Development of the Digital Health Literacy Instrument

Measuring a Broad Spectrum of Health 1.0 and Health 2.0 Skills

Datos Bibliográficos

ID23323933
AutoresRosalie van der Vaart (0000-0002-8787-4186, Leiden University), Constance H C Drossaert (0000-0002-7083-3169, University of Twente, autor de correspondencia)
Año2017
Volumen19
Número1
Páginase27
Fecha de publicación2017-01-24
Peer ReviewedSí
Open AccessSí
TipoARTICLE
RevistaJournal of Medical Internet Research (JOURNAL)
Identificadores de la revistaISSN: 1438-8871 • E-ISSN: 1438-8871
EditorialJMIR Publications Inc. (PUBLISHER • CA)
DOI10.2196/jmir.6709
PMID28119275
OpenAlexW2580360748
IdiomaEN
Citas recibidas90
Referencias citadas33

BACKGROUND: With the digitization of health care and the wide availability of Web-based applications, a broad set of skills is essential to properly use such facilities; these skills are called digital health literacy or eHealth literacy. Current instruments to measure digital health literacy focus only on information gathering (Health 1.0 skills) and do not pay attention to interactivity on the Web (Health 2.0). To measure the complete spectrum of Health 1.0 and Health 2.0 skills, including actual competencies, we developed a new instrument. The Digital Health Literacy Instrument (DHLI) measures operational skills, navigation skills, information searching, evaluating reliability, determining relevance, adding self-generated content, and protecting privacy. OBJECTIVE: Our objective was to study the distributional properties, reliability, content validity, and construct validity of the DHLI's self-report scale (21 items) and to explore the feasibility of an additional set of performance-based items (7 items). METHODS: We used a paper-and-pencil survey among a sample of the general Dutch population, stratified by age, sex, and educational level (T1; N=200). The survey consisted of the DHLI, sociodemographics, Internet use, health status, health literacy and the eHealth Literacy Scale (eHEALS). After 2 weeks, we asked participants to complete the DHLI again (T2; n=67). Cronbach alpha and intraclass correlation analysis between T1 and T2 were used to investigate reliability. Principal component analysis was performed to determine content validity. Correlation analyses were used to determine the construct validity. RESULTS: Respondents (107 female and 93 male) ranged in age from 18 to 84 years (mean 46.4, SD 19.0); 23.0% (46/200) had a lower educational level. Internal consistencies of the total scale (alpha=.87) and the subscales (alpha range .70-.89) were satisfactory, except for protecting privacy (alpha=.57). Distributional properties showed an approximately normal distribution. Test-retest analysis was satisfactory overall (total scale intraclass correlation coefficient=.77; subscale intraclass correlation coefficient range .49-.81). The performance-based items did not together form a single construct (alpha=.47) and should be interpreted individually. Results showed that more complex skills were reflected in a lower number of correct responses. Principal component analysis confirmed the theoretical structure of the self-report scale (76% explained variance). Correlations were as expected, showing significant relations with age (ρ=-.41, P<.001), education (ρ=.14, P=.047), Internet use (ρ=.39, P<.001), health-related Internet use (ρ=.27, P<.001), health status (ρ range .17-.27, P<.001), health literacy (ρ=.31, P<.001), and the eHEALS (ρ=.51, P<.001). CONCLUSIONS: This instrument can be accepted as a new self-report measure to assess digital health literacy, using multiple subscales. Its performance-based items provide an indication of actual skills but should be studied and adapted further. Future research should examine the acceptability of this instrument in other languages and among different populations.

Construct validity · Content validity · Cronbach's alpha · Digital health · eHealth · Environmental health · Health care · Health literacy · Medical education · Population · Psychometrics · Applied Psychology · Clinical Psychology · Health Literacy and Information Accessibility · Medicine · Mobile Health and mHealth Applications · Psychology · Social Media in Health Education