Use of the Pregnancy Physical Activity Questionnaire (PPAQ) to Identify Behaviors Associated With Appropriate Gestational Weight Gain During Pregnancy
Bibliographic record
Abstract
BACKGROUND: The Pregnancy Physical Activity Questionnaire (PPAQ) assesses physical activity practices of pregnant women. The purpose of this study was to identify specific pregnancy practices that were associated with a healthy gestational weight gain (GWG). METHODS: Associations between PPAQ scores, pedometer steps, energy intakes (EI), energy expenditures (EE), and rate of GWG were assessed for 61 pregnant women in their second or third trimester during a home visit. Principle component analyses (PCA) were used to cluster PPAQ questions into FACTORS associated with either rate or total GWG, physical activity (PA), EE, EI, and parity. RESULTS: PCA identified 3 FACTORS: Factor 1 associated EE with parity and child care; Factor 2 clustered several structured exercise activities; and Factor 3 grouped walking, playing with pets, and shopping with pedometer steps. Only Factor 3 clustered steps with weekly rate of GWG. EI was not associated with PA or GWG. CONCLUSIONS: PCA analysis identified 15 of 32 PPAQ questions that were related to increased physical activity in pregnant women, but only walking and pedometer steps were associated with GWG. Our analysis supports daily walking as the preferred PA for achieving a healthy rate of GWG.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 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".