The Expectations of Low and High Risk Pregnant Women Who Seeking Obstetrical Care in a Highly Specialized Hospital
Bibliographic record
Abstract
Background: In the context of a highly specialized hospital, birth care might be is expected to be more medicalized and technocratic for both low and high risk pregnant women.Objective: This study aimed to explore the expectation of low and high risk pregnant women who seeking an obstetrical care in a highly specialized hospital.Methods: A single case study design was chosen for this study. The case under study was a tertiary and university affiliated hospital in Montreal, Canada. The data were collected through semi-structured interviews, field notes, participant observations and self-administered questionnaire. An inductive qualitative content analysis was used.Results: As a whole 157 women were participated in the study. The analysis of data showed that both high and low risk women felt more satisfied with the care they received if they were provided with informed choices, had the right to participate in the decision-making process and were surrounded by competent care providers and obstetric technology. The presence of an attentive care provider during labour who humanly cared for women and her family considered as essential component of birth care by women participant.Conclusion: A birth care provider in a tertiary hospital setting should aim to meet both physiological and psychological aspects of birth care, including respect of the fears, beliefs, values, and needs of women and their families. Integration of competent and caring professionals, as well as the use of obstetric technology, could enhance the level of certainty and assurance in both high-risk and low risk women in a tertiary hospital.
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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 | 0.003 | 0.011 |
| 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 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".