Menopause experiences of women in rural areas
Bibliographic record
Abstract
AIM: This paper is a report of a study to explore the menopause experiences of women living in rural areas. BACKGROUND: The menopausal phase can be physically and emotionally unsettling in a woman's life. Evidence has shown that a woman's ability to cope with the stresses of menopause can be enhanced through education and social support, yet there is a paucity of research in relation to the experiences of menopausal women in rural areas, where access to supportive services is often limited. METHOD: Naturalistic inquiry was used to explore the experiences of 25 menopausal women who were living in rural areas in Nova Scotia, Canada. Participants were interviewed in focus group and individual sessions, conducted during 2006. Verbatim transcripts of the interviews were analysed using thematic analysis. FINDINGS: Women living in rural communities described a need to understand fully the intensity of menopause-related symptoms, including changes to their physical and mental wellbeing. Participants described struggling to sift through excessive and conflicting information from a variety of venues and identified a need to receive reliable information from sources they trusted. They described the menopause experience as having a significant impact on their personal relationships and identified social support and humour as their primary coping strategies. CONCLUSION: Menopause is a significant life event affecting millions of women globally. Nurses are uniquely situated to provide comprehensive women's health care and must employ innovative strategies to provide support to women living in rural communities to enhance both health and wellbeing as they transition through menopause and as they age.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 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".