A survey of health care practitioners’ attitudes toward shared decision‐making for choice of next birth after cesarean
Bibliographic record
Abstract
BACKGROUND: Patients with a history of cesarean may benefit from shared decision-making (SDM) interventions, such as patient decision aids, that provide individualized clinical information and help to clarify personal preferences. We sought to understand the factors that influence how care practitioners support choices for mode of birth and what individual and health system factors influence uptake of SDM in routine care. METHODS: We conducted a cross-sectional survey of health care practitioners in British Columbia, Canada (2016-2017). Participants included family physicians, midwives, obstetricians, and registered nurses. We conducted descriptive and inferential analyses of quantitative data and subjected the open-ended survey responses to thematic analysis. RESULTS: Analysis of survey responses (n = 307) suggested there was no significant association between the size of the participant hospital and their medico-legal concerns about mode of birth. Environmental factors that may influence the use of SDM included the length of time it takes to initiate an emergency cesarean and the timing of when the SDM intervention is introduced to the patient. No participants reported protocols prohibiting VBAC at their hospital. Participants preferred an SDM approach where the pregnant person is involved in making the final decision for mode of birth. CONCLUSIONS: Although maternity care practitioners express attitudes and behaviors that may support SDM for mode of birth after cesarean, implementing SDM using a patient decision aid alone may be challenging because of environmental factors. Our study demonstrates how survey data can aid in identifying how, when, where, for whom, and why an SDM intervention could be implemented.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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".