The Psychometric Properties of Two Brief Measures of Teamwork in Sport
Bibliographic record
Abstract
In the current study, the structural and external validity of data derived from two shorter versions of the Multidimensional Assessment of Teamwork in Sport (MATS) were examined using multilevel analyses. Evidence of model-data fit was shown for both a 5-factor model comprising 19 items (with subscales assessing teamwork preparation, execution, evaluation, adjustments, and management of team maintenance) and a single-factor model comprising five items (providing a global estimate of teamwork). In general, data from both versions were positively and significantly correlated with (and distinct from) athletes' perceptions of team cohesion, collective efficacy, performance satisfaction, enjoyment in their sport, and commitment to their team and their coaches' transformational leadership. The measures appear well suited to detect between-teams differences, as evidenced by intraclass correlation coefficients and acceptable reliability estimates of team-level scores. In summary, the 19-item Multidimensional Assessment of Teamwork in Sport-Short and five-item Multidimensional Assessment of Teamwork in Sport-Global provide conceptually and psychometrically sound questionnaires to briefly measure teamwork in sport.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".