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Record W2404292802 · doi:10.1123/tsp.2016-0028

Perceived Outcomes of a Biofeedback and Neurofeedback Training Intervention for Optimal Performance: Learning to Enhance Self-Awareness and Self-Regulation With Olympic Athletes

2016· article· en· W2404292802 on OpenAlexaffabout
Margaret Dupee, Tanya Forneris, Penny Werthner

Bibliographic record

VenueThe Sport Psychologist · 2016
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsUniversity of CalgaryUniversity of Ottawa
Fundersnot available
KeywordsAthletesNeurofeedbackPsychologyIntervention (counseling)Applied psychologyBiofeedbackSport psychologyPhysical therapyMedicinePsychiatryElectroencephalography

Abstract

fetched live from OpenAlex

The purpose of this study was to explore the perceived outcomes of a biofeedback and neurofeedback training intervention with high performance athletes. Five Olympic level athletes preparing for world championships and the 2012 Olympic Games took part in a 20 session intervention over the period of one year. At the completion of the intervention, a semistructured interview was conducted with each athlete. The athletes indicated that they became more self-aware, were better able to self-regulate both their physiological and psychological states, developed a greater sense of personal control, and a greater understanding of skills inherent in the field of sport psychology. Three of the athletes made the Canadian Olympic team for the 2012 Olympic Games and two of those athletes won bronze medals. The present study suggests that biofeedback and neurofeedback training may be useful in enabling athletes to perform optimally, in both training and competition, on a consistent basis.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.063
Threshold uncertainty score0.709

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.025
GPT teacher head0.332
Teacher spread0.307 · 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 teacher head, 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

Citations39
Published2016
Admission routes2
Has abstractyes

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