@Article{信息:doi 10.2196 / / jmir.7.5。e59，作者=“Griffiths, Kathleen M and Tang, Thanh Tin and Hawking, David and Christensen, Helen”，标题=“抑郁症网站质量的自动评估”，期刊=“J Med Internet Res”，年=“2005”，月=“12”，日=“30”，卷=“7”，数=“5”，页=“e59”，关键词=“质量指标;抑郁症;互联网;万维网;效度;背景:由于万维网上的健康信息质量参差不齐，因此需要有方法帮助消费者识别含有循证信息的健康网站。手动评估工具可以帮助消费者评估网站的质量。然而，这些工具没有经过很好的验证，而且往往不切实际。有必要开发更好的消费者工具，特别是探索评估网上健康信息质量的自动化程序的潜力。 Objective: This study (1) describes the development of an automated quality assessment procedure (AQA) designed to automatically rank depression websites according to their evidence-based quality; (2) evaluates the validity of the AQA relative to human rated evidence-based quality scores; and (3) compares the validity of Google PageRank and the AQA as indicators of evidence-based quality. Method: The AQA was developed using a quality feedback technique and a set of training websites previously rated manually according to their concordance with statements in the Oxford University Centre for Evidence-Based Mental Health's guidelines for treating depression. The validation phase involved 30 websites compiled from the DMOZ, Yahoo! and LookSmart Depression Directories by randomly selecting six sites from each of the Google PageRank bands of 0, 1-2, 3-4, 5-6 and 7-8. Evidence-based ratings from two independent raters (based on concordance with the Oxford guidelines) were then compared with scores derived from the automated AQA and Google algorithms. There was no overlap in the websites used in the training and validation phases of the study. Results: The correlation between the AQA score and the evidence-based ratings was high and significant (r=0.85, P<.001). Addition of a quadratic component improved the fit, the combined linear and quadratic model explaining 82 percent of the variance. The correlation between Google PageRank and the evidence-based score was lower than that for the AQA. When sites with zero PageRanks were included the association was weak and non-significant (r=0.23, P=.22). When sites with zero PageRanks were excluded, the correlation was moderate (r=.61, P=.002). Conclusions: Depression websites of different evidence-based quality can be differentiated using an automated system. If replicable, generalizable to other health conditions and deployed in a consumer-friendly form, the automated procedure described here could represent an important advance for consumers of Internet medical information. ", issn="1438-8871", doi="10.2196/jmir.7.5.e59", url="//www.mybigtv.com/2005/5/e59/", url="https://doi.org/10.2196/jmir.7.5.e59", url="http://www.ncbi.nlm.nih.gov/pubmed/16403723" }