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Action Effects on Visual Perception of Distances: A Multilevel Bayesian Meta-Analysis
Lisa Molto1, Ladislas Nalborczyk1,2, Richard Palluel-Germain1
1Laboratoire de Psychologie et NeuroCognition (LPNC), Centre National de la Recherche Scientifique (CNRS), Université Grenoble Alpes.
Psychological Science
|April 10, 2020
Summary
Action constraints, like physical effort, slightly increase perceived distance. This meta-analysis confirms a small but significant effect, suggesting our actions subtly shape how we see space.
Area of Science:
- Cognitive Psychology
- Perception Science
- Human Motor Control
Background:
- Previous research indicates a link between physical actions and the visual perception of distances.
- The hypothesis is that increased effort or constraints in performing an action lead to an overestimation of the distance involved.
Purpose of the Study:
- To quantitatively assess the influence of action constraints on distance perception using a meta-analytic approach.
- To investigate whether the effect varies across different types of action constraints (effort, weight, tool use) or motor intentions.
Main Methods:
- Conducted a multilevel Bayesian meta-analysis of 37 studies, incorporating data from 1,035 participants.
- Analyzed effect sizes (Hedges's g) to determine the overall magnitude of the action-constraint effect on distance estimation.
- Examined moderators such as action-constraint category and motor intention.
Main Results:
- A small but statistically significant effect of action constraints on distance perception was found (Hedges's g = 0.29).
- The effect showed minor variations across different action-constraint categories but was not influenced by motor intention.
- The possibility of experimental demand biases was considered but not definitively supported or dismissed by the data.
Conclusions:
- Action constraints exert a small, reliable influence on visual distance estimation, suggesting a genuine perceptual effect.
- The findings provide guidelines for interpreting effect sizes and determining sample sizes for future research in this area.
- Researchers are encouraged to contribute data to an online repository to facilitate ongoing updates to the meta-analysis.
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