%0期刊文章%@ 1438- 8871% I JMIR出版物%V 24卡塔尔世界杯8强波胆分析% N 3% P e32777% T电子健康素养问卷(eHLQ)的有效性证据第2部分:混合方法评估澳大利亚社区卫生环境中的测试内容、响应过程和内部结构%A Cheng,Christina A Elsworth,Gerald R %A Osborne,Richard H +斯威本科技大学健康科学学院全球健康与公平中心，AMCD大楼9层907室，453/469-477 Burwood路，Hawthorn, 3122，澳大利亚，61 392145470cccheng@swin.edu.au %K eHealth %K健康素养%K健康公平%K问卷设计%K有效性证据%K eHLQ %K手机%D 2022 %7 8.3.2022 %9原始论文%J J医学互联网Res %G英语%X背景:数字技术改变了我们管理健康的方式，需要eHealth素养来参与健康技术。如果用户的电子卫生素养需求得不到满足，任何电子卫生战略都将是无效的。一个强有力的电子卫生知识普及措施对于了解这些需求至关重要。电子卫生素养框架确定了电子卫生素养的7个维度，在此基础上编制了电子卫生素养问卷。该工具在丹麦环境中已经表现出强大的心理测量特性，但有效性测试应该是一个持续和累积的过程。目的:本研究旨在评估澳大利亚社区卫生环境中eHLQ测试内容、反应过程和内部结构的效度证据。方法:采用混合方法和认知访谈法对测试内容和反应过程进行证据检验，而对内部结构进行横断面调查。数据收集于澳大利亚维多利亚州3个不同的社区卫生站。 Psychometric testing included both the classical test theory and item response theory approaches. Methods included Bayesian structural equation modeling for confirmatory factor analysis, internal consistency and test-retest for reliability, and the Bayesian multiple-indicators, multiple-causes model for testing of differential item functioning. Results: Cognitive interviewing identified only 1 confusing term, which was clarified. All items were easy to read and understood as intended. A total of 525 questionnaires were included for psychometric analysis. All scales were homogenous with composite scale reliability ranging from 0.73 to 0.90. The intraclass correlation coefficient for test-retest reliability for the 7 scales ranged from 0.72 to 0.95. A 7-factor Bayesian structural equation modeling using small variance priors for cross-loadings and residual covariances was fitted to the data, and the model of interest produced a satisfactory fit (posterior productive P=.49, 95% CI for the difference between observed and replicated chi-square values −101.40 to 108.83, prior-posterior productive P=.92). All items loaded on the relevant factor, with loadings ranging from 0.36 to 0.94. No significant cross-loading was found. There was no evidence of differential item functioning for administration format, site area, and health setting. However, discriminant validity was not well established for scales 1, 3, 5, 6, and 7. Item response theory analysis found that all items provided precise information at different trait levels, except for 1 item. All items demonstrated different sensitivity to different trait levels and represented a range of difficulty levels. Conclusions: The evidence suggests that the eHLQ is a tool with robust psychometric properties and further investigation of discriminant validity is recommended. It is ready to be used to identify eHealth literacy strengths and challenges and assist the development of digital health interventions to ensure that people with limited digital access and skills are not left behind. %M 35258475 %R 10.2196/32777 %U //www.mybigtv.com/2022/3/e32777 %U https://doi.org/10.2196/32777 %U http://www.ncbi.nlm.nih.gov/pubmed/35258475