Bibliographic record
Abstract
The present study was designed to examine the effect of self-talk on anxiety, self-confidence and basketball free throw performance. In the baseline condition high school basketball players completed the CSAI-2 inventory prior to completing 20 free throws. Participants were then randomly assigned to one of two conditions: a self-talk group (n = 10) or control group (n = 9) who received time-management training. Participants were requested to practice their assigned mental skill until the next testing session, three days later. The same testing conditions were present in the post-intervention phase as in the baseline. It was hypothesized that the participants who received self-talk training would experience decreased levels of anxiety, increased levels of self-confidence, and improved free throw shooting performance in the post-intervention trial compared to baseline measures. A mixed design was used to analyze the results. Overall, the self-talk training did show a positive effect resulting in increased self-confidence post-intervention compared to the control group, F(1, 17) = 7.11, p = .016. The control group did not produce any significant differences from pre- to post-intervention. The self-talk group showed significant improvements in overall performance, t(9) = -3.40, p < 0.05; somatic anxiety, t(9) = 2.355, p < 0.05; and self-confidence, t(9) = -2.273, p < 0.05. Encouraging athletes to use self-talk strategies is beneficial even in a brief time frame.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".