Understanding Contextual Relation in Promotion Physical Exercise from Autonomy Support
Bibliographic record
Abstract
To analyze the relationship between perception of support for student autonomy and the interaction of different motivational contexts of the intention to do physical exercise from the framework of the trans-contextual model of motivation (Hagger & Chatzisarantis, 2016) was the aim of this study. The sample consisted of 441 adolescents in physical education classes aged between 12 and 16 (Mage = 14.74, SD = .80), who responded to various questionnaires on perceived autonomy support, motivation in the education and leisure contexts, and intention to do exercise. The model was tested using a structural equation model. The results of structural equation modeling [χ2 (48, N = 441) = 489,69, p = .001, χ2/d.f = 3.98, CFI = .94, IFI = .94, TLI = .93, RMSEA = .08] marked that perceived autonomy support from the teacher was positively relacionated with intrinsic motivation in physical education classes, which in turn was positively associated with intrinsic motivation in leisure time. Perceived autonomy support from family and peers was positively associated with motivation in leisure time, which in turn positively associated with the attitude and control standards. While the intention to practice physical activity was positively associated with the main concepts of the theory of planned behavior. Results are discussed in view of the importance of considering the importance of social models in the stage of adolescence, highlighting the role of promoting autonomy and their influence on inter-contextual motivation in physical exercise.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".