A Prospective Examination of Exercise and Barrier Self-efficacy to Engage in Leisure-Time Physical Activity During Pregnancy
Bibliographic record
Abstract
BACKGROUND: Pregnant women without medical contraindications should accumulate 30 min of moderate exercise on most days of the week, yet many pregnant women do not exercise at recommended levels. PURPOSE: The purpose the study was to examine barriers to leisure-time physical activity (LTPA) and investigate barrier and exercise self-efficacy as predictors of self-reported LTPA during pregnancy. METHODS: Pregnant women (n = 160) completed questionnaires eliciting barriers to LTPA, measures of exercise and barrier self-efficacy, and 6-week LTPA recall at gestational weeks 18, 24, 30, and 36. RESULTS: A total of 1,168 barriers were content-analyzed, yielding nine major themes including fatigue, time constraints, and physical limitations. Exercise self-efficacy predicted LTPA from gestational weeks 18 to 24 (beta = 0.32, R(2) = 0.26) and weeks 30 to 36 (beta = 0.41, R(2) = 0.37), while barrier self-efficacy predicted LTPA from weeks 24 to 30 (beta = 0.40, R(2) = 0.32). CONCLUSIONS: Pregnant women face numerous barriers to LTPA during pregnancy, the nature of which may change substantially over the course of pregnancy. Higher levels of self-efficacy to exercise and to overcome exercise barriers are associated with greater LTPA during pregnancy. Research and interventions to understand and promote LTPA during pregnancy should explore the dynamic nature of exercise barriers and foster women's confidence to overcome physical activity barriers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".