Factors influencing participation and regular attendance in a program combining physical activity and nutritional advice for overweight and obese pregnant women
Bibliographic record
Abstract
BACKGROUND: Educational programs incorporating physical activity (PA) sessions and nutritional workshops have demonstrated potential benefits for overweight and obese pregnant women. However, participation in such programs remains challenging. This prospective study aimed to investigate the factors influencing participation and regular attendance, while examining changes in health behaviors, along with obstetric and neonatal outcomes. METHODS: Pregnant women with at 12-22 weeks' gestation a BMI ≥ 25 kg/m2 were invited to join an educational program combining three nutritional workshops conducted in groups and 12 weekly PA sessions. They self-selected their participation into the program. Regardless of program uptake and regularity of attendance, the women's PA levels, eating behaviors, and affectivity were assessed using validated questionnaires at 20-24 weeks, 32-34 weeks, and postpartum. A multivariable logistic regression model was used to determine the factors influencing participation. RESULTS: Of the 187 women enrolled in the study, 61.5% agreed to participate in the program. Of these, only 45% attended six or more sessions (regardless of the nature of sessions, i.e. nutritional workshops and/or PA sessions), while only 8.7% attended six or more PA sessions. Participation was associated with higher rates of problematic eating behaviors and lower PA levels at baseline, while regular attendance was mainly associated with higher household incomes. No significant difference was observed between participants and non-participants in terms of changes in eating behaviors, PA levels, or affectivity. However, at the 32-34 week visit, regular participants displayed a higher change in positive affectivity, but unexpectedly also in cognitive restraint, than non-regular participants, a difference that did not persist at postpartum. CONCLUSION: The educational program combining nutrition and PA was shown to be safe. Women facing challenges related to health behavior displayed a willingness to sign up for the program, but tailored interventions addressing their individual challenges are needed to improve attendance. Accordingly, four recommendations are proposed for the design of future interventions. TRIAL REGISTRATION: ClinicalTrials.gov; Identifier: NCT02701426; date of first registration: 08/03/2016.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".