Online information on Crohn's disease in Chinese: an evaluation of its quality and readability

Abstract

Objective To assess the quality and readability of patient‐education information on Crohn's disease on the internet in China. Methods Baidu and Sogou were chosen as search engines, and the top 58 webpages on Crohn's disease meeting the inclusion criteria were evaluated. After the data were screened, the quality of information was assessed by two specialists using a simplified DISCERN system. Different levels of official Chinese‐teaching materials were used to build a readability model to predict the readability of these information. Results Altogether 13 pieces of information were included in this study, all of which were derived from commercial webpages. The simplified DISCERN system found an excellent consistency in the Chinese literature, and Spearman's coefficient was 0.685, 0.556 and 0.607, respectively (P < 0.001), for publication reliability, treatment options and the total score. Most of the information lacked clear sources and conflicts of interest statements. The corresponding DISCERN scores were all below 2. In terms of treatment options, many webpages did not provide adequate information about the prognosis, possible side effects of treatment and risks of developing cancer. The scores of treatment‐related DISCERN items were all below 2 as well. The webpages did not show enough readability. Altogether 84.6% of the information exceeded the middle‐school readability level, and 69.2% exceeded the high‐school level. Conclusions The quality of patient‐education information on Crohn's disease on the internet in China is worrisome, with poor readability, which should be addressed by the academic community.

Predicting Writing Styles of Web-Based Materials for Children’s Health Education Using the Selection of Semantic Features: Machine Learning Approach

“…Key assessment criteria of PEMAT include health information understandability, relevance, and actionability [8,9]. Much of the current research has focused on exploring these assessment dimensions separately using long-standing readability tools [10][11][12][13] or machine learning algorithms of natural language features [14][15][16] using features such as general medical vocabularies, consumer medical vocabulary, natural language features such as a part of speech features [17][18][19], and other metadata [20]. Furthermore, many of these data-intensive and data-driven studies did not consider insights from research fields directly relevant to health educational resource development and evaluation.…”

Large Language Models (LLMs) vs. Specialist Doctors: A Comparative Study on Health Information in specific medical domains. (Preprint)

“…9,10 However, the quality of health information on the internet about chronic diseases, such as Inflammatory Bowel Disease (IBD), varies widely and has been considered a challenge for patient self-management and education. [11][12][13][14][15][16][17] Inflammatory Bowel Disease, including Crohn's disease and ulcerative colitis, is an increasingly prevalent chronic intestinal disease in China, characterized by primary invasion of the digestive system and cumulative multi-system involvement of autoimmune diseases, with no cure currently available. Patients have a strong need to learn and reinforce self-care abilities, among which the WeChat public account of the China Crohn's and Colitis Foundation (CCCF) is the most popular with IBD patients.…”

“…When faced with unsatisfactory responses or doubts about AI Hallucination, consider first whether the prompts (terminology) you provide as the output party have been broken down for laypersons to understand.In previous evaluations of English and Chinese IBD information, 14,15,31 the readability levels of web health information were generally too high, unsuitable for public dissemination. 13 Simultaneously, there are also articles indicating that the English output generated by ChatGPT is at a university level. 9 This aligns with the common complaint heard by the author in work settings from patients: doctors chatter on, but I can't understand a word they're saying.…”

Patient education information material assessment criteria: A scoping review

“…The findings indicated that 229 studies evaluated readability in the context of patient education, with 91 of those evaluated using only readability criteria (Abdul Rahman et al, 2020;Ahmadzadeh et al, 2014;Al Aqeel et al, 2018;Alderson et al, 2020;Alejos et al, 2021;Alpaydin et al, 2021;Alshaikh et al, 2021;Alshehri & Joury, 2019;Alwani et al, 2021;Ang et al, 2022;Arif & Ghezzi, 2018;Arslan et al, 2020;Avancini et al, 2021;Azer et al, 2017;Azer et al, 2018;Bacher et al, 2020;Bai et al, 2019;Barnes & Davies, 2015;Bernstam et al, 2005;Best et al, 2015;Betschart et al, 2017;Bojrab 2nd et al, 2020;Boureanu et al, 2021;Brennan et al, 2021;Carden et al, 2007;Cheah et al, 2020;Cheng et al, 2016;Choudhery et al, 2020;Colaco et al, 2013;Coleman et al, 2022;Cook et al, 2017;Corredera et al, 2018;Crabtree & Lee, 2022;Dalton et al, 2015;Davis et al, 1998;De Felippe & Kar, 2015;Docimo Jr. et al, 2022;Dorcely et al, 2015;Doubleday et al, 2021;…”