title: HON label and DISCERN as content quality indicators of health-related websites.
abstract: Content quality indicators are warranted in order to help patients and consumers to judge the content quality of health-related on-line information. The aim of the present study is to evaluate web-based information on health topics and to assess particular content quality indicators like HON (Health on the Net) and DISCERN. The present study is based on the analysis of data issued from six previous studies which assessed with a standardized tool the general and content quality (evidence-based health information) of health-related websites. Keywords related to Social phobia, bipolar disorders, pathological gambling as well as cannabis, alcohol and cocaine addiction were entered into popular World Wide Web search engines. Websites were assessed with a standardized proforma designed to rate sites on the basis of accountability, presentation, interactivity, readability and content quality (evidence-based information). "Health on the Net" (HON) quality label, and DISCERN scale scores were used to verify their efficiency as quality indicators. Of 874 websites identified, 388 were included. Despite an observed association with higher content quality scores, the HON label fails to predict good content quality websites when used in a multiple regression. Sensibility and specificity of a DISCERN score >40 in the detection of good content quality websites were, respectively, 0.45 and 0.96. The DISCERN is a potential quality indicator with a relatively high specificity. Further developments in this domain are warranted in order to facilitate the identification of high-quality information on the web by patients.
authors.affiliation: Division of Addictology, Geneva University Hospitals, Rue verte, 2, 1205 Geneva, Switzerland. yasser.khazaal@hcuge.ch
authors.forename: Yasser
authors.initials: Y
authors.lastname: Khazaal
authors.forename: Anne
authors.initials: A
authors.lastname: Chatton
authors.forename: Daniele
authors.initials: D
authors.lastname: Zullino
authors.forename: Riaz
authors.initials: R
authors.lastname: Khan
mesh_terms: D032882:Comprehension; D054626:Consumer Health Information / Q000592:standards*; D004954:Esthetics; D019317:Evidence-Based Medicine; D005163:Factor Analysis, Statistical; D006801:Humans; D033181:Information Dissemination / Q000379:methods; D020407:Internet / Q000592:standards*; D001523:Mental Disorders; D019984:Quality Indicators, Health Care / Q000592:standards*; D012044:Regression Analysis; D015203:Reproducibility of Results; D057386:Search Engine; D012680:Sensitivity and Specificity; D014584:User-Computer Interface