Evaluating Physical Activity Questionnaires for Postpartum Women
Bibliographic record
Abstract
BACKGROUND: Maintaining adequate physical activity (PA) is essential for recovery and long-term health in postpartum women undergoing physical therapy and rehabilitation. However, no self-report measure has been specifically developed for these women, and selecting appropriate existing tools available for postpartum PA monitoring remains challenging. This study aimed to evaluate the suitability of commonly used PA questionnaires by comparing their outcomes with objective activity data from a wearable tracker. METHODS: This quantitative cross-sectional observational study examined the relationship between self-reported and objectively measured physical activity. Twenty-three postpartum women (average 5 months postpartum) participating in rehabilitation were recruited. Three 7-day recall PA questionnaires were administered: the International Physical Activity Questionnaire - Short Form (IPAQ-SF), the Kaiser Physical Activity Survey (KPAS), and the Pregnancy Physical Activity Questionnaire (PPAQ). Objective PA data (daily step count and distance) were concurrently collected over a two-week period using the AmazFit Band 5 Fitness Tracker, with only the second week in the analysis. RESULTS: The IPAQ-SF showed moderate-to-strong correlations with both average daily step count (r = 0.781, p < 0.001) and distance (r = 0.783, p < 0.001). In contrast, the PPAQ (r = 0.708, p < 0.001) and KPAS (r = 0.645, p < 0.01) correlated significantly only with their respective sports activity subcomponents. CONCLUSIONS: Among the assessed tools, the IPAQ-SF demonstrated the strongest alignment with objective activity metrics, making it a more suitable option for assessing total PA in postpartum women. However, the PPAQ and KPAS provided valuable insights into specific components of PA, particularly household chores and caregiving tasks, which are highly informative during the postpartum period.
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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 | 0.008 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".