Evidence map›Paper›PMID 38769485›Full record

ArticleBMC primary care2024

Barriers and benefits of mHealth for community health workers in integrated community case management of childhood diseases in Banda Parish, Kampala, Uganda: a cross-sectional study.

Winnifred K Kansiime, Edwinah Atusingwize, Rawlance Ndejjo, Emmanuel Balinda, Moses Ntanda, Richard K Mugambe, David Musoke

Abstract read
In one paragraph

Article in BMC primary care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

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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

7 authors.

Winnifred K KansiimeDepartment of Disease Control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda. winniekansiime@musph.ac.ug.
Edwinah AtusingwizeDepartment of Disease Control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.
Rawlance NdejjoDepartment of Disease Control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.
Emmanuel BalindaDepartment of Disease Control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.
Moses NtandaDepartment of Networks, College of Computing and Information Science, Makerere University, P.O. Box 7072, Kampala, Uganda.
Richard K MugambeDepartment of Disease Control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.
David MusokeDepartment of Disease Control and Environmental Health, School of Public Health, College of Health Sciences, Makerere University, P.O. Box 7072, Kampala, Uganda.

Funding

Makerere University Research and Innovation Fund 003010-1-4
6 · The paper itself

Abstract

backgroundLow-quality data presents a significant challenge for community health workers (CHWs) in low and middle-income countries (LMICs). Mobile health (mHealth) applications offer a solution by enabling CHWs to record and submit data electronically. However, the barriers and benefits of mHealth usage among CHWs in informal urban settlements remain poorly understood. This study sought to determine the barriers and benefits of mHealth among CHWs in Banda parish, Kampala.

methodsThis qualitative study involved 12 key informant interviews (KIIs) among focal persons from Kampala City Council Authority (KCCA) and NGOs involved in data collected by CHWs, and officials from the Ministry of Health (MOH) and two mixed-sex Focused Group Discussions (FGDs) of CHWs from Banda parish, Kampala district. Data analysis utilised Atlas Ti Version 7.5.7. Thematic analysis was conducted, and themes were aligned with the social-ecological model.

resultsThree themes of institutional and policy, community and interpersonal, and individual aligning to the Social ecological model highlighted the factors contributing to barriers and the benefits of mHealth among CHWs for iCCM. The key barriers to usability, acceptability and sustainability included high training costs, CHW demotivation, infrastructure limitations, data security concerns, community awareness deficits, and skill deficiencies. Conversely, mHealth offers benefits such as timely data submission, enhanced data quality, geo-mapping capabilities, improved CHW performance monitoring, community health surveillance, cost-effective reporting, and CHW empowering with technology.

conclusionDespite limited mHealth experience, CHWs expressed enthusiasm for its potential. Implementation was viewed as a solution to multiple challenges, facilitating access to health information, efficient data reporting, and administrative processes, particularly in resource-constrained settings. Successful mHealth implementation requires addressing CHWs' demotivation, ensuring reliable power and network connectivity, and enhancing capacity for digital data ethics and management. By overcoming these barriers, mHealth can significantly enhance healthcare delivery at the community level, leveraging technology to optimize resource utilization and improve health outcomes. mHealth holds promise for transforming CHW practices, yet its effective integration necessitates targeted interventions to address systemic challenges and ensure sustainable implementation in LMIC contexts.

Indexed as

Community Health WorkersTelemedicineAdultCase ManagementChildCommunity Health ServicesCross-Sectional StudiesFemaleFocus GroupsHumansMaleQualitative ResearchUgandaBarriersBenefitsCommunity health workersInformal settlementmHealthVillage health team

Identifiers

PMID38769485
PMCPMC11103880

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.