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- Automated Quality Rating (1)
- Corona Virus Disease (COVID)-19 (1)
- DeLeon and McLean's information system success model (1)
- Developing countries (1)
- Ebola virus disease (EVD) (1)
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- Emerging and re-emerging infectious disease pandemics (1)
- Enhancing (1)
- Evidence-based Health care information (1)
- Health Care Information Quality on the Web (1)
- Health information system (HIS) (1)
- Health information systems models (1)
- Health information systems research (1)
- Information Quality Assessment (1)
- Mixed methods (1)
- Semantic Analysis (1)
- Structural equation modelling (SEM) (1)
- Text Classification (1)
- Thematic analysis. (1)
- Validating (1)
Articles 1 - 2 of 2
Full-Text Articles in Library and Information Science
Improving Developing Countries’ Health Information Systems Capacity For Infectious Disease Pandemic Responses: A Case Study Of The Ebola Virus Disease And The Coronavirus Disease Pandemics, Uche Ikenyei
Electronic Thesis and Dissertation Repository
There is increasing evidence to demonstrate that current information system theoretical models meant to assess the success of the health information systems (HIS) lack the applicable theoretical underpinning suitable for developing countries. This stems partly from a theory-evidence gap where theoretical models developed in the West are applied in developing country contexts but lack tailoring to localized, contextual realities. Therefore, this study addresses this gap by enhancing the DeLeon and McLean's information system success model with six contextual factors peculiar to the infectious disease HISs in a developing country context.
This study took place in two developing countries, Liberia and …
Semantics-Based Automated Quality Assessment Of Depression Treatment Web Documents, Yanjun Zhang
Semantics-Based Automated Quality Assessment Of Depression Treatment Web Documents, Yanjun Zhang
Electronic Thesis and Dissertation Repository
The past decade has witnessed a dramatic expansion in the amount of publicly available health care information on the Web. The health care information on the web, however, is of extremely variable quality. The evaluation of content quality is a big challenge because non-automated methods for information content rating can be easily overwhelmed by the huge data volume. This study proposes an automated approach for assessing the quality of web health care information through comparing the text content with evidence-based health care recommendations. This method relies on semantic analysis and text classification to identify the presentation of evidence-based recommendations in …