The effect of attentional focus on the self-efficacy-performance relationship in a continuous running task: A pilot study
Bibliographic record
Abstract
Research has shown that the self-efficacy-performance relationship is reciprocal in continuous sport tasks with high self-efficacy leading to increased performance (LaForge-MacKenzie & Sullivan, in submission). However, an internal focus of attention may be detrimental to performance (e.g., Wulf, 2007) and is further associated with low self-efficacy whereas high self-efficacy is associated with a broad focus (Bandura & Jourden, 1991). As high confidence and focused attention have been shown to be important to peak running performance (Brewer, Van Raalte, Linder, & VanRaalte, 1991), the purpose of the present pilot study was to examine the effects of the direction of attention on the self-efficacy-performance relationship. Twenty-six participants were randomly assigned to three attention conditions: internal (9 participants), external (9 participants), and control (8 participants). Participants were required to run continuously for one kilometer employing their specific attentional focus and respond to a one-item self-efficacy measure every 200 meters. Path analyses revealed significant efficacy-to-performance pathways in the external (p < .05, βs ranging from -.25 to -.35) and internal conditions (p < .05, βs ranging from -.49 to -.59). Contrary to previous research, consistent, reciprocal relationships were absent from all conditions. However, the results showed that external focus was beneficial to the efficacy-performance relationship in the middle of the task whereas internal focus was beneficial late in the task. These results support the suggestion that internal focus increases at the end of a running performance (e.g., Lima-Silva, Silva-Cavalcante, Pires, Bertuzzi, Oliveira, & Bishop, 2012), and in this case, positively affects the efficacy-performance relationship.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".