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Record W4390691355 · doi:10.1080/10413200.2023.2296902

Research note: Evaluating the efficacy of an online post event reflection tool in competitive sport

2024· article· en· W4390691355 on OpenAlexaff
Mark W. Bruner, Colin D. McLaren, Darren Turcotte, Chloë Marshall

Bibliographic record

VenueJournal of Applied Sport Psychology · 2024
Typearticle
Languageen
FieldPsychology
TopicSport Psychology and Performance
Canadian institutionsCape Breton UniversityNipissing University
Fundersnot available
KeywordsPsychologySport psychologyIce hockeyEvent (particle physics)Applied psychologyReflection (computer programming)CoachingTeam sportAthletesTask (project management)Work (physics)EngineeringComputer sciencePhysical medicine and rehabilitationPhysical therapy

Abstract

fetched live from OpenAlex

In competitive sport environments, coaches and sport psychology practitioners work to optimize individual and team performance. One strategy identified as a key to optimal sport performance is athlete self-awareness. This study evaluated the efficacy of a novel, online post-event reflection (PER) tool. Using a mixed methods design, 22 members of a competitive women’s ice hockey team completed the PER across one season. The PER demonstrated efficacy through tailored insight used as a basis for athlete discussions, complementing other performance-related feedback. Follow-up interviews with three team members and the head coach provided additional support for the efficacy of the PER.Lay summary: In competitive sport environments, coaches and sport psychology practitioners work to optimize individual and team performance. This study provides evidence to support the use a novel, online post-event reflection tool by athletes, coaches, and sport psychology practitioners to enhance athlete self-awareness of mental skills and performance.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesResearch integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.909
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.003
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 head0.118
GPT teacher head0.520
Teacher spread0.402 · 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.

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
Published2024
Admission routes1
Has abstractyes

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