Cross-Validation of Ratings of Perceived Exertion Derived from Heart Rate Target Ranges Recommended for Pregnant Women
Bibliographic record
Abstract
International Journal of Exercise Science 13(3): 1340-1351, 2020. Currently, there are no established evidence-based rating of perceived exertion (RPE) targets for physical activity (PA) in pregnant women. Yet, a set of target heart rate (HR) ranges have been recommended. Using the Borg Scale, we aimed to determine and validate the RPE target ranges for different PA intensities derived from the recommended HR ranges in the 2019 Canadian Guideline for PA throughout pregnancy. We assessed 13 pregnant women (age: 31.2 ± 3.5 years; gestational age: 20.5 ± 5.0 weeks) using the following three phases: 1) the incremental submaximal walking test to develop the linear regression equation; 2) establishment of the RPE targets for light- and moderate-intensity PA; 3) moderate-intensity exercise session aiming to cross-validate RPE targets in women whose HR ranges were within (Step 1; six participants; 36 RPE values) or outside (Step 2; seven participants; 42 RPE values) the guideline. Study Phase 1 showed a strong linear relationship between RPE x HR (RPE = -7.370 + 0.155*HR; R2 = 0.863). RPE targets for pregnant women aged ≤ 29 years are 8-12 (light-intensity) and 12-15 (moderate-intensity), respectively. For women aged ≥ 30 years, RPE targets are 8-11 (light-intensity) and 11-14 (moderate-intensity), respectively. The cross-validation suggested no differences between predicted (13.4 ± 0.7) vs. observed RPE (13.3 ± 1.4; p = 0.703) and a strong % agreement (Step 1 = 80.6%; Step 2 = 73.8%) between observed RPE and its predicted range. Thus, we have determined pregnancy-specific, evidence-based RPE targets. These RPE targets will help exercise professionals, other health care providers, and pregnant women to easily monitor exercise intensity during pregnancy to meet recommended Canadian PA Guideline.
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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 | 0.009 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".