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

Formative Evaluation of Digital Health Interventions (2914) Consumer & Patient Education and Shared-Decision Making (780) Artificial Intelligence (1833) Artificial Intelligence, Machine Learning, and Natural Language Processing for Public Health (68)

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
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JMIR Formative Res: The Readability and Quality of Web-Based Patient Information on Nasopharyngeal Carcinoma: Quantitative Content Analysis https://t.co/ypwy5dd2ai https://t.co/XGHbrYgVgf

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RT @jmirpub: JMIR Formative Res: The Readability and Quality of Web-Based Patient Information on Nasopharyngeal Carcinoma: Quantitative Con…

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The Readability and Quality of Web-Based Patient Information on Nasopharyngeal Carcinoma: Quantitative Content Analysis https://t.co/ilLbxKdsp6

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The Readability and Quality of Web-Based Patient Information on Nasopharyngeal Carcinoma: Quantitative Content Analysis https://t.co/jc0XQEUZZM https://t.co/Jkl8YWGnyk

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