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Record W2033826262 · doi:10.1016/j.jmwh.2009.10.015

The Use of Complementary and Alternative Medicines Among a Sample of Canadian Menopausal‐Aged Women

2010· article· en· W2033826262 on OpenAlexaffabout
Carole Lunny, Shawn N. Fraser

Bibliographic record

VenueJournal of Midwifery & Women s Health · 2010
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsAthabasca University
Fundersnot available
KeywordsMedicineAlternative medicineMenopauseQuality of life (healthcare)Family medicineMeditationPopulationDemographicsGerontologyTraditional medicineInternal medicineDemographyNursingEnvironmental health

Abstract

fetched live from OpenAlex

INTRODUCTION: Despite questionable efficacy and safety, many women use a variety of complementary and alternative medicine (CAM) therapies to relieve menopause symptoms. METHODS: We examined the determinants and use of CAM therapies among a sample of menopausal-aged women in Canada by using a cross-sectional Web-based survey. RESULTS: Four hundred twenty-three women who were contacted through list serves, e-mail lists, and Internet advertisements provided complete data on demographics, use of CAM, therapies, and menopausal status and symptoms. Ninety-one percent of women reported trying CAM therapies for their symptoms. Women reported using an average of five kinds of CAM therapies. The most common treatments were vitamins (61.5%), relaxation techniques (57.0%), yoga/meditation (37.6%), soy products (37.4%), and prayer (35.7%). The most beneficial CAM therapies reported were prayer/spiritual healing, relaxation techniques, counseling/therapy, and therapeutic touch/Reiki. Demographic factors and menopausal symptoms contributed to 14% of the variance (P < .001) in the number of CAM therapies tried. DISCUSSION: Results support previous research showing that menopausal women have high user rates of CAM therapy and show that specific demographic factors and somatic symptomatology relate to use of CAM therapies. Health care providers can benefit from understanding the determinants and use of CAM by women during the menopause transition if they are to help and provide quality care for this population.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.114
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.067
GPT teacher head0.338
Teacher spread0.271 · 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 designObservational
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

Citations60
Published2010
Admission routes2
Has abstractyes

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