Evidence map›Paper›PMID 36326997›Full record

ArticleBehavior research methods2023

Evaluating CloudResearch's Approved Group as a solution for problematic data quality on MTurk.

David J Hauser, Aaron J Moss, Cheskie Rosenzweig, Shalom N Jaffe, Jonathan Robinson, Leib Litman

Abstract read
In one paragraph

Article in Behavior research methods, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 49 papers.

0numbers the graph read from it
0cells of the map it votes in
49citing 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

49 citing papers in PubMed.

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  20. Profitable third-party punishment destabilizes cooperation.Proceedings of the National Academy of Sciences of the United States of America · 2025
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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

6 authors.

David J HauserDepartment of Psychology, Queen's University, Kingston, ON, Canada. david.hauser@queensu.ca.ORCID 0000-0002-5480-5213
Aaron J MossCloudResearch, Queens, NY, USA.ORCID 0000-0003-4396-4128
Cheskie RosenzweigCloudResearch, Queens, NY, USA.ORCID 0000-0003-2403-6940
Shalom N JaffeCloudResearch, Queens, NY, USA.ORCID 0000-0002-7523-5213
Jonathan RobinsonCloudResearch, Queens, NY, USA.ORCID 0000-0001-5353-7969
Leib LitmanCloudResearch, Queens, NY, USA.ORCID 0000-0001-6598-2701

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Maintaining data quality on Amazon Mechanical Turk (MTurk) has always been a concern for researchers. These concerns have grown recently due to the bot crisis of 2018 and observations that past safeguards of data quality (e.g., approval ratings of 95%) no longer work. To address data quality concerns, CloudResearch, a third-party website that interfaces with MTurk, has assessed ~165,000 MTurkers and categorized them into those that provide high- (~100,000, Approved) and low- (~65,000, Blocked) quality data. Here, we examined the predictive validity of CloudResearch's vetting. In a pre-registered study, participants (N = 900) from the Approved and Blocked groups, along with a Standard MTurk sample (95% HIT acceptance ratio, 100+ completed HITs), completed an array of data-quality measures. Across several indices, Approved participants (i) identified the content of images more accurately, (ii) answered more reading comprehension questions correctly, (iii) responded to reversed coded items more consistently, (iv) passed a greater number of attention checks, (v) self-reported less cheating and actually left the survey window less often on easily Googleable questions, (vi) replicated classic psychology experimental effects more reliably, and (vii) answered AI-stumping questions more accurately than Blocked participants, who performed at chance on multiple outcomes. Data quality of the Standard sample was generally in between the Approved and Blocked groups. We discuss how MTurk's Approval Rating system is no longer an effective data-quality control, and we discuss the advantages afforded by using the Approved group for scientific studies on MTurk.

Indexed as

CrowdsourcingData AccuracyAttentionHumansSelf ReportSurveys and QuestionnairesData qualityParticipant recruitmentResponse biasTest validity

Identifiers

PMID36326997
PMCPMC10700412

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.