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Record W4388633462 · doi:10.5114/jhk/173023

The Impact of Hemispheric Activity Priming on Choking Under Pressure in Badminton Tasks: A Study of Three Fundamental Skills

2023· article· en· W4388633462 on OpenAlexaff
Wei Wang, Melanie Gregg, Hairui Liu

Bibliographic record

VenueJournal of Human Kinetics · 2023
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsChokingPriming (agriculture)PsychologyCognitive psychologyDevelopmental psychologyPhysical medicine and rehabilitationMedicine

Abstract

fetched live from OpenAlex

Choking under pressure occurs when an individual experiences a decrease in performance despite their efforts to perform well. The self-focus approach suggests that pressure increases conscious attention on the performance process, disrupting the automatic or overlearned nature of execution. Hemispheric asymmetries in the brain and skilled performance indicate that left-hemispheric activity decreases, while right-hemispheric activity enhances. Previous studies have attempted to prevent choking by inhibiting the left hemisphere or enhancing the right hemisphere's activity. This study examined whether increased hemispheric activity priming can extenuate motor skill failure under pressure in badminton tasks. The study involved 32 right-handed college students who completed five conditions in pressure-free blocks versus choking under-pressure blocks with priming intervention. Results showed a significant improvement in motor learning from pre- to post-tests, but participants still choked under pressure during skill execution. Furthermore, the priming strategy (hand squeezing) did not alleviate the pressure to benefit performance. The study provides evidence of performance decrements under pressure conditions, and the priming strategy did not alleviate choking.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.050
GPT teacher head0.407
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations1
Published2023
Admission routes1
Has abstractyes

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