Team resilience in high-performance women’s football: Contextual stressors and opportunities for development
Bibliographic record
Abstract
The purpose of this study was to conduct a pre-intervention team resilience needs assessment in the context of high-performance women’s football. The needs assessment included a review of the literature, focus group discussions, and input from an expert steering group. Following scoping meetings with senior personnel from the National Governing Body, teams in the top two tiers of a professional women’s football league and within the academy structure were contacted. Five focus groups made up of football players were conducted. Altogether, 27 participants (Mage = 23.96, SD = 4.49) took part. The focus groups were analyzed using reflexive thematic analysis from a critical realist standpoint. The study identified the contextual stressors that high-performance women’s football teams encounter (i.e., organizational stressors arising from a newly professionalized environment and on-pitch stressors arising from low social resources), effective team resilience practices currently employed by group members (i.e., establishing a strong foundation for high quality relationships; unity in managing pressure; and learning from setbacks to inform future preparation for adversity) and the perceived gaps for team resilience development (i.e., limited effectiveness and inconsistent use of deliberate pressure training; inadequate psycho-social resources; and lack of effective proactive group level strategies during pressure). The study highlighted the importance of a systematic needs assessment within an Intervention Mapping Framework prior to undertaking an intervention as several nuances to the specific context of high-performance women’s football were identified.
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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 | 0.007 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".