Body-related self-conscious emotions and reasons for exercise: A latent class analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Body-related self-conscious emotions are important predictors of exercise motivation, yet the association between body-related self-conscious emotions and reasons for exercise has not been explored. Researchers have typically examined body-related emotions (e.g., shame, guilt, pride, embarrassment, envy) in isolation, but they may interact in unique ways to predict reasons for exercise. The present study examined how patterns of body-related emotions were associated with exercise reasons. In an online survey, participants ( N = 520; M age = 35.43 ± 10.09; 57.5 % men) reported their experience of body-related self-conscious emotions and exercise reasons over the past week. Latent class analysis revealed a three-class model of emotions, resulting in a High Emotionality class (i.e., experiencing positive and negative emotions), a Negative Emotions class, and a Pride class. Individuals who experienced negative emotions about their bodies engaged in exercise for appearance reasons, while individuals who felt proud about their bodies and did not report the negatively valenced emotions reported exercising for health reasons. These findings underscore the importance of investigating how multiple body-related self-conscious emotions influence reasons for exercising. Understanding how patterns of body-related self-conscious emotions are experienced could inform future research on factors that may precede exercise motivation and increase exercise behavior.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it