Reliability of information available on popular websites about vaccination of pregnant women

ABSTRACT Objective: To analyze the reliability of information available on popular websites about vaccination of pregnant women according to the recommendations of the Brazilian Ministry of Health. Method: Descriptive and comparative study. For data collection, a checklist composed of information on recommended, contraindicated, and indicated vaccines in special situations during pregnancy, according to the Ministry of Health, was elaborated. Results: None of the analyzed websites presented all the recommended information. Contraindications, most common adverse events, simultaneous administration of vaccines, information on the DT vaccine, and recommended vaccines in special situations were presented by a minority of websites. Conclusion: Information available on websites about the vaccination of pregnant women is not always based on the recommendations and misinformation may interfere with the acceptance of this practice. The importance of the professionals of the multidisciplinary team as information mediators, particularly the nurse, is emphasized, as is the need for regulating the production and dissemination of information on the internet.

SELECTIVELY MATERIALIZING DATA IN MEDIATORS BY ANALYZING USER QUERIES

There is currently great interest in building information mediators that can integrate information from multiple data sources such as databases or Web sources. The query response time for such mediators is typically quite high, mainly due to the time spent in retrieving data from remote sources. We present an approach for optimizing the performance of information mediators by selectively materializing data. We first present our overall framework for materialization in a mediator environment. The data is materialized selectively. We outline the factors that are considered in selecting data to materialize. We present an algorithm for identifying classes of data to materialize by analyzing one of the factors which is the distribution of user queries. We present results with an implemented version of our optimization system for the Ariadne information mediator, which show the effectiveness of our algorithm in extracting patterns of frequently accessed classes from user queries. We also demonstrate the effectiveness of approach in optimizing mediator performance by materializing such classes.