-3

Persistent barriers to the use of maternal, newborn and child health services in Garissa sub-county, Kenya: a qualitative study

2020· article· en· W3022953960 on OpenAlexafffund
Isaac Kisiangani, Elmi Mohamed, Pauline Bakibinga, Shukri F. Mohamed, Lyagamula Kisia, Peter Kibe, Peter Otieno, Naïm Afeich, Amina Abdullahi Nyaga, Ngugi Njoroge, Rumana Noor, Abdhalah Ziraba

Bibliographic record

VenueBMC Pregnancy and Childbirth · 2020
Typearticle
Languageen
FieldMedicine
TopicGlobal Maternal and Child Health
Canadian institutionsMcGill University
FundersDepartment for International DevelopmentCanadian Intensive Care Foundation
KeywordsFocus groupQualitative researchMedicinePsychological interventionNursingQualitative propertyHealth careService providerHealth services researchParticipatory action researchPublic healthService (business)SociologyEconomic growthMarketingBusiness

Abstract

fetched live from OpenAlex

BACKGROUND: North Eastern Kenya has persistently had poor maternal, new-born and child health (MNCH) indicators. Barriers to access and utilisation of MNCH services are structural, individual and community-level factors rooted in sociocultural norms. A package of interventions was designed and implemented in Garissa sub-County aimed at creating demand for services. Community Health Volunteers (CHVs) were trained to generate demand for and facilitate access to MNCH care in communities, while health care providers were trained on providing culturally acceptable and sensitive services. Minor structural improvements were made in the control areas of two facilities to absorb the demand created. Community leaders and other social actors were engaged as influencers for demand creation as well as to hold service providers accountable. This qualitative research was part of a larger mixed methods study and only the qualitative results are presented. In this paper, we explore the barriers to health care seeking that were deemed persistent by the end of the intervention period following a similar assessment at baseline. METHODS: An exploratory qualitative research design with participatory approach was undertaken as part of an impact evaluation of an innovation project in three sites (two interventions and one control). Semi-structured interviews were conducted with women who had given birth during the intervention period. Focus group discussions were conducted among the wider community members and key informant interviews among healthcare managers and other stakeholders. Participants were purposively selected. Data were analysed using content analysis by reading through transcripts. Interview data from different sources on a single event were triangulated to increase the internal validity and analysis of multiple cases strengthened external validity. RESULTS: Three themes were pre-established: 1) barriers and solutions to MNCH use at the community and health system level; 2) perceptions about women delivering in health facilities and 3) community/social norms on using health facilities. Generally, participants reported satisfaction with services offered in the intervention health facilities and many indicated that they would use the services again. There were notable differences between the intervention and control site in attitudes towards use of services (skilled birth attendance, postnatal care). Despite the apparent improvements, there still exist barriers to MNCH services use. Persistent barriers identified were gender of service provider, insecurity, poverty, lack of transport, distance from health facilities, lack of information, absence of staff especially at night-time and quality of maternity care. CONCLUSION: Attitudes towards MNCH services are generally positive, however some barriers still hinder utilization. The County health department and community leaders need to sustain the momentum gained by ensuring that service access and quality challenges are continually addressed.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.039
Threshold uncertainty score0.077

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.006
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0120.004
Scholarly communication0.0020.002
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.035
GPT teacher head0.299
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations38
Published2020
Admission routes2
Has abstractyes

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