Women's exercise motivation as a predictor of positive affect: Preliminary findings from an experience sampling study
Bibliographic record
Abstract
Women can accrue unique benefits in mental and physical health with regular engagement in physical activity. Indeed, the accumulation of positive affective experiences with repeated exercise sessions can lead to greater well-being and to sustaining an active lifestyle over time. However, the short- and long-term relationships between exercise and indicators of well-being (i.e., positive affect) are particularly complex, prompting the need to better understand the role of motivation in predicting these associations. Using self-determination theory (SDT), the purpose of this experience sampling study was to (a) examine acute changes in positive affect from pre- to post- to three hours-post exercise over a two-week period and (b) to explore the influence of situational motivation on these changes in affect. Preliminary regression results with a subsample of 30 active women with multiple life roles (mean age = 42.73) showed that, respectively, situational identified and introjected regulations predicted consistent increases in positive affect with exercise (ps < .05). In addition, data collected over the 14-day period revealed a significant decrease in positive affect three-hours post exercise (p < .05) that was not predicted by pre-exercise situational motivational regulations. The applicability of these findings, in terms of designing exercise-based wellness interventions for women that borrow from the principles of self-determination theory, is examined. The utility of daily experience sampling protocols for this type of research is also discussed.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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 | 0.001 |
| 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 teacher head, 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".