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Record W1965204659 · doi:10.1155/2014/958524

Association between Disease‐Specific Quality of Life and Complementary Medicine Use in Patients with Rhinitis in Taiwan: A Cross‐Sectional Survey Study

2014· article· en· W1965204659 on OpenAlexaff
Malcolm Koo, Kai‐Li Liang, Rong‐San Jiang, Hsin Tsao, Yueh‐Chiao Yeh

Bibliographic record

VenueEvidence-based Complementary and Alternative Medicine · 2014
Typearticle
Languageen
FieldMedicine
TopicAllergic Rhinitis and Sensitization
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsCross-sectional studyMedicineAssociation (psychology)Family medicineDiseaseEnvironmental healthQuality of life (healthcare)PsychologyInternal medicinePathology

Abstract

fetched live from OpenAlex

Rhinitis is a common medical condition and can seriously impact patients' quality of life. The objective of this study was to investigate the association between disease-specific quality of life and use of complementary and alternative medicine (CAM) modalities among Taiwanese rhinitis patients. A cross-sectional survey was undertaken at the outpatient department of otolaryngology in a medical center in Taiwan. Sociodemographic information, disease-specific quality of life (Chinese version of the 31-item Rhinosinusitis Outcome Measure, CRSOM-31), and previous use of CAM modalities for treatment of rhinitis of the patients were ascertained. Factor analysis was performed to reduce the number of CAM modalities. The resulting factors were analyzed for their association with CRSOM-31 score using linear regression analyses. Results from the multiple linear regression analyses indicated that Factor 1 (traditional Chinese medicine), Factor 2 (mind-body modalities), Factor 3 (manipulative-based modalities), female sex, and smoking were significantly associated with a worse disease-specific quality of life. In conclusion, various CAM modalities, female sex, and smoking were independent predictors of a worse disease-specific quality of life in Taiwanese patients with rhinitis.

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)0.003
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 score0.024
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.167
GPT teacher head0.362
Teacher spread0.195 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueEvidence-based Complementary and Alternative MedicineSame topicAllergic Rhinitis and SensitizationFrench-language works237,207