Women's Satisfaction with Their Involvement in Health Care Decisions During a High‐Risk Pregnancy
Bibliographic record
Abstract
BACKGROUND: Increasingly, women seek involvement in decisions about their health care. The purpose of this study was to examine women's experience of, and satisfaction with, their involvement in health care decisions during a high-risk pregnancy. METHODS: Forty-seven women with hypertension or threatened preterm delivery (including multiple births) were interviewed after the birth of their child. They received prenatal care at home from nurses in a community program or were hospitalized. The in-depth interviews were audiotaped and transcribed; data were analyzed using constant comparative methods. RESULTS: Women identified an increased feeling of responsibility for the health of their baby and themselves, but differed in choosing active or passive involvement in health care decisions. Women who wanted active involvement achieved it through one of three processes: struggling for, negotiating, or being encouraged. Women who wanted passive involvement and women facing health crises used the process of trusting in the expertise of nurses and physicians. Women were satisfied if the care from health care professionals was congruent with how they wanted to be involved in decision-making. CONCLUSIONS: Although most women want to be actively involved in health decision-making during a high-risk pregnancy, some prefer a passive role. The setting of prenatal care, community-based or in-hospital, was less important than the ability of nurses and physicians to support the woman in her preferred role in decision-making.
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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 | 0.004 | 0.017 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".