A scoping review on interpersonal coping in sports
Bibliographic record
Abstract
Social relationships become crucial in times of stress and adversity. While research on interpersonal coping has acknowledged human interdependency and is gaining momentum in sport psychology, a lack of conceptual clarity and divergence in nomenclature is currently hindering the field to move forward. Thus, the aim of this scoping review was to map the current evidence on contextual characteristics, antecedents, strategies, and outcomes of interpersonal coping (i.e. communal coping, dyadic coping) in sports. Six databases were systematically searched utilizing the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Eleven studies were included in the current review and subject to data extraction and quality assessment. Data were charted according to the PRISMA extension checklist for Scoping reviews (PRISMA-ScR). Findings show that communal coping has primarily served to investigate joint coping efforts of teams or families during significant events or transitions, while dyadic coping sheds light on stressor management between athletes, or athletes and their coaches. Further, most studies were theory-driven and employed a qualitative methodology with a cross-sectional study design. Multi-group sampling was largely neglected. We conclude by explicating research gaps based on the populations and topics studied as well as the methodologies used to propose fruitful avenues for future research.
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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 | 0.011 | 0.045 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.016 | 0.016 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".