The influence of attentional focus on the self-efficacy-performance relationship in a continuous running task
Bibliographic record
Abstract
The self-efficacy-performance relationship in continuous sport tasks has been shown to be significantly reciprocal yet unequal with stronger influences in the performance-to-self-efficacy pathway rather than self-efficacy-to-performance pathway (e.g., LaForge-MacKenzie & Sullivan, 2014b). Bandura (2012) suggested that sociocognitive variables may influence this relationship. Attention as a sociocognitve factor may bias the processing of performance and self-efficacy information (Bandura, 1982, 1997; Bandura & Jourden, 1991). As confidence and attention are important aspects of peak running performance (Brewer, Van Raalte, Linder, & VanRaalte, 1991), the primary purpose of the present study was to examine the self-efficacy-performance relationship under three conditions of attentional focus. The secondary purpose was to examine self-efficacy and performance as separate constructs under the same conditions of attention. Participants ran continuously for one kilometer in one of three randomly assigned attentional focus conditions: internal-focus (n = 51), external-focus (n = 50), and control (n = 49). Self-efficacy was assessed using a one-item measure every 200 meters. Path analyses examining the primary objective revealed significant self-efficacy-to-performance pathways in all conditions: external-focus (p < .05, βs ranging from -.17 to -.32), internal-focus (p < .05, βs ranging from -.26 to -.36), and control (p < .05, βs ranging from -.29 to -.42). Significant reciprocal relationships were absent in all conditions. ANOVAs examining the secondary objectives found significantly faster performance in the control condition at the start (F (2, 147) = 3.86, p < .05) and end of the task (F (2, 147) = 3.56, p < .05). Self-efficacy was significantly higher in the internal-focus condition at the end of the task (Self-Efficacy 4 (F (2, 147) = 3.21, p < .05) and Self-Efficacy 5 (F (2, 147) = 4.74, p < .05). In contrast to previous within-trial research (e.g., LaForge-MacKenzie & Sullivan, 2014b) self-efficacy-to-performance effects were more significant and robust than performance-to-self-efficacy effects. These results provided support for Bandura’s (2012) suggestion that sociocognitive factors may have the ability to alter the causal structure of the self-efficacy-performance relationship, proposing complexities in the self-efficacy-performance relationship (Sitzmann &Yeo, 2013). Results were discussed from both theoretical and applied perspectives.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".