Understanding the potential contribution of a third “T” to FITT exercise prescription: the case of timing in exercise for obesity and cardiometabolic management in children
Bibliographic record
Abstract
Currently, exercise prescription relies heavily on parameters included in the FITT principle: frequency, intensity, time (duration), and type of exercise. In this paper, the benefits of including timing (FITT+T), referring to when exercise is performed in relation to meal-time, is discussed. Current research indicates that timing is outcome-specific. Total energy and lipid intakes, and postprandial hypertriglyceridemia can be reduced when exercise is performed pre-meal, while glycemic control is improved with post-meal exercise. Although findings indicate that timing can aid in obesity management and cardiometabolic-risk reduction, most research involves adult subjects and acute investigations. Some research with children, concerning the effect of timing on appetite, indicates that pre-meal exercise helps regulate energy balance, but also identifies key differences in response compared with adults. Overall, current findings support the benefits of timing, but research is required to establish guidelines that are specific to the pediatric population and their health-related goals, while incorporating other FITT components.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".