BACKGROUND: The Internet, with its capacity to provide information that transcends time and space barriers, continues to transform how people find and apply information to their own lives. With the current explosion in electronic sources of health information, including thousands of websites and hundreds of mobile phone health apps, electronic health literacy is gaining an increasing prominence in health and medical research. An important dimension of electronic health literacy is the ability to appraise the quality of information that will facilitate everyday health care decisions. Health information seekers explore their care options by gathering information from health websites, blogs, Web-based forums, social networking websites, and advertisements, despite the fact that information quality on the Internet varies greatly. Nonetheless, research has lagged behind in establishing multidimensional instruments, in part due to the evolving construct of health literacy itself. OBJECTIVE: The purpose of this study was to examine psychometric properties of a new electronic health literacy (ehealth literacy) measure in a national sample of Internet users with specific attention to older users. Our paper is motivated by the fact that ehealth literacy is an underinvestigated area of inquiry. METHODS: Our sample was drawn from a panel of more than 55,000 participants maintained by Knowledge Networks, the largest national probability-based research panel for Web-based surveys. We examined the factor structure of a 19-item electronic Health Literacy Scale (e-HLS) through exploratory factor analysis (EFA) and confirmatory factor analysis, internal consistency reliability, and construct validity on sample of adults (n=710) and a subsample of older adults (n=194). The AMOS graphics program 21.0 was used to construct a measurement model, linking latent factors obtained from EFA with 19 indicators to determine whether this factor structure achieved a good fit with our entire sample and the subsample (age ≥ 60 years). Linear regression analyses were performed in separate models to examine: (1) the construct validity of the e-HLS and (2) its association with respondents' demographic characteristics and health variables. RESULTS: The EFA produced a 3-factor solution: communication (2 items), trust (4 items), and action (13 items). The 3-factor structure of the e-HLS was found to be invariant for the subsample. Fit indices obtained were as follows: full sample: χ(2) (710)=698.547, df=131, P<.001, comparative fit index (CFI)=0.94, normed fit index (NFI)=0.92, root mean squared error of approximation (RMSEA)=0.08; and for the older subsample (age ≥ 60 years): χ(2) (194)=275.744, df=131, P<.001, CFI=0.95, NFI=0.90, RMSEA=0.08. CONCLUSIONS: The analyses supported the e-HLS validity and internal reliability for the full sample and subsample. The overwhelming majority of our respondents reported a great deal of confidence in their ability to appraise the quality of information obtained from the Internet, yet less than half reported performing quality checks contained on the e-HLS.