Does Exercise Choice Matter For Cardiorespiratory Fitness Improvements?
Bibliographic record
Abstract
Low cardiorespiratory fitness (CRF) is an important risk factor for cardiometabolic disease and individuals with prediabetes tend to have low CRF. Trials that have compared High-Intensity Interval Training(HIIT) to Moderate-Intensity Continuous Training(MICT) by imposingindividuals to HIIT or MICT haveestablished that HIIT is effective for improving CRF. However, to maintain these improvements, individuals need to adhere to HIIT. Self-determination theory states that providingchoicehas a positive impact on exercise adherence. PURPOSE:To address whether having the choice to engage in HIITor MICT for 6-months (CHOICE) leads to greater changes in CRF (absolute and relative VO2peak) at 6-months when compared to IMposed HIIT (IM-HIIT)or IMposed MICT (IM-MICT) in adults with prediabetes. METHODS: In this single-site randomized trial, 68 low-active adults (56.8±6.6 yrs, mean±SD) living with prediabetes were randomized to CHOICE (n=24), IM-HIIT (n=21), or IM-MICT (n=23). After an initial supervised training period (6 sessions over 3 weeks) participants exercised unsupervised on their own in free-living conditions for 6 months. A ramp increase cycle ergometer test to exhaustion was conducted by the same technician pre- and post-testing to determine VO2peak. Missing data was accounted for using linear interpolations generated with SPSS®v.20.0. RESULTS: ANCOVA results with baseline CRF as a covariate revealed no significant differences between increases in absolute VO2peak (CHOICE: 0.38, 95% CI; 0.20, 0.55, vs. IM-HIIT: 0.56, 95% CI; 0.37, 0.74 vs. IM-MICT: 0.30, 95% CI; 0.12, 0.48 L/min, F2,64=1.99, P=.14), with similar findings for relative VO2peak (F2,67=0.32, P=.73). Within group changes over time indicated small effect sizes (Hedge’s g) for increases in absolute (CHOICE= 0.00; HIIT = 0.26; and MICT=0.01) and relative VO2peak over time (CHOICE = 0.11; HIIT = 0.33; and MICT=0.15). CONCLUSION:Changes in CRF between groups randomized to perform HIIT or MICT, or given the choice of HIIT or MICT, were not significantly different at 6-months post-intervention. Providing choice for selecting HIIT or MICT did not appear to enhance the benefits of exercise for improving fitness in low active adults. Supported by the Research Endowment from the American College of Sports Medicine Foundation.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".