Interactions of sprint interval exercise and psychological need-support on subsequent food intake among physically inactive men and women
Bibliographic record
Abstract
The aim of this study was to investigate the effect of sprint interval training (SIT) and psychological need-support in exercise on postexercise appetite and energy intake. Forty physically inactive men and women (body mass index, 24.6 ± 4.8 kg·m−2; peak oxygen consumption, 26.6 ± 4.9 mL·kg−1·min−1) were randomised to either a need-support or no-support condition, with each participant completing 2 experimental trials involving 30 min of moderate-intensity continuous training (MICT; 60% peak oxygen consumption) and SIT (alternating 15 s at 170% peak oxygen consumption and 60 s at 32% peak oxygen consumption) matched for total work. Perceptions of appetite and appetite-related blood variables were assessed, together with ad libitum energy intake for 3 h following exercise using a laboratory test meal and available snacks. Greater enjoyment, perceived exertion, heart rate, and blood lactate were observed in SIT compared with MICT (all p ≤ 0.006). Ratings of perceived appetite were similar across conditions and trials (p > 0.05); however, active ghrelin was lower following SIT compared with MICT (p < 0.001), and there was a significant condition-by-type interaction for energy intake (p = 0.033), with participants in the support group consuming less energy from foods following SIT (1895 ± 1040 kJ) than MICT (2475 ± 1192 kJ). Findings from this work highlight the need to reconsider traditional exercise guidelines where dietary intake is a concern. Novelty Enjoyment was greater during SIT compared with MICT. Enjoyment and choice were higher among participants provided with psychological need-support. In a need-supportive environment, SIT reduced subsequent energy intake compared with MICT.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| 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".