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Record W4411327887 · doi:10.1177/17479541251347546

Initial development and validation of the Italian version of the Coaching Life Skills in Sport Questionnaire (IT-CLSS-Q)

2025· article· en· W4411327887 on OpenAlexaff
Paolo Albiero, Flavia Paoletti, Nicolò Maria Iannello, Nicla Cucinella, Sonia Ingoglia, Martin Camiré

Bibliographic record

VenueInternational Journal of Sports Science & Coaching · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicYouth Development and Social Support
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsCoachingPsychologyApplied psychologyPhysical therapyMedical educationMedicine

Abstract

fetched live from OpenAlex

Several studies have stated that coaches’ ability to teach life skills to their athletes intentionally is associated with various aspects of positive youth development. This study aimed to adapt and validate the English version of the Coaching Life Skills in Sport Questionnaire in the Italian context (IT-CLSS-Q), a tool developed to assess the intentionality of coaches in teaching and transferring life skills through sport. The original English version was adapted to Italian using the back-translation procedure. A sample of 590 youth sport coaches completed the IT-CLSS-Q. The confirmatory factor analysis confirmed the five-factor structure of the original questionnaire, and the reliability analyses demonstrated high internal consistency for all subscales. Measurement invariance testing showed consistency between groups with different coaching experience, while significant correlations with empathy and leadership self-efficacy supported the construct validity of the questionnaire. Overall, the results indicate that IT-CLSS-Q is a useful tool for evaluating life skills coaching in Italy, providing a foundation for future research and interventions to improve positive youth development through sport. Future research should include a more balanced representation of disciplines and genders, integrating athletes’ perspectives and longitudinal studies to deepen understanding of the long-term impact of life skills transfer.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.022
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.012
GPT teacher head0.317
Teacher spread0.306 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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