Examining real-time physical activity in adolescents using the Multi-Process Action Control Model: An ecological momentary assessment study
Bibliographic record
Abstract
The purpose of this study was to examine real-time associations between reflective (i.e., state motivation), regulatory (i.e., self-control), and reflexive (i.e., habit) constructs from the Multi-Process Action Control (M-PAC) model and real-time moderate-to-vigorous physical activity (MVPA) behaviour among adolescents using ecological momentary assessments. One hundred and ninety adolescents (Mage = 15.76 ± .47 years; n = 101 males) wore an accelerometer for seven consecutive days and responded to digital survey prompts up to four times daily during the after-school periods. MVPA in the 60-minute time window following each survey prompt was recorded. Multilevel mixed-effects linear and logistic models were computed with disaggregated between- and within-person effects to analyze the data. Results from both linear and logistic multilevel models revealed adolescents with higher state motivation in general and experiencing higher state motivation than one’s typical levels were associated with engaging in more MVPA and higher likelihood of engaging in ≥10 minutes of MVPA. Engaging in activities less consistent with habitual behaviours were associated with more MVPA and higher likelihood of engaging in ≥10 minutes of MVPA. By contrast, self-control was not associated with MVPA. Results from this study extend previous work demonstrating the importance of conscious and non-conscious processes on MVPA behaviour by examining associations in real-time using intensive longitudinal methods. Collectively, this study provides partial support for use of the M-PAC framework to explain acute MVPA among adolescents in real-time and natural contexts.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".