Co-Regulation of Physiological Arousal in Social Support Interactions among University Athletes: The Role of Co-rumination
Bibliographic record
Abstract
Social support plays a crucial role in promoting positive outcomes for athletes, including reduced stress and enhanced well-being. However, the dynamics of social support processes in sport are complex and multifaceted, and existing research lacks insight into actual social support interactions among teammates. Additionally, the physiological arousal shared between athletes during discussions about sport-related stressors remains poorly understood. This study aimed to observe social support behaviors exhibited by athletes during discussions of sport-related stressors while continuously recording athletes’ physiological arousal, specifically focusing on co-regulation of heart rate variability. Laboratory-based conversations were conducted with 46 dyads of university athletes (mean age = 20.2 years, SD = 1.9). Video recordings, self-report data, and continuous recordings of heart rate variability were analyzed. Findings revealed that athlete dyads commonly engaged in co-rumination, collectively emphasizing negative feelings associated with their stressors. Post-conversation stress ratings were lower than pre-conversation stress ratings, suggesting that discussing stressors with a teammate may alleviate athletes' stress. Yet analyses indicated a positive association between co-rumination and perceived stress. Moreover, co-rumination related with co-dysregulated physiological arousal—a process in which partners’ physiological arousal is linked and mutually amplifying and may be related with regulatory failures. These results highlight the significance of considering co-rumination and its association with co-dysregulated physiological arousal in social support interactions. Future research should explore the impact of co-rumination on stress perception and physiological responses among athletes.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".