The Effects of a Peer Modeling Intervention on Cardiorespiratory Fitness Parameters and Self-Efficacy in Obese Adolescents
Bibliographic record
Abstract
Inconsistencies exist in the assessment and interpretation of peak VO2 in the pediatric obese population, as cardiorespiratory fitness assessments are effort-dependent and psychological variables prevalent in this population must be addressed. This study examined the effect of a peer modeling intervention on cardiorespiratory fitness performance and task self-efficacy in obese youth completing a maximal treadmill test. Forty-nine obese (BMI ≥ 95th percentile for age and sex) youth were randomized to an experimental (received an intervention) or to a control group. The outcome variables were mean and variability cardiorespiratory fitness (peak VO2, heart rate, duration, respiratory exchange ratio), rating of perceived exertion, and task self-efficacy scores. Irrespective of whether a mean or variability score was used, receiving the intervention was associated with non-significant trends in fitness parameters and task self-efficacy over time, favoring the experimental group. Cardiorespiratory fitness and task self-efficacy were moderately correlated at both time points. To elucidate the aforementioned findings, psychosocial factors affecting obese youth and opportunities to modify the peer modeling intervention should be considered. Addressing these factors has the potential to improve standard of care in a clinical setting regarding pretest patient education.
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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 | 0.000 |
| 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".