Evidence map›Paper›PMID 29302882›Full record

ReviewJournal of general internal medicine2018

Comparing Amazon's Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature.

Karoline Mortensen, Taylor L Hughes

Abstract readReview
In one paragraph

Review in Journal of general internal medicine, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 183 papers.

0numbers the graph read from it
0cells of the map it votes in
183citing 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

183 citing papers in PubMed.

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123 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

2 authors.

Karoline MortensenDepartment of Health Sector Management and Policy School of Business Administration , University of Miami, Coral Gables, FL, USA. Kmortensen@bus.miami.edu.
Taylor L HughesDuke University, Durham, NC, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe goal of this article is to conduct an assessment of the peer-reviewed primary literature with study objectives to analyze Amazon.com 's Mechanical Turk (MTurk) as a research tool in a health services research and medical context.

methodsSearches of Google Scholar and PubMed databases were conducted in February 2017. We screened article titles and abstracts to identify relevant articles that compare data from MTurk samples in a health and medical context to another sample, expert opinion, or other gold standard. Full-text manuscript reviews were conducted for the 35 articles that met the study criteria.

resultsThe vast majority of the studies supported the use of MTurk for a variety of academic purposes. DISCUSSION: The literature overwhelmingly concludes that MTurk is an efficient, reliable, cost-effective tool for generating sample responses that are largely comparable to those collected via more conventional means. Caveats include survey responses may not be generalizable to the US population.

Indexed as

Biomedical ResearchCrowdsourcingData CollectionHumansReproducibility of ResultsAlternate data sourcesAmazon Mechanical TurkHealth and medical researchMTurk

Identifiers

PMID29302882
PMCPMC5880761

What OpenQuestion holds

Textmetadata
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.