Treating Yourself in a Fairway: Examining the Contribution of Self-Compassion and Well-Being on Performance in a Putting Task
Bibliographic record
Abstract
Researchers have advocated for greater insight regarding the contributions of psychological resources to sports performance. The purpose of this study was to examine the contributions of self-compassion and well-being to sports performance using a golf putting task. Male golfers (N = 87, Mage = 54.94; SDage = 15.37 years) completed the Self-Compassion Scale—Athlete Version and the Warwick Edinburgh Mental Well-Being Scale immediately prior to the golf putting task which consisted of 15 consecutive putts from 7 feet on an outdoor practice green. Performance was assessed immediately following the putting task. Simple linear regression analyses showed that self-compassion did not predict ‘perceived’ (β = −0.20, p = 0.06; ƒ2 = 0.04) or ‘actual’ (β = −0.17, p = 0.11; ƒ2 = 0.03) performance. Similarly, well-being did not predict ‘perceived’ (β = −0.16, p = 0.15; ƒ2 = 0.03) or ‘actual’ performance (β = −0.01, p = 0.91; ƒ2 = 0.00). Overall, the conclusions from this study offer converging evidence that self-compassion and well-being may not impact putting performance in adult male golfers. Greater insight into whether, and if so under what conditions, self-compassion and well-being matter to sports performance warrants additional scrutiny.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".