Evidence map›Paper›PMID 38594665›Full record

ArticleBMC health services research2024

On-demand mobile hypertension training for primary health care workers in Nigeria: a pilot study.

Joseph Odu, Kufor Osi, Leander Nguyen, Allison Goldstein, Lawrence J Appel, Kunihiro Matsushita, Dike Ojji, Ikechukwu A Orji, Morenike Alex-Okoh, Deborah Odoh and 9 more

Open access · goldAbstract read
In one paragraph

Article in BMC health services research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.8field-weighted citation impact, top 27% of its field
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 8 institutions in 2 countries.

Joseph OduResolve To Save Lives, New York, USA.
Kufor OsiResolve To Save Lives, New York, USA.
Leander NguyenColumbia University Irving Medical Center, New York, USA.
Allison GoldsteinResolve To Save Lives, New York, USA.
Lawrence J AppelWelch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.
Kunihiro MatsushitaWelch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins University, Baltimore, MD, USA.
Dike OjjiDepartment of Internal Medicine, Faculty of Clinical Sciences, University of Abuja, Abuja, Nigeria.
Ikechukwu A OrjiCardiovascular Research Unit, University of Abuja Teaching Hospital, Gwagwalada, Abuja, Nigeria.
Morenike Alex-OkohFederal Ministry of Health, Abuja, Nigeria.
Deborah OdohFederal Ministry of Health, Abuja, Nigeria.
Malau Mangai TomaFederal Ministry of Health, Abuja, Nigeria.
Chris Ononiwu ElemuwaNational Primary Health Care Development Agency, Abuja, Nigeria.
Suleiman LamordeNational Primary Health Care Development Agency, Abuja, Nigeria.
Hasana BarayaNational Primary Health Care Development Agency, Abuja, Nigeria.
Mary T DewanWorld Health Organization, Abuja, Nigeria.
Obagha ChijiokeWorld Health Organization, Abuja, Nigeria.
Andrew E MoranResolve To Save Lives, New York, USA.
Emmanuel AgogoResolve To Save Lives, New York, USA.
Marshall P ThomasResolve To Save Lives, New York, USA. mthomas.consultant@resolvetosavelives.org.
Federal Ministry of Health · NGNational Primary Health Care Development Agency · NGColumbia University Irving Medical Center · USJohns Hopkins University · USWorld Health Organization - Nigeria · NGUniversity of Abuja · NGUniversity of Abuja Teaching Hospital · NGVital Strategies · US

Funding

Gates Foundation OPP1175906World Health Organization 001
6 · The paper itself

Abstract

backgroundOnly one out of every ten Nigerian adults with hypertension has their blood pressure controlled. Health worker training is essential to improve hypertension diagnosis and treatment. In-person training has limitations that mobile, on-demand training might address. This pilot study evaluated a self-paced, case-based, mobile-optimized online training to diagnose and manage hypertension for Nigerian health workers.

methodsTwelve hypertension training modules were developed, based on World Health Organization and Nigerian guidelines. After review by local academic and government partners, the course was piloted by Nigerian health workers at government-owned primary health centers. Primary care physician, nurse, and community health worker participants completed the course on their own smartphones. Before and after the course, hypertension knowledge was evaluated with multiple-choice questions. Learners provided feedback by responding to questions on a Likert scale.

resultsOut of 748 users who sampled the course, 574 enrolled, of whom 431 (75%) completed the course. The average pre-test score of completers was 65.4%, which increased to 78.2% on the post-test (P < 0.001, paired t-test). Health workers who were not part of existing hypertension control programs had lower pre-test scores and larger score gains. Most participants (96.1%) agreed that the training was applicable to their work, and nearly all (99.8%) agreed that they enjoyed the training.

conclusionsAn on-demand mobile digital hypertension training increases knowledge of hypertension management among Nigerian health workers. If offered at scale, such courses can be a tool to build health workforce capacity through initial and refresher training on current clinical guidelines in hypertension and other chronic diseases in Nigeria as well as other countries.

Indexed as

HypertensionAdultCommunity Health WorkersHumansNigeriaPilot ProjectsPrimary Health CareClinical guidelinesHypertensionmHealthMobile technologyOnline learningPrimary health care

Identifiers

PMID38594665
PMCPMC11005121
OpenAlexW4394602749

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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 OpenQuestion graph.