“I hate it when that happens too!”: observed and perceived exchanges of social support between university student-athletes during discussions of stressors
Bibliographic record
Abstract
Receiving social support is often related to adaptive outcomes for athletes, such as reduced stress and greater wellbeing. Nevertheless, in some cases, receiving social support may not reduce, or even heighten, stress reactions. Thus, research is needed to better understand the complex dynamics of social support processes among athletes. Though substantial research has examined social support in sport, the majority of these studies relied on self-report measures; there is a lack of information about the actual interactions that constitute social support exchanges among teammates. This study sought to fill this gap by observing athletes’ discussions of stressful experiences, with a focus on understanding the types of social support behaviours that are displayed. University athlete dyads (N = 46 dyads, Mage = 20.2 years, SD = 1.9) were asked to complete surveys and engage in a conversation regarding stressors in a lab setting. The conversations were video-recorded and analysed along with self-reported survey data. Results showed that in addition to emotional, esteem, and informational support, athletes commonly engaged in co-rumination – collective discussions of stressful experiences with a persistent focus on negative feelings associated with the experience. Correlational analysis revealed that observed informational support was positively associated with perceived emotional and informational support, and co-rumination was positively associated with perceived stress. Emotional, esteem, and informational support did not relate to stress perceptions. The findings were interpreted to highlight the importance of considering co-rumination and we suggest potential avenues for future research on social support in sport that might further illuminate this salient component.
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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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| 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".