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Record W4210941118 · doi:10.1080/17461391.2022.2041101

Moderators of the coach leadership and athlete motivation relationship

2022· article· en· W4210941118 on OpenAlexaff
Cristina López de Subijana, Luc J. Martin, Cailie S. McGuire, Jean Côté

Bibliographic record

VenueEuropean Journal of Sport Science · 2022
Typearticle
Languageen
FieldPsychology
TopicMotivation and Self-Concept in Sports
Canadian institutionsQueen's University
Fundersnot available
KeywordsPsychologyAthletesTransformational leadershipTransactional leadershipApplied psychologyPerspective (graphical)Social psychologyDevelopmental psychologyPhysical therapyMedicine

Abstract

fetched live from OpenAlex

ABSTRACT The purpose of this study was to determine whether the relationship between coach leadership and athlete motivation was moderated by age, gender, competition level, and seasons spent with a coach. This study involved data from two previous studies that explored this relationship yet provides a novel perspective through the lens of important moderators. Three‐hundred and three athletes ( M age = 17.6 years; SD = 3.20; 49.7% women and 50.3% men) responded to questionnaires pertaining to their coaches’ leadership behaviours and their own sport motivation. Multiple regression analyses using moderators were conducted. Age, competition level, and seasons spent with the coach significantly moderated the relationships of interest. Coach transformational leadership predicted intrinsic and extrinsic motivation to a greater extent when athletes were younger than 20.8 and 18.2 years of age, respectively. Further, coach transactional leadership predicted intrinsic and extrinsic motivation to a greater extent when athletes had trained for more than two seasons with their coach. Results emphasize the need to consider athlete characteristics from both research and practitioner perspectives. Herein, we advocate for increased awareness amongst key sport stakeholders on the influence that a coach can have on younger athletes’ motivation and the importance of developing coach‐athlete relationships over time.

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)0.003
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 score0.016
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.087
GPT teacher head0.280
Teacher spread0.194 · 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

Citations19
Published2022
Admission routes1
Has abstractyes

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