Introjected regulation and perceived intensity: Do they interact in predicting changes in positive affect with physical activity?
Bibliographic record
Abstract
Self-Determination Theory's (SDT) behavioural regulations may be important in explaining the underlying relationship between physical activity (PA) and well-being (e.g., positive affect). Mixed evidence regarding the specific influence of introjected regulation on behavioural persistence and well-being warrants further investigation of its effect on the immediate PA-affect response. In addition, research reveals that PA intensity, which has been associated with PA-induced mood changes, may be linked to one's motivational style. The purpose of this experimental study was to examine the interaction between introjected regulation and Ratings of Perceived Exertion (i.e., intensity; RPE) in predicting changes in positive affect with an acute bout of PA. Fourty-one active adult women engaged in a 30-minute self-paced treadmill run. Situational motivation for running, pre- and post-running positive affect, and RPE were assessed via validated self-report questionnaires. Hierarchical regression analyses revealed a significant interaction effect of RPE and introjection on the change in positive affect from pre- to post-running, s = -.30, p < .05. At low levels of introjection, the influence of RPE on the change in affect was considerable, with higher RPE ratings being associated with greater increases in positive affect. The need to examine these relationships in association with well-being over the long term, as well as some applied implications of these results, is discussed.
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 | 0.003 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".