Impact of exercise video-guided bodyweight interval training on psychophysiological outcomes in inactive adults with obesity
Bibliographic record
Abstract
Purpose Determine the impact of a 6-week YouTube-instructed bodyweight interval training (BW-IT) program on cardiometabolic health, muscular strength, and factors related to exercise adherence in adults with obesity. Methods Fourteen adults (30.7 ± 10.3 yrs, BMI 35.5 ± 5.4 kg/m2) participated in this study. The BW-IT program progressed bi-weekly from a 1:3 to 1:1 work-to-rest ratio, using maximum effort intervals of high knees, squat jumps, scissor jacks, jumping lunges, and burpees. Pre- and post-intervention measures included peak oxygen consumption ( V˙ O2peak), relative quadriceps isometric muscular strength, waist circumference (WC), body composition via bioelectrical impedance, and cardiometabolic blood markers (blood glucose, insulin, lipid panel, and C-reactive protein). Self-efficacy (task and scheduling) and physical activity enjoyment (PACES) were also assessed. Results Relative isometric muscular strength increased by 12.5% (p = 0.02, dz 0.4) and absolute V˙ O2peak by 4.2% (p = 0.03, dz = 0.2). WC reduced by 2.1% (p < 0.001, dz = 0.2). Task self-efficacy was similar pre- to post-intervention (p = 0.53, dz = 0.2), while scheduling self-efficacy was reduced (p < 0.004, dz = 1.1). PACES scores were 9.6% higher week one compared to week six of BW-IT (p = 0.003, dz = 0.6). No changes occurred in body composition or cardiometabolic blood markers. Conclusion In previously inactive adults with obesity, 18 sessions of YouTube-instructed bodyweight interval training elicited small to moderate effects on lower extremity muscular strength, cardiorespiratory fitness, and waist circumference. Future studies may benefit from longer interventions and adding a greater variety of calisthenics to determine interventions that improve physiological health and maintain or enhance factors associated with exercise adherence.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".