Evidence map›Paper›PMID 42282089›Full record

ArticleCampbell systematic reviews2026

PROTOCOL: Artificial Intelligence and Other Digital Tools Used by, and for Community Health Workers (CHWs) in Low and Middle-Income Countries (LMICs) to Improve Outcomes and Increase Effectiveness: An Evidence and Gap Map.

William C Philbrick, Jacob Milnor, Feven Tassaw Mekuria, Perpetua Mbachu, Patricia Mechael, Brian Ssennoga, Zeus Aranda

Abstract read
In one paragraph

Article in Campbell systematic reviews, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

William C PhilbrickSitara International Research and Consulting, Atlanta, Georgia, USA.
Jacob MilnorEvandro Chagas National Institute of Disease, Oswaldo Cruz Foundation, Rio de Janeiro, Brazil.
Feven Tassaw MekuriaCARE USA, Atlanta, USA.
Perpetua Mbachureach52, Maputo, Mozambique.
Patricia MechaelHealth.Enabled, Washington, DC, USA.
Brian SsennogaAmii (Alberta Machine Intelligence Institute), Edmonton, Canada.
Zeus ArandaPartners in Health, Angel Albino Corzo, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This is the protocol for the development of a Campbell Collaboration evidence and gap map (EGM). This protocol presents the methodology for developing the EGM. The objectives of this EGM include answering the following questions related to the use of Artificial Intelligence (AI) and other digital health tools by, and for CHWs in LMICs. (1) What are the primary digital tools used by and for CHWs in LMICs, and for what purposes? (2) To what extent, if any, is AI specifically being utilized by or for CHWs? (3) What is the empirical evidence supporting the effectiveness of such tools, including AI, and the quality of that evidence? (4) Does the use of digital tools and job aids by CHWs in LMICs contribute to (1) greater effectiveness and efficiency in carrying out assigned CHWs' responsibilities; and (2) better health and other well-being outcomes for the clients and communities the CHWs serve? (5) What are the risks and drawbacks of using digital tools, especially AI? What safeguarding strategies are employed to mitigate these risks? (6) What are the primary gaps in the evidence for using digital tools, including AI, used by, and for CHWs in LMICs?

Indexed as

AIartificial intelligenceCHWcommunity health workersdigital healthlow and middle income countries, LMICs, mHealth, eHealth

Identifiers

PMID42282089
PMCPMC13251846

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.