CARDIORESPIRATORY RESPONSES FOLLOWING AN 8-WEEK DEEP WATER RUNNING TRAINING PROGRAM IN ELDERLY WOMEN
Bibliographic record
Abstract
This study compared and contrasted the acute and training responses of deep water running (DWR) to treadmill running (TMR) in elderly women. Twenty inactive, healthy women (mean age = 64.5 ± 3.5 yrs) volunteered to participate in this study. Subjects were randomly assigned to either a control or exercise group. Maximal TMR exercise response was achieved using a graded protocol of 3.5mph, increasing 2%grade/min. Maximal DWR exercise response utilized a tethered apparatus starting at an initial load of 300g and increasing 100g/min. Training intensities, for the exercise group, were set at 70%, 75%, and 80% of pre-training DWR maximal heart rates (HRmax) during weeks 1–2, 3–5, 6–8, respectively. Maximal oxygen consumption (VO2max), ventilation (VE), heart rate (HR), respiratory exchange ratio (RER), and blood lactate concentrations (Blac) were measured during DWR and TMR maximal tests, both pre and post training. A within subject repeated measures ANOVA was performed to determine whether statistical differences occurred across exercise conditions (TMR vs DWR), over time (training effect), and with training responses between TMR and DWR (specificity of training). Data obtained pertaining to the acute responses of DWR and TMR revealed significantly higher TMR VO2max (23.9 vs. 18.5 and 21.6 vs 17.7 ml/kg/min, p < 0.05) and HR (164.5 vs 157.7 and 161.8 vs. 156.1 bpm, p < 0.05) compared to DWR for exercise and control groups, respectively. Training for 8-weeks with DWR increased TMR VE (14%, p < 0.05), TMR VO2max (18%, p < 0.05), DWR VE (15%, p < 0.05), and DWR VO2max (10%, p > 0.05). However, group interaction over time between the VO2max values of the control and exercise groups was significant (p < 0.05). Findings indicate lower metabolic responses for DWR when compared to TMR and 8-weeks of DWR training results in significant increases in aerobic capacity for both TMR and DWR.
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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 | 0.000 |
| 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) | 0.000 | 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".