High maternal self-efficacy is associated with meeting Institute of Medicine gestational weight gain recommendations
Bibliographic record
Abstract
OBJECTIVE: Fetal exposure to an intrauterine environment affected by maternal obesity and excessive gestational weight gain increases the likelihood of infants born large for gestational age and childhood obesity. This study examined behavioural factors and lifestyle practices associated with women's perceived attainability of meeting the 2009 Institute of Medicine (IOM) weight gain guidelines. METHODS: Cross-sectional data were collected from pregnant (n = 320) and postpartum (n = 1179) women who responded to the validated Canadian Electronic Maternal (EMat) health survey. Consenting women completed the survey through REDCap™ a secure, web-based data capture platform. Multiple logistic regression analyses were used to evaluate correlates associated with meeting or not meeting IOM recommendations. Odds ratios (ORs) were adjusted for relevant behavioural and sociodemographic covariates. RESULTS: There were no significant differences between adjusted and unadjusted ORs for self-efficacy, barriers, and facilitators to weight gain during pregnancy. Women who reported worry regarding weight gain were significantly less likely to meet IOM guidelines (OR = 0.48, 95% CI = 0.33-0.69). Perceived controllability of behaviour was significantly associated with meeting IOM guidelines. An internal locus of control for weight gain was associated with an increased odds of meeting guidelines when women perceived to be in control of their weight gain (OR = 1.75, 95% CI = 1.29-2.37), healthy and exercised (OR = 1.91, 95% CI = 1.34-2.71), and when no barriers to healthy weight gain were perceived (OR = 1.43, 95% CI = 1.04-1.95); whereas, an external locus of control in which women viewed weight gain as beyond their control, was associated with a significantly reduced odds of achieving guidelines (OR = 0.58, 95% CI = 0.39-0.88). CONCLUSIONS: Self-efficacy and perceived controllability of behaviour are key factors to consider when developing pregnancy-specific interventions to help women achieve guideline-concordant weight gain and ensure the downstream health of both mother and infant.
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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 | 0.010 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".