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Record W3111622221 · doi:10.1080/13548506.2020.1856896

Health related quality of life and its impacts by chronic diseases in urban community population, Shanghai, China in 2015

2020· article· en· W3111622221 on OpenAlexaff
Rui Chang, Xiaolin Qian, Zeliang Xuan, Yingsheng Xu, Yue Chen, Haiyan Gu, Chaowei Fu

Bibliographic record

VenuePsychology Health & Medicine · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicHealth Systems, Economic Evaluations, Quality of Life
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsMedicineEQ-5DQuality of life (healthcare)Chronic diseaseVisual analogue scaleChinaDiabetes mellitusDemographyDiseaseHealth related quality of lifeCross-sectional studyPopulationGerontologyEnvironmental healthPhysical therapyInternal medicinePathology

Abstract

fetched live from OpenAlex

This survey aimed to describe the health-related quality of life (HRQoL) and to explore the relationship between chronic diseases and HRQoL among urban residents in Shanghai, China. A cross-sectional study of 9 426 adults was conducted in Xuhui District of Shanghai, China in 2015. The EuroQol five-dimension three-level (EQ-5D-3 L) was used to measure HRQoL. The average age of subjects was 55.6 ± 17.4 years and 53% were female. Their mean values of utility and visual analogue scale (VAS) were 0.974 ± 0.099 and 80.00 ± 12.36, respectively, which were above the Chinese norm values. Women had lower scores compared with men. The utility value decreased with age, which accelerated after the age of 55 years. Chronic conditions including diabetes, tumor, cardiovascular disease, and respiratory disease, were significantly related to HRQoL, and the reported proportions of problems in the five dimensions increased with the number of chronic diseases (p < 0.05). Chronic diseases except for respiratory disease had a negative effect on HRQoL utility value and VAS score after the adjustment for covariates (p < 0.05). Chronic diseases had a negative impact on both EQ-5D-3 L utility and VAS scores, although the health-related quality of life for the study was above the national average.

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)0.024
metaresearch head score (Gemma)0.009
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.405
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0240.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
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 head0.360
GPT teacher head0.514
Teacher spread0.155 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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