‘It’s not me, it’s them’ – a report describing the weight-related attitudes towards obesity in pregnancy among maternal healthcare providers
Bibliographic record
Abstract
BACKGROUND: Occurrences of weight stigma have been documented in prenatal clinical settings from the perspective of pregnant patients, however little is known from the viewpoint of healthcare providers themselves. Reported experiences of weight stigma caused by maternal healthcare providers may be due to negative attitudes towards obesity in pregnancy and a lack of obesity specific education. The objective of this study was to assess weight-related attitudes and assumptions towards obesity in pregnancy among maternal healthcare providers in order to inform future interventions to mitigate weight stigma in prenatal clinical settings. METHODS: A cross-sectional survey was administered online for maternal healthcare providers in Canada that assessed weight-related attitudes and assumptions towards lifestyle behaviours in pregnancy for patients who have obesity. Participants indicated their level of agreement on a 5-point likert scale, and mean scores were calculated with higher scores indicating poorer attitudes. Participants reported whether they had observed weight stigma occur in clinical settings. Finally, participants were asked whether or not they had received obesity-specific training, and attitude scores were compared between the two groups. RESULTS: Seventy-two maternal healthcare providers (midwives, OBGYNs, residents, perinatal nurses, and family physicians) completed the survey, and 79.2% indicated that they had observed pregnant patients with obesity experience weight stigma in a clinical setting. Those who had obesity training perceived that their peers had poorer attitudes (3.7 ± 0.9) than those without training (3.1 ± 0.7; t(70) = 2.23, p = 0.029, Cohen's d = 0.86). CONCLUSIONS: Weight stigma occurs in prenatal clinical environments, and this was confirmed by maternal healthcare providers themselves. These findings support advocacy efforts to integrate weight stigma related content and mitigation strategies in medical education for health professionals, including maternal healthcare providers. Future work should include prospective examination of weight related attitudes among maternal healthcare providers and implications of obesity specific education, including strategies on mitigating weight stigma in the delivery of prenatal care.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".