Automatic and Motivational Correlates of Physical Activity: Does Intensity Moderate the Relationship?
Bibliographic record
Abstract
The purpose of this study was to examine the predictive capability of a habit construct, controlling for intention and perceived behavioral control, with moderate and strenuous intensity physical activity. This approach was expanded through an examination of whether conscious deliberation in the initiation of physical activity would attenuate these findings and a test of the intention-habit interaction. Participants were 337 undergraduate students who completed the habit measure and measures of intention, deliberation, and perceived behavioral control phrased in either moderate or vigorous intensities at time 1. This was followed by a measure of behaviour 2 weeks later. Results using stacked structural equation models (moderate and vigorous intensity) demonstrated the direct effect of habit and accounted for a significant effect on physical activity after controlling for intention and perceived behavioral control; this effect was invariant to intensity and conscious deliberation. A 3-way interaction, however, was identified for the habit X intention relationship and intensity. In the moderate intensity condition, individuals who reported higher habits showed a lower intention-behavior relationship when compared with those who reported modest or low habits. By contrast, individuals who reported high habit levels in the vigorous physical activity condition demonstrated a larger intention-behavior relationship than their modest and low habit counterparts. The results support the notions that some properties of physical activity may have an automatic component and that habits may be important to physical activity action initiation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.003 | 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".