This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2410) Consumer & Patient Education and Shared-Decision Making (679) Artificial Intelligence (1371) Artificial Intelligence (86) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (36)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/47762, first published .
The Readability and Quality of Web-Based Patient Information on Nasopharyngeal Carcinoma: Quantitative Content Analysis

The Readability and Quality of Web-Based Patient Information on Nasopharyngeal Carcinoma: Quantitative Content Analysis

The Readability and Quality of Web-Based Patient Information on Nasopharyngeal Carcinoma: Quantitative Content Analysis

Authors of this article:

Denise Jia Yun Tan1 Author Orcid Image ;   Tsz Ki Ko1 Author Orcid Image ;   Ka Siu Fan2 Author Orcid Image
Article Authors Cited by (3) Tweetations (4) Metrics

Journals

  1. Ko T, Tan D, Fan K. Evaluation of the Quality and Readability of Web-Based Information Regarding Foreign Bodies of the Ear, Nose, and Throat: Qualitative Content Analysis. JMIR Formative Research 2024;8:e55535 View
  2. Liu Z, Chen Y, Lin Y, Ai M, Lian D, Zhang Y, Shen Y, Yu F. YouTube/ Bilibili/ TikTok videos as sources of medical information on laryngeal carcinoma: cross-sectional content analysis study. BMC Public Health 2024;24(1) View
  3. Shamil E, Ko T, Fan K, Schuster-Bruce J, Jaafar M, Khwaja S, Eynon-Lewis N, D'Souza A, Andrews P. Assessing the Quality and Readability of Online Patient Information: ENT UK Patient Information e-Leaflets versus Responses by a Generative Artificial Intelligence. Facial Plastic Surgery 2024 View