{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T06:08:20Z","timestamp":1789020500249,"version":"build-2803163510"},"reference-count":37,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T00:00:00Z","timestamp":1788998400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Res. Metr. Anal."],"abstract":"<jats:sec>\n                    <jats:title>Introduction<\/jats:title>\n                    <jats:p>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\u2013South data-driven health collaborations, with particular attention to which factors exert the strongest statistically significant influence on collaboration effectiveness.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>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.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      The analysis focuses on governance and leadership, human capacity, and project and institutional practices. Human capacity is the strongest positive predictor of collaboration effectiveness (\u03b2 = 0.467,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.008). Project and institutional practices show a significant negative association with collaboration effectiveness (\u03b2 = \u22120.464,\n                      <jats:italic>p<\/jats:italic>\n                      = 0.016). Governance and leadership also demonstrate a significant effect on collaboration outcomes.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Discussion<\/jats:title>\n                    <jats:p>The findings demonstrate that sustainable and equitable North\u2013South 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.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/frma.2026.1885894","type":"journal-article","created":{"date-parts":[[2026,9,10]],"date-time":"2026-09-10T06:04:53Z","timestamp":1789020293000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Determinants of collaboration dynamics and challenges in North-South data-driven health research in the African context: an epistemic injustice perspective"],"prefix":"10.3389","volume":"11","author":[{"given":"Rahel","family":"Bekele","sequence":"first","affiliation":[{"name":"School of Information Science, Addis Ababa University","place":["Addis Ababa, Ethiopia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anne","family":"Moen","sequence":"additional","affiliation":[{"name":"Department of Public Health Sciences, University of Oslo","place":["Oslo, Norway"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Merga","family":"Belina","sequence":"additional","affiliation":[{"name":"Department of Statistics, Addis Ababa University","place":["Addis Ababa, Ethiopia"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaija","family":"Saranto","sequence":"additional","affiliation":[{"name":"Department of Health and Social Management, University of Eastern Finland","place":["Kuopio, Finland"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kiros","family":"Berhane","sequence":"additional","affiliation":[{"name":"Department of Biostatistics, Mailman School of Public Health, Columbia University","place":["New York, NY, United States"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,9,10]]},"reference":[{"key":"B1","doi-asserted-by":"crossref","first-page":"151","DOI":"10.1079\/9781786390042.0151","article-title":"\u201cData troubles: collaboration and the future of partnership,\u201d","volume-title":"Global Health Research in an Unequal World: Ethics Case Studies from Africa","author":"Aellah","year":"2016"},{"key":"B2","doi-asserted-by":"publisher","first-page":"e0000016","DOI":"10.1371\/journal.pdig.0000016","article-title":"To explain or not to explain? 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