Evidence map›Paper›PMID 36575350›Full record

ArticleMemory & cognition2023

Motor imagery and engagement favour spatial reasoning.

Francesco Ianì, Walter Schaeken, Ivan Nabil Ras, Monica Bucciarelli

Open access · bronzeAbstract read
PubMed Publisher
In one paragraph

Article in Memory & cognition, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.4field-weighted citation impact, top 31% of its field
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

0 citing papers in PubMed, 2 citations in OpenAlex.

No citing paper in PubMed yet.

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

4 authors at 2 institutions in 2 countries.

Francesco IanìDipartimento di Psicologia, Università degli studi di Torino, Via Verdi, 10, 10123, Turin, Italy. francesco.iani@unito.it.
Walter SchaekenFaculty of Psychology and Educational Sciences, KU Leuven, Leuven, Belgium.
Ivan Nabil RasDipartimento di Psicologia, Università degli studi di Torino, Via Verdi, 10, 10123, Turin, Italy.
Monica BucciarelliDipartimento di Psicologia, Università degli studi di Torino, Via Verdi, 10, 10123, Turin, Italy.
University of Turin · ITKU Leuven · BE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Based on the assumption that spatial reasoning relies on the construction of mental models of the states of affairs described in the premises, and on evidence that sensory-motor imagery can enhance cognitive abilities, we hypothesised that imagining moving the objects mentioned in the premises to the specific spatial locations should favour spatial reasoning. The results of Experiment 1 confirmed the prediction: when participants imagined moving the objects mentioned in the premises (dynamic-engagement condition), they drew accurate inferences faster compared with participants who merely read the premises (static-non-engagement condition). Experiment 2 was in part a replication of Experiment 1 but included two additional experimental conditions to control for possible effects of self-engagement in reasoning: in one condition, participants imagined that someone else was moving the objects (dynamic-non-engagement condition), and in the other condition, participants imagined that they were observing the objects (static-engagement condition). The results revealed an interaction between motor imagery and engagement in decreasing response times to spatial problems. We discuss the practical implications of the current results.

Indexed as

ImaginationProblem SolvingCognitionHumansModels, PsychologicalEngagementMental modelsMotor imagerySpatial reasoning

Identifiers

PMID36575350
OpenAlexW4312208368

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.