Self-compassion and exercise: Men and women's reactions to a recalled exercise failure
Bibliographic record
Abstract
Exercise improves health and wellbeing, yet people experience setbacks when trying to adhere to exercise. Self-compassion (i.e., treating oneself kindly when facing challenges) can help people cope with exercise setbacks. Most exercise and self-compassion research has been conducted with women but self-compassion should help with exercise failures regardless of gender. The purpose of this study was to establish whether gender moderates the association between self-compassion and responses to an exercise setback. Using an online survey, undergraduate exercisers (N = 117, Mage = 20.97) recalled an exercise setback and how they responded regarding motivation, goal re-engagement, rumination, and affect. Using PROCESS, moderation analysis revealed gender (binary) did not moderate the relationships between self-compassion and responses to the exercise setback. Some moderated effects were found when gender was treated as a continuous variable; self-compassion had a stronger negative relationship with two forms of motivation (amotivation: b = -0.59, 95% CI [-0.98, -0.20], t = -3.02, p = .003; and identified regulation: b = 0.40, 95% CI [0.06, 0.74], t = 2.33, p = .021) at high levels of masculinity, while a stronger negative relationship between self-compassion and state rumination was established at high levels of femininity, b = -0.58, 95% CI [-0.92, -0.25], t = -3.50, p < .001. Findings for most outcomes suggest that self-compassion is associated with adaptive responses to setbacks regardless of gender. Researchers should study effects of self-compassion in exercise contexts across genders and the gender continuum, and continue exploring whether gender influences self-compassion's effects in exercise contexts. Key words: self-compassion, physical activity, exercise failure, gender
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".