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Hepatitis B screening among Chinese Americans: a structural equation modeling analysis

Overview of attention for article published in BMC Infectious Diseases, March 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (59th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

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4 tweeters
facebook
1 Facebook page

Citations

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14 Dimensions

Readers on

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79 Mendeley
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Title
Hepatitis B screening among Chinese Americans: a structural equation modeling analysis
Published in
BMC Infectious Diseases, March 2015
DOI 10.1186/s12879-015-0854-7
Pubmed ID
Authors

Grace X Ma, Guo Yolanda Zhang, Shumenghui Zhai, Xiang Ma, Yin Tan, Steven E Shive, Min Qi Wang

Abstract

Hepatitis B Virus (HBV) disproportionately affects new immigrants from endemic regions such as China. Untreated infections increase health risks for liver diseases including cancer. Yet most of those infected are unaware of their disease limiting prevention and early treatment options. The purpose of this community based study was to evaluate a heuristic model identifying factors contributing to Hepatitis B (HBV) screening among Chinese Americans. A cross-sectional design included a sample of 924 Chinese men and women 18 years of age and older of which 718 had complete data for final analysis. Confirmatory factor analysis verified conceptual indicators including access/satisfaction with health care and enabling, predisposing, cultural, and health belief factors. Structural equation modeling was used to identify direct and indirect predictors of Hepatitis B screening. Bivariate analysis revealed that Chinese respondents who were never screened for HBV were significantly more likely to be below age 40 (69.8%), male (69.2%), had less than a high school education (76.4%), with less than 6 years living in the US (72.8%) and had no health insurance (79.2%). The final model identified enabling factors (having health insurance, a primary health care provider to go to when sick and more frequent visits to a doctor in the last year) as the strongest predictor of HBV screening (coefficient = 0.470, t = 7.618, p < .001). Predisposing factors (education variables) were also significantly related to HBV screening. Cultural factors and Satisfaction with Health care were associated with HBV screening only through their significant relationships with enabling factors. The tested theoretical model shows promise in predicting HBV testing among Chinese Americans. Increasing access to health care by expanding insurance options and improving culturally sensitivity in health systems are critical to reach new immigrants like Chinese for HBV screening. Yet such strategies are consistent with DHHS Action plan for the Prevention and Treatment of Viral Hepatitis. Implementing community-based strategies like partnering with relevant Community-Based Organizations are important for meeting HBV policy targets.

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 79 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 79 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 16%
Student > Bachelor 12 15%
Student > Doctoral Student 9 11%
Student > Master 9 11%
Student > Ph. D. Student 7 9%
Other 5 6%
Unknown 24 30%
Readers by discipline Count As %
Medicine and Dentistry 17 22%
Nursing and Health Professions 11 14%
Social Sciences 10 13%
Economics, Econometrics and Finance 5 6%
Psychology 5 6%
Other 5 6%
Unknown 26 33%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 March 2015.
All research outputs
#1,950,023
of 4,888,304 outputs
Outputs from BMC Infectious Diseases
#875
of 2,628 outputs
Outputs of similar age
#56,738
of 146,154 outputs
Outputs of similar age from BMC Infectious Diseases
#33
of 145 outputs
Altmetric has tracked 4,888,304 research outputs across all sources so far. This one has received more attention than most of these and is in the 59th percentile.
So far Altmetric has tracked 2,628 research outputs from this source. They receive a mean Attention Score of 3.1. This one has gotten more attention than average, scoring higher than 65% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 146,154 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 59% of its contemporaries.
We're also able to compare this research output to 145 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.