How Did Participating in a Prenatal Nutrition and Exercise Program Influence Postpartum Behaviour During COVID-19?
Bibliographic record
Abstract
Lifestyle interventions focusing on prenatal physical activity (PA) and healthy nutritional habits can carry forward into the postpartum period. As many health resources, like PA facilities and postpartum support groups, were inaccessible due to the Coronavirus-19 (COVID-19) pandemic restrictions, it may be plausible that individuals who participated in a prenatal lifestyle intervention continued engaging in positive health behaviours on their own. This study explored experiences of postpartum individuals during the pandemic who had engaged in a prenatal PA and nutrition program prior to COVID-19. Semi-structured interviews were completed with postpartum individuals following a qualitative description approach. The study objectives were to identify and summarize the impact of the COVID-19 pandemic on PA and nutritional behaviours postpartum, and the role of previous participation in a prenatal lifestyle intervention, pre-pandemic, on PA and nutritional habits during postpartum quarantine restrictions. Thirteen participants completed interviews and reported that overall, PA levels stayed the same however, there was a change in PA type, as walking became the prominent choice of PA. Diet became more limited and involved a great deal of meal planning. Participation in a prenatal lifestyle intervention prior to the pandemic positively impacted PA and nutritional habits postpartum during COVID-19 restrictions. Specifically, it enabled individuals to implement walking as a daily PA habit and encouraged important concepts such as mindful eating and meal planning. Prenatal lifestyle interventions can be beneficial in establishing healthy postpartum habits, even during pandemic restrictions.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".