Experiencing defeat in competition: Cognitive appraisal, stress, and emotion regulation in competitors high and low in self-compassion
Bibliographic record
Abstract
Performers in achievement domains inevitably have to manage losses and mistakes, but differ in their responses to these events. The purpose of this study was to examine if trait self-compassion predicted responses to a competition failure. Fifty-seven participants (28 male; Mage=21.46 years, SD=2.99) completed three computer-based where outcome was controlled so they lost significantly more often than they won. Participants in the upper quartile comprised a high self-compassion [HSCG; n=14 (6 male); self-compassion: M=3.98, SD=0.20], and those in the lowest quartile a self-compassion [LSCG; n=15 (6 male); self-compassion: M=2.20, SD=0.35]. HSCG demonstrated more adaptive responses to competition losses than LSCG. Prior to the competition, the low self-compassion group reported higher threat appraisals [t(27)=3.19] and stress [t(20.18)=2.60]. After the first competition, LSCG reported higher demands [t(27)=2.32] and stress [t(27)=3.74], and lower perceptions of resources [t(27)=-2.26]. After the second competition, LSCG reported higher demands [t(27)=2.47], threat appraisal [t(27)=3.02], and stress [t(27)=4.57]. LSCG also reported higher levels of stress after completing all competitions [t(27)=4.05]. A 2x4 repeated measures ANOVA indicated a significant group x time interaction for stress [F(120, 48)=1.66] and negative affect [F(96.44, 38.58)=1.65]. Participants low in self-compassion reported higher levels of negative affect prior to competition, after each competition, and at conclusion. HSCG reported engaging in more acceptance [t(27)= -3.61] and planning [t(27)=-3.62], and less catastrophizing [t(27)=6.76] and other blame [t(19.44)=2.66]. All results were significant (p< .05). Collectively, self-compassion is associated with adaptive emotion regulation strategies and lower threat appraisal and stress when experiencing defeat in competition.Acknowledgments: Supported by the University of Alberta Human Performance Fund
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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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".