Evidence map›Paper›PMID 42332117›Full record

ArticleNature human behaviour2026

Representativeness and response validity across nine opt-in online samples.

Michael N Stagnaro, James N Druckman, Adam J Berinsky, Antonio A Arechar, Robb Willer, David G Rand

Abstract read
In one paragraph

Article in Nature human behaviour, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Michael N StagnaroSloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA. mnstag@mit.edu.ORCID http://orcid.org/0000-0001-5512-7218
James N DruckmanDepartment of Political Science, University of Rochester, Rochester, NY, USA.ORCID http://orcid.org/0000-0002-1249-6790
Adam J BerinskyDepartment of Political Science, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-7827-9396
Antonio A ArecharDepartment of Applied Economics, Center for Research and Teaching in Economics (CIDE), Aguascalientes, Mexico.ORCID http://orcid.org/0000-0002-2537-8830
Robb WillerDepartment of Sociology, Stanford University, Stanford, CA, USA.ORCID http://orcid.org/0000-0003-3404-6472
David G RandSloan School of Management, Massachusetts Institute of Technology, Cambridge, MA, USA.ORCID http://orcid.org/0000-0001-8975-2783

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The study of human behaviour has shifted in the past 15 years. It increasingly relies on opt-in non-probability online data sources. Here we offer an analysis of nine such sources (N = 13,053), aiming to inform researchers conducting experiments or correlational studies. We assess response validity (attentiveness, effort, honesty, speeding and attrition), the extent to which samples represent the underlying population (demographics, attitude representativeness and experimental treatment effects) and professionalism (number and frequency of studies taken and modality of device on which studies are taken). We document substantial variation across samples on each dimension. Samples using demographic quotas display relatively higher amounts of representativeness across multiple indicators (beyond demographics) but often exhibit less response validity. However, inclusion of two attention checks early in a survey can enhance response validity without negatively impacting representativeness. We offer guidance for choosing opt-in samples, depending on the purpose of the research and resource constraints.

Indexed as

InternetResearch DesignHumansReproducibility of ResultsSurveys and Questionnaires

Identifiers

PMID42332117
PMCPMC13485695

What Socratic 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 Socratic graph.