Women's perceptions about seeing the ultrasound picture before an abortion
Bibliographic record
Abstract
OBJECTIVES: To gain a better understanding of women's perceptions and experiences of viewing the ultrasound (US) before an abortion. METHODS: This mixed-methods study included questionnaires and interviews. Women presenting for medical and surgical abortion at two urban abortion clinics completed questionnaires asking if they wished to view the US image and those women who had done so answered questions about their perceptions. A randomly selected ten women were interviewed six weeks later about their perceptions. The interviews were audio-taped, transcribed and analysed for salient themes. RESULTS: The 350 participants had a mean age of 27.6 years, 0.68 births, and were at a mean of 49.1 days gestation at the time of the procedure. Most women (254/350, 72.6%) chose to view the US and 179/219 (86.3%) found it a positive experience. Older women and those who had children were less likely to want to view the US image (p = 0.001). All ten interviewees recommended that this choice be offered to every woman and recommended more communication between care providers and patients at the time of the US. None of the women changed her mind about having the abortion after having seen the US. CONCLUSIONS: Offering the choice to view the ultrasound is both feasible and beneficial to women having abortions. Our findings support those of the only other study published on the subject.
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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 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| 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".