PL.33 Can We Improve Women’s Operative Vaginal Birth Experience?
Bibliographic record
Abstract
Background Obstetric practise is emotive, challenging and has long term impact both in terms of delivering new life but also for the mother where much of her experience occurs in labour and delivery. Aim of this study To investigate the non-technical skills for operative vaginal delivery that have an impact on women’s birth experience when having an OVD. Method Sixteen women who had an OVD of a term baby underwent a semi structured interview 6–8 weeks postnatal. The interview recordings were transcribed verbatim. Thematic coding of data was carried out. Consistency of interpretation was ascertained by two researchers. Results One of the key themes identified by women was a ‘feeling of loss of control’ and a ‘need for explanation’ of events to enable empowerment and reinforce control back to the woman. Women reported that ‘loss of control is very worrying and overwhelming’. This want of ownership to the process of operative delivery is further highlighted by the ‘need for partnership between the healthcare provider and the woman’, ‘enabling autonomy’ and ‘avoiding a paternalistic relationship’. Greater information for OVD in antenatal classes was suggested in order to counteract a common theme of negative perceptions of an operative delivery. Conclusion Vulnerability of the women’s feelings highlights the importance of non technical skills in ensuring a woman feels trust, is empowered and in control. These non-technical skills need to be taught, learnt and practised to ensure a woman’s experience if safe, positive and pays justice to the delight of having a child.
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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 | 0.002 | 0.008 |
| 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 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.026 | 0.003 |
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".