Evidence map›Paper›PMID 42787236›Full record

ArticleFrontiers in research metrics and analytics2026

Determinants of collaboration dynamics and challenges in North-South data-driven health research in the African context: an epistemic injustice perspective.

Rahel Bekele, Anne Moen, Merga Belina, Kaija Saranto, Kiros Berhane

Abstract read
In one paragraph

Article in Frontiers in research metrics and analytics, 2026. 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

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

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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

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5 · Who and what money

Authors and funding

5 authors.

Rahel BekeleSchool of Information Science, Addis Ababa University, Addis Ababa, Ethiopia.
Anne MoenDepartment of Public Health Sciences, University of Oslo, Oslo, Norway.
Merga BelinaDepartment of Statistics, Addis Ababa University, Addis Ababa, Ethiopia.
Kaija SarantoDepartment of Health and Social Management, University of Eastern Finland, Kuopio, Finland.
Kiros BerhaneDepartment of Biostatistics, Mailman School of Public Health, Columbia University, New York, NY, United States.

Funding

Advancing Public Health Research in Eastern Africa through Data Science Training (APHREA-DST)U2RTW012123 · FIC · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI Rahel Bekele, Kiros T Berhane · 2021 to 2026
$1.9M
FIC NIH HHS U2R TW012123
6 · The paper itself

Abstract

Introduction: Collaborations between Global North and South institutions are increasingly important for advancing artificial intelligence (AI) and data science in healthcare, offering opportunities to address context-specific challenges and reduce inequities. However, these partnerships often face persistent issues related to sustainability, equity, and long-term impact. Drawing on concepts of epistemic injustice and structural imbalances between partners, this study examines the factors shaping the effectiveness of North-South data-driven health collaborations, with particular attention to which factors exert the strongest statistically significant influence on collaboration effectiveness. Methods: The study conducted a cross-sectional survey of participants from the Data Science Initiative for Africa (DS-I Africa) network, covering the entire continent of Africa, and their partners from the Global North, and applies structural equation modeling to assess key determinants of collaboration outcomes. Results: The analysis focuses on governance and leadership, human capacity, and project and institutional practices. Human capacity is the strongest positive predictor of collaboration effectiveness (β = 0.467, Discussion: The findings demonstrate that sustainable and equitable North-South collaborations depend on the alignment of governance, human capacity, and institutional practices. Moreover, addressing epistemic injustice requires system-level changes that promote shared leadership, ethical data governance, and strengthening human capacity as a reciprocal and inclusive process central to achieving balanced knowledge production and long-term collaboration impact.

Indexed as

artificial intelligencedata scienceepistemic injusticeequity in global health researchhealth research collaborationhuman capacity in research partnershipNorth-South collaborationNorth-South collaboration research practice

Identifiers

PMID42787236
PMCPMC13601277

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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.