Self-reported leisure-time physical activity during pregnancy and relationship to psychological well-being
Bibliographic record
Abstract
The psychological benefits of physical exercise have been reported in numerous populations. While studies have found elevated stress and depressed mood during pregnancy and no adverse birth effects associated with low to moderate intensity exercise, few have examined exercise in relation to psychosocial outcomes during pregnancy. The present study examined leisure-time physical activity (LTPA) patterns during pregnancy and its association to psychological well-being. In each trimester of pregnancy 180 women self-reported on frequency, form and duration of LTPA through structured interviews. Beginning in the third month of pregnancy, data was collected monthly on depressed mood (Lubin depression adjective checklist), state-anxiety, pregnancy-specific stress (pregnancy experiences questionnaire) and Hassles Scale. Independent samples t-tests comparing exercisers and non-exercisers in each trimester showed exercisers reported significantly less depressed mood, daily hassles, state-anxiety and pregnancy-specific stress in the first and second trimester. Women who exercised in the third trimester reported less state-anxiety in that trimester compared to non-exercisers. The results indicate a consistent association between enhanced psychological well-being, as measured by a variety of psychosocial inventories, and LTPA participation particularly during the first and second trimesters of pregnancy. In healthy pregnant women, even low-intensity regular exercise may be a potentially effective low-cost method of enhancing psychological well-being.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".