Evidence map›Paper›PMID 41253438›Full record

ArticleBMJ health & care informatics2025

Evaluating community-based digital health interventions to improve COVID-19 outcomes in rural Indonesia: a quasi-experimental study.

Sujarwoto Sujarwoto, Holipah Holipah, Sri Andarini, Ismiarta Aknuranda, Eduwin Pakpahan, Delvac Oceandy, Gindo Tampubolon, Asri Maharani

Abstract read
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Article in BMJ health & care informatics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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0citing papers in PubMed
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1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Sujarwoto SujarwotoPublic Administration, Universitas Brawijaya, Malang, Indonesia sujarwoto@ub.ac.id.ORCID http://orcid.org/0000-0003-4197-4592
Holipah HolipahDepartment of Public Health, Universitas Brawijaya, Malang, Indonesia.
Sri AndariniDepartment of Public Health, Universitas Brawijaya, Malang, Indonesia.
Ismiarta AknurandaDepartment of Information Science, Universitas Brawijaya, Malang, Indonesia.
Eduwin PakpahanDepartment of Mathematics, Physics and Electrical Engineering, Northumbria University, Newcastle upon Tyne, UK.
Delvac OceandyDivision of Cardiovascular Sciences, School of Health Sciences, The University of Manchester, Manchester, UK.
Gindo TampubolonGlobal Development Institute, The University of Manchester, Manchester, UK.
Asri MaharaniDivision of Nursing, Midwifery and Social Work, The University of Manchester, Manchester, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesCOVID-19 has challenged health systems in low-income and middle-income countries, particularly in rural areas where communities face barriers to information, prevention and timely care. Digital health interventions delivered through community health workers (CHWs) offer a promising approach to closing these gaps. This study evaluated whether a CHW-led digital intervention improved knowledge, attitudes and practices (KAP), vaccination uptake, COVID-19 outcomes and access to hospital care in rural Indonesia.

methodsA quasi-experimental study was conducted from June 2022 to June 2023 with 10 023 individuals across four intervention and four control villages in Malang Regency. In intervention villages, CHWs used a mobile application (

resultsIntervention participants demonstrated greater improvements in attitudes (mean change=3.5, SD=2.1) and practices (0.02, SD=2.2) compared with controls (attitudes: -2.2, SD=4.6; practices: -2.0, SD=2.1). Vaccine uptake was higher in intervention villages (50.6% vs 40.9%), while COVID-19 diagnoses were lower (1.5% vs 2.4%). Among diagnosed cases, hospitalisation was more frequent in intervention villages (21.3% vs 14.5%). DISCUSSION: The intervention enhanced CHWs' effectiveness in promoting protective behaviours, facilitating early detection and improving referrals. These findings highlight the potential scalability of CHW-led digital health strategies in low-resource settings.

conclusionIntegrating digital tools into CHW-led care can strengthen COVID-19 prevention, vaccination and access to hospital care in rural populations.

Indexed as

Community Health WorkersCOVID-19Health Knowledge, Attitudes, PracticeTelemedicineAdultDigital HealthFemaleHealth Services AccessibilityHumansIndonesiaMaleMiddle AgedMobile ApplicationsRural PopulationSARS-CoV-2Community Health WorkersCOVID-19Public HealthPublic health informatics

Identifiers

PMID41253438
PMCPMC12636966

What OpenQuestion holds

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LicenceCC BY-NC
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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.