{"title":"Digital Health Literacy Questionnaire for Older Adults: Instrument Development and Validation Study.","authors":"Xinxin Wang, Chengrui Zhang, Yue Qi, Ying Xing, Yawen Liu, Jiayi Sun, Wei Luan","doi":"10.2196/64193","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>The integration of digital technology into older adult health and care has enhanced the intelligence of health and older adult care products and services while also transforming how seniors acquire and share health information. Assessing older adults' digital health literacy (DHL) is crucial for developing targeted interventions.</p><p><strong>Objective: </strong>This study aims to develop and validate a DHL assessment questionnaire for older adults. It also seeks to evaluate the questionnaire's scientific validity and feasibility among community-dwelling older adults in China, providing a reliable tool for assessing their level of DHL.</p><p><strong>Methods: </strong>A literature review, focus group discussions, and the Delphi method were used to construct the questionnaire item pool and perform item screening. Item analysis was conducted for comprehensive evaluation, and questionnaire validity was assessed through construct validity (exploratory factor analysis, confirmatory factor analysis, convergent validity, and discriminant validity), content validity, and criterion-related validity. Reliability was analyzed using Cronbach alpha coefficient, split-half reliability, and test-retest reliability.</p><p><strong>Results: </strong>The study included 710 participants. Item analysis indicated that the questionnaire had strong discriminant validity. Correlation coefficient analysis showed that the item-total correlation coefficients ranged from 0.497 to 0.920 (P<.01). After multiple exploratory factor analyses, 6 common factors were extracted, with a cumulative variance contribution rate of 73.745%. Confirmatory factor analysis demonstrated a good model fit (χ<sup>2</sup>/df=2.803, root-mean-square error of approximation=0.071, comparative fit index=0.907, goodness-of-fit index=0.773, incremental fit index=0.908, Tucker-Lewis index=0.901, normed fit index=0.863). The questionnaire demonstrated favorable convergent validity, content validity, and criterion-related validity. The total Cronbach α coefficient was 0.976, with dimension-specific Cronbach α coefficients ranging from 0.819 to 0.952, indicating satisfactory internal consistency. Additionally, the test-retest reliability coefficient for the total questionnaire was 0.925, demonstrating good stability over time.</p><p><strong>Conclusions: </strong>This study developed a questionnaire specifically designed to assess DHL in older adults through a scientifically rigorous and systematic process. The questionnaire demonstrates strong psychometric properties and can serve as an empirical tool for health professionals to design personalized intervention policies and enhance health service delivery.</p>","PeriodicalId":16337,"journal":{"name":"Journal of Medical Internet Research","volume":"27 ","pages":"e64193"},"PeriodicalIF":5.8000,"publicationDate":"2025-03-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Medical Internet Research","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.2196/64193","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0
Abstract
Background: The integration of digital technology into older adult health and care has enhanced the intelligence of health and older adult care products and services while also transforming how seniors acquire and share health information. Assessing older adults' digital health literacy (DHL) is crucial for developing targeted interventions.
Objective: This study aims to develop and validate a DHL assessment questionnaire for older adults. It also seeks to evaluate the questionnaire's scientific validity and feasibility among community-dwelling older adults in China, providing a reliable tool for assessing their level of DHL.
Methods: A literature review, focus group discussions, and the Delphi method were used to construct the questionnaire item pool and perform item screening. Item analysis was conducted for comprehensive evaluation, and questionnaire validity was assessed through construct validity (exploratory factor analysis, confirmatory factor analysis, convergent validity, and discriminant validity), content validity, and criterion-related validity. Reliability was analyzed using Cronbach alpha coefficient, split-half reliability, and test-retest reliability.
Results: The study included 710 participants. Item analysis indicated that the questionnaire had strong discriminant validity. Correlation coefficient analysis showed that the item-total correlation coefficients ranged from 0.497 to 0.920 (P<.01). After multiple exploratory factor analyses, 6 common factors were extracted, with a cumulative variance contribution rate of 73.745%. Confirmatory factor analysis demonstrated a good model fit (χ2/df=2.803, root-mean-square error of approximation=0.071, comparative fit index=0.907, goodness-of-fit index=0.773, incremental fit index=0.908, Tucker-Lewis index=0.901, normed fit index=0.863). The questionnaire demonstrated favorable convergent validity, content validity, and criterion-related validity. The total Cronbach α coefficient was 0.976, with dimension-specific Cronbach α coefficients ranging from 0.819 to 0.952, indicating satisfactory internal consistency. Additionally, the test-retest reliability coefficient for the total questionnaire was 0.925, demonstrating good stability over time.
Conclusions: This study developed a questionnaire specifically designed to assess DHL in older adults through a scientifically rigorous and systematic process. The questionnaire demonstrates strong psychometric properties and can serve as an empirical tool for health professionals to design personalized intervention policies and enhance health service delivery.
期刊介绍:
The Journal of Medical Internet Research (JMIR) is a highly respected publication in the field of health informatics and health services. With a founding date in 1999, JMIR has been a pioneer in the field for over two decades.
As a leader in the industry, the journal focuses on digital health, data science, health informatics, and emerging technologies for health, medicine, and biomedical research. It is recognized as a top publication in these disciplines, ranking in the first quartile (Q1) by Impact Factor.
Notably, JMIR holds the prestigious position of being ranked #1 on Google Scholar within the "Medical Informatics" discipline.