Evidence map›Paper›PMID 39328371›Full record

ArticleSouth African journal of science

Data science research in sub-Saharan Africa: Ethical considerations in crowdsourcing for community engagement.

Suzanne Day, Stuart Rennie

Abstract read
In one paragraph

Article in South African journal of science. 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

2 authors.

Suzanne DayDepartment of Medicine, Division of Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0001-7546-8749
Stuart RennieDepartment of Social Medicine, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA.ORCID 0000-0003-3844-972X

Funding

Research for Ethical Data Science in Southern Africa (REDSSA)U01MH127704 · NIMH · STELLENBOSCH UNIVERSITY · PI MOODLEY, KEYMANTHRI, RENNIE, STUART · 2021 to 2024
$1.6M
NIMH NIH HHS U01 MH127704
6 · The paper itself

Abstract

The growth in data science research in sub-Saharan Africa raises important ethical questions for the collection and use of 'big data' in this context, with particularly disparate implications for the most vulnerable and marginalised populations. While enhanced public involvement may be able to mitigate some of these risks, data science presents some unique barriers to community engagement efforts, including limited data literacy, lack of transparency in data collection and use, and little opportunity to 'opt out' from participation. The participatory approach of crowdsourcing offers a promising solution to address the critical need for community engagement. Crowdsourcing involves inviting a group to contribute solutions to a problem, and then publicly sharing the results for implementation. By crowdsourcing stakeholder ideas for innovative ways to enhance public involvement in data science research, the Research for Ethical Data Science in Southern Africa (REDSSA) project is leading the efforts to close the community engagement gap. Promising strategies that emerge from these efforts will ultimately help to shape more ethical and equitable data science research in Africa as this field continues to grow.

Indexed as

community engagementcrowdsourcingdata scienceethicssub-Saharan Africa

Identifiers

PMID39328371
PMCPMC11426195

What OpenQuestion holds

Textmetadata
LicenceCC BY
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 OpenQuestion graph.