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Record W2016999450 · doi:10.1300/j013v38n01_04

Women's Hysterectomy Experiences and Decision-Making

2003· article· en· W2016999450 on OpenAlexaff
Ayşe K. Üskül, Farah Ahmad, Nicholas Leyland, Donna E. Stewart

Bibliographic record

VenueWomen & Health · 2003
Typearticle
Languageen
FieldMedicine
TopicUterine Myomas and Treatments
Canadian institutionsUniversity Health NetworkUniversity of TorontoYork University
Fundersnot available
KeywordsHysterectomyMedicineGynecologyMedical informationFamily medicineObstetricsSurgery

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.671
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.018
GPT teacher head0.323
Teacher spread0.305 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designOther design
Domainnot available
GenreEmpirical

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".

Quick stats

Citations23
Published2003
Admission routes1
Has abstractyes

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