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Purpose The aim of the present study is to assess the quality and reliability of web-based information about restorative treatment in pediatric patients on the internet using different scales. Materials and Methods Websites obtained by using keywords about restorative treatment in pediatric patients on Google and Yandex were included in the study. The study was conducted in English on a total of 440 websites. Websites were evaluated using the quality criteria for consumer health information (DISCERN toolkit), Journal of American Medical Association (JAMA) benchmarks, and Health on the Net Code of Conduct Certification (HONCode). Results The mean DISCERN points of the websites were moderate. Among the evaluated websites, the quality of the knowledge in 20% of the websites was low. The rate of websites with a score below 40 was 37.5%. None of them has reached an excellent score. No websites met all JAMA criteria. There was no HONCode Certificate on any website. Conclusion This study showed that the quality of the web-based information about restorative treatment in pediatric patients was generally inadequate and scientifically imperfect.

Background As representatives of health information communication platforms accessed through mobile phones and mobile terminals, health-related WeChat public accounts (HWPAs) have a large consumer base in the Chinese-speaking world. However, there is still a lack of general understanding of the status quo of HWPAs and the quality of the articles they release. Objective The aims of this study were to assess the conformity of HWPAs to the Health on the Net Foundation Code of Conduct (HONcode) and to evaluate the suitability of articles disseminated by HWPAs. Methods The survey was conducted from April 23 to May 5, 2019. Based on the monthly (March 1-31, 2019) WeChat Index provided by Qingbo Big Data, the top 100 HWPAs were examined to evaluate their HONcode compliance. The first four articles published by each HWPA on the survey dates were selected as samples to evaluate their suitability. All materials were assessed by three raters. The materials were assessed using the HONcode checklist and the Suitability Assessment of Materials (SAM) score sheet. Data analysis was performed with SPSS version 17.0 (SPSS Inc, Chicago, IL, USA) and Excel version 2013 (Microsoft Inc, Washington DC, USA). Results A total of 93 HWPAs and 210 of their released articles were included in this study. For six of the eight principles, the 93 HWPAs nearly consistently did not meet the requirements of the HONcode. The HWPAs certified by Tencent Corporation (66/93, 71%) were generally slightly superior to those without such certification (27/93, 29%) in terms of compliance with HONcode principles. The mean SAM score for the 210 articles was 67.72 (SD 10.930), which indicated “adequate” suitability. There was no significant difference between the SAM scores of the articles published by certified and uncertified HWPAs (P=.07), except in the literacy requirements dimension (tdf=97=–2.418, P=.02). Conclusions The HWPAs had low HONcode conformity. Although the suitability of health information released by HWPAs was at a moderate level, there were still problems identified, such as difficulty in tracing information sources, excessive implicit advertisements, and irregular usage of charts. In addition, the low approval requirements of HWPAs were not conducive to improvement of their service quality.

Background: To earn HONcode certification, a website must conform to the 8 principles of the HONcode of Conduct In the current manual process of certification, a HONcode expert assesses the candidate website using precise guidelines for each principle. In the scope of the European project KHRESMOI, the Health on the Net (HON) Foundation has developed an automated system to assist in detecting a website’s HONcode conformity. Automated assistance in conducting HONcode reviews can expedite the current time-consuming tasks of HONcode certification and ongoing surveillance. Additionally, an automated tool used as a plugin to a general search engine might help to detect health websites that respect HONcode principles but have not yet been certified. Objective: The goal of this study was to determine whether the automated system is capable of performing as good as human experts for the task of identifying HONcode principles on health websites. Methods: Using manual evaluation by HONcode senior experts as a baseline, this study compared the capability of the automated HONcode detection system to that of the HONcode senior experts. A set of 27 health-related websites were manually assessed for compliance to each of the 8 HONcode principles by senior HONcode experts. The same set of websites were processed by the automated system for HONcode compliance detection based on supervised machine learning. The results obtained by these two methods were then compared. Results: For the privacy criterion, the automated system obtained the same results as the human expert for 17 of 27 sites (14 true positives and 3 true negatives) without noise (0 false positives). The remaining 10 false negative instances for the privacy criterion represented tolerable behavior because it is important that all automatically detected principle conformities are accurate (ie, specificity [100%] is preferred over sensitivity [58%] for the privacy criterion). In addition, the automated system had precision of at least 75%, with a recall of more than 50% for contact details (100% precision, 69% recall), authority (85% precision, 52% recall), and reference (75% precision, 56% recall). The results also revealed issues for some criteria such as date. Changing the “document” definition (ie, using the sentence instead of whole document as a unit of classification) within the automated system resolved some but not all of them. Conclusions: Study results indicate concordance between automated and expert manual compliance detection for authority, privacy, reference, and contact details. Results also indicate that using the same general parameters for automated detection of each criterion produces suboptimal results. Future work to configure optimal system parameters for each HONcode principle would improve results. The potential utility of integrating automated detection of HONcode conformity into future search engines is also discussed. [J Med Internet Res 2015;17(6):e135]

Background: In today's technologically advanced world, 75% of patients have used Google to search for health information. As a result, health care professionals fear that patients may be misinformed. Currently, there is a paucity of data on the quality and readability of Web-based health information on fractures. Objectives: In this study, we assessed the quality and readability of Web-based health information related to the 10 most common fractures. Methods: Using the Google search engine, we assessed websites from the first results page for the 10 most common fractures using lay search terms. Website quality was measured using the DISCERN instrument, which scores websites as very poor (15-22.5), poor (22.5-37.5), fair (37.5-52.5), good (52.5-67.5), or excellent (67.5-75). The presence of Health on the Net code (HONcode) certification was assessed for all websites. Website readability was measured using the Flesch Reading Ease Score (0-100), where 60-69 is ideal for the general public, and the Flesch-Kincaid Grade Level (FKGL; −3.4 to ∞), where the mean FKGL of the US adult population is 8. Results: Overall, website quality was “fair” for all fractures, with a mean (standard deviation) DISCERN score of 50.3 (5.8). The DISCERN score correlated positively with a higher website position on the search results page (r2=0.1, P=.002) and with HONcode certification (P=.007). The mean (standard deviation) Flesch Reading Ease Score and FKGL for all fractures were 62.2 (9.1) and 6.7 (1.6), respectively. Conclusion: The quality of Web-based health information on fracture care is fair, and its readability is appropriate for the general public. To obtain higher quality information, patients should select HONcode-certified websites. Furthermore, patients should select websites that are positioned higher on the results page because the Google ranking algorithms appear to rank the websites by quality. [Interact J Med Res 2016;5(2):e19]