Knowledge translation tool to improve pregnant women’s awareness of gestational weight gain goals and risks of gaining outside recommendations: a non-randomized intervention study
Bibliographic record
Abstract
BACKGROUND: There is an urgent need to prevent excessive pregnancy weight gain, a contributor to both maternal and child obesity. However, the majority of women had reported not being counseled to gain an appropriate amount of gestational weight by their health care providers. We developed a knowledge translation (KT) tool designed to facilitate the clinical interaction between pregnant women and their health care providers (HCPs). We piloted the tool on the impact on women's knowledge of gestational weight gain (GWG) goals, and evaluated its potential in promoting appropriate knowledge about GWG within the 2009 Institute of Medicine guidelines. METHODS: We conducted a prospective cohort study, comparing women's knowledge about GWG after the KT tool to women from the same clinics and care providers the year prior. Our primary outcome was the proportion of women who reported receiving an appropriate GWG recommendation from their care provider. We evaluated knowledge on a survey conducted at enrollment in the cohort at ≤ 20 weeks gestation and evaluated participant satisfaction with the KT tool in the third trimester. We performed univariate and multivariable logistic regression analyses for differences in outcomes with historical controls from the same clinics. Our a priori sample size calculation required 130 participants to demonstrate a 15% increase in reported counseling about gestational weight gain. RESULTS: One hundred and forty-six women were recruited and 131 (90%) completed the enrollment survey. Women who received the KT tool were more likely to report receiving a specific GWG recommendation from their HCP (adjusted odds ratio [AOR] 3.45, 95% confidence interval [CI] 2.22-5.37) and discussing GWG topics with their HCP (AOR 7.96, 95% CI 4.41-14.37), and believing that there were risks to their infants with inadequate GWG (AOR 2.48, 95% CI 1.14-5.37). Half of women (49.5%) indicated that they would recommend the tool to a friend. CONCLUSIONS: Women who received the KT tool reported receiving more counseling on GWG from their HCPs and were more aware of the risks of gaining outside appropriate GWG recommendations. The association between GWG education and GWG requires further research.
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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 | 0.009 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".