MétaCan
Menu
← Back to cohort
Record W4417054008 · doi:10.1371/journal.pone.0336168

Barriers and facilitators of messaging platforms as a means of maternal support and care in rural communities: A systematic review

2025· review· en· W4417054008 on OpenAlexaff
Shahreen Rahman, Asua Okolie, Dianne Bryant, Edward Kwabena Ameyaw, Obidimma Ezezika

Bibliographic record

VenuePLoS ONE · 2025
Typereview
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsLondon Health Sciences CentreWestern University
Fundersnot available
KeywordsMEDLINESystematic reviewHealth careRegister (sociolinguistics)Health services research

Abstract

fetched live from OpenAlex

Improving maternal support in rural communities through messaging platforms can be a crucial strategy for enhancing antenatal visit rates and improving maternal health outcomes. Currently, there is a significant gap in maternal healthcare access in rural areas, where pregnant women often face barriers such as distance to healthcare facilities, lack of healthcare providers, and limited access to educational resources. This review explored the barriers and facilitators to providing maternal support through messaging platforms. A protocol for this systematic review was developed and registered in the PROSPERO international prospective register of systematic reviews database (Registration number: CRD42023492705). A comprehensive search was conducted on OVID MEDLINE, OVID EMBASE, EBSCO CINAHL, and SCOPUS, focusing on primary research articles published between January 1, 2003, and January 30, 2025. Eligibility criteria required studies to report on maternal support utilizing messaging platforms in rural populations globally. The search strategy yielded a total of 665 studies, of which 15 studies met the eligibility criteria. The quality of eligible studies was evaluated using the Mixed Methods Appraisal Tool, and data were extracted from the articles and analyzed using the Consolidated Framework for Implementation Research. Evidence from the studies indicated that messaging interventions positively impacted maternal health knowledge, access to perinatal services, and communication. Significant barriers were identified, including network connectivity issues in rural areas, affordability of airtime and phones, storage capacity of phones, resistance based on religious beliefs, reliance on traditional birth attendants, and literacy challenges. Facilitators in the messaging interventions included the educational nature of the messages, tailored advice related to pregnancy stages, timely support from community health workers, and improved access to transport for healthcare visits. Tailoring interventions to specific community needs and incorporating educational elements can enhance the engagement and success of messaging platforms targeting maternal health. The identified barriers and facilitators can inform the effective use of messaging platforms by ensuring they are accessible, affordable, and culturally appropriate to support maternal health in rural communities. Trial registration PROSPERO international prospective register of systematic reviews database (Registration number: CRD42023492705).

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)0.017
metaresearch head score (Gemma)0.066
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.017
Threshold uncertainty score0.090

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.066
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0070.007
Bibliometrics0.0090.011
Science and technology studies0.0010.001
Scholarly communication0.0030.003
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.072
GPT teacher head0.408
Teacher spread0.336 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations1
Published2025
Admission routes1
Has abstractyes

Explore more

Same venuePLoS ONE→Same topicMobile Health and mHealth Applications→French-language works237,207→