Women prefer proactive support from providers for treatment of heavy menstrual bleeding: A qualitative study in adult women with moderate or severe Von Willebrand disease
Bibliographic record
Abstract
OBJECTIVE: To explore key factors for successful support in women with moderate or severe Von Willebrand disease (VWD) who are faced with heavy menstrual bleeding (HMB) and surgery. DESIGN: A qualitative study design with focus-group interviews and thematic analysis of the discussions. SETTINGS AND POPULATION: Eleven VWD women aged 41-68 years (median age 58 years) who had had a hysterectomy or bipolar radiofrequency ablation (BRA) because of HMB participated in this study. Three of the 11 participants had VWD diagnosed before surgery. Two focus groups were conducted in the summer of 2012. Patients were identified through participation in a nationwide study on Von Willebrand disease in the Netherlands (WiN study). Inclusion criteria were at least 18 years of age, fluent in Dutch, diagnosed with VWD (based on Von Willebrand factor (VWF) antigen and/or activity levels < 30 IU/dL) and previous surgical therapy for HMB. FINDINGS: The following key factors were identified during focus-group interviews: receiving information, proactive support from providers and considering bleeding disorders as a cause of HMB. Other topics were as follows: experiences with VWD and/or surgery, how relieved patients were when menses stopped, patients hoped that in future, providers would work better together so that women receive the best care. CONCLUSIONS: In this focus-group study among women with VWD who underwent surgery because of HMB, support by professionals could be improved by considering a bleeding disorder in women with HMB, providing information about different types of surgery and shared decision-making regarding type of interventions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".