The Motivational Implications of Characteristics of Exercise Bouts
Bibliographic record
Abstract
The purpose of this research was to examine the psychological adaptations to two different exercise prescriptions. The dependent variables were three types of self-efficacy: task (for elemental aspects of the behavior); coping (for exercising under challenging circumstances); and scheduling (for arranging one's time commitments to exercise regularly). Participants were randomly assigned to one of two 12-week exercise prescriptions: a higher-intensity, shorter-duration condition (about 70 percent VO(2max), n = 21) and a lower-intensity, longer-duration condition (about 50 percent VO(2max), n = 23). The two conditions were equated for total work output (by manipulation of duration) in megajoules. The two exercise conditions produced similar aerobic fitness gains. Thus, the results regarding self-efficacy are not confounded by differential physical effects of the exercise prescriptions. Both groups were found to increase in task self-efficacy. The higher-intensity, shorter-duration group, however, showed an overall advantage in terms of coping (F[1,41] = 10.48, p< .002), and a group by time interaction was found for scheduling self-efficacy (F[2,39] = 3.81, p< .03) in favor of the higher-intensity, shorter-duration group. The motivational implications of the exercise prescriptions are discussed in terms of self-efficacy theory. It is concluded that it is important to consider not only the physical fitness implications of exercise prescription, but also the motivational implications. It is suggested that characteristics of the exercise bouts may influence motivation for subsequent physical activity involvement.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".