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Record W2939515678

Prevalence and severity of menopausal symptoms among menopausal women, Babol, Iran

2017· article· en· W2939515678 on OpenAlexaff
Sorayya Mohammadzadeh, Zeinab Hedayati, Niloufar Ahmadi, Fatemeh Bayyani, Sepideh Mashayekh‐Amiri

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2017
Typearticle
Languageen
FieldHealth Professions
TopicHealth and Wellbeing Research
Canadian institutionsEagle Ridge Hospital
Fundersnot available
KeywordsMedicineMenopauseObstetricsGynecologyInternal medicine
DOInot available

Abstract

fetched live from OpenAlex

Background: Understanding prevalence of various menopausal symptoms and symptom severity in Iran will enhance reproductive health care. The aim of the study was to determine the prevalence and severity of menopausal symptoms among menopausal women in Babol, Iran. Methods: A cross sectional study was conducted on the 150 healthy postmenopausal women aged between 45–65 years in Babol city (located in Northern Iran), and cluster sampling was used as a method of sampling. The questionnaires used in this study include: symptom score card for measuring the frequency and severity of menopausal symptoms and socio demographic data. Results: The mean ± SD age at natural menopause was 48.5 ± 4.1 years. The most prevalent symptoms were back pain and joint pain (48.7%), anxiety and unusual tiredness (48.0%), irritability (46.7%), muscle pains (44.0%) and hot flashes (42.7%). The average overall symptom score card in the study for menopausal symptoms was 22.1 ± 9.8. The severity of symptoms was in the range of mild to moderate in 42% of samples, and 58% of samples had moderate to severe symptoms. Conclusion: This study showed that more than half of the women had moderate to severe menopausal symptoms and an earlier mean age of menopause (48.5 y) for women in Babol, Iran.

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)0.008
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0080.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0030.001
Scholarly communication0.0010.003
Open science0.0040.003
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0110.000

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 head0.292
GPT teacher head0.629
Teacher spread0.337 · 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.

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

Citations2
Published2017
Admission routes1
Has abstractyes

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