Document Type
Article
Abstract
Background: Digital technologies are reshaping health care, making digital health literacy (DHL) a critical competency for navigating online health information. Although widely conceived and measured as a unidimensional measure of DHL, the literature increasingly supports a multidimensional framing of the eHealth Literacy Scale (eHEALS). Studies propose alternative factor structures that can better inform population-level interventions, but these studies have not accounted for the ordinal nature of eHEALS response data. Objective: This study aimed to identify and validate an alternate multidimensional structure of eHEALS accounting for its ordinal response scale. Methods: Data were drawn from the 2022 GetCheckedOnline community survey of consenting English-speaking British Columbia residents aged ≥16 years who reported sexual activity in the past 12 months. Participants were recruited through geo-targeted digital advertisements, community outreach, and in-person recruitment at public events, and community locations. DHL was measured using eHEALS, with responses collected on a 5-point Likert scale. Descriptive statistics summarized eHEALS responses using means, medians, and IQRs. Exploratory and confirmatory factor analyses were used to assess the scale’s structure using polychoric correlations and standard model fit indices. Reliability and validity were evaluated using polychoric ordinal alpha, average variance extracted, and composite reliability, with missing data addressed via multiple imputation. Results: Overall, 1657 participants met inclusion criteria with a mean age of 33.0 (SD 11.77, 95% CI 32.4-33.6) years. Among these 47.3% (95% CI 44.9%-49.7%) identified as women, 30.4% (95% CI 28.1%-32.6%) identified as racialized minorities, 80.5% (95% CI 78.5%-82.3%) reported easy internet access, and 32.2% (95% CI 30.0%-34.5%) had a bachelor’s degree or higher. Across eHEALS items, median scores were 4.0 (IQR 1.0-2.0) with excellent internal consistency (polychoric ordinal α=.92). Exploratory factor analysis supported a 3-factor solution explaining 65.7% of the variance, demonstrated through confirmatory factor analysis (χ217=71.7, P<.001, root-mean-square error of approximation=0.059, standardized root-mean-square residual=0.026, comparative fit index=0.969, Tucker-Lewis Index=0.948). The final model included Information Navigation (standardized loadings=0.765-0.917), Resource Appraisal (0.825-0.892), and Confidence in Use (0.803 for both items), with composite reliability (0.784-0.900), and average variance extracted (0.503-0.738) supporting construct validity. Conclusions: This study confirms a multidimensional structure of eHEALS, identifying Information Navigation, Resource Appraisal, and Confidence in Use as key dimensions of DHL. This revised model enhances measurement precision, enabling more accurate identification of populations with limited DHL and informing the development of targeted, equity-oriented interventions. Future research should aim to confirm this multidimensional structure in more diverse populations and explore how distinct DHL domains influence access to digital health services in various contexts. Additionally, ongoing scale development must adapt to account for the role of emerging technologies, including artificial intelligence and social media algorithms in health care.
Digital Object Identifier (DOI)
Publication Info
Published in Journal of Medical Internet Research, 2025.
APA Citation
Iyamu, I., Gorun, P., Chang, H.-J., Sierra-Rosales, R., Haag, D., Pedersen, H., Bartlett, S., Lachowsky, N., McKee, G., Worthington, C., Grennan, T., Donelle, L., Grace, D., & Gilbert, M. (2025). Development and Validation of a Revised Multidimensional Digital Health Literacy Scale: Secondary Analysis Using Cross-Sectional Data From the 2022 GetCheckedOnline Community Survey In British Columbia, Canada. Journal of Medical Internet Research, 27, e78008.https://doi.org/10.2196/78008
Rights
©Ihoghosa Iyamu, Pierce Gorun, Hsiu-Ju Chang, Rodrigo Sierra-Rosales, Devon Haag, Heather Pedersen, Sofia Bartlett, Nathan Lachowsky, Geoffrey McKee, Catherine Worthington, Troy Grennan, Lorie Donelle, Daniel Grace, Mark Gilbert. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 15.Dec.2025. This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research (ISSN 1438-8871), is properly cited. The complete bibliographic information, a link to the original publication on https://www.jmir.org/, as well as this copyright and license information must be included.