Healthcare providers’ gestational weight gain counselling practises and the influence of knowledge and attitudes: a cross-sectional mixed methods study
Bibliographic record
Abstract
OBJECTIVE: To understand current gestational weight gain (GWG) counselling practices of healthcare providers, and the relationships between practices, knowledge and attitudes. DESIGN: Concurrent mixed methods with data integration: cross-sectional survey and semistructured interviews. PARTICIPANTS: Prenatal healthcare providers in Canada: general practitioners, obstetricians, midwives, nurse practitioners and registered nurses in primary care settings. RESULTS: Typically, GWG information was provided early in pregnancy, but not discussed again unless there was a concern. Few routinely provided women with individualised GWG advice (21%), rate of GWG (16%) or discussed the risks of inappropriate GWG to mother and baby (20% and 19%). More routinely discussed physical activity (46%) and food requirements (28%); midwives did these two activities more frequently than all other disciplines (P<0.001). Midwives interviewed noted a focus on overall wellness instead of weight, and had longer appointment times which allowed them to provide more in-depth counselling. Regression results identified that the higher priority level that healthcare providers place on GWG, the more likely they were to report providing GWG advice and discussing risks of GWG outside recommendations (β=0.71, P<0.001) and discussing physical activity and food requirements (β=0.341, P<0.001). Interview data linked the priority level of GWG to length of appointments, financial compensation methods for healthcare providers and the midwifery versus medical model of care. CONCLUSIONS: Interventions for healthcare providers to enhance GWG counselling practices should consider the range of factors that influence the priority level healthcare providers place on GWG counselling.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.002 |
| 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) | 0.000 | 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 teacher head, 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".