Evidence map›Paper›PMID 32226403›Full record

ArticleFrontiers in psychology2020

Flow States and Associated Changes in Spatial and Temporal Processing.

Scott Sinnett, Joshua Jäger, Sarah Morgana Singer, Roberta Antonini Philippe

Abstract read
In one paragraph

Article in Frontiers in psychology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 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

4 authors.

Scott SinnettDepartment of Psychology, University of Hawaii at Manoa, Honolulu, HI, United States.
Joshua JägerInstitute of Psychology, University of Bern, Bern, Switzerland.
Sarah Morgana SingerInstitute of Psychology, University of Bern, Bern, Switzerland.
Roberta Antonini PhilippeLaboratoire PHASE, Institut des Sciences du Sport, Faculté des Sciences Sociales et Politiques, Université de Lausanne, Lausanne, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improved perception during high performance is a commonly reported phenomenon. However, it is difficult to determine whether these reported changes experienced during flow states reflect veridical changes in perceptual processing, or if instead are related to some form of memory or response bias. Flow is a state in which an individual experiences high focus and involvement in a specific task, and typically experiences a lack of distractibility, a disordered sense of time, great enjoyment, and increased levels of performance. The present pre-registered study investigated 27 athletes and musicians using a temporal order judgement (TOJ) task before and after a sports or music performance over three sessions. Participants' flow experiences were surveyed in order to measure how modulations of flow over successive performances potentially modulates spatiotemporal perception and processing. Hierarchical linear modeling showed a positive moderation of subjectively experienced flow and performance on post-measures of a TOJ task. Specifically, the higher the subjective flow experience of the sport or music performance was rated, the better the participant performed in the post-performance TOJ task compared to the pre-performance TOJ task. The findings of the present study provide a more comprehensive explanation of human perception during flow at high level performances and suggest important insights regarding the possibility of modulated temporal processing and spatial attention.

Indexed as

flowhierarchical linear modelinghigh performancemusicperceptionspatial attentionsporttemporal processing

Identifiers

PMID32226403
PMCPMC7080955

What OpenQuestion holds

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Registered trials

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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.