Evidence map›Paper›PMID 31959234›Full record

SynthesisInfectious diseases of poverty2020

Crowdsourcing in health and medical research: a systematic review.

Cheng Wang, Larry Han, Gabriella Stein, Suzanne Day, Cedric Bien-Gund, Allison Mathews, Jason J Ong, Pei-Zhen Zhao, Shu-Fang Wei, Jennifer Walker and 5 more

Abstract readSystematic Review
In one paragraph

Synthesis in Infectious diseases of poverty, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 64 papers.

0numbers the graph read from it
0cells of the map it votes in
64citing 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

64 citing papers in PubMed.

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  20. Fostering citizen-engaged HIV implementation science.Journal of the International AIDS Society · 2024
    Article

4 more citing papers are in PubMed but not listed here.

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

15 authors.

Cheng WangDermatology Hospital of Southern Medical University, Guangzhou, China.
Larry HanDepartment of Biostatistics, Harvard Chan School of Public Health, Boston, MA, USA.
Gabriella SteinSocial Entrepreneurship to Spur Health, Guangzhou, China.
Suzanne DayInstitute of Global Health and Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, USA.
Cedric Bien-GundUniversity of North Carolina Project-China, Guangzhou, China.
Allison MathewsInstitute of Global Health and Infectious Diseases, University of North Carolina at Chapel Hill, Chapel Hill, USA.
Jason J OngSocial Entrepreneurship to Spur Health, Guangzhou, China.
Pei-Zhen ZhaoDermatology Hospital of Southern Medical University, Guangzhou, China.
Shu-Fang WeiSocial Entrepreneurship to Spur Health, Guangzhou, China.
Jennifer WalkerHealth Sciences Library, University of North Carolina, Chapel Hill, USA.
Roger ChouDepartment of Medical Informatics and Clinical Epidemiology, Oregon Health & Sciences University, Portland, USA.
Amy LeeSocial Entrepreneurship to Spur Health, Guangzhou, China.
Angela ChenDepartment of Orthopaedics, Brigham and Women's Hospital, Boston, USA.
Barry BayusKenan-Flagler School of Business, University of North Carolina at Chapel Hill, Chapel Hill, USA.
Joseph D TuckerSocial Entrepreneurship to Spur Health, Guangzhou, China. jdtucker@med.unc.edu.

Funding

Wake Forest Clinical and Translational Science AwardUL1TR001420 · NCATS · WAKE FOREST UNIVERSITY HEALTH SCIENCES · PI ARD, JAMY D, FOLEY, KRISTIE L · 2015 to 2023
$32.3M
NCATS NIH HHS UL1 TR001420
6 · The paper itself

Abstract

backgroundCrowdsourcing is used increasingly in health and medical research. Crowdsourcing is the process of aggregating crowd wisdom to solve a problem. The purpose of this systematic review is to summarize quantitative evidence on crowdsourcing to improve health.

methodsWe followed Cochrane systematic review guidance and systematically searched seven databases up to September 4th 2019. Studies were included if they reported on crowdsourcing and related to health or medicine. Studies were excluded if recruitment was the only use of crowdsourcing. We determined the level of evidence associated with review findings using the GRADE approach.

resultsWe screened 3508 citations, accessed 362 articles, and included 188 studies. Ninety-six studies examined effectiveness, 127 examined feasibility, and 37 examined cost. The most common purposes were to evaluate surgical skills (17 studies), to create sexual health messages (seven studies), and to provide layperson cardio-pulmonary resuscitation (CPR) out-of-hospital (six studies). Seventeen observational studies used crowdsourcing to evaluate surgical skills, finding that crowdsourcing evaluation was as effective as expert evaluation (low quality). Four studies used a challenge contest to solicit human immunodeficiency virus (HIV) testing promotion materials and increase HIV testing rates (moderate quality), and two of the four studies found this approach saved money. Three studies suggested that an interactive technology system increased rates of layperson initiated CPR out-of-hospital (moderate quality). However, studies analyzing crowdsourcing to evaluate surgical skills and layperson-initiated CPR were only from high-income countries. Five studies examined crowdsourcing to inform artificial intelligence projects, most often related to annotation of medical data. Crowdsourcing was evaluated using different outcomes, limiting the extent to which studies could be pooled.

conclusionsCrowdsourcing has been used to improve health in many settings. Although crowdsourcing is effective at improving behavioral outcomes, more research is needed to understand effects on clinical outcomes and costs. More research is needed on crowdsourcing as a tool to develop artificial intelligence systems in medicine.

trial registrationPROSPERO: CRD42017052835. December 27, 2016.

Indexed as

Biomedical ResearchCrowdsourcingHumansChallenge contestCrowdsourcingHealthInnovationMedicineSystematic review

Identifiers

PMID31959234
PMCPMC6971908

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.