Evidence map›Paper›PMID 22829343›Full record

ArticlePsychonomic bulletin & review2012

Is the Web as good as the lab? Comparable performance from Web and lab in cognitive/perceptual experiments.

Laura Germine, Ken Nakayama, Bradley C Duchaine, Christopher F Chabris, Garga Chatterjee, Jeremy B Wilmer

Abstract readComparative Study
PubMed Publisher
In one paragraph

Article in Psychonomic bulletin & review, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 233 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
233citing papers in PubMed, 2 pooled it
–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

233 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. A digital intervention for cognitive deficits following COVID-19: a randomized clinical trial.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
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  10. Personality trait and state associations with cognitive functioning and variability in middle-aged and older adults.The journals of gerontology. Series B, Psychological sciences and social sciences · 2026
    Article
  11. Intact Visual Correlation Detection in Autistic Adults.Autism research : official journal of the International Society for Autism Research · 2026
    Article
  12. Judgment of Learning Reactivity for Emotional Faces.Behavioral sciences (Basel, Switzerland) · 2026
    Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Distractor avoidance and early quitting in visual search.Attention, perception & psychophysics · 2025
    Article
  18. Article
  19. Article
  20. Review

173 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

6 authors.

Laura GermineDepartment of Psychology, Harvard University, 768 William James Hall, 33 Kirkland Street, Cambridge, MA 02138, USA. lgermine@gmail.com
Ken Nakayama
Bradley C Duchaine
Christopher F Chabris
Garga Chatterjee
Jeremy B Wilmer

Funding

NEI NIH HHS R01 EY01363
6 · The paper itself

Abstract

With the increasing sophistication and ubiquity of the Internet, behavioral research is on the cusp of a revolution that will do for population sampling what the computer did for stimulus control and measurement. It remains a common assumption, however, that data from self-selected Web samples must involve a trade-off between participant numbers and data quality. Concerns about data quality are heightened for performance-based cognitive and perceptual measures, particularly those that are timed or that involve complex stimuli. In experiments run with uncompensated, anonymous participants whose motivation for participation is unknown, reduced conscientiousness or lack of focus could produce results that would be difficult to interpret due to decreased overall performance, increased variability of performance, or increased measurement noise. Here, we addressed the question of data quality across a range of cognitive and perceptual tests. For three key performance metrics-mean performance, performance variance, and internal reliability-the results from self-selected Web samples did not differ systematically from those obtained from traditionally recruited and/or lab-tested samples. These findings demonstrate that collecting data from uncompensated, anonymous, unsupervised, self-selected participants need not reduce data quality, even for demanding cognitive and perceptual experiments.

Indexed as

CognitionInternetPattern Recognition, VisualResearch DesignAdolescentAdultAgedAge FactorsFaceFemaleHumansLaboratoriesMaleMiddle AgedMotivationPatient Selection

Identifiers

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.