Encouraging Exercise in Pregnancy Through a Video Education Tool: A Pilot Study
Bibliographic record
Abstract
Topics in Exercise Science and Kinesiology Volume 4: Issue 1, Article 17, 2023. Evidence-based guidelines recommend physical activity during pregnancy, however, most pregnant individuals fail to achieve the minimum recommended amount of physical activity. Uncertainty about the safety of physical activity is a common reason why pregnant individuals do not participate in regular physical activity. The purpose of this study was to develop an evidence-based educational video and evaluate its effectiveness at improving pregnant individuals’ attitudes regarding the safety of physical activity during pregnancy. Pregnant individuals attending their first prenatal appointment from an urban academic interprofessional teaching unit in Toronto, Canada were invited to participate. Participants (n=37) completed a survey during their first trimester (x̄= 12.4 weeks gestation) before watching an evidence-based physical activity safety video. The cohort was then asked to complete surveys two months later in their second trimester (x̄= 22.6 weeks gestation) after watching the video. While all participants felt confident engaging in physical activity pre-intervention (100%), most participants expressed benefit from further education (80.8%). After watching the video, there was a significant difference in participants’ beliefs regarding high impact activities (p=0.03) and knowledge about physical activity amount as recommended by current guidelines (p<0.01). Overall, participants felt the video improved their knowledge about the safety of physical activity during pregnancy (90.9%) and they would recommend the video to other pregnant individuals (95.5%). The evidence-based video provided to patients early in pregnancy appears effective in reinforcing positive attitudes towards the safety of prenatal physical activity. Future studies exploring more diverse populations are needed to confirm the results of this pilot study.
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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".