Does Physical Activity Intensity Moderate Social Cognition and Behavior Relationships?
Bibliographic record
Abstract
OBJECTIVE: Public health messaging about physical activity (PA) sometimes combines moderate and vigorous intensity, but the variance/invariance of the motives for PA by intensity has received scant attention. Thus, the purpose of this study was to examine the beliefs and motivations associated with regular moderate- and vigorous-intensity PA in a college sample using the framework of Ajzen's Theory of Planned Behavior (TPB). PARTICIPANTS AND METHODS: A college sample of 337 participants was randomly assigned to complete measures of the TPB framed for either vigorous- or moderate-intensity PA and subsequently completed self-reported measures of PA 2 weeks later. RESULTS: Mean comparisons indicated that participants held higher mean behavioral beliefs about the benefits of vigorous PA for improving appearance and fitness, but vigorous PA was perceived to take more time than moderate-intensity activities. A stacked structural equation model and follow-up Fisher z tests, however, suggested no differences between the associations of TPB constructs with intention or PA by intensity. CONCLUSIONS: The findings provide support for the current public health approach of combining moderate and vigorous physical activity messaging through the general invariance of motives by intensity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".