Adaptation and Validation of a Portuguese Version of the Sports Motivation Scale-II (SMS-II-P) Showing Invariance for Gender and Sport Type
Bibliographic record
Abstract
In the present cross-sectional study, we adapted and examined the validity of a Portuguese version of the Sport Motivation Scale II (SMS-II-P) within a sample of 1148 Portuguese athletes (women = 546, men = 602) with a mean age of 18.45 years ( SD = 5.36), participating in a variety of sports (i.e., football, basketball, swimming, and athletics). We conducted confirmatory factor analysis, convergent and discriminant validity analysis, and multigroup analysis across participants’ sport type (team and individual) and gender. We also examined the correlations between the SMS-II-P behavioral regulations and basic psychological needs satisfaction. The results supported that the SMS-II-P had good psychometric properties and was invariant across gender and sport type. The scale demonstrated good convergent and discriminant validity, and the subscales achieved adequate internal consistency. Correlations between the six types of regulation measured in the SMS-II supported the distinction between autonomous and controlled behavioral regulations, and the correlations between these subscales and other measures of autonomy, competence, and relatedness satisfaction provided evidence of the self-determination continuum. Implications of this research for assessing Portuguese athletes and conducting future research are discussed.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".