Relations among Exercise Imagery, Self-Efficacy, Exercise Behavior, and Intentions
Bibliographic record
Abstract
The purpose of the present study was to determine whether exercise imagery contributed to the prediction of exercise behavior and intentions over and above self-efficacy. Whereas self-efficacy has been demonstrated to be a robust predictor of exercise intentions and behavior such a role of imagery has not been examined. Imagery, however, has been postulated to be a potential source of self-efficacy beliefs, therefore, it is possible that the influence of these two variables might not be independent. Recently, different types of self-efficacy (task, coping, and scheduling) and different types of imagery (appearance, technique, and energy) have been proposed and associated with different levels of exercise involvement. The relative influence of these types of self-efficacy and imagery was assessed in two samples of exercisers ( n = 388, n = 223) using hierarchical regressions. Results indicated that scheduling and coping efficacy were important predictors of exercise behavior, and that two types of self-efficacy and appearance imagery were significant predictors of behavioral intention. These results offer support for different functions of the different types of self-efficacy and imagery. They also suggest that influence of self-efficacy and imagery on behavioral intentions is not redundant.
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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 | 0.001 | 0.009 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".