ArticleJournal of epidemiology and community health1999
DISCERN: an instrument for judging the quality of written consumer health information on treatment choices.
Article in Journal of epidemiology and community health, 1999. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05222763 (Effect Of Web - Supported Interactıve Nursıng Program After Mastectomy On Body Value, Care Dependence And Psychosocıal Adaptatıon To Dısease-Self-Awareness Levels Accordıng To Self-Regulatıon Model), which is not on this map. Cited by 1,418 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Effect Of Web - Supported Interactıve Nursıng Program After Mastectomy On Body Value, Care Dependence And Psychosocıal Adaptatıon To Dısease-Self-Awareness Levels Accordıng To Self-Regulatıon Model: Mıxed Method Study
Who cites it
1,418 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- ChatGPT provides accurate and safe responses to patient questions on hip arthroscopy, while completeness remains variable: A systematic review and single-arm meta-analysis.Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA · 2026Pooled it
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- Integrating large language models into prostate cancer training: evidence from comparative benchmarking and a pilot randomized trial.BMC medical education · 2026Trial
- The effect of training provided according to the health promotion model on premenstrual symptoms, emotional eating behavior, and perceived stress.BMC women's health · 2026Trial
- The effect of infertility support education on treatment outcomes in women with unexplained infertility.Journal of comparative effectiveness research · 2026Trial
- Perceived usefulness of online videos for hereditary breast cancer communication in Japan: Patient and provider perspectives.Public health in practice (Oxford, England) · 2026Article
- Patient-centered online health information on diverticulitis: Assessing the readability, content, and overall quality.American journal of surgery · 2026Article
- Concise Commentary: AI-Generated GI Patient Education-High Quality, yet Readability May Limit Utility.Digestive diseases and sciences · 2026Article
- Comment on "Readability, Quality, Understandability, and Actionability of ChatGPT-Generated GI Patient Education Versus AGA Patient Center".Digestive diseases and sciences · 2026Article
- Evaluating influenza-related short videos on Chinese platforms: information quality, user engagement, and public health implications.NPJ primary care respiratory medicine · 2026Article
- Decision-relevant patient information in YouTube videos on robotic surgery for endometriosis: a cross-sectional content analysis.Journal of robotic surgery · 2026Article
- Evaluating COPD care assistance: a comparative study of ChatGPT-3.5, ChatGPT-4.0, and ERNIE bot performance.Journal of global health · 2026Article
- Reliability and quality of YouTube exercise videos for people living with lung cancer: a cross-sectional content analysis.Journal of cancer survivorship : research and practice · 2026Article
- Quality, understandability, and actionability of Arabic web-based content on periodontal and related oral surgical procedures: a cross-sectional infodemiological study.The Saudi dental journal · 2026Article
- Educational quality of YouTube content on healthcare waste management relevant to dentistry: a cross-sectional study.BMC oral health · 2026Article
- Quality evaluation of short videos about insomnia on TikTok and Bilibili: A cross-sectional study.Medicine · 2026Article
- Accessibility and Decision-Supportive Quality of Benign Breast Disease Articles on Chinese Hospital WeChat Public Accounts: Nationwide Cross-Sectional Study.JMIR medical informatics · 2026Article
- Quality, Reliability, and Content Characteristics of Metabolic Bariatric Surgery Videos on TikTok, YouTube, and Facebook: A Mixed-Methods Cross-Platform Analysis.Obesity surgery · 2026Article
- Reliability, Readability, and Safety of Generative AI Chatbots for Osteoporosis Health Counseling: A Multidimensional Cross-Sectional Comparative Study.Health science reports · 2026Article
- Comparative Evaluation of AI Chatbots for Testicular Cancer Education: Validity, Information Quality, and Readability.Annals of surgical oncology · 2026Article
1,358 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo develop a short instrument, called DISCERN, which will enable patients and information providers to judge the quality of written information about treatment choices. DISCERN will also facilitate the production of new, high quality, evidence-based consumer health information.
designAn expert panel, representing a range of expertise in consumer health information, generated criteria from a random sample of information for three medical conditions with varying degrees of evidence: myocardial infarction, endometriosis, and chronic fatigue syndrome. A graft instrument, based on this analysis, was tested by the panel on a random sample of new material for the same three conditions. The panel re-drafted the instrument to take account of the results of the test. The DISCERN instrument was finally tested by a national sample of 15 information providers and 13 self help group members on a random sample of leaflets from 19 major national self help organisations. Participants also completed an 8 item questionnaire concerning the face and content validity of the instrument.
resultsChance corrected agreement (weighted kappa) for the overall quality rating was kappa = 0.53 (95% CI kappa = 0.48 to kappa = 0.59) among the expert panel, kappa = 0.40 (95% CI kappa = 0.36 to kappa = 0.43) among information providers, and kappa = 0.23 (95% CI kappa = 0.19 to kappa = 0.27) among self help group members. Higher agreement levels were associated with experience of using the instrument and with professional knowledge of consumer health information. Levels of agreement varied across individual items on the instrument, reflecting the need for subjectivity in rating certain criteria. The trends in levels of agreement were similar among all groups. The final instrument consisted of 15 questions plus an overall quality rating. Responses to the questionnaire after the final testing revealed the instrument to have good face and content validity and to be generally applicable.
conclusionsDISCERN is a reliable and valid instrument for judging the quality of written consumer health information. While some subjectivity is required for rating certain criteria, the findings demonstrate that the instrument can be applied by experienced users and providers of health information to discriminate between publications of high and low quality. The instrument will also be of benefit to patients, though its use will be improved by training.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.