Perspectives and decision-making about menopausal therapies in women who had bilateral oophorectomy
Bibliographic record
Abstract
OBJECTIVE: The aim of the study was to explore the process of decision-making about menopausal treatments in women who have had surgical menopause as a result of bilateral oophorectomy (≤50 y). METHODS: We used a descriptive qualitative research design. Women who had a surgical menopause were purposefully selected from the Edmonton Menopause Clinics. Focus groups were held, each with six to nine participants. All sessions were audio-recorded and transcribed verbatim. Data were analyzed using qualitative content analysis. RESULTS: We conducted five focus groups from June 30 to July 21, 2016 (N = 37). One-third of the women had the surgery within the last 5 years. Almost all women had a concurrent hysterectomy (97%) and were current users of hormone therapy (70%). Four main themes identified were "perceptions of surgical menopause," "perceptions of received support," "being my own advocate," and "concept of adequate support." Women shared that the experience was worse than their expectations and did not believe they were given adequate support to prepare them to make therapy decisions. Women had to "be their own advocates" and seek support from within the healthcare system and outside to cope with their health issues. To make an informed decision about treatments postsurgery, women expressed a need to learn more about the symptoms of surgical menopause, treatment options, resources, avenues for support, and stories of similar experiences, preferably before the surgery. CONCLUSIONS: We identified several modifiable deterrents to decision-making in early surgical menopause which can help inform the development of a patient decision aid for this context.
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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 | 0.007 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".