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Action Effects on Visual Perception of Distances: A Multilevel Bayesian Meta-Analysis
Author(s) -
Molto Lisa,
Nalborczyk Ladislas,
Palluel-Germain Richard,
Morgado Nicolas
Publication year - 2020
Publication title -
psychological science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.641
H-Index - 260
eISSN - 1467-9280
pISSN - 0956-7976
DOI - 10.1177/0956797619900336
Subject(s) - bayesian probability , perception , meta analysis , multilevel model , psychology , action (physics) , cognitive psychology , computer science , econometrics , statistics , artificial intelligence , mathematics , physics , medicine , quantum mechanics , neuroscience
Previous studies have suggested that action constraints influence visual perception of distances. For instance, the greater the effort to cover a distance, the longer people perceive this distance to be. The present multilevel Bayesian meta-analysis (37 studies with 1,035 total participants) supported the existence of a small action-constraint effect on distance estimation, Hedges's g = 0.29, 95% credible interval = [0.16, 0.47]. This effect varied slightly according to the action-constraint category (effort, weight, tool use) but not according to participants' motor intention. Some authors have argued that such effects reflect experimental demand biases rather than genuine perceptual effects. Our meta-analysis did not allow us to dismiss this possibility, but it also did not support it. We provide field-specific conventions for interpreting action-constraint effect sizes and the minimum sample sizes required to detect them with various levels of power. We encourage researchers to help us update this meta-analysis by directly uploading their published or unpublished data to our online repository ( https://osf.io/bc3wn/ ).

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