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Menopause experiences of women in rural areas

2008· article· en· W2124345893 on OpenAlexaffabout
Sheri Price, Sandra Storey, Margaret Lake

Bibliographic record

VenueJournal of Advanced Nursing · 2008
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsNova Scotia Health AuthorityIzaak Walton Killam Health Centre
Fundersnot available
KeywordsMenopauseThematic analysisFocus groupGerontologyCoping (psychology)Mental healthRural areaSocial supportMedicinePsychologyQualitative researchNursingSocial psychologyClinical psychologyPsychiatrySociology

Abstract

fetched live from OpenAlex

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.

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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.357
Threshold uncertainty score0.300

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 head0.027
GPT teacher head0.349
Teacher spread0.322 · 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 designQualitative
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

Citations37
Published2008
Admission routes2
Has abstractyes

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