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Record W1979158643 · doi:10.12927/whp.2010.21723

Use of Health Services by Women with Gynecological Symptoms in Rural China

2010· article· en· W1979158643 on OpenAlexvenueno aff
Zhen Jiang, Debin Wang, Hong Qian, Nicola Cherry, Jing Cheng, Jing Chai, Sen Yang, Xuejun Zhang

Bibliographic record

VenueWorld health & population · 2010
Typearticle
Languageen
FieldMedicine
TopicMenstrual Health and Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsChinaMedicinePublic healthHealth servicesEnvironmental healthNursingPolitical sciencePopulation

Abstract

fetched live from OpenAlex

BACKGROUND: To examine the relation between demographic factors and symptom type in the use of gynecological health services in rural China. METHODS: Married women aged 19 to 45 years from three rural communities in Anhui province, central China, were invited to participate in a structured interview in the summer of 2006. They provided information on gynecological symptoms, healthcare-seeking behaviour and socio-demographic characteristics. Risk factors were analyzed using logistic regression. RESULTS: 860/1221(70.4%) reported at least one gynecological symptom during the previous year, with 485 (39.7%) reporting three or more. Of the women with symptoms, 36.7% sought treatment during the previous year. Younger women and those with multiple symptoms were more likely than others to seek treatment. Women with abnormal vaginal bleeding or discharge were more likely to delay seeking treatment. Years of education were strongly related to seeking treatment. More highly educated women and women with a higher household income were more likely than others to seek treatment at the highest level (county or city hospital) of the tertiary healthcare system rather than at a village clinic or township hospital. Women who did not seek treatment were more likely to report that they saw no need than to say that they could not afford care. CONCLUSION: There may be a misperception of the need for, and utility of, treatment for gynecological symptoms, particularly in more disadvantaged women. Interventions should both address women's negative perceptions and reinforce the capacity of the local health facilities to ensure effective care.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.062
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.015
GPT teacher head0.318
Teacher spread0.302 · 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

Citations1
Published2010
Admission routes1
Has abstractyes

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