MétaCan
Menu
Back to cohort
Record W108944037

Hepatitis B knowledge and practices among Chinese immigrants to the United States.

2006· article· en· W108944037 on OpenAlexaff
Vicky Taylor, Shin Ping Tu, Erica Woodall, Elizabeth Acorda, Hueifang Chen, John H. Choe, Lin Li, Yutaka Yasui, T. Gregory Hislop

Bibliographic record

VenuePubMed · 2006
Typearticle
Languageen
FieldMedicine
TopicHepatitis B Virus Studies
Canadian institutionsUniversity of British ColumbiaUniversity of AlbertaBC Cancer Agency
Fundersnot available
KeywordsMedicineHepatitis BCarriageHepatitis B virusTransmission (telecommunications)Chinese americansImmigrationEthnic groupDemographyFamily medicineImmunologyVirusPathology
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Chinese immigrants to the United States experience high rates of liver cancer. Chronic carriage of hepatitis B virus (HBV) is the most common underlying cause of liver cancer among Chinese Americans. Our objective was to describe Chinese immigrants' hepatitis B knowledge, testing, and vaccination levels. METHODS: A community-based, in-person survey of Chinese men and women was conducted in Seattle during 2005. Our study sample included 395 individuals. RESULTS: Less than one-half (48%) of our study group indicated they had received a hepatitis B blood test, and about one-third (31%) indicated they had been vaccinated against hepatitis B. The proportions of respondents who knew HBV can be spread during childbirth, during sexual intercourse, and by sharing razors were 70%, 54%, and 55%, respectively. Less than one-quarter of the study group knew that HBV cannot be spread by eating food that was prepared by an infected person (23%) and by sharing eating utensils with an infected person (16%). DISCUSSION: Over 50% of our respondents did not recall being tested for HBV. Important knowledge deficits about routes of hepatitis B transmission were identified. Continued efforts should be made to develop and implement hepatitis B educational campaigns for Chinese immigrant communities.

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)0.000
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 score0.077
Threshold uncertainty score0.888

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.282
Teacher spread0.261 · 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

Citations101
Published2006
Admission routes1
Has abstractyes

Explore more

Same venuePubMedSame topicHepatitis B Virus StudiesFrench-language works237,207