JMIR Publications

ABSTRACT

Background:

The World Wide Web has become an essential source of health information. Especially the COVID-19 pandemic has shown that the amount and the quality of information provided can lead to an information overload. Therefore, people do need certain skills to search, identify and evaluate information from the internet. In the context of health information, these competences are described as eHealth literacy, which could be confirmed as predictor of various health-related outcomes. Existing instruments assessing eHealth literacy reveal limitation of methodological standards of test development and validation. Furthermore, existing scales do not cover the entire cognitive processes, which are proposed within the construct of eHealth literacy.

Objective:

The objective of this study is the development and validation of an extended eHealth literacy scale to provide an economic and empirically confirmed measurement of eHealth literacy in German language.

Methods:

For development, items from 2 international, validated instruments were merged to cover a wide bandwidth of the construct of eHealth literacy. Translation into German followed scientific guidelines and recommendations ensuring content validity. A convenience sample of N=470 German-speaking people was collected from October to November 2020. Validation was carried out by confirmatory factor analysis. Correlations were performed to examine for convergent, discriminant, and criterion validity. Additionally, analyses of measurement invariance of gender, age, and educational level were conducted.

Results:

Analyses revealed a 3-factorial model of eHealth literacy. By item-reduction, the 3 factors information seeking, information identification, and information evaluation were measured with 11 items reaching good model fits (CFI: 0.959 ; TLI: 0.945; RMSEA: 0 .068; SRMR: 0.045). Convergent validity was confirmed by positive correlations of information seeking, information identification, and information evaluation with health literacy (r=0.43, P<.001; r= 0.53, P<.001; r= 0.55, P<.001, respectively). No significant correlations with impulsivity (r=-0.06, P=.16; r=-0.08, P=.08; r=-0.08, P=.10, respectively) confirmed discriminant validity. Criterion validity was supported by positive correlations of information identification and information evaluation with mental health (r=0.29, P<.001; r= 0.21, P<.001, respectively). Analyses with further variables confirmed convergent, discriminant and criterion validity. Strict measurement invariance of gender (CFI: 0.941; TLI: 0.941 ; RMSEA: 0.073; SRMR: 0.059), age (CFI: 0.943; TLI: 0.943 ; RMSEA: 0.070; SRMR: 0 .053), and educational level (CFI: 0.956; TLI: 0.959 ; RMSEA: 0.059; SRMR: 0.060) was confirmed.

Conclusions:

Following scientific suggestions for translation and performing analyses confirming 3-factorial structure, we developed the 3-factor eHealth literacy inventory (3F-EHLI) as an economic and valid assessment of eHealth literacy. By verifying measurement invariance of gender, age, and educational level, the 3F-EHLI is an applicable measurement independently of these main sociodemographic variables. The 3F-EHLI represents a valid and economic instrument international further development of the measurement of the important health-related construct of eHealth literacy.