MétaCan
Menu
← Back to cohort
Record W4200298057 · doi:10.1136/bmjopen-2020-047556

Implementation and impact of mobile health (mHealth) in the management of diabetes mellitus in Africa: a systematic review protocol

2021· review· en· W4200298057 on OpenAlexaff
Franklin O. Dike, Jean Claude Mutabazi, Blessing Chinenye Ubani, Ahmed Sherif Isa, Chidiebele Malachy Ezeude, Ezekiel Musa, Henry Iheonye, Isah Idris Ainavi

Bibliographic record

VenueBMJ Open · 2021
Typereview
Languageen
FieldHealth Professions
TopicMobile Health and mHealth Applications
Canadian institutionsUniversité de MontréalCentre Hospitalier de l’Université de Montréal
Fundersnot available
KeywordsmHealthMedicineHealth careMEDLINEMobile phoneScopusSystematic reviewCochrane LibraryPopulationGrey literatureFamily medicineAlternative medicineEnvironmental healthNursingPsychological interventionPathologyComputer science

Abstract

fetched live from OpenAlex

INTRODUCTION: The WHO has proposed the concept of mobile health (mHealth) to support healthcare systems delivery worldwide. mHealth basically involves the use of Information and Communication Technology for healthcare provision or delivery services. Africa has seen a remarkable increase in mobile phone availability and usage in the last decade. The incidence and prevalence of diabetes mellitus (DM) in Africa have also been on the increase in the last decade, in sharp contrast to an ailing healthcare system. We aim to review the extent of implementation of mHealth in the management of DM in Africa, and estimate its impact in helping patients achieve desired glycaemic target, sustain control and prevent complications in the past decade. METHODS AND ANALYSIS: Studies assessing the utilisation of mhealth in the management of patients with DM in Africa will be considered based on the PICO method: Population, Intervention, Comparator, and Outcomes. Medline, PubMed, SCOPUS and the Pan African Clinical Trials Registry, among others will be searched. Two authors independent of each other shall screen titles and abstracts retrieved using the search strategy, retrieve the full text articles and assess them for eligibility and extract data. A third reviewing author will be brought in to resolve any disagreement between the two authors by discussion. The 'Cochrane Collaboration Risk of Bias Tool' will be used to assess the quality of included studies. A narrative synthesis of extracted data and, where the characteristics of the eligible studies permit, a meta-analysis (which will be reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines) will be done. ETHICS AND DISSEMINATION: No ethical approval will be required since only published data will be used. Dissemination of results will be through peer reviewed publication and conference presentation. PROSPERO REGISTRATION NUMBER: CRD42021218674.

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)0.058
metaresearch head score (Gemma)0.054
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: Protocol · Consensus signal: Protocol
Teacher disagreement score0.058
Threshold uncertainty score0.306

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0580.054
Meta-epidemiology (narrow)0.0050.005
Meta-epidemiology (broad)0.0200.015
Bibliometrics0.0160.013
Science and technology studies0.0030.005
Scholarly communication0.0070.008
Open science0.0050.005
Research integrity0.0060.005
Insufficient payload (model declined to judge)0.0560.006

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 head0.246
GPT teacher head0.633
Teacher spread0.387 · 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
GenreProtocol

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

Citations13
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueBMJ Open→Same topicMobile Health and mHealth Applications→French-language works237,207→