Tracing Adolescent Girls' Motivation Longitudinally: From FitClub Participation to Leisure-Time Physical Activity
Bibliographic record
Abstract
Scientific evidence reveals a significant decline in exercise behaviors during adolescence. Although multiple school-based initiatives have been implemented in Canada, little is known of how these initiatives affect students' motivation for subsequent physical activity (PA). The transcontextual model of motivation offers an interesting approach to assessing the long-term, motivational impact of school-based interventions, and we used this model to study how adolescent girls' need satisfactions, first observed within supervised PA (in the FitSpirit FitClub), correlated with their inclinations toward nonsupervised PA behaviors later. Adolescent girls in this study ( N = 259; M = 14.34, SD = 1.49 years) completed a transcontextual model of motivation-based questionnaire regarding their basic psychological needs, motivation, attitudes, subjective norms, perceived behavioral control, intentions, and PA practice during their FitSpirit club participation. Three weeks after this participation, they reported their PA levels again. The girls' basic psychological needs predicted their autonomous motivation in the FitClub. Their autonomous motivation predicted subjective norms and perceived behavioral control; these factors then determined their intentions to be physically active, and their PA intentions predicted their actual PA behavior during personal (leisure) time three weeks later. Two indirect paths were statistically significant for predicting PA intentions, and three indirect paths were significant for predicting leisure-time PA. Activity motivation, first developed within a supervised context, can increase subsequent leisure-time PA.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".