BACKGROUND. Consumers increasingly consult the Internet for breast cancer information. Concerned about accuracy, multiple organizations developed quality criteria for online content. However, the effectiveness of these tools is unknown. The authors determined whether existing quality criteria can identify inaccurate breast cancer information online. METHODS. The authors identified 343 unique webpages by using 15 breast cancer-related queries on 5 popular web search-engines. Each page was assessed for 15 quality criteria and 3 website characteristics, link type (sponsored or not), search engine used to find the page, and domain extension. Two clinician-reviewers independently assessed accuracy and topics covered. The authors then determined whether quality criteria, website characteristics, and topics were associated with the presence of inaccurate statements. RESULTS. The authors found 41 inaccurate statements on 18 webpages (5.2%). No quality criteria or website characteristic, singly or in combination, reliably identified inaccurate information. The total number of quality criteria met by a website accounted for a small fraction of the variability in the presence of inaccuracies (point biserial r = -0.128; df = 341; P = .018; r2 = 0.016). However, webpages containing information on complementary and alternative medicine (CAM) were significantly more likely to contain inaccuracies compared with pages without CAM information (odds ratio [OR], 15.6; P < .001). CONCLUSIONS. Most breast cancer information that consumers are likely to encounter online is accurate. However, commonly cited quality criteria do not identify inaccurate information. Webpages that contain information about CAM are relatively likely to contain inaccurate statements. Consumers searching for health information online should still consult a clinician before taking action.
- Breast neoplasms
- Complementary therapies/*standards/trends
- Health education/methods
- Information services/*standards/utilization
- Internet/*standards/statistics & numerical data/trends