Generalized self‐efficacy and performance on the 20‐metre shuttle run in children
Bibliographic record
Abstract
It has been argued that motivation significantly affects the measurement of aerobic capacity when using field tests with children. In this study, the impact of generalized self-efficacy on performance (Stage Completed) in the Léger shuttle run is examined in a cohort of children (N = 2,245, 9.38 +/- 0.52 years old) in Grade 4 from 75 elementary schools. Children completed the Children's Self-perceptions of Adequacy in and Predilection for Physical Activity scale (CSAPPA) to establish levels of generalized self-efficacy toward physical activity, were measured for height and weight, and then completed the Léger Shuttle run to predict aerobic capacity. Regression analysis was used to study the impact of self-efficacy on test performance. After adjusting for age, gender, and BMI, two of the three CSAPPA factor subscales, higher perceived adequacy regarding physical activity (beta = 0.196, P < 0.001) and greater predilection to select physical over sedentary activities (beta = 0.123, P < 0.001), were independently associated with better test performance as indicated by stage completed. Together, self-efficacy accounted for 9% of the total variation in Léger shuttle run performance. A significant interaction between BMI and perceived adequacy was found (beta = -0.106, P < 0.005). Children with both high BMI scores and below average perceived adequacy had the poorest performance results. Generalized self-efficacy, as measured by the CSAPPA, is significantly related to Léger shuttle run performance. Moreover, self-efficacy influences the relationship between other known factors affecting test performance (BMI), suggesting that self-perception of ability/competence has a complex effect on test performance. These results illustrate the importance of considering psychological factors when interpreting physiologic assessments in children.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".