Co-design and clinician evaluation of resources to address weight stigma in antenatal care
Bibliographic record
Abstract
BACKGROUND: Weight stigma is a commonly reported experience in maternity care that negatively impacts the health of mothers and their babies. Knowledge to inform weight stigma reduction efforts in antenatal care is urgently required. This study aimed to co-design weight stigma reduction resources in antenatal care and evaluate clinician perspectives of the resources regarding their relevance to practice, strengths, and areas for improvement. METHODS: We conducted a five-phase co-design project involving consumers (n = 8) and clinicians (midwives n = 16, obstetrician n = 1), with outputs from each stage informing the next: (1) engaging with key stakeholders; (2) prioritising the voices of lived experience through a consumer stories video; (3) three co-design workshops to inform resource development; (4) resource production; and (5) qualitative evaluation of the resources. The co-developed resources were evaluated via interview where clinicians viewed or listened to the resources and described their engagement and satisfaction with the resources, their relevance to practice, and perspectives on the strengths, areas for improvement, and feasibility for achieving the resources' intended goal. Transcripts were analysed using descriptive thematic analysis. RESULTS: We produced a set of evidence-based resources co-designed by consumers and clinicians including a consumer video designed to elicit empathy about lived experiences of weight stigma in maternity care, images representing women with diverse body sizes for use in clinic waiting rooms, a short podcast to raise awareness of weight stigma in maternity care, and signposts for the antenatal clinic to prompt clinicians to consider weight stigma in everyday clinical interactions. Clinicians who saw the resources reported that they were valuable and relevant to practice and were important and helpful introductory materials to the issue of weight stigma. Pragmatic examples of reducing weight stigma in clinical interactions were requested. CONCLUSIONS: Maternity care clinicians have an appetite to improve their learning opportunities to tackle weight stigma in practice. Further refinement of the resources, evaluation of the effectiveness at changing clinician behaviour, and implementation into health services are logical next steps. Reducing women's experiences of weight stigma should lead to better care and better pregnancy outcomes for larger bodied women. CLINICAL TRIAL NUMBER: Not applicable.
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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 | 0.099 | 0.174 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.009 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 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".