Obstetrician, Family Physician, or Midwife: Preferences of the Next Generation of Maternity Care Consumers
Bibliographic record
Abstract
Objective: The purpose of this study was to identify the views of a cohort of Canadian university students related to maternity care provider preferences and the reasons for these preferences. Relationships between care provider preferences, childbirth attitudes, and desire for epidural anesthesia and cesarean section (CS) were also examined. Methods: This was a large cross-sectional survey (N = 3,680) of male and female university students at the University of British Columbia (male, 991; female, 2,676). Students were invited to participate via an electronic letter of invitation containing a link to this online survey.Results: Approximately half of all participants (51.8% for women and 43.7% for men) selected an obstetrician as one of their preferred care providers; somewhat fewer selected a family physician (40.1% for women and 32.8% for men), and even fewer selected a registered midwife (30.1% for women and 18.0% for men). Among the 11 reasons for these preferences (coded from open-ended responses), the most common were expert/specialist, safety, and quality of relationship with care provider. Attitudes toward vaginal birth as well as mode of delivery and pain management preferences were found to relate to caregiver preferences.Conclusion: Provider preferences among university students are largely driven by perceived risk, level of confidence in birth, and attitudes toward obstetric interventions. These preferences, in combination with the current shortage of maternity providers in Canada, indicate a need for restructuring maternity care human resources.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".