Principal Component Analysis: A Tool for Identifying Web Document Characteristics Affecting Quality of Drug Information Websites - Lawan Sratthaphut, Krittika Tanyasaensook, Piyaporn Tunneekul (Journal of Applied Pharmaceutical Science, 2017)
The objective of our study was to identify Web document characteristics affecting quality of drug information websites using principal component analysis (PCA) technique in order to assist consumers, patients, and Web developers for observing good designing aspects to achieve information quality. Internet websites were collected by using the 8 search terms and 3 mostly utilized search engines in Thailand. Thirty five drug information websites were assessed with two independent raters to find out the quality in drug information providing using DISCERN criteria. Sixteen characteristics of Web document were investigated. PCA was applied to the data and the principal components were plotted and visualized structurally for detection the most important characteristics which related to the quality of drug information websites. The six PCs accounted for 73.39% of the total variance. The overall mean of DISCERN score for quality was “fair” at 52.5 (range, 21–72; SD = 11.1). Four attributes then were chosen to be the factors which mostly influence quality status of drug information websites. These findings provide consumers and patients to observe the quality of sites that provide drug information as well as to support Web authors for improving the quality of drug information websites.
Keywords: Drug information, Principal component analysis, Web document, HTML document, Internet.