Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jul 3, 2022
Date Accepted: Jan 10, 2023
Development of the Simplified-Chinese Version of the DISCERN Instrument: Translation, Adaptation, and Validation
ABSTRACT
Background:
There is a wide variation in the quality of information available to patients who seek information on the treatment of the diseases afflicting them. To help patients find clear and accessible information, many scales have been designed to evaluate the quality of health information. These instruments are primarily in English. Few of them have been translated and adapted into simplified-Chinese tools for health information assessment in China.
Objective:
This study aimed to translate and adapt DISCERN into the first simplified-Chinese version and to validate the psychometric properties of this newly-developed scale for judging the quality of patient-oriented health information on treatment choices in China.
Methods:
First we translated DICERN into simplified-Chinese using rigorous guidelines for translation and validation studies. We tested translation equivalence and measured the content validity index. Then we presented the simplified-Chinese instrument to 2 health educators and asked them to use it to assess the quality of 15 lung cancer-related materials. Subsequently, we invited another 3 health educators to rate 1 lung cancer-related brochure. Finally, we calculated Cohen’s kappa coefficient and Cronbach’s alpha to determine the reliability of the new instrument.
Results:
We decided on the final version of the simplified-Chinese DISCERN (C-DISCERN) after resolving all problems in translation, adaptation, and content validation. The C-DISCERN was valid and reliable: (1) the content validity index was .98 (47/48) in clarity and .94 (45/48) in relevance; (2) Cohen’s kappa coefficient for interrater agreement was .53 (p<.05); and (3) Cronbach’s alpha for internal consistency was .93 (confidence interval=95%) for the whole translated scale.
Conclusions:
The C-DISCERN is the first simplified-Chinese version of the DISCERN instrument. Its validity and reliability has been attested for assessing the quality of patient-targeted information for treatment choices.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.