ArticlePloS one2024
Effectiveness and equity of mHealth apps for preeclampsia management in LMICs: A rapid review protocol.
Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- The Effect of Nursing Interventions in Women With Gestational Hypertension: A Systematic Review and Meta-Analysis.Nursing & health sciences · 2025Pooled it
- The influence of mobile health intervention on the rate of prenatal diagnosis and pregnancy outcomes among pregnant women with high-risk prenatal screening results: protocol for a randomized controlled trial.Frontiers in psychiatry · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionPreeclampsia remains a formidable public health challenge, particularly in low- and middle-income countries (LMICs), where it significantly contributes to the high rates of maternal and neonatal morbidity and mortality. The advent of mobile health (mHealth) applications presents a promising avenue for enhancing the management of preeclampsia. This review protocol is designed to systematically assess the effectiveness and equity of mHealth apps in managing preeclampsia within LMICs, with a focus on clinical outcomes and the broader implications for accessibility, affordability, and cultural relevance. MATERIALS AND
methodsTo achieve the objectives of this review, a rapid review methodology will be employed, encompassing a structured search strategy to identify pertinent studies from databases such as PubMed, Cochrane Library, and Google Scholar, as well as grey literature. The inclusion criteria are set to encompass randomized controlled trials (RCTs), controlled clinical trials (CCTs), observational studies, and qualitative studies that offer insights into the effectiveness and user experience of mHealth apps for preeclampsia management. Participants in these studies will include pregnant women at risk for or diagnosed with preeclampsia, healthcare providers, and app developers. The quality of the included studies will be critically appraised using standardized tools, and data extraction will focus on study characteristics, interventions, outcomes, and equity considerations. DISCUSSION: The implications of this review are far-reaching, offering the potential to inform stakeholders including policymakers, healthcare providers, and app developers about the deployment and development of mHealth solutions for preeclampsia management in LMICs. Ultimately, the anticipated findings of this review are expected to contribute significantly to the understanding of mHealth apps' role in improving preeclampsia management and addressing healthcare disparities, thereby guiding future strategies to enhance maternal and neonatal health outcomes in LMICs.
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What Socratic holds
Registered trials
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 Socratic graph.