Women's Hysterectomy Experiences and Decision-Making
Bibliographic record
Abstract
The goal of the study was to examine women's experiences with gynaecologic symptoms and how they decided to undergo hysterectomy. For this purpose, twenty-nine women were interviewed in hospital within three days of undergoing hysterectomy. The interviews elicited information about the nature of the problem that caused the women to seek medical help, actions taken to solve their problem, their relationship with their gynaecologist, information seeking patterns and decision-making about hysterectomy. Although findings revealed that the symptoms women suffered had a negative impact on their lives, most women delayed seeking medical help and attributed their symptoms to factors other than a physical problem in their reproductive system. Most of the participants' information about the symptoms and possible treatments came from their consulting other women with similar problems. The women reported that their gynaecologist did not initiate a comprehensive discussion about other treatments and their advantages and disadvantages. Only women who had informed themselves about other treatments actively discussed alternatives to hysterectomy with their physicians. The women's decision-making process about undergoing hysterectomy was difficult and depended primarily on the women's illness experiences, age, wish for future children, information they gathered from their gynaecologist and from other women. The findings are discussed in relation to the importance of information provision by gynaecologists and its effects on women's decision-making about hysterectomy.
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.000 | 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".