A Season-Long Goal-Setting Intervention for Elite Youth Basketball Teams
Bibliographic record
Abstract
The current study involved a season-long team goal-setting intervention within an elite youth sport population. Participants were 75 male basketball players (Mage = 16.23 years, SD = 1.40) from 6 teams that were randomly assigned to team goal-setting (n = 3) or no-treatment control (n = 3) conditions. The intervention condition received a 3-stage team goal-setting program throughout the season, whereas no systematic program was delivered to the control teams. All participants completed questionnaires assessing perceptions of team cohesion and motivational climate at 3 time-points throughout the season (beginning, midseason, end-season). Data were first analyzed using a multivariate analysis of covariance to determine differences in cohesion and motivational climate throughout the season, with pretest scores and age included as covariates. In addition, a series of multiple mediation analyses were conducted to determine whether motivational climate mediated the relationship between preseason and postseason cohesion perceptions. Findings suggest that although perceptions of cohesion remained constant for the control condition teams, those in the intervention condition experienced a decrease throughout the season. In addition, increase in ego-involving climate within the intervention group negatively affected the cohesion perceptions throughout the season; however, task-involving motivational climate decreased for teams in the intervention condition. These results highlight the importance of accounting for additional variables when conducting team-building interventions, and findings are discussed in relation to their implications for the literature, in concert with practical implications and future directions.Lay Summary: This study extends the team-building literature by conducting a season-long goal-setting intervention in elite youth sport. In recognizing previously identified limitations within the field, the intervention involved both direct and indirect delivery methods, was conducted across the entire season, and included additional constructs beyond cohesion and a control condition.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".