Application of the Multi-Process Action Control Model to Predict Physical Activity During Late Adolescence
Bibliographic record
Abstract
The aim of this study was to apply the Multi-Process Action Control model to examine how the additions of regulatory and reflexive processes predict physical activity (PA) behaviors among adolescents. Our sample included 1,176 Grade 11 students (Mage = 15.85 ± 0.38) recruited from a large school board in Southern Ontario. Participants completed a questionnaire including measures of self-reported PA and PA cognitions derived from the Multi-Process Action Control model. Results found the reflective process explaining 16.5% of the variance in PA, with the additions of regulatory and reflexive processes significantly improving the explained variance by 5.1% and 8.2%, respectively. Final models revealed coping planning (estimate = 45.10, p = .047), identity (estimate = 55.82, p < .001), and habit (estimate = 64.07, p < .001) as significant predictors of PA. Findings reinforce the need for integrative models to better understand PA, with coping planning, habit formation, and development of an active identity to be salient targets for intervention during adolescence.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".